initial commit

.vscode/settings.json

@@ -1,6 +0,0 @@
-{
-    "[python]": {
-        "editor.defaultFormatter": "ms-python.black-formatter"
-    },
-    "python.formatting.provider": "none"
-}

README.md

@@ -1,21 +1,10 @@
 ---
 title: Pdf Rag Metadata Demo
-emoji: 🌍
+emoji: 📄
 colorFrom: yellow
 colorTo: indigo
 sdk: docker
 pinned: false
 license: gpl-3.0
 short_description: PDF RAG metadata demo
----
-
-This is a templated Space for [Shiny for Python](https://shiny.rstudio.com/py/). 
-
-
-To get started with a new app do the following:
-
-1) Install Shiny with `pip install shiny`
-2) Create a new app with `shiny create`
-3) Then run the app with `shiny run --reload`
-
-To learn more about this framework please see the [Documentation](https://shiny.rstudio.com/py/docs/overview.html).
+---

app.py

@@ -1,162 +1,192 @@
-import faicons as fa
-import plotly.express as px
-
-# Load data and compute static values
-from shared import app_dir, tips
-from shinywidgets import render_plotly
-
-from shiny import reactive, render
-from shiny.express import input, ui
-
-bill_rng = (min(tips.total_bill), max(tips.total_bill))
-
-# Add page title and sidebar
-ui.page_opts(title="Restaurant tipping", fillable=True)
-
-with ui.sidebar(open="desktop"):
-    ui.input_slider(
-        "total_bill",
-        "Bill amount",
-        min=bill_rng[0],
-        max=bill_rng[1],
-        value=bill_rng,
-        pre="$",
-    )
-    ui.input_checkbox_group(
-        "time",
-        "Food service",
-        ["Lunch", "Dinner"],
-        selected=["Lunch", "Dinner"],
-        inline=True,
-    )
-    ui.input_action_button("reset", "Reset filter")
-
-# Add main content
-ICONS = {
-    "user": fa.icon_svg("user", "regular"),
-    "wallet": fa.icon_svg("wallet"),
-    "currency-dollar": fa.icon_svg("dollar-sign"),
-    "ellipsis": fa.icon_svg("ellipsis"),
+import base64
+
+from llama_index.core.schema import BaseNode
+from shiny import ui, render, App
+import logging
+from pathlib import Path
+from llama_index.core.storage.docstore import SimpleDocumentStore
+import json
+
+from structure_parsers import parse_structure
+
+root_logger = logging.getLogger()
+logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.INFO)
+root_logger.setLevel(logging.ERROR)
+
+
+parsed_structure_info = {
+    "landscape": """
+    Structure parsed from PDF using Gemini (landscape mode):
+    - Indentation shows parent/child relationships
+    - Numbers in [] represent:
+      * Positive numbers: page numbers
+      * Negative numbers: abstract nodes grouping related sections
+    """,
+    "portrait": """
+    Structure parsed from PDF using Gemini (portrait mode):
+    - Indentation shows parent/child relationships
+    - Numbers in [] represent:
+      * Positive numbers: line numbers
+      * Negative numbers: abstract nodes grouping related sections
+    """,
 }
 
-with ui.layout_columns(fill=False):
-    with ui.value_box(showcase=ICONS["user"]):
-        "Total tippers"
-
-        @render.express
-        def total_tippers():
-            tips_data().shape[0]
-
-    with ui.value_box(showcase=ICONS["wallet"]):
-        "Average tip"
-
-        @render.express
-        def average_tip():
-            d = tips_data()
-            if d.shape[0] > 0:
-                perc = d.tip / d.total_bill
-                f"{perc.mean():.1%}"
-
-    with ui.value_box(showcase=ICONS["currency-dollar"]):
-        "Average bill"
-
-        @render.express
-        def average_bill():
-            d = tips_data()
-            if d.shape[0] > 0:
-                bill = d.total_bill.mean()
-                f"${bill:.2f}"
-
-
-with ui.layout_columns(col_widths=[6, 6, 12]):
-    with ui.card(full_screen=True):
-        ui.card_header("Tips data")
-
-        @render.data_frame
-        def table():
-            return render.DataGrid(tips_data())
-
-    with ui.card(full_screen=True):
-        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
-            "Total bill vs tip"
-            with ui.popover(title="Add a color variable", placement="top"):
-                ICONS["ellipsis"]
-                ui.input_radio_buttons(
-                    "scatter_color",
-                    None,
-                    ["none", "sex", "smoker", "day", "time"],
-                    inline=True,
-                )
-
-        @render_plotly
-        def scatterplot():
-            color = input.scatter_color()
-            return px.scatter(
-                tips_data(),
-                x="total_bill",
-                y="tip",
-                color=None if color == "none" else color,
-                trendline="lowess",
+# Load the docstore
+data_dir = Path(__file__).parents[1] / "data"
+docstore = SimpleDocumentStore.from_persist_path(str(data_dir / "storage_metadata" / "processed_docstore_storage.json"))
+
+
+def get_pdf_data_url(file_path):
+    """Convert PDF file to data URL for embedding"""
+    try:
+        with open(file_path, "rb") as f:
+            pdf_data = f.read()
+            b64_data = base64.b64encode(pdf_data).decode()
+            return f"data:application/pdf;base64,{b64_data}"
+    except Exception as e:
+        logger.error(f"Error reading PDF file: {e}")
+        return None
+
+
+def get_str_structure(doc: BaseNode) -> str:
+    """Return a string representation of the document structure."""
+    tree = parse_structure(doc)
+    return str(tree)
+
+
+def format_metadata_value(value):
+    # Try to parse as JSON if it looks like a dict/list string
+    if isinstance(value, str):
+        if (value.startswith("{") and value.endswith("}")) or (value.startswith("[") and value.endswith("]")):
+            try:
+                parsed = json.loads(value)
+                return ui.tags.pre(json.dumps(parsed, indent=2, ensure_ascii=False))
+            except:
+                pass
+
+        # Handle multiline strings
+        if "\n" in value:
+            return ui.tags.pre(value)
+
+    # Handle lists and dicts directly
+    if isinstance(value, (dict, list)):
+        return ui.tags.pre(json.dumps(value, indent=2, ensure_ascii=False))
+
+    # Default case
+    return str(value)
+
+
+# Define UI
+def get_doc_choices():
+    return [(doc_id, doc.metadata.get("filename", doc_id)) for doc_id, doc in docstore.docs.items()]
+
+
+app_ui = ui.page_fluid(
+    # Summary section
+    ui.card(
+        ui.h2("Document Store Summary"),
+        ui.output_text("doc_count"),
+        # min_height=200,
+    ),
+    # Document selection and display
+    ui.card(
+        ui.layout_sidebar(
+            ui.sidebar(
+                ui.h3("Document Selection"),
+                ui.input_select("selected_doc_id", "Select Document", choices=dict(get_doc_choices())),
+            ),
+            ui.h2("Document display"),
+            ui.output_ui("display_panel"),
+            ui.h2("Document Details"),
+            ui.output_ui("metadata_panel"),
+        )
+    ),
+)
+
+
+def server(input, output, session):
+    @output
+    @render.text
+    def doc_count():
+        return f"Total documents: {len(docstore.docs)}"
+
+    @output
+    @render.ui
+    def display_panel():
+        if not input.selected_doc_id():
+            return ui.p("Please select a document")
+
+        try:
+            doc = docstore.docs.get(input.selected_doc_id())
+            if not doc:
+                logger.error(f"Document not found: {input.selected_doc_id()}")
+                return ui.p("Error: Document not found")
+
+            pdf_path = doc.metadata.get("file_path")
+            pdf_data_url = get_pdf_data_url(pdf_path) if pdf_path else None
+
+            return ui.div(
+                ui.h3(f"Display panel for: {doc.metadata.get('filename', 'Unknown')}"),
+                ui.row(
+                    ui.column(
+                        6,  # Left column (PDF)
+                        ui.h4("PDF View"),
+                        ui.tags.iframe(
+                            src=pdf_data_url,
+                            style="width: 100%; height: 800px; border: 1px solid #ddd;",
+                            type="application/pdf",
+                        )
+                        if pdf_data_url
+                        else ui.p("No PDF available"),
+                    ),
+                    ui.column(
+                        6,  # Right column (Markdown)
+                        ui.h4("Content"),
+                        ui.div(
+                            ui.markdown(doc.text),
+                            style="height: 800px; overflow-y: auto; border: 1px solid #ddd; padding: 1rem;",
+                        ),
+                    ),
+                ),
             )
 
-    with ui.card(full_screen=True):
-        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
-            "Tip percentages"
-            with ui.popover(title="Add a color variable"):
-                ICONS["ellipsis"]
-                ui.input_radio_buttons(
-                    "tip_perc_y",
-                    "Split by:",
-                    ["sex", "smoker", "day", "time"],
-                    selected="day",
-                    inline=True,
-                )
-
-        @render_plotly
-        def tip_perc():
-            from ridgeplot import ridgeplot
-
-            dat = tips_data()
-            dat["percent"] = dat.tip / dat.total_bill
-            yvar = input.tip_perc_y()
-            uvals = dat[yvar].unique()
-
-            samples = [[dat.percent[dat[yvar] == val]] for val in uvals]
-
-            plt = ridgeplot(
-                samples=samples,
-                labels=uvals,
-                bandwidth=0.01,
-                colorscale="viridis",
-                colormode="row-index",
+        except Exception as e:
+            logger.exception("Error displaying document metadata")
+            return ui.p(f"Error: {str(e)}")
+
+    @output
+    @render.ui
+    def metadata_panel():
+        if not input.selected_doc_id():
+            return ui.p("Please select a document")
+
+        try:
+            doc = docstore.docs.get(input.selected_doc_id())
+            if not doc:
+                logger.error(f"Document not found: {input.selected_doc_id()}")
+                return ui.p("Error: Document not found")
+
+            return ui.div(
+                ui.h3(f"Metadata for: {doc.metadata.get('filename', 'Unknown')}"),
+                ui.tags.table(
+                    ui.tags.thead(ui.tags.tr(ui.tags.th("Property"), ui.tags.th("Value"))),
+                    ui.tags.tbody(
+                        *[
+                            ui.tags.tr(ui.tags.td(key), ui.tags.td(format_metadata_value(value)))
+                            for key, value in doc.metadata.items()
+                        ]
+                    ),
+                    class_="table table-striped",
+                ),
+                ui.h3(f"Parsed Structure for: {doc.metadata.get('filename', 'Unknown')}"),
+                ui.markdown(parsed_structure_info.get(doc.metadata.get("format", ""), "")),
+                ui.tags.pre(get_str_structure(doc)),
             )
 
-            plt.update_layout(
-                legend=dict(
-                    orientation="h", yanchor="bottom", y=1.02, xanchor="center", x=0.5
-                )
-            )
-
-            return plt
-
-
-ui.include_css(app_dir / "styles.css")
-
-# --------------------------------------------------------
-# Reactive calculations and effects
-# --------------------------------------------------------
-
-
-@reactive.calc
-def tips_data():
-    bill = input.total_bill()
-    idx1 = tips.total_bill.between(bill[0], bill[1])
-    idx2 = tips.time.isin(input.time())
-    return tips[idx1 & idx2]
+        except Exception as e:
+            logger.exception("Error displaying document metadata")
+            return ui.p(f"Error: {str(e)}")
 
 
-@reactive.effect
-@reactive.event(input.reset)
-def _():
-    ui.update_slider("total_bill", value=bill_rng)
-    ui.update_checkbox_group("time", selected=["Lunch", "Dinner"])
+app = App(app_ui, server)

data/cache/2023-conocophillips-aim-presentation.pdf.md

@@ -0,0 +1,2475 @@
+ConocoPhillips
+2023 Analyst & Investor Meeting
+
+--- end page 1
+
+# Today's Agenda
+
+Opening
+Ryan Lance Chairman and CEO
+
+Strategy and Portfolio
+Dominic Macklon EVP, Strategy, Sustainability and Technology
+
+Alaska and International
+Andy O'Brien SVP, Global Operations
+
+LNG and Commercial
+Bill Bullock EVP and CFO
+
+Lower 48
+Nick Olds EVP, Lower 48
+
+Financial Plan
+Bill Bullock EVP and CFO
+
+Closing
+Ryan Lance Chairman and CEO
+
+10-Minute Break
+
+Q&A Session
+
+ConocoPhillips
+2
+
+--- end page 2
+
+# Cautionary Statement
+This presentation provides management's current operational plan for ConocoPhillips over roughly the next decade, for the assets currently in our portfolio, and is subject to multiple assumptions, including, unless otherwise specifically noted:
+*   an oil price of $60/BBL West Texas Intermediate in 2022 dollars, escalating at 2.25% annually;
+*   an oil price of $65/BBL Brent in 2022 dollars, escalating at 2.25% annually;
+*   a gas price of $3.75/MMBTU Henry Hub in 2022 dollars, escalating at 2.25% annually;
+*   an international gas price of $8/MMBTU Title Transfer Facility & Japan Korea Marker in 2022 dollars, escalating at 2.25% annually;
+*   cost and capital escalation in line with price escalation; planning case at $60/BBL WTI assumes capital de-escalation from levels observed in 2022;
+*   all production compound annual growth rates (CAGR) are calculated for the 10-year period 2023 - 2032;
+*   inclusion of carbon tax in the cash flow forecasts for assets where a tax is currently assessed. If no carbon tax exists for the asset, it is not included in the cash flow forecasts;
+*   Cost of Supply displayed in WTI, includes carbon tax where carbon policy exists and a proxy carbon price for assets without existing carbon policies. Please refer to the Cost of Supply definition in the Appendix for additional information on how carbon costs are included
+in the Cost of Supply calculation.
+
+As a result, this presentation contains forward-looking statements as defined under the federal securities laws. Forward-looking statements relate to future events, plans and anticipated results of operations, business strategies, and other aspects of our operations or
+operating results. Graphics that project into a future date constitute forward-looking statements. Also, words and phrases such as "anticipate," "estimate," "believe," "budget," "continue," "could," "intend," "may," "plan," "potential," "predict," "seek," "should," "will," "would,"
+"expect," "objective," "projection," "forecast," "goal," "guidance," "outlook," "effort," "target" and other similar words can be used to identify forward-looking statements. However, the absence of these words does not mean that the statements are not forward-looking.
+
+Where, in any forward-looking statement, the company expresses an expectation or belief as to future results, such expectation or belief is based on management's good faith plans and objectives under the assumptions set forth above (unless noted otherwise) and
+believed to be reasonable as of April 12, 2023, the date of this presentation. These statements are not guarantees of future performance and involve certain risks and uncertainties and are subject to change as management is continually assessing factors beyond our control
+that may or may not be currently known. Given the foregoing and the extended time horizon of this presentation, actual outcomes and results will likely differ from what is expressed or forecast in the forward-looking statements, and such differences may be material.
+Factors that could cause actual results or events to differ materially from what is presented include changes in commodity prices, including a prolonged decline in these prices relative to historical or future expected levels; global and regional changes in the demand, supply,
+prices, differentials or other market conditions affecting oil and gas, including changes resulting from any ongoing military conflict, including the conflict between Russia and Ukraine and the global response to such conflict, security threats on facilities and infrastructure, or
+from a public health crisis or from the imposition or lifting of crude oil production quotas or other actions that might be imposed by OPEC and other producing countries and the resulting company or third-party actions in response to such changes; insufficient liquidity or
+other factors, such as those listed herein, that could impact our ability to repurchase shares and declare and pay dividends such that we suspend our share repurchase program and reduce, suspend, or totally eliminate dividend payments in the future, whether variable or
+fixed; changes in expected levels of oil and gas reserves or production; potential failures or delays in achieving expected reserve or production levels from existing and future oil and gas developments, including due to operating hazards, drilling risks or unsuccessful
+exploratory activities; unexpected cost increases, inflationary pressures or technical difficulties in constructing, maintaining or modifying company facilities; legislative and regulatory initiatives addressing global climate change or other environmental concerns; public health
+crises, including pandemics (such as COVID-19) and epidemics and any impacts or related company or government policies or actions; investment in and development of competing or alternative energy sources; potential failures or delays in delivering on our current or
+future low-carbon strategy, including our inability to develop new technologies; disruptions or interruptions impacting the transportation for our oil and gas production; international monetary conditions and exchange rate fluctuations; changes in international trade
+relationships or governmental policies, including the imposition of price caps or the imposition of trade restrictions or tariffs on any materials or products (such as aluminum and steel) used in the operation of our business, including any sanctions imposed as a result of any
+ongoing military conflict, including the conflict between Russia and Ukraine; our ability to collect payments when due, including our ability to collect payments from the government of Venezuela or PDVSA; our ability to complete any announced or any future dispositions or
+acquisitions on time, if at all; the possibility that regulatory approvals for any announced or any future dispositions or acquisitions will not be received on a timely basis, if at all, or that such approvals may require modification to the terms of the transactions or our remaining
+business; business disruptions following any announced or future dispositions or acquisitions, including the diversion of management time and attention; the ability to deploy net proceeds from our announced or any future dispositions in the manner and timeframe we
+anticipate, if at all; potential liability for remedial actions under existing or future environmental regulations; potential liability resulting from pending or future litigation, including litigation related directly or indirectly to our transaction with Concho Resources Inc.; the impact
+of competition and consolidation in the oil and gas industry; limited access to capital or insurance or significantly higher cost of capital or insurance related to illiquidity or uncertainty in the domestic or international financial markets or investor sentiment; general domestic
+and international economic and political conditions or developments, including as a result of any ongoing military conflict, including the conflict between Russia and Ukraine; changes in fiscal regime or tax, environmental and other laws applicable to our business; and
+disruptions resulting from accidents, extraordinary weather events, civil unrest, political events, war, terrorism, cybersecurity threats or information technology failures, constraints or disruptions; and other economic, business, competitive and/or regulatory factors affecting
+our business generally as set forth in our filings with the Securities and Exchange Commission. Unless legally required, ConocoPhillips expressly disclaims any obligation to update any forward-looking statements, whether as a result of new information, future events or
+otherwise. We assume no duty to update these statements as of any future date and neither future distribution of this material nor the continued availability of this material in archive form on our website should be deemed to constitute an update or re-affirmation of these
+figures as of any future date. Any future update of these figures will be provided only through a public disclosure indicating that fact.
+
+Use of Non-GAAP Financial Information - This presentation includes non-GAAP financial measures, which help facilitate comparison of company operating performance across periods and with peer companies. Any historical non-GAAP measures included herein will be
+accompanied by a reconciliation to the nearest corresponding GAAP measure both at the end of this presentation and on our website at www.conocophillips.com/nongaap. For forward-looking non-GAAP measures, we are unable to provide a reconciliation to the most
+comparable GAAP financial measures because the information needed to reconcile these measures is dependent on future events, many of which are outside management's control as described above. Additionally, estimating such GAAP measures and providing a
+meaningful reconciliation consistent with our accounting policies for future periods is extremely difficult and requires a level of precision that is unavailable for these future periods and cannot be accomplished without unreasonable effort. Forward looking non-GAAP
+measures are estimated consistent with the relevant definitions and assumptions.
+
+Cautionary Note to U.S. Investors - The SEC permits oil and gas companies, in their filings with the SEC, to disclose only proved, probable and possible reserves. We use terms and metrics such as "resource" or "Estimated Ultimate Recovery (EUR)" in this presentation that
+we are prohibited from using in filings with the SEC under the SEC's guidelines. U.S. investors are urged to consider closely the oil and gas disclosures in our Form 10-K and other reports and filings with the SEC. Copies are available from the SEC and from the
+ConocoPhillips website.
+
+ConocoPhillips 3
+
+
+--- end page 3
+
+ConocoPhillips
+Opening
+Ryan Lance
+Chairman and CEO
+
+--- end page 4
+
+# ConocoPhillips Remains the Must-Own E&P Company
+
+120
+100
+The Macro
+Oil Price ($/BBL WTI)
+What You'll Hear Today
+We are committed to
+delivering superior returns
+**on** and **of** capital
+through the cycles
+
+80
+60
+40
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+We have a **deep, durable**
+and **diverse** portfolio
+
+20
+0
+2019
+2021
+2023
+2024+
+We are progressing our
+**2050 Net-Zero ambition** and
+accelerating our 2030 GHG emissions
+intensity reduction target
+
+ConocoPhillips
+5
+
+--- end page 5
+
+We Are Committed to Our Returns-Focused Value Proposition
+
+### Triple Mandate
+Aligned to Business Realities
+
+![Figure 1: Triple Mandate with three sections: MEET TRANSITION PATHWAY DEMAND (green), DELIVER COMPETITIVE RETURNS (orange), ACHIEVE NET-ZERO EMISSIONS AMBITION¹ (blue)](image_reference)
+
+### Foundational Principles
+
+![Figure 2: Foundational Principles including Balance Sheet Strength, RETURNS, Disciplined Investments, Peer-Leading Distributions, ESG Excellence, Deliver Superior Returns Through Cycles](image_reference)
+
+### Clear and Consistent Priorities
+1
+Sustain production
+and pay dividend
+
+2
+Annual dividend growth
+
+3
+'A'-rated balance sheet
+
+4
+>30% of CFO
+shareholder payout
+
+5
+Disciplined investment
+to enhance returns
+
+¹Scope 1 and 2 emissions on a gross operated and net equity basis.
+Cash from operations (CFO) is a non-GAAP measure defined in the Appendix.
+
+--- end page 6
+
+# We Are Continuously Improving
+
+|                                  | 2016        | 2019        | 2022        |
+| :------------------------------- | :---------- | :---------- | :---------- |
+|                                  | $43/BBL WTI | $57/BBL WTI | $94/BBL WTI |
+| Return on Capital Employed       | -4%         | 10%         | 27%         |
+| Return of Capital¹               | $1.11/share | $4.45/share | $11.73/share |
+| Net Debt                         | $24B        | $7B         | $7B         |
+| Cash From OperationsFree Cash Flow | $5B \| $OB | $12B \| $5B | $29B \| $18B |
+| Resource <$40/BBL WTI            | ~10 BBOE    | ~15 ВВОЕ    | ~20 BBOE    |
+| Production                       | 1.6 MMBOED  | 1.3 MMBOED  | 1.7 MMBOED  |
+| Emissions Intensity²(kg CO2e/BOE) | ~39         | ~36         | ~22         |
+
+Foundational
+Principles
+
+Peer-Leading
+Distributions
+and Returns
+
+Balance Sheet
+Strength
+
+Disciplined
+Investments
+
+ESG
+Excellence
+
+¹Defined in the Appendix and presented on a per-share basis using average outstanding diluted shares. ²Gross operated GHG emissions (Scope 1 and 2), 2022 is a preliminary estimate.
+Cash from operations (CFO), free cash flow (FCF), net debt and return on capital employed (ROCE) are non-GAAP measures. Definitions and reconciliations are included in the Appendix.
+
+--- end page 7
+
+# We Have a Compelling 10-Year Plan that Sets us Apart
+
+$350
+$300
+$250
+$200
+$150
+$100
+$50
+10-Year Plan ($B)
+CFO at
+2023-2032
+$80/BBL WTI
+Upside Sensitivity
+CFO at
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+Additional
+Distributions
+30% of CFO
+Distribution
+Commitment
+Capital
+$0
+Cash 1
+Cash¹
+Sources
+Uses
+
+Peer leading ROCE improving through time
+
+Top quartile ordinary dividend growth
+
+>90% market cap² distributed
+
+~$35/BBL WTI FCF Breakeven³
+
+~6% CFO CAGR, ~11% FCF CAGR
+
+Unhedged for price upside
+
+Cash includes cash, cash equivalents, restricted cash and short-term investments. 2Market cap of ~$121B at March 31, 2023, close. 3Average over the next 10 years.
+CAGRs calculated from FY2024 at $60/BBL WTI. Cash from operations (CFO), free cash flow (FCF) and return on capital employed (ROCE) are non-GAAP measures. Definitions are included in the Appendix.
+
+ConocoPhillips 8
+
+
+--- end page 8
+
+ConocoPhillips
+Strategy and Portfolio
+Dominic Macklon
+EVP, Strategy, Sustainability and Technology
+
+--- end page 9
+
+# Strategy Powers Our Returns-Focused Value Proposition
+
+$
+### Rigorous Capital Allocation Framework
+
+Commitment to
+disciplined reinvestment rate
+
+Cost of Supply analysis
+informs investment decisions
+
+### Differentiated Portfolio
+Depth, Durability and Diversity
+
+~20 BBOE, <$40/BBL WTI
+low Cost of Supply resource base
+
+Leading Lower 48
+unconventional position,
+complemented with premium
+Alaska and International assets
+
+### Valued Role in the
+Energy Transition
+
+Accelerating GHG-intensity
+reduction target through 2030
+
+Built attractive
+LNG portfolio
+
+Balance of short-cycle,
+flexible unconventional
+with select longer-cycle,
+low-decline conventional
+
+Reinvestment rate is a non-GAAP measure defined in the Appendix.
+Strong track record of active
+portfolio management
+
+Evaluating longer term
+low-carbon options in
+hydrogen and CCS
+ConocoPhillips 10
+
+--- end page 10
+
+# Commitment to Disciplined Reinvestment Rate
+
+## Industry Growth Focus
+
+>100%
+Reinvestment Rate
+
+## ConocoPhillips Strategy Reset
+
+<60%
+Reinvestment Rate
+
+## Disciplined Reinvestment Rate is the Foundation for Superior Returns on and of Capital, while Driving Durable CFO Growth
+
+~50%
+10-Year
+Reinvestment Rate
+
+~6%
+CFO CAGR
+2024-2032
+
+at $60/BBL WTI
+Mid-Cycle
+Planning Price
+
+ConocoPhillips Average Annual Reinvestment Rate (%)
+
+100%
+
+75%
+
+50%
+
+25%
+
+~$75/BBL
+WTI
+Average
+
+~$63/BBL
+WTI
+Average
+
+0%
+
+2012-2016
+
+2017-2022
+
+at $80/BBL
+WTI
+
+2023E
+
+at $60/BBL
+WTI
+
+at $80/BBL
+WTI
+
+at $80/BBL
+WTI
+
+at $60/BBL
+WTI
+
+2024-2028
+
+2029-2032
+
+Historic Reinvestment Rate
+Reinvestment Rate at $60/BBL WTI
+--- Reinvestment Rate at $80/BBL WTI
+
+Reinvestment rate and cash from operations (CFO) are non-GAAP measures. Definitions and reconciliations are included in the Appendix.
+ConocoPhillips 11
+
+--- end page 11
+
+# Cost of Supply Analysis Informs Investment Decisions
+
+Cost of Supply = Our North Star
+$/BBL WTI Oil Price Required to Achieve a Point-Forward 10% Return
+
+Fully Burdened Metric
+With All Components Rigorously
+Calculated For Each Entity
+
+WTI Cost of Supply ($/BBL)
+
+Facilities
+
+G&A
+Transport
+Lifting
+
+Wells
+
+Capital
+
+<$40/BBL
+
+OPEX
+
+Royalty
+
+Taxes
+
+Product Mix
+
+Differential to WTI
+
+WTI COS
+
+Low Cost of Supply Wins
+
+Reflective of a typical Permian development well.
+
+ConocoPhillips
+12
+
+
+--- end page 12
+
+# Secondary Investment Criteria Reinforce Resilient, Durable Returns
+
+Investment Criteria
+
+Balanced, Diversified, Disciplined Production Growth
+
+Production Mix¹
+Oil ~55% NGL ~15% North American Gas ~15% International Gas ~15%
+
+Production (MBOED)
+
+Secondary Criteria
+Disciplined
+Reinvestment Rate
+Returns of capital
+Cost of
+Supply
+Returns on capital
+
+Balance of short-cycle, flexible
+unconventional with longer-cycle,
+low-decline conventional
+
+Product mix and market exposure
+
+Predictable execution
+
+¹Average anticipated production mix from 2023-2032; oil includes bitumen.
+Reinvestment rate is a non-GAAP measure defined in the Appendix.
+
+[Graph 1: Production (MBOED)]
+| Year | Production CAGR | LNG + Surmont | Conventional | Unconventional (Lower 48 + Montney) |
+|---|---|---|---|---|
+| 2023E | ~4-5% 10-Year Production CAGR |  |  |  |
+|  |  | ~2% CAGR | ~3% CAGR | ~6% CAGR |
+| 2032 |  |  |  |  |
+
+--- end page 13
+
+# Our Differentiated Portfolio: Deep, Durable and Diverse
+
+$50
+
+~20 BBOE of Resource
+Under $40/BBL Cost of Supply
+
+~$32/BBL
+Average Cost of Supply
+
+Diverse Production Base
+10-Year Plan Cumulative Production (BBOE)
+
+Lower 48
+
+Alaska
+
+WTI Cost of Supply ($/BBL)
+$40
+
+$30
+
+$20
+
+$10
+
+$0
+0
+5
+10
+15
+Resource (BBOE)
+Lower 48
+Canada
+Alaska
+ΕΜΕΝΑ
+Asia Pacific
+
+Costs assume a mid-cycle price environment of $60/BBL WTI.
+Permian
+GKA
+GWA
+GPA WNS
+EMENA
+Norway
+Qatar Libya
+Asia Pacific Canada
+Montney
+APLNG
+20
+Bakken
+Eagle Ford
+Other
+Malaysia China Surmont
+
+ConocoPhillips
+14
+
+--- end page 14
+
+# Strong Track Record of Active Portfolio Management
+
+2016 |  | 2022
+-----------------|----------------------------------------------------|-----------------
+Production | 1.6 MMBOED | 1.7 MMBOED
+Resource <$40/BBL WTI | ~10 BBOE | ~20 BBOE
+Average Cost of Supply | <$40/BBL WTI | ~$32/BBL WTI
+Resource Life | >18 years | >30 years
+Emissions Intensity¹ | ~39 kg CO₂e/BOE | ~22 kg CO2e/BOE
+
+ | WNS and GKA Working Interest Consolidations |
+ |---|
+ | 2018 |
+ | Montney Acreage Acquisition | Concho and Shell Permian Acquisitions | APLNG Acquisition |
+ |---|---|---|
+ | 2020 | 2021 | 2022 |
+ | 2017 | 2019 |  |
+ |---|---|---|
+ | San Juan Exit Canada Cenovus Transaction | U.K. Exit | Niobrara and Australia-West Exits | Indonesia Exit |
+
+Cost of Supply Framework Drives Disciplined Transactions
+~$25B of Both Acquisitions and Divestitures Since 20162
+
+¹Gross operated GHG emissions (Scope 1 and 2), 2022 is a preliminary estimate. ²Dispositions include contingent payment proceeds and sale of CVE shares.
+
+--- end page 15
+
+# Accelerating Our GHG-Intensity Reduction Target Through 2030
+Emissions Reduction Opportunities
+Pathway to Net-Zero¹
+
+Methane Venting
+and Flaring
+
+Electrification
+
+Optimization
+and Efficiency
+Emissions Intensity (kg CO2e/BOE)
+
+![Figure 1: Graph illustrates Pathway to Net-Zero Emissions Intensity (kg CO2e/BOE).  The X axis shows years 2016, 2022E, 2030, and 2050.  The Y axis shows values from 0 to 50, in increments of 10.  Two data series are plotted: Gross Operated (blue bars and line) and Net Equity (gray line). The graph shows a reduction from approximately 40 kg CO2e/BOE in 2016 to a projected value between 10 and 20 kg CO2e/BOE by 2030 for Gross Operated, and a similar reduction for Net Equity. Key reduction targets of 50% and 60% are highlighted on the graph.](image_reference)
+
+Strategic Pilots
+and Studies
+
+Near-Term (2025)
+*   Zero routine flaring by 2025²
+
+Medium-Term (2030)
+*   NEW: Reduce GHG intensity 50-60% (from 40-50%)³
+*   Near-zero methane intensity target <1.5 kg CO2e/BOE
+
+Long-Term (2050)
+*   Net-zero emissions ambition¹
+
+Progressing Toward Net-Zero Ambition
+
+¹Scope 1 and 2 emissions on a gross operated and net equity basis. ²In line with the World Bank Zero Routine Flaring initiative, ConocoPhillips premise is five years earlier than World Bank 2030 goal.
+³ Reduction from a 2016 baseline.
+
+ConocoPhillips 16
+
+--- end page 16
+
+# LNG: A Crucial Fuel for Energy Transition
+
+## U.S. Electric Power Sector Emissions
+Drop with Shift from Coal to Natural Gas¹
+
+![Figure 1: Line chart showing the percentage share of electricity generation from coal and gas in the US from 2001 to 2021. Coal decreases from 51% to 40%, while gas increases from 17% to 20%.](image_reference)
+
+![Figure 2: Line chart showing CO₂ emissions in millions of metric tons from 2001 to 2021. Total decreases by >30%.](image_reference)
+
+## Global Coal Consumption²
+Has Yet to Definitively Peak
+
+![Figure 3: Line chart showing global coal consumption in MT from 2000 to 2020.](image_reference)
+
+## U.S. LNG Reduces Carbon Intensity of Electricity³
+
+![Figure 4: Bar chart comparing the kg CO₂e per MWh of Germany domestic coal and Germany U.S. Permian LNG. Domestic coal is approximately 1,100 and U.S. Permian LNG is approximately 600.](image_reference)
+
+>40% Reduction
+in lifecycle GHG emissions
+when switching from domestic
+coal to imported LNG
+
+## Strong LNG Growth Outlook4
+
+![Figure 5: Stacked area chart showing strong LNG growth outlook from 2022 to 2050. Operational and under construction are represented. >300 MTPA Supply Gap by 2050](image_reference)
+
+1U.S E.I.A Power Plant Operations Report. 2IEA, Global Coal Consumption, 2000-2025. 3ICF International, Update to the Life-Cycle Analysis of GHG Emissions for US LNG Exports. 4Source Wood Mackenzie Q4 2022.
+
+
+--- end page 17
+
+# 10-Year Plan Reflects Durable Returns-Focused Value Proposition
+
+## Capital ($B)
+
+~$11B
+2023 Capital
+
+12
+
+9
+
+6
+
+3
+
+25
+
+20
+
+15
+
+0
+
+2023E
+
+2024-2028
+Average
+
+2029-2032
+Average
+
+## Production (MBOED)
+
+~4-5%
+10-Year
+Production CAGR
+
+2,500
+
+2,000
+
+1,500
+
+1,000
+
+500
+
+0
+
+2023E
+
+2024-2028
+Average
+
+2029-2032
+Average
+
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+## FCF ($B)
+
+10
+
+$80/BBL
+WTI
+Upside Sensitivity
+
+$60/BBL
+WTI
+Mid-Cycle
+Planning Price
+
+0
+
+2023E
+
+2024-2028
+Average
+
+> $115B FCF
+Over the Next 10 Years
+at $60/BBL WTI
+
+2029-2032
+Average
+
+~$35/BBL WTI FCF
+Breakeven
+Average Over the Next 10 Years
+
+ConocoPhillips 18
+
+--- end page 18
+
+ConocoPhillips
+Alaska and International
+Andy O'Brien
+SVP, Global Operations
+
+--- end page 19
+
+Alaska and International: Our Unique Diversification Advantage
+
+Portfolio Diversification
+
+*   ~9 BBOE, <$40/BBL WTI
+    Cost of Supply resource base
+
+*   Leveraging existing infrastructure
+    across conventional assets
+
+*   Low-decline, low capital-intensity
+    LNG and Surmont
+
+High-Margin Production Growth
+
+*   World-class Qatar LNG resource expansion
+    builds upon 20-year relationship
+
+*   Progressing Montney unconventional
+    toward development mode
+
+*   Investing for the future with the
+    high-margin Willow project
+
+$
+
+Significant Free Cash Flow
+
+*   Low reinvestment rate underpins
+    distribution capacity
+
+*   High-value, Brent-linked
+    production
+
+*   Delivering value with additional
+    APLNG shareholding interest
+
+Free cash flow (FCF) and reinvestment rate are non-GAAP measures defined in the Appendix.
+
+ConocoPhillips 20
+
+--- end page 20
+
+# Low Capital Intensity Production Growth
+
+Material Low Cost of Supply Resource Base
+Leveraging Existing Infrastructure
+
+~$30/BBL
+Average
+Cost of Supply
+
+![Figure 1: A cost of supply chart with the x-axis representing resource in BBOE from 0 to 9 and the y-axis representing WTI cost of supply in $/BBL from 0 to 50. There are vertical bars of different colors depicting the resource and cost of supply levels for LNG, Surmont, Montney, Conventional International, and Alaska.](image_reference)
+
+Capital-Efficient Production Growth
+Underpins Growing Distribution Capacity
+
+Production Mix¹
+Oil ~60% NGL ~5% North American Gas ~5% International Gas ~30%
+
+![Figure 2: A production mix chart with the x-axis representing the years 2023E, 2024-2028 Average, and 2029-2032 Average, and the y-axis representing Production in MBOED from 0 to 1,200. There are vertical bars of different colors depicting the production mix for LNG, Surmont, Montney, Conventional International, and Alaska.](image_reference)
+
+4% CAGR at ~40% Reinvestment Rate
+Over the Next 10 Years at $60/BBL WTI
+
+
+--- end page 21
+
+# LNG: Expanding World-Class Assets
+
+![Figure 1: Image of a large LNG tanker docked at a port facility, with "Qatar" labeled next to the tanker.](image_reference)
+
+## Qatargas 3
+
+- Legacy position supplying Asian and European markets
+
+## North Field Expansion Projects
+
+- Building on our 20-year relationship with Qatar
+- Awarded 2 MTPA net; NFE first LNG in 2026 and NFS in 2027
+- NFE and NFS add trains 15-20 in Qatar's LNG portfolio
+
+## APLNG
+
+- 90% of volumes under long-term contracts
+- Increased shareholding interest by 10% in 1Q 2022; expecting to recoup ~50% of purchase price by end of 2Q 2023
+- Acquiring up to an additional 2.49% shareholding interest and preparing to take over upstream operatorship upon Origin Sale¹
+
+![Graph 1: Bar graph showing Expanding LNG Production for 2023E, 2024-2028 Average, and 2029-2032 Average. Y-axis labeled "Production (MBOED)" from 0 to 300 in increments of 100. Series include APLNG, QG3, and Qatar Expansion.](image_reference)
+
+## Growing Reliable LNG Cash Flows
+
+Subject to EIG closing its announced acquisition of Origin Energy (the current upstream operator); EIG's transaction with Origin, as well as ConocoPhillips' shareholding acquisition are subject to
+Australian regulatory approvals and other customary closing conditions. The 2.49% purchase is also subject to shareholder's pre-emptive rights.
+
+ConocoPhillips 22
+
+
+--- end page 22
+
+# Surmont: Leveraging Low Capital Intensity for Decades of Flat Production
+
+## Optimizing the Machine
+*   Record 2H 2022 production
+
+*   Low sustaining capital requirements
+
+*   Advantaged operating cost due to top-quartile steam-oil ratio
+
+### Production (MBOED)1
+
+![Figure 1: Bar chart of Production (MBOED) from 2014 to 2022. X-axis is year, Y-axis is MBOED from 0 to 80 in increments of 20. "LAST NEW PAD" and "RECORD PRODUCTION" are labeled above the 2014 and 2022 bars, respectively.](image_reference)
+
+## First New Pad Drilled Since 2016 Developed at <$15/BBL WTI COS
+24 Well Pairs with 25 MBOED Gross Peak Rate
+
+![Figure 2: Aerial view of an oil drilling site in the snow. The location "Pad 267" is noted on the image.](image_reference)
+
+### Average Well Cost² ($MM)
+
+![Figure 3: Bar chart of Average Well Cost ($MM) for 2016 Pads and Pad 267. X-axis is Pad type, Y-axis is cost in $MM from 0 to 6 in increments of 2. A downward arrow labeled "Decreased 30%" is between the two bars.](image_reference)
+
+## Transformative Emissions Reduction³ Opportunities
+*   1/3 through current technology pilots
+
+*   1/3 through new technologies
+
+*   CCS and offsets to achieve net-zero
+
+### Emissions Reduction Pathway (Net MMTeCO2e)
+
+![Figure 4: Line graph showing the Emissions Reduction Pathway from 2023 to 2050. The line starts at the "CURRENT TECH" level and trends down to the "NEW TECH" level, eventually to the "CCS & OFFSETS" level.](image_reference)
+
+Production Records Achieved
+Through Optimization
+
+Raises Production Plateau
+into 2030s
+
+Multiple Options for
+Emissions Reduction
+
+1Net before royalty shown to remove price related royalty impacts. 2Includes drill, completions and facilities (excluding pipelines). 3Net equity Scope 1 and 2 emissions.
+
+ConocoPhillips 23
+
+
+--- end page 23
+
+# Montney: Building Another Core Unconventional Business
+
+### Appraisal Defined Optimal Plan
+• Concluded testing of multiple well configurations and completion designs
+• Recent strong well results lead to high-graded, two-layer development plan
+
+40
+Cost of Supply Improvement
+($/BBL WTI)
+
+Driving to
+Mid-$30s CoS
+0
+Current
+Pads
+Development
+Phase
+
+High-Graded Resource of
+1.8 BBOE at Mid-$30s CoS
+
+### Moving to Development Phase
+• Adding second rig in 2024
+• Running one continuous frac crew
+• Refining completion design
+• CPF2 start-up expected in 3Q 2023
+
+![Figure 1: CPF2](image_reference)
+
+Leveraging
+Unconventional Expertise
+
+### Significant Production Growth
+• 60% liquids production, priced off WTI
+• Long-term commercial offtake secured
+
+150
+Production
+(MBOED)
+
+100
+
+50
+
+0
+2023E
+2024-2028
+Average
+2029-2032
+Average
+
+20% CAGR
+Over 10 Years
+
+
+--- end page 24
+
+# International Conventional: Steady Cash Flow Generator
+
+![Figure 1: Eldfisk](image_reference)
+
+## Brent-Linked Oil and International Gas
+
+### Norway – 115 MBOED
+
+*   Four subsea tie backs on track for onstream in 2024
+*   Greater Ekofisk Area license extended through 2048
+
+### Libya – 50 MBOED
+
+*   Increased working interest to ~20% in Waha Concession
+*   Long-term optionality
+
+### Malaysia – 40 MBOED
+
+*   Low Cost of Supply projects offsetting decline
+
+### China - 30 MBOED
+
+*   Production sharing contract terms aligned to 2039
+*   Progressing offshore windfarm in China
+
+### ~$1B Per Year Free Cash Flow
+
+Over the Next 10 Years at $60/BBL WTI
+
+[Graph 1: Production (MBOED)]
+
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| :---- | :---- | :---------------- | :---------------- |
+| Value | 213   | 225               | 202               |
+
+Country production numbers quoted are 2023 estimates.
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+--- end page 25
+
+# Alaska Conventional: Legacy World-Class Basin
+
+![Figure 1: Map of Alaska Conventional showing Central Processing Facility (CPF)/Project, ConocoPhillips Interest Acreage, Opportunity Reservoir Extent, Pipeline System, and Future Project](no_image_available)
+
+*   Central Processing Facility (CPF)/Project
+*   ConocoPhillips Interest Acreage
+*   Opportunity Reservoir Extent
+*   Pipeline System
+*   Future Project
+
+**Leveraging Existing Infrastructure**
+
+*   Largest producer, with 40+ years of experience across significant infrastructure
+*   Robust inventory of projects with a ~$25/BBL Cost of Supply for over a decade
+
+**Disciplined Development Plan**
+
+![Figure 2: Disciplined Development Plan Pie Chart](no_image_available)
+
+*   New pads filling existing capacity e.g., Nuna, E News
+*   ~$1B Capex per Year
+*   Drilling from existing pads e.g., Coyote, Fiord West Kuparuk, Torok
+
+![Graph 1: 100% of Production Priced at Brent+](no_image_available)
+
+|         | Production (MBOED) |
+| :------ | :----------------- |
+| 2023E   | 195               |
+| 2024-2028 Average | 214               |
+| 2029-2032 Average | 229               |
+
+40+ Years Later, ~2-3% Production Growth
+Over the Next 10 Years
+
+--- end page 26
+
+# Willow: Building on Our Long History
+
+![Figure 1: Oil field Map and Legends](image_reference)
+
+National Petroleum
+Reserve - Alaska
+
+Western
+North Slope
+2000
+
+Greater
+Kuparuk Area
+1981
+
+Prudhoe Bay
+Non-operated
+1977
+
+Nuna
+
+FWK
+
+ENEWS
+
+CD5
+
+WILLOW
+
+BT2 ▲
+
+Coyote
+
+▲ 1FL NEWS
+
+GMT-1
+
+GMT-2
+
+BT1
+
+BT3
+
+N
+
+0
+10
+20
+Miles
+
+ED8
+
+Alaska State
+Lands
+
+Central Processing
+Facility (CPF)/Project
+
+ConocoPhillips
+Interest Acreage
+
+Opportunity
+Reservoir Extent
+
+Pipeline System
+
+Future CPF/Project
+
+Willow Interest Acreage
+
+## Legacy Infrastructure
+
+**13**
+Central Processing Facilities
+
+**~120**
+Drill Sites
+
+**~410**
+Miles of Corridor
+Road and Pipelines
+
+## Willow
+
+**1**
+Central Processing Facility
+
+**3**
+Drill Sites
+
+**~26**
+Miles of Corridor
+Road and Pipelines
+
+## Significant Opportunity Without "Mega-Project" Risks
+
+**Extensive Definition**
+100% FEED complete at FID
+
+**Simple Governance**
+100% ConocoPhillips owned
+
+**Limited Complexity**
+No "first-of-a-kind" designs
+
+**Proven Execution Model**
+Executed similar drill site, pipeline
+and road scope over past five years
+with proven North Slope contractors
+
+Modular facilities designed and built
+in U.S. by top-tier Gulf Coast contractors
+
+ConocoPhillips 27
+
+--- end page 27
+
+# Willow: Delivering Competitive Returns Into the Next Decade
+
+Capex of $1-1.5B per Year from 2024-2028
+
+*   Drill sites and drilling
+*   Infrastructure, roads, pipelines, power and pads
+*   Central processing facility
+
+$7-7.5B
+to First Oil
+
+Key Construction Milestones
+
+|        |        |        |        |        |        |        |
+| :----- | :----- | :----- | :----- | :----- | :----- | :----- |
+| 2023   | 2024   | 2025   | 2026   | 2027   | 2028   | 2029   |
+| Winter road and pipeline construction | Central processing facility fabrication and delivery | First Oil |
+| Operation center fabrication and delivery | Complete tie-ins to new drill sites and existing infrastructure |        |
+| Central processing facility procurement | Commence drilling program |        |
+
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+Volume Ramp and Strong Margins Drive FCF
+
+Pre-drilling strategy fills facility at startup
+
+Premium-quality light crude
+compared to current Alaska average
+
+Leverages existing pipeline infrastructure
+
+Production (MBOED)
+
+Willow:
+100% Oil
+
+[Graph 1: Production (MBOED)]
+|        | 2023E | 2024-2028 Average | 2029-2032 Average |
+| :----- | :---- | :---------------- | :---------------- |
+| Legacy Alaska | 200   | 230               | 240               |
+| Willow   | 0     | 0                 | 160               |
+
+
+--- end page 28
+
+# Alaska and International: Our Unique Diversification Advantage
+
+**Capital** ($B)
+
+[Graph 1: Capital Spending Forecast]
+| Period          | Amount ($B) |
+|-----------------|-------------|
+| 2023E           | 3.5         |
+| 2024-2028 Average | 4.3         |
+| 2029-2032 Average | 3.0         |
+
+**Production** (MBOED)
+
+[Graph 2: Production Forecast]
+| Period          | Amount (MBOED) |
+|-----------------|----------------|
+| 2023E           | 780            |
+| 2024-2028 Average | 870            |
+| 2029-2032 Average | 1,000          |
+
+**FCF** ($B)
+
+[Graph 3: Free Cash Flow Forecast]
+| Period          | Amount ($B) |
+|-----------------|-------------|
+| 2023E           | 5.2          |
+| 2024-2028 Average | 6.2       |
+| 2029-2032 Average | 7.8          |
+
+$80/BBL WTI
+Upside Sensitivity
+
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+
+> $50B FCF and ~40% Reinvestment Rate
+Over the Next 10 Years at $60/BBL WTI
+
+Free cash flow (FCF) and reinvestment rate are non-GAAP measures defined in the Appendix.
+
+ConocoPhillips 29
+
+--- end page 29
+
+ConocoPhillips
+LNG and Commercial
+Bill Bullock
+EVP and CFO
+
+--- end page 30
+
+# LNG Opportunities Underpinned by Strong Commercial Acumen
+
+![Figure 1: LNG image of a ship, LNG tank, and a globe.](image_reference)
+
+- Rapidly Growing LNG Market
+- Robust demand in Asia and Europe driven by energy security and the energy transition
+- Qatar and Australia are foundational LNG investments
+- North American gas production fuels LNG supply growth
+
+- Adding North America to Low-Cost LNG Footprint
+- Port Arthur is a premier LNG development
+- Long-term optionality on the Gulf and West Coasts
+- Offtake margins enhanced by diversion capability
+
+- Extensive Commercial Footprint
+- Global market presence
+- Second-largest natural gas marketer in North America¹
+- 60+ years experience with LNG
+
+¹Natural Gas Intelligence North American Marketer Rankings as of Q3 2022, published in December 2022.
+
+--- end page 31
+
+# Attractive Global LNG Portfolio
+
+Key LNG Supply and Demand Markets by 2035
+(ΜΤΡΑ)1
+
+*   Supply Demand
+
+ConocoPhillips Assets at Nexus of Supply and Demand
+*   Asia and Europe to remain significant demand centers
+*   Qatar and Australia provide reliable LNG
+*   North America dominates LNG supply growth
+
+ConocoPhillips Global Net LNG Exposure
+(ΜΤΡΑ)
+
+APLNG
+QG3
+NFE/NFS
+PA LNG3
+
+ConocoPhillips Net LNG Capital Spend ($B)
+
+~$3.7B
+Cumulative Capital
+
+[Graph 1: ConocoPhillips Global Net LNG Exposure and Net LNG Capital Spend]
+|Data|2023|2028|2032|
+|---|---|---|---|
+|APLNG|5|5|5|
+|QG3|3|3|3|
+|NFE/NFS|0|3|3|
+|PA LNG3|0|4|4|
+
+|Data|2023E|2024-2028 Average|2029-2032 Average|
+|---|---|---|---|
+|Value|7|0.3|0.4|
+
+1Wood Mackenzie Q4 2022, North America as marginal supplier. 2Offtake and/or equity at Energia Costa Azul (ECA) Phase 2 and offtake from ECA Phase 1.
+35 MTPA offtake and access to excess cargoes when Phase 1 liquefaction exceeds the 10.5 MTPA contracted under long term SPAs.
+
+--- end page 32
+
+# Port Arthur is a Premier LNG Development
+
+![Figure 1: Map of the United States showing the locations of Permian, Haynesville, Marcellus, PA LNG, and West Coast Optionality. An aerial view of the Port Arthur LNG facility is also shown.](image_reference)
+
+*Permian*
+
+*West Coast
+Optionality¹*
+
+*Haynesville*
+
+*PA LNG*
+
+*Marcellus*
+
+## FID of Port Arthur Phase 1
+
+- FERC-approved and construction-ready with high-quality operator and EPC contractor
+- ConocoPhillips to manage gas supply
+- Near Gulf Coast infrastructure and fastest growing low-cost, low-GHG gas basins
+- ConocoPhillips participation launched project
+
+## Strategic Optionality
+
+- Access to low-cost uncontracted excess capacity
+- Secured long-term optionality on the Gulf and West Coasts¹
+- Prioritizing market development and offtake over additional equity
+- Evaluating development of CCS projects at Port Arthur facility
+
+## Low-Cost Offtake Secured
+
+- 5 MTPA offtake from Port Arthur Phase 1²
+- Top tier liquefaction fee³
+- Marketing currently underway; receiving significant customer interest
+
+¹Offtake and/or equity on up to six additional trains at Port Arthur, offtake and/or equity at ECA Phase 2, and offtake from ECA Phase 1.
+²20-year agreement. ³Wood Mackenzie Q4 2022, contract fixed liquefaction fees.
+
+ConocoPhillips 33
+
+--- end page 33
+
+# ConocoPhillips Commercial Advantage
+
+Port Arthur LNG Marketing Example: Sale into Germany
+
+European
+Re-Gas
+
+Global Marketing Presence: >10 BCFD and >1 MMBOD¹
+
+*   ConocoPhillips holds re-gas capacity in Germany's first
+    onshore LNG terminal for portion of Port Arthur LNG
+*   Captures Trading Hub Europe (THE) price with diversion
+    capability when other international prices exceed THE
+*   Managed and marketed by experienced ConocoPhillips
+    commercial organization
+
+A
+Global Gas,
+Power and LNG
+
+OPTIMIZED LNG
+CASCADE PROCESS
+Licensing2
+
+1-
+Global Crude
+and NGL
+
+London
+Singapore
+Houston
+Calgary
+Beijing
+Tokyo
+
+9x Equity
+Gas marketed
+globally
+
+6.0 GWh
+Power marketed
+
+~1 ΜΤΡΑ
+Spot sales
+into Asia
+
+113 ΜΤΡΑ
+Utilizing Optimized
+Cascade® Process
+
+2nd Largest
+Global LNG
+technology provider
+
+25 Cargoes
+Marketed globally
+per month
+
+45%
+Brent-linked
+
+180 MBOD
+North American
+export capacity
+
+¹FY2022 data unless otherwise footnoted. ²Based on total global installed production capacity of 113 MTPA associated with 26 licensed LNG trains in operation.
+
+--- end page 34
+
+ConocoPhillips
+
+Lower 48
+Nick Olds
+EVP, Lower 48
+
+--- end page 35
+
+Premier Lower 48 Assets Underpin Our Returns-Focused Strategy
+
+Industry Leader Focused
+on Maximizing Returns
+
+Largest Lower 48 unconventional
+producer with deep, durable and
+diverse unconventional portfolio
+
+Disciplined development optimizing
+returns and recovery
+
+$
+Production and Free Cash Flow
+Growth into the Next Decade
+
+Permian premising
+~7% production growth, doubling
+free cash flow by end of decade
+
+Eagle Ford and Bakken
+delivering material free cash flow
+
+Delivering Continuous
+Improvements
+
+Accelerating technology
+across four core basins
+to enhance value
+
+Delivering on emissions reductions
+and sustainable development
+
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+ConocoPhillips 36
+
+--- end page 36
+
+# Deep, Durable and Diverse Portfolio with Significant Growth Runway
+
+2022 Lower 48 Unconventional Production¹ (MBOED)
+
+1,200
+~$32/BBL
+
+1,000 ConocoPhillips
+800
+600
+400
+200
+0
+Net Remaining Well Inventory2
+
+15,000
+ConocoPhillips
+12,000
+9,000
+6,000
+3,000
+0
+WTI Cost of Supply ($/BBL)
+Average
+Cost of Supply
+$40
+$30
+$20
+$10
+$0
+0
+2
+4
+6
+8
+10
+Resource (BBOE)
+Delaware Basin
+Midland Basin
+Eagle Ford
+Bakken
+Other
+
+Largest Lower 48 Unconventional Producer, Growing into the Next Decade
+
+¹Source: Wood Mackenzie Lower 48 Unconventional Plays 2022 Production. Competitors include CVX, DVN, EOG, FANG, MRO, OXY, PXD and XOM, greater than 50% liquids weight. ²Source: Wood Mackenzie (March 2023), Lower 48
+onshore operated inventory that achieves 15% IRR at $50/BBL WTI. Competitors include CVX, DVN, EOG, FANG, MRO, OXY, PXD, and XOM.
+
+ConocoPhillips 37
+
+--- end page 37
+
+# Delaware: Vast Inventory with Proven Track Record of Performance
+
+![Figure 1: Mapa de Nuevo México y Texas, mapa de la zona de Delaware con zonas de alto y bajo coste de suministro, gráfico circular de inventario operado de Permian a 10 años](image_reference)
+
+### Prolific Acreage Spanning Over ~659,000 Net Acres¹
+
+### 12-Month Cumulative Production³ (BOE/FT)
+
+[Graph 1: Producción acumulada de 12 meses]
+| Months | 2019 | 2020 | 2021 | 2022 |
+|---|---|---|---|---|
+| 1 | 5 | 6 | 7 | 7 |
+| 2 | 9 | 11 | 12 | 13 |
+| 3 | 12 | 14 | 16 | 18 |
+| 4 | 15 | 17 | 20 | 22 |
+| 5 | 18 | 20 | 23 | 26 |
+| 6 | 20 | 23 | 26 | 29 |
+| 7 | 23 | 25 | 29 | 32 |
+| 8 | 25 | 28 | 31 | 35 |
+| 9 | 27 | 30 | 34 | 37 |
+| 10 | 30 | 32 | 36 | 40 |
+| 11 | 32 | 34 | 38 | 41 |
+| 12 | 34 | 36 | 40 | 43 |
+
+~30% Improved Performance from 2019 to 2022
+
+### Delaware Basin Well Capex/EUR4 ($/BOE)
+
+[Graph 2: Capex/EUR de pozos en la cuenca de Delaware]
+|  | ConocoPhillips |  |  |  |  |  |  |  |
+|---|---|---|---|---|---|---|---|---|
+| Capex/EUR | 7.6 | 10.1 | 10.2 | 10.3 | 11.5 | 12.3 | 15.3 | 19.3 | 24.8 |
+
+**High Single-Digit Production Growth**
+
+¹Unconventional acres. ²Source: Enverus and ConocoPhillips (March 2023). ³Source: Enverus (March 2023) based on wells online year. ⁴Source: Enverus (March 2023). Average single well capex/EUR. Top eight public operators based on wells online in years 2021-2022, greater than 50% oil weight. COP based on COP well design. Competitors include: CVX, DVN, EOG, MTDR, OXY, PR and XOM.
+
+
+--- end page 38
+
+# Midland: Acreage in the Heart of Liquids-Rich Basin
+
+![Figure 1: New Mexico and Texas map with a high-margin play spanning over ~251,000 net acres. Total 10-Year Operated Permian Inventory is 35% Delaware Basin and Midland Basin. A cost of supply map of low and high supplies.](image_reference)
+
+High-Margin Play Spanning Over
+~251,000 Net Acres¹
+
+12-Month Cumulative Production³ (BOE/FT)
+
+![Graph 1: 12-Month Cumulative Production (BOE/FT), with months on the X axis and the rate on the Y axis.](image_reference)
+
+Midland Basin Well Capex/EUR4 ($/BOE)
+
+![Graph 2: Midland Basin Well Capex/EUR, with the company and amount in $/BOE.](image_reference)
+
+Low to Mid Single-Digit Production Growth
+
+Unconventional acres. ²Source: Enverus and ConocoPhillips (March 2023). ³Source: Enverus (March 2023) based on wells online year.
+4Source: Enverus (March 2023). Average single well capex/EUR. Top eight public operators based on wells online in years 2021-2022, greater than 50% oil weight. Competitors include FANG, OVV, OXY, PXD, SM, VTLE and XOM.
+
+--- end page 39
+
+# Continuously Optimizing Permian Acreage and Value
+
+## Acreage Trades
+### Illustration
+Pre-Trade
+
+Post-Trade
+
+ConocoPhillips Acreage Trade-in Trade-out
+
+### Trade Area
+LOVING
+
+REEVES
+
+## Permian-Operated Inventory
+Complementary Positions Enable
+Trade and Core-Up Opportunities
+
+~30-40% Cost of Supply Improvement
+from Lateral-Length Extensions
+
+~60%
+2 miles
+or greater
+
+## Recent Acreage Trade Metrics
+↑2x
+Lateral Length
+
+30%
+Capex/FT
+
+130%
+Cost of Supply
+
+~20%
+1.5 miles
+to 2 miles
+
+Vast Long-Lateral Inventory Enhances Returns and Durability
+
+ConocoPhillips 40
+
+
+--- end page 40
+
+# Permian Drives Free Cash Flow in Lower 48
+
+~7%
+10-Year Production CAGR
+
+Production (MBOED)
+
+Growing to Plateau
+in the 2nd Decade
+
+~$50%
+Reinvestment Rate¹
+
+< $35/BBL
+Program Cost of Supply
+
+FCF ($B)
+
+~$45B FCF
+Generated Over
+the Next 10 Years
+at $60/BBL WTI
+
+| 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- |
+| 2023E | 2024-2028 Average | 2029-2032 Average |
+| $60/BBL WTI Mid-Cycle Planning Price | $80/BBL WTI Upside Sensitivity |
+
+Top-Tier Permian Position, Growing into the Next Decade
+
+¹Over the next 10 years at $60/bbl.
+Reinvestment rate and free cash flow (FCF) are non-GAAP measures defined in the Appendix.
+
+--- end page 41
+
+# Eagle Ford and Bakken Delivering Material Free Cash Flow
+
+~199,000 Net Acres¹ in Eagle Ford
+~560,000 Net Acres¹ in Bakken
+
+Consistent and Proven Track Record
+in Basin Sweet Spots
+
+Sustains Production
+Over the Decade
+
+![Figure 1: Maps showing Eagle Ford and Bakken with areas shaded according to cost of supply.](image_reference)
+
+Eagle Ford
+
+Bakken
+
+Low
+High
+Cost of Supply²
+
+[Graph 1: Eagle Ford Well Capex/EUR³ ($/BOE)]
+|     | ConocoPhillips |
+| ----------- | ----------- |
+|     | 10 |
+|  | 20 |
+|  | 30 |
+
+[Graph 2: Bakken Well Capex/EUR⁴ ($/BOE)]
+|     | ConocoPhillips |
+| ----------- | ----------- |
+|     | 8 |
+|  | 10 |
+|  | 15 |
+
+[Graph 3: Production (MBOED)]
+| Metric | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+| Bakken | 100 | 100 | 90 |
+| Eagle Ford | 230 | 230 | 240 |
+|     | 300 | 300 | 300 |
+|  | 400 | 400 | 400 |
+
+Delivers ~$20B FCF
+Over the Next 10 Years at $60/BBL WTI
+
+¹Unconventional acres. ²Source: Enverus and ConocoPhillips (March 2023). ³Source: Enverus (March 2023); Average single well capex/EUR; Top eight public operators based on wells online in vintage years 2019-2022, greater than
+50% oil weight; Competitors include: BP, CHK, CPE, DVN, EOG, MGY and MRO. ⁴Source: Enverus (March 2023); Average single well capex/EUR; Top eight operators based on wells online in vintage years 2019-2022, greater than 50%
+oil weight; Competitors include CHRD, Continental, DVN, ERF, HES, MRO and XOM.
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+--- end page 42
+
+# Enhancing Value and Lowering Emissions through Technology
+
+## Drilling
+
+![Figure 1: Permian Real-Time Ops Center](image_reference)
+
+Permian Real-Time Ops Center
+
+Real-time analytics
+improve curve build
+time by 20% in Eagle Ford
+
+Permian drilling efficiencies¹
+improved ~50% since 2019
+
+## Completions
+
+![Figure 2: E-Frac](image_reference)
+
+E-Frac
+
+Dual fuel and E-frac
+reduce emissions ~10% to ~40%
+compared to diesel
+
+>50% of Permian completions
+to be Simulfrac'd in 2023
+
+## Operations
+
+![Figure 3: Autonomous Drone Pilot](image_reference)
+
+Autonomous Drone Pilot
+
+Real-time intelligent
+production surveillance, automation
+and process optimization
+
+Drone-based surveillance increases
+inspection frequency
+
+Leveraging Operational Wins Across Core Four Basins
+
+¹Permian drilling efficiencies defined as measured depth (feet) per day.
+
+
+--- end page 43
+
+# Delivering on Emissions Reductions and Sustainable Development
+
+Lower 48 GHG Intensity¹ (kg CO2e/BOE)
+
+28
+
+2019
+
+~50%
+Reduction
+
+<15
+
+2022²
+
+Lower 48 Associated Gas Flaring³ (%)
+
+1.7%
+
+~80%
+Reduction
+
+2019
+
+0.3%
+
+2022²
+
+Permian Recycled Frac Water (%)
+
+52%
+
+>3X
+Increase
+
+2019
+
+11%
+
+2022
+
+# Focused Plans to Further Reduce Emissions and Maximize Water Reuse
+
+Reducing
+Methane and Flaring
+
+Improving
+Facilities Design
+
+Electrifying
+Compression
+
+Optimizing
+D&C Power
+
+Water
+Conservation
+
+¹Gross operated GHG Emissions (Scope 1 and 2). ²Preliminary estimates. Includes Permian, Eagle Ford and Bakken only. ³Excludes safety, assist gas, pilot gas, tanks and emergency shutdown flaring.
+
+--- end page 44
+
+# Significant Free Cash Flow Growth Over the Decade
+
+## Capital ($B)
+
+[Graph 1: Capital ($B)]
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+|  | 6 | 7 | 8 |
+
+## Production (MBOED)
+
+[Graph 2: Production (MBOED)]
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+|  | 1,100 | 1,300 | 1,450 |
+
+## FCF ($B)
+
+[Graph 3: FCF ($B)]
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+|  | 6.5 | 8 | 12 |
+
+$80/BBL WTI
+Upside Sensitivity
+
+$60/BBL WTI
+Mid-Cycle Planning Price
+
+~$65B FCF and ~50% Reinvestment Rate
+Over the Next 10 Years at $60/BBL WTI
+
+--- end page 45
+
+ConocoPhillips
+
+# Financial Plan
+
+Bill Bullock
+EVP and CFO
+
+--- end page 46
+
+A Financial Plan with Durability of Returns and Cash Flow Growth
+
+Consistent Returns
+on and of Capital
+
+Peer-leading ROCE
+improving through time
+
+CFO-based distribution framework
+with compelling shareholder returns
+
+Cash Flow Growth
+into the Next Decade
+
+~6% CFO CAGR1
+through the plan
+
+Disciplined capital investment
+accelerates FCF growth
+
+Battle-Tested
+Financial Priorities
+
+'A'-rated balance sheet
+resilient through cycles
+
+Stress-tested
+financial durability
+
+1CAGR calculated from FY2024 at $60/BBL WTI.
+Return on capital employed (ROCE), cash from operations (CFO) and free cash flow (FCF) are non-GAAP measures defined in the Appendix.
+
+--- end page 47
+
+# Committed to Top-Quartile Returns on Capital
+
+## Five-Year Average ROCE¹
+Peer-Leading ROCE Performance
+
+![Figure 1: A bar chart displays five-year average ROCE. The y-axis is labeled with percentages from 0% to 16%, in increments of 2%. The x-axis displays data for ConocoPhillips, independent peers, and integrated peers. ConocoPhillips is represented by a red bar reaching 14%. Independent peers are represented by a series of grey bars of decreasing height. Integrated peers are represented by a series of darker grey bars, also decreasing in height.](image.png)
+
+## Earnings ($B)
+Low Cost of Supply Investments Fuel Expanding Margins
+
+~10% CAGR
+2024-2032 at $60/BBL WTI
+
+![Figure 2: A bar chart displays earnings in billions of dollars. The y-axis is labeled with values from 0 to 30. The x-axis displays the years 2023E, 2024-2028 Average, and 2029-2032 Average, each with a blue bar rising to around 11, 14, and 18 respectively.](image.png)
+
+## Return on Capital Employed (ROCE)
+Near-Term Delivery of S&P 500 Top-Quartile ROCE
+
+![Figure 3: A bar chart displays the return on capital employed (ROCE). The y-axis displays values from 0% to 40%, in increments of 10%. The x-axis shows 2023E, 2024-2028 Average, and 2029-2032 Average, each with a blue bar, and with a green line indicating the S&P 500 Top Quartile.](image.png)
+
+1Source: Bloomberg Return on Capital 2018 through 2022. 2Integrated peers include CVX and XOM. Independent peers include APA, DVN, EOG, HES, OXY and PXD. 3Represents top quartile of five-year average ROCE (2018-2022)
+for constituents as of December 31, 2022.
+Earnings refers to net income. Return on capital employed (ROCE) is a non-GAAP measure defined in the Appendix.
+
+
+--- end page 48
+
+# Cash Flow Growth into the Next Decade
+
+## Cash From Operations ($B)
+
+![Graph 1: Cash From Operations ($B)](image_reference)
+
+|                             | 2023E | 2024-2028 Average | 2029-2032 Average |
+| -------------------------- | ----- | ----------------- | ----------------- |
+| $60/BBL WTI Mid-Cycle Planning Price | 22    | 24                | 27                |
+| $80/BBL WTI Upside Sensitivity |       | 3                 | 7                 |
+
+~6% CAGR
+2024-2032 at $60/BBL WTI
+
+## Free Cash Flow ($B)
+
+![Graph 2: Free Cash Flow ($B)](image_reference)
+
+|                             | 2023E | 2024-2028 Average | 2029-2032 Average |
+| -------------------------- | ----- | ----------------- | ----------------- |
+| $60/BBL WTI Mid-Cycle Planning Price | 11    | 13                | 18                |
+| $80/BBL WTI Upside Sensitivity |       | 2                 | 5                 |
+
+~11% CAGR
+2024-2032 at $60/BBL WTI
+
+~$3.5B of Annual CFO is from
+Longer-Cycle Projects¹
+2029-2032 Average at $60/BBL WTI
+
+> $115B FCF Available
+for Distribution
+Over the Next 10 Years at $60/BBL WTI
+
+¹2029-2032 annual average CFO from longer-cycle projects of ~$5B at $80/BBL WTI. Longer-cycle projects are Willow, Port Arthur LNG Phase 1 and North Field Expansions.
+Cash from operations (CFO) and free cash flow (FCF) are non-GAAP measures defined in the Appendix.
+
+--- end page 49
+
+# CFO-Based Framework Delivers Leading Returns of Capital
+
+## Five-Year Distribution as % of CFO1
+Consistent Execution on Our Priorities
+
+![Graph 1: Five-Year Distribution as % of CFO1 Chart](image_reference)
+
+|        |  |
+| ----------- | ----------- |
+| ConocoPhillips | 44%  |
+| Integrated Peers³  | 41%  |
+| Independent Peers³   | 34% |
+
+## Five-Year Distribution Yield2
+Track Record of Leading Distributions
+
+![Graph 2: Five-Year Distribution Yield2 Chart](image_reference)
+
+|        |  |
+| ----------- | ----------- |
+| ConocoPhillips | 7%  |
+| Independent Peers³  | 6%  |
+| Integrated Peers³   | 5% |
+
+## Compelling Shareholder Returns Through Cycles
+
+### Tier 1
+Ordinary Dividend
+
+S&P Top-Quartile
+Dividend Growth
+
++
+
+### Tier 2
+Share Buybacks
+
+Reduces Absolute
+Dividend Over Time
+
++
+
+### Tier 3
+VROC
+
+Flexible Channel for
+Higher Commodity Prices
+
+<sup>1</sup>Source: Bloomberg. 2018-2022 weighted-average of dividend paid and share buybacks as a percentage of CFO. <sup>2</sup>Source: Bloomberg; 2018-2022 average of dividend paid and share buybacks as a percentage of year-end market cap.
+<sup>3</sup>Integrated peers include CVX and XOM. Independent peers include APA, DVN, EOG, HES, OXY and PXD.
+Cash from operations (CFO) is a non-GAAP measure defined in the Appendix.
+
+ConocoPhillips 50
+
+--- end page 50
+
+# Fortress Balance Sheet: A Strategic Asset
+
+### Gross Debt Profile
+
+$20B
+
+$3B
+
+$17B
+
+$2B
+
+$15B
+
+2021
+Debt Reduction
+Achieved
+2022
+Natural
+Maturities
+2026
+
+### On Target
+
+$5B debt reduction by 2026
+
+~$250MM/year interest reduction
+
+Weighted-average maturity extension of three years
+
+### Net Debt/CFO
+Consensus 2023¹
+
+3.0X
+
+2.0X
+
+1.0X
+
+0.0X
+
+Integrated
+Peers²
+ConocoPhillips
+0.3x
+Independent
+Peers ²
+S&P 500
+Energy
+S&P 500
+
+### Net Debt/CFO at $60/BBL WTI
+
+0.3x
+
+0.2x
+
+2024-2028
+Average
+2029-2032
+Average
+
+Source: Bloomberg Net Debt to CFO. As of March 30, 2023. ²Integrated peers include CVX and XOM. Independent peers include APA, DVN, EOG, HES, OXY and PXD.
+Net debt and cash from operations (CFO) are non-GAAP measures defined in the Appendix.
+
+--- end page 51
+
+# Plan Resilient Through Stress Test
+
+Our Rationale for Holding Cash
+
+1.5x
+Two-Year $40/BBL WTI¹ Stress Test
+Net Debt/CFO
+
+Longer-cycle projects
+
+1.0x
+Share buybacks
+
+0.5x
+Strategic
+Cash
+Down-cycle price protection
+
+0.0x
+2023
+Consensus²
+2024
+2025
+2026
+2027
+2028
+Business development
+optionality
+
+$60/BBL WTI (Base Plan) Two-Years at $40/BBL WTI
+Reserve Cash
+~$2-3B
+Maintain near-term
+operating plan even with
+price volatility
+
+Cash and CFO Fund Consistent Execution in Low Price Scenario
+
+Maintain capital program,
+including longer-cycle projects
+
+Meet 30% distribution commitment through
+ordinary dividend and share buybacks
+Operating Cash
+~$1B
+Daily operating and
+working capital
+
+<1.5x leverage ratio through the down-cycle
+
+No additional debt required
+
+¹2022 Real, escalating at 2.25% annually. ²Source: Bloomberg Net Debt to CFO. As of March 30, 2023.
+Net debt and cash from operations (CFO) are non-GAAP measures defined in the Appendix.
+
+--- end page 52
+
+# A Powerful Plan with Differential Upside
+
+$350
+
+10-Year Plan ($B)
+2023-2032
+
+$300
+
+CFO at
+$80/BBL WTI
+Upside Sensitivity
+
+$250
+
+$200
+
+$150
+
+$100
+
+$50
+Additional
+Distributions
+
+CFO at
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+
+30% of CFO
+Distribution
+Commitment
+
+Capital
+
+$0
+Cash 1
+
+Cash¹
+Sources
+Uses
+
+Peer leading ROCE improving through time
+
+Top quartile ordinary dividend growth
+
+>90% market cap² distributed
+
+~$35/BBL WTI FCF Breakeven³
+
+~6% CFO CAGR, ~11% FCF CAGR
+
+Unhedged for price upside
+
+Cash includes cash, cash equivalents, restricted cash and short-term investments. ²Market cap of ~$121B at March 31, 2023 close. ³Average over the next 10 years.
+CAGRs calculated from FY2024 at $60/BBL WTI. Cash from operations (CFO), free cash flow (FCF) and return on capital employed (ROCE) are non-GAAP measures. Definitions are included in the Appendix.
+
+ConocoPhillips 53
+
+
+--- end page 53
+
+ConocoPhillips
+
+# Closing
+
+Ryan Lance
+Chairman and CEO
+
+--- end page 54
+
+# ConocoPhillips Remains the Must-Own E&P Company
+
+## What You
+## Heard Today
+
+We are committed to
+delivering superior returns
+**on** and **of** capital
+through the cycles
+
+We have a **deep, durable**
+and **diverse** portfolio
+
+We are progressing our
+**2050 Net-Zero ambition** and
+accelerating our 2030 GHG emissions
+intensity reduction target
+
+## Foundational
+## Principles
+
+Balance Sheet
+Strength
+
+Disciplined
+Investments
+
+**RETURNS**
+
+Peer-Leading
+Distributions
+
+ESG
+Excellence
+
+Deliver Superior Returns
+Through Cycles
+
+## A Compelling Returns
+## Focused 10-Year Plan
+
+*Peer leading* ROCE
+*improving through time*
+
+**Top quartile** ordinary dividend growth
+
+**>90% market cap¹ distributed**
+
+**~$35/BBL** WTI FCF Breakeven²
+
+**~6%** CFO CAGR, **~11%** FCF CAGR
+
+Unhedged for **price upside**
+
+¹Market cap of ~$121B at March 31, 2023 close. ²Average over the next ten years.
+CAGRs calculated from FY2024 at $60/BBL WTI. Cash from operations (CFO), free cash flow (FCF) and return on capital employed (ROCE) are non-GAAP measures defined in the appendix.
+
+ConocoPhillips 55
+
+--- end page 55
+
+ConocoPhillips
+# Appendix
+
+Reconciliations, Abbreviations and Definitions
+
+--- end page 56
+
+# Abbreviations
+
+APLNG: Australia Pacific LNG
+B: billion
+BBL: barrel
+BBOE: billions of barrels of oil equivalent
+BCFD: billion cubic feet per day
+BOE: barrels of oil equivalent
+CAGR: compound annual growth rate
+CAPEX: capital expenditures and investments
+CCS: carbon capture and storage
+CFO: cash from operations
+CO2: carbon dioxide
+CO₂e: carbon dioxide equivalent
+CoS: Cost of Supply
+CPF: central processing facility
+E-FRAC: electric frac
+EMENA: Europe, Middle East and North Africa
+EPC: engineering procurement and construction
+ESG: environmental, social and governance
+EUR: estimated ultimate recovery
+FEED: front end engineering design
+FERC: Federal Energy Regulatory Commission
+FCF: free cash flow
+FID: final investment decision
+FT: foot
+G&A: general and administrative
+GAAP: generally accepted accounting principles
+GHG: greenhouse gas emissions
+
+GKA: Greater Kuparuk Area
+GPA: Greater Prudhoe Area
+GWA: Greater Willow Area
+GWh: gigawatt-hour
+KG: kilograms
+LNG: liquefied natural gas
+MBOD: thousands of barrels of oil per day
+MBOED: thousands of barrels of oil equivalent per day
+MM: million
+MMBOD: millions of barrels of oil per day
+MMBOED: millions of barrels of oil equivalent per day
+MT: million tonnes
+MTPA: million tonnes per annum
+MWh: megawatt-hour
+NFE: North Field East
+NFS: North Field South
+NGL: natural gas liquids
+OPEX: operating expenses
+PA LNG: Port Arthur LNG
+QG3: Qatargas 3
+ROCE: return on capital employed
+Te: tonnes
+THE: Trading Hub Europe
+VROC: variable return of cash
+WNS: Western North Slope
+WTI: West Texas Intermediate
+
+ConocoPhillips 57
+
+--- end page 57
+
+# Non-GAAP Reconciliations
+
+Use of Non-GAAP Financial Information: ConocoPhillips' financial information includes information prepared in conformity with generally accepted accounting principles
+(GAAP) as well as non-GAAP information. It is management's intent to provide non-GAAP financial information to enhance understanding of our consolidated financial information
+as prepared in accordance with GAAP. This non-GAAP information should be considered by the reader in addition to, but not instead of, the financial statements prepared in
+accordance with GAAP. Each historical non-GAAP financial measure included in this presentation is presented along with the corresponding GAAP measure, so as not to imply that
+more emphasis should be placed on the non-GAAP measure. The non-GAAP financial information presented may be determined or calculated differently by other companies.
+
+# Reconciliation of Return on Capital Employed (ROCE)
+
+[Table 1: Reconciliation of Return on Capital Employed (ROCE)]
+|                                                                  | 2016    | 2019    | 2022    |
+| ---------------------------------------------------------------- | ------- | ------- | ------- |
+| **Numerator**                                                    |         |         |         |
+| Net Income (Loss) Attributable to ConocoPhillips                | (3,615) | 7,189   | 18,680  |
+| Adjustment to Exclude Special Items                              | 307     | (3,153) | (1,340) |
+| Net Income Attributable to Noncontrolling Interests             | 56      | 68      | -       |
+| After-tax Interest Expense                                       | 796     | 637     | 641     |
+| ROCE Earnings                                                    | (2,456) | 4,741   | 17,981  |
+|                                                                  |         |         |         |
+| **Denominator**                                                  |         |         |         |
+| Average Total Equity¹                                            | 37,837  | 33,713  | 48,801  |
+| Average Total Debt²                                              | 28,225  | 14,930  | 17,742  |
+| Average Capital Employed                                         | 66,062  | 48,643  | 66,543  |
+|                                                                  |         |         |         |
+| ROCE (percent)                                                   | -4%     | 10%     | 27%     |
+
+¹Average total equity is the average of beginning total equity and ending total equity by quarter.
+²Average total debt is the average of beginning long-term debt and short-term debt and ending long-term debt and short-term debt by quarter.
+
+--- end page 58
+
+# Non-GAAP Reconciliations – Continued
+
+Reconciliation of Net Cash Provided by Operating Activities to Cash from Operations to Free Cash Flow
+($ Millions, Except as Indicated)
+
+|                     | 2016  | 2019  | 2022  |
+|---------------------|-------|-------|-------|
+| Net Cash Provided by Operating Activities | 4,403 | 11,104 | 28,314 |
+| Adjustments:          |       |       |       |
+| Net Operating Working Capital Changes | (481) | (579) | (234) |
+| Cash from Operations  | 4,884 | 11,683 | 28,548 |
+| Capital Expenditures and Investments | (4,869) | (6,636) | (10,159) |
+| Free Cash Flow        | 15    | 5,047 | 18,389 |
+
+Reconciliation of Debt to Net Debt ($ Millions, Except as Indicated)
+
+|                | 2016   | 2019   | 2022   |
+|----------------|--------|--------|--------|
+| Total Debt     | 27,275 | 14,895 | 16,643 |
+| Less:          |        |        |        |
+| Cash and Cash Equivalents¹ | 3,610  | 5,362  | 6,694  |
+| Short-Term Investments | 50     | 3,028  | 2,785  |
+| Net Debt         | 23,615 | 6,505  | 7,164  |
+
+¹Includes restricted cash of $0.3B in 2019 and $0.2B in 2022.
+
+--- end page 59
+
+## Non-GAAP Reconciliations – Continued
+
+Reconciliation of Reinvestment Rate ($ Millions, Except as Indicated)
+
+[Table 1: Reconciliation of Reinvestment Rate]
+|                        | 2012  | 2013  | 2014  | 2015  | 2016  | 2017  | 2018  | 2019  | 2020  | 2021  | 2022  |
+| :--------------------- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- |
+| Numerator              |       |       |       |       |       |       |       |       |       |       |       |
+| Capital Expenditure and Investments | 14,172 | 15,537 | 17,085 | 10,050 | 4,869 | 4,591 | 6,750 | 6,636 | 4,715 | 5,324 | 10,159 |
+| Denominator            |       |       |       |       |       |       |       |       |       |       |       |
+| Net Cash Provided by Operating Activities | 13,922 | 16,087 | 16,735 | 7,572 | 4,403 | 7,077 | 12,934 | 11,104 | 4,802 | 16,996 | 28,314 |
+| Net Operating Working Capital Changes | (1,239) | 48    | (505) | (22)  | (481) | 15    | 635   | (579) | (372) | 1,271 | (234) |
+| Cash from Operations   | 15,161 | 16,039 | 17,240 | 7,594 | 4,884 | 7,062 | 12,299 | 11,683 | 5,174 | 15,725 | 28,548 |
+| Reinvestment Rate      | 93%   | 97%   | 99%   | 132%  | 100%  | 65%   | 55%   | 57%   | 91%   | 34%   | 36%   |
+
+**104%** Average 2012-2016 Reinvestment Rate
+
+**56%** Average 2017-2022 Reinvestment Rate
+
+Reinvestment rates in 2012-2016 and 2017-2022 columns represent the simple averages of corresponding years.
+
+--- end page 60
+
+# Definitions
+
+Non-GAAP Measures
+
+Cash from operations (CFO) is calculated by removing the impact from operating working capital from cash provided by operating activities. The company believes that the non-
+GAAP measure cash from operations is useful to investors to help understand changes in cash provided by operating activities excluding the impact of working capital changes
+across periods on a consistent basis and with the performance of peer companies in a manner that, when viewed in combination with the Company's results prepared in accordance
+with GAAP, provides a more complete understanding of the factors and trends affecting the Company's business and performance. Additionally, when the company estimates CFO
+based on sensitivities, it assumes no operating working capital changes, and therefore CFO equals cash provided by operating activities.
+
+Free cash flow is defined as cash from operations net of capital expenditures and investments. The company believes free cash flow is useful to investors in understanding how
+existing cash from operations is utilized as a source for sustaining our current capital plan and future development growth. Free cash flow is not a measure of cash available for
+discretionary expenditures since the company has certain non-discretionary obligations such as debt service that are not deducted from the measure.
+
+Net debt includes total balance sheet debt less cash, cash equivalents and short-term investments. The company believes this non-GAAP measure is useful to investors as it
+provides a measure to compare debt less cash, cash equivalents and short-term investments across periods on a consistent basis.
+
+Reinvestment rate defined as total capital expenditures divided by cash from operations. Cash from operations is a non-GAAP measure defined in this Appendix. The company
+believes reinvestment rate is useful to investors in understanding the execution of the company's disciplined and returns-focused capital allocation strategy.
+
+Return on capital employed (ROCE) is a measure of the profitability of the company's capital employed in its business operations compared with that of its peers. The company
+calculates ROCE as a ratio, the numerator of which is net income, and the denominator of which is average total equity plus average total debt. The net income is adjusted for
+after-tax interest expense, for the purposes of measuring efficiency of debt capital used in operations; net income is also adjusted for non-operational or special items impacts to
+allow for comparability in the long-term view across periods. The company believes ROCE is a good indicator of long-term company and management performance as it relates to
+capital efficiency, both absolute and relative to the company's primary peer group.
+
+--- end page 61
+
+# Definitions
+
+Other Terms
+Cost of Supply is the WTI equivalent price that generates a 10% after-tax return on a point-forward and fully burdened basis. Fully burdened includes capital infrastructure, foreign
+exchange, price-related inflation, G&A and carbon tax (if currently assessed). If no carbon tax exists for the asset, carbon pricing aligned with internal energy scenarios are applied.
+All barrels of resource in the Cost of Supply calculation are discounted at 10%.
+
+Distributions is defined as the total of the ordinary dividend, share repurchases and variable return of cash (VROC). Also referred to as return of capital.
+
+Free cash flow breakeven is the WTI price at which cash from operations equals capital expenditures and investments. Also referred to as capital breakeven. Cash from operations
+is a non-GAAP measure defined in this Appendix.
+
+Leverage ratio refers to net debt divided by cash from operations. Net debt and cash from operations are non-GAAP measures defined in this Appendix.
+
+Optimized Cascade® Process is a ConocoPhillips proprietary licensed process for technology to liquefy natural gas. More information can be found at
+http://Inglicensing.conocophillips.com/what-we-do/Ing-technology/optimized-cascade-process.
+
+Reserve replacement is defined by the Company as a ratio representing the change in proved reserves, net of production, divided by current year production. The Company
+believes that reserve replacement is useful to investors to help understand how changes in proved reserves, net of production, compare with the Company's current year
+production, inclusive of acquisitions and dispositions.
+
+Resources: The company estimates its total resources based on the Petroleum Resources Management System (PRMS), a system developed by industry that classifies recoverable
+hydrocarbons into commercial and sub-commercial to reflect their status at the time of reporting. Proved, probable and possible reserves are classified as commercial, while
+remaining resources are categorized as sub-commercial or contingent. The company's resource estimate includes volumes associated with both commercial and contingent
+categories. The SEC permits oil and gas companies, in their filings with the SEC, to disclose only proved, probable and possible reserves. U.S. investors are urged to consider closely
+the oil and gas disclosures in our Form 10-K and other reports and filings with the SEC.
+
+Resource life is calculated as total resource under $40 Cost of Supply divided by 2022 production.
+
+Return of capital is defined as the total of the ordinary dividend, share repurchases and variable return of cash (VROC). Also referred to as distributions.
+
+--- end page 62
+

data/cache/2023-conocophillips-aim-presentation.pdf.reformatted.md

@@ -0,0 +1,2390 @@
+# ConocoPhillips 2023 Analyst & Investor Meeting
+
+--- end page 1
+
+## Today's Agenda
+
+*   Opening
+    *   Ryan Lance Chairman and CEO
+
+*   Strategy and Portfolio
+    *   Dominic Macklon EVP, Strategy, Sustainability and Technology
+
+*   Alaska and International
+    *   Andy O'Brien SVP, Global Operations
+
+*   LNG and Commercial
+    *   Bill Bullock EVP and CFO
+
+*   Lower 48
+    *   Nick Olds EVP, Lower 48
+
+*   Financial Plan
+    *   Bill Bullock EVP and CFO
+
+*   Closing
+    *   Ryan Lance Chairman and CEO
+
+*   10-Minute Break
+
+*   Q&A Session
+
+ConocoPhillips
+2
+
+--- end page 2
+
+## Cautionary Statement
+
+This presentation provides management's current operational plan for ConocoPhillips over roughly the next decade, for the assets currently in our portfolio, and is subject to multiple assumptions, including, unless otherwise specifically noted:
+
+*   an oil price of $60/BBL West Texas Intermediate in 2022 dollars, escalating at 2.25% annually;
+*   an oil price of $65/BBL Brent in 2022 dollars, escalating at 2.25% annually;
+*   a gas price of $3.75/MMBTU Henry Hub in 2022 dollars, escalating at 2.25% annually;
+*   an international gas price of $8/MMBTU Title Transfer Facility & Japan Korea Marker in 2022 dollars, escalating at 2.25% annually;
+*   cost and capital escalation in line with price escalation; planning case at $60/BBL WTI assumes capital de-escalation from levels observed in 2022;
+*   all production compound annual growth rates (CAGR) are calculated for the 10-year period 2023 - 2032;
+*   inclusion of carbon tax in the cash flow forecasts for assets where a tax is currently assessed. If no carbon tax exists for the asset, it is not included in the cash flow forecasts;
+*   Cost of Supply displayed in WTI, includes carbon tax where carbon policy exists and a proxy carbon price for assets without existing carbon policies. Please refer to the Cost of Supply definition in the Appendix for additional information on how carbon costs are included in the Cost of Supply calculation.
+
+As a result, this presentation contains forward-looking statements as defined under the federal securities laws. Forward-looking statements relate to future events, plans and anticipated results of operations, business strategies, and other aspects of our operations or operating results. Graphics that project into a future date constitute forward-looking statements. Also, words and phrases such as "anticipate," "estimate," "believe," "budget," "continue," "could," "intend," "may," "plan," "potential," "predict," "seek," "should," "will," "would," "expect," "objective," "projection," "forecast," "goal," "guidance," "outlook," "effort," "target" and other similar words can be used to identify forward-looking statements. However, the absence of these words does not mean that the statements are not forward-looking.
+
+Where, in any forward-looking statement, the company expresses an expectation or belief as to future results, such expectation or belief is based on management's good faith plans and objectives under the assumptions set forth above (unless noted otherwise) and believed to be reasonable as of April 12, 2023, the date of this presentation. These statements are not guarantees of future performance and involve certain risks and uncertainties and are subject to change as management is continually assessing factors beyond our control that may or may not be currently known. Given the foregoing and the extended time horizon of this presentation, actual outcomes and results will likely differ from what is expressed or forecast in the forward-looking statements, and such differences may be material. Factors that could cause actual results or events to differ materially from what is presented include changes in commodity prices, including a prolonged decline in these prices relative to historical or future expected levels; global and regional changes in the demand, supply, prices, differentials or other market conditions affecting oil and gas, including changes resulting from any ongoing military conflict, including the conflict between Russia and Ukraine and the global response to such conflict, security threats on facilities and infrastructure, or from a public health crisis or from the imposition or lifting of crude oil production quotas or other actions that might be imposed by OPEC and other producing countries and the resulting company or third-party actions in response to such changes; insufficient liquidity or other factors, such as those listed herein, that could impact our ability to repurchase shares and declare and pay dividends such that we suspend our share repurchase program and reduce, suspend, or totally eliminate dividend payments in the future, whether variable or fixed; changes in expected levels of oil and gas reserves or production; potential failures or delays in achieving expected reserve or production levels from existing and future oil and gas developments, including due to operating hazards, drilling risks or unsuccessful exploratory activities; unexpected cost increases, inflationary pressures or technical difficulties in constructing, maintaining or modifying company facilities; legislative and regulatory initiatives addressing global climate change or other environmental concerns; public health crises, including pandemics (such as COVID-19) and epidemics and any impacts or related company or government policies or actions; investment in and development of competing or alternative energy sources; potential failures or delays in delivering on our current or future low-carbon strategy, including our inability to develop new technologies; disruptions or interruptions impacting the transportation for our oil and gas production; international monetary conditions and exchange rate fluctuations; changes in international trade relationships or governmental policies, including the imposition of price caps or the imposition of trade restrictions or tariffs on any materials or products (such as aluminum and steel) used in the operation of our business, including any sanctions imposed as a result of any ongoing military conflict, including the conflict between Russia and Ukraine; our ability to collect payments when due, including our ability to collect payments from the government of Venezuela or PDVSA; our ability to complete any announced or any future dispositions or acquisitions on time, if at all; the possibility that regulatory approvals for any announced or any future dispositions or acquisitions will not be received on a timely basis, if at all, or that such approvals may require modification to the terms of the transactions or our remaining business; business disruptions following any announced or future dispositions or acquisitions, including the diversion of management time and attention; the ability to deploy net proceeds from our announced or any future dispositions in the manner and timeframe we anticipate, if at all; potential liability for remedial actions under existing or future environmental regulations; potential liability resulting from pending or future litigation, including litigation related directly or indirectly to our transaction with Concho Resources Inc.; the impact of competition and consolidation in the oil and gas industry; limited access to capital or insurance or significantly higher cost of capital or insurance related to illiquidity or uncertainty in the domestic or international financial markets or investor sentiment; general domestic and international economic and political conditions or developments, including as a result of any ongoing military conflict, including the conflict between Russia and Ukraine; changes in fiscal regime or tax, environmental and other laws applicable to our business; and disruptions resulting from accidents, extraordinary weather events, civil unrest, political events, war, terrorism, cybersecurity threats or information technology failures, constraints or disruptions; and other economic, business, competitive and/or regulatory factors affecting our business generally as set forth in our filings with the Securities and Exchange Commission. Unless legally required, ConocoPhillips expressly disclaims any obligation to update any forward-looking statements, whether as a result of new information, future events or otherwise. We assume no duty to update these statements as of any future date and neither future distribution of this material nor the continued availability of this material in archive form on our website should be deemed to constitute an update or re-affirmation of these figures as of any future date. Any future update of these figures will be provided only through a public disclosure indicating that fact.
+
+Use of Non-GAAP Financial Information - This presentation includes non-GAAP financial measures, which help facilitate comparison of company operating performance across periods and with peer companies. Any historical non-GAAP measures included herein will be accompanied by a reconciliation to the nearest corresponding GAAP measure both at the end of this presentation and on our website at www.conocophillips.com/nongaap. For forward-looking non-GAAP measures, we are unable to provide a reconciliation to the most comparable GAAP financial measures because the information needed to reconcile these measures is dependent on future events, many of which are outside management's control as described above. Additionally, estimating such GAAP measures and providing a meaningful reconciliation consistent with our accounting policies for future periods is extremely difficult and requires a level of precision that is unavailable for these future periods and cannot be accomplished without unreasonable effort. Forward looking non-GAAP measures are estimated consistent with the relevant definitions and assumptions.
+
+Cautionary Note to U.S. Investors - The SEC permits oil and gas companies, in their filings with the SEC, to disclose only proved, probable and possible reserves. We use terms and metrics such as "resource" or "Estimated Ultimate Recovery (EUR)" in this presentation that we are prohibited from using in filings with the SEC under the SEC's guidelines. U.S. investors are urged to consider closely the oil and gas disclosures in our Form 10-K and other reports and filings with the SEC. Copies are available from the SEC and from the ConocoPhillips website.
+
+ConocoPhillips 3
+
+--- end page 3
+
+## Opening
+
+Ryan Lance
+Chairman and CEO
+
+ConocoPhillips
+Opening
+Ryan Lance
+Chairman and CEO
+
+--- end page 4
+
+## ConocoPhillips Remains the Must-Own E&P Company
+
+![Oil Price Chart]
+
+120
+100
+The Macro
+Oil Price ($/BBL WTI)
+What You'll Hear Today
+We are committed to
+delivering superior returns
+**on** and **of** capital
+through the cycles
+
+80
+60
+40
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+We have a **deep, durable**
+and **diverse** portfolio
+
+20
+0
+2019
+2021
+2023
+2024+
+We are progressing our
+**2050 Net-Zero ambition** and
+accelerating our 2030 GHG emissions
+intensity reduction target
+
+ConocoPhillips
+5
+
+--- end page 5
+
+## We Are Committed to Our Returns-Focused Value Proposition
+
+### Triple Mandate
+Aligned to Business Realities
+
+![Figure 1: Triple Mandate with three sections: MEET TRANSITION PATHWAY DEMAND (green), DELIVER COMPETITIVE RETURNS (orange), ACHIEVE NET-ZERO EMISSIONS AMBITION¹ (blue)](image_reference)
+
+### Foundational Principles
+
+![Figure 2: Foundational Principles including Balance Sheet Strength, RETURNS, Disciplined Investments, Peer-Leading Distributions, ESG Excellence, Deliver Superior Returns Through Cycles](image_reference)
+
+### Clear and Consistent Priorities
+1
+Sustain production
+and pay dividend
+
+2
+Annual dividend growth
+
+3
+'A'-rated balance sheet
+
+4
+>30% of CFO
+shareholder payout
+
+5
+Disciplined investment
+to enhance returns
+
+¹Scope 1 and 2 emissions on a gross operated and net equity basis.
+Cash from operations (CFO) is a non-GAAP measure defined in the Appendix.
+
+--- end page 6
+
+## We Are Continuously Improving
+
+|                                  | 2016        | 2019        | 2022        |
+| :------------------------------- | :---------- | :---------- | :---------- |
+|                                  | $43/BBL WTI | $57/BBL WTI | $94/BBL WTI |
+| Return on Capital Employed       | -4%         | 10%         | 27%         |
+| Return of Capital¹               | $1.11/share | $4.45/share | $11.73/share |
+| Net Debt                         | $24B        | $7B         | $7B         |
+| Cash From OperationsFree Cash Flow | $5B \| $OB | $12B \| $5B | $29B \| $18B |
+| Resource <$40/BBL WTI            | ~10 BBOE    | ~15 ВВОЕ    | ~20 BBOE    |
+| Production                       | 1.6 MMBOED  | 1.3 MMBOED  | 1.7 MMBOED  |
+| Emissions Intensity²(kg CO2e/BOE) | ~39         | ~36         | ~22         |
+
+Foundational
+Principles
+
+Peer-Leading
+Distributions
+and Returns
+
+Balance Sheet
+Strength
+
+Disciplined
+Investments
+
+ESG
+Excellence
+
+¹Defined in the Appendix and presented on a per-share basis using average outstanding diluted shares. ²Gross operated GHG emissions (Scope 1 and 2), 2022 is a preliminary estimate.
+Cash from operations (CFO), free cash flow (FCF), net debt and return on capital employed (ROCE) are non-GAAP measures. Definitions and reconciliations are included in the Appendix.
+
+--- end page 7
+
+## We Have a Compelling 10-Year Plan that Sets us Apart
+
+![10-Year Plan Graph]
+
+$350
+$300
+$250
+$200
+$150
+$100
+$50
+10-Year Plan ($B)
+CFO at
+2023-2032
+$80/BBL WTI
+Upside Sensitivity
+CFO at
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+Additional
+Distributions
+30% of CFO
+Distribution
+Commitment
+Capital
+$0
+Cash 1
+Cash¹
+Sources
+Uses
+
+Peer leading ROCE improving through time
+
+Top quartile ordinary dividend growth
+
+>90% market cap² distributed
+
+~$35/BBL WTI FCF Breakeven³
+
+~6% CFO CAGR, ~11% FCF CAGR
+
+Unhedged for price upside
+
+Cash includes cash, cash equivalents, restricted cash and short-term investments. 2Market cap of ~$121B at March 31, 2023, close. 3Average over the next 10 years.
+CAGRs calculated from FY2024 at $60/BBL WTI. Cash from operations (CFO), free cash flow (FCF) and return on capital employed (ROCE) are non-GAAP measures. Definitions are included in the Appendix.
+
+ConocoPhillips 8
+
+--- end page 8
+
+## Strategy and Portfolio
+
+Dominic Macklon
+EVP, Strategy, Sustainability and Technology
+
+ConocoPhillips
+Strategy and Portfolio
+Dominic Macklon
+EVP, Strategy, Sustainability and Technology
+
+--- end page 9
+
+## Strategy Powers Our Returns-Focused Value Proposition
+
+$
+### Rigorous Capital Allocation Framework
+
+*   Commitment to disciplined reinvestment rate
+*   Cost of Supply analysis informs investment decisions
+
+### Differentiated Portfolio
+Depth, Durability and Diversity
+
+*   ~20 BBOE, <$40/BBL WTI low Cost of Supply resource base
+*   Leading Lower 48 unconventional position, complemented with premium Alaska and International assets
+*   Balance of short-cycle, flexible unconventional with select longer-cycle, low-decline conventional
+
+### Valued Role in the Energy Transition
+
+*   Accelerating GHG-intensity reduction target through 2030
+*   Built attractive LNG portfolio
+*   Strong track record of active portfolio management
+*   Evaluating longer term low-carbon options in hydrogen and CCS
+
+Reinvestment rate is a non-GAAP measure defined in the Appendix.
+ConocoPhillips 10
+
+--- end page 10
+
+## Commitment to Disciplined Reinvestment Rate
+
+### Industry Growth Focus
+
+>100%
+Reinvestment Rate
+
+### ConocoPhillips Strategy Reset
+
+<60%
+Reinvestment Rate
+
+### Disciplined Reinvestment Rate is the Foundation for Superior Returns on and of Capital, while Driving Durable CFO Growth
+
+~50%
+10-Year
+Reinvestment Rate
+
+~6%
+CFO CAGR
+2024-2032
+
+at $60/BBL WTI
+Mid-Cycle
+Planning Price
+
+ConocoPhillips Average Annual Reinvestment Rate (%)
+
+![Reinvestment Rate Chart]
+
+100%
+
+75%
+
+50%
+
+25%
+
+~$75/BBL
+WTI
+Average
+
+~$63/BBL
+WTI
+Average
+
+0%
+
+2012-2016
+
+2017-2022
+
+at $80/BBL
+WTI
+
+2023E
+
+at $60/BBL
+WTI
+
+at $80/BBL
+WTI
+
+at $80/BBL
+WTI
+
+at $60/BBL
+WTI
+
+2024-2028
+
+2029-2032
+
+Historic Reinvestment Rate
+Reinvestment Rate at $60/BBL WTI
+--- Reinvestment Rate at $80/BBL WTI
+
+Reinvestment rate and cash from operations (CFO) are non-GAAP measures. Definitions and reconciliations are included in the Appendix.
+ConocoPhillips 11
+
+--- end page 11
+
+## Cost of Supply Analysis Informs Investment Decisions
+
+### Cost of Supply = Our North Star
+
+$/BBL WTI Oil Price Required to Achieve a Point-Forward 10% Return
+
+Fully Burdened Metric
+With All Components Rigorously
+Calculated For Each Entity
+
+![WTI Cost of Supply chart]
+
+WTI Cost of Supply ($/BBL)
+
+Facilities
+
+G&A
+Transport
+Lifting
+
+Wells
+
+Capital
+
+<$40/BBL
+
+OPEX
+
+Royalty
+
+Taxes
+
+Product Mix
+
+Differential to WTI
+
+WTI COS
+
+Low Cost of Supply Wins
+
+Reflective of a typical Permian development well.
+
+ConocoPhillips
+12
+
+--- end page 12
+
+## Secondary Investment Criteria Reinforce Resilient, Durable Returns
+
+### Investment Criteria
+
+Balanced, Diversified, Disciplined Production Growth
+
+*   Production Mix¹
+    *   Oil ~55%
+    *   NGL ~15%
+    *   North American Gas ~15%
+    *   International Gas ~15%
+
+*   Production (MBOED)
+
+### Secondary Criteria
+
+*   Disciplined Reinvestment Rate
+*   Returns of capital
+*   Cost of Supply
+*   Returns on capital
+
+*   Balance of short-cycle, flexible unconventional with longer-cycle, low-decline conventional
+*   Product mix and market exposure
+*   Predictable execution
+
+¹Average anticipated production mix from 2023-2032; oil includes bitumen.
+Reinvestment rate is a non-GAAP measure defined in the Appendix.
+
+[Graph 1: Production (MBOED)]
+| Year | Production CAGR | LNG + Surmont | Conventional | Unconventional (Lower 48 + Montney) |
+|---|---|---|---|---|
+| 2023E | ~4-5% 10-Year Production CAGR |  |  |  |
+|  |  | ~2% CAGR | ~3% CAGR | ~6% CAGR |
+| 2032 |  |  |  |  |
+
+--- end page 13
+
+## Our Differentiated Portfolio: Deep, Durable and Diverse
+
+$50
+
+~20 BBOE of Resource
+Under $40/BBL Cost of Supply
+
+~$32/BBL
+Average Cost of Supply
+
+### Diverse Production Base
+
+10-Year Plan Cumulative Production (BBOE)
+
+Lower 48
+
+Alaska
+
+![WTI Cost of Supply Chart]
+
+WTI Cost of Supply ($/BBL)
+$40
+
+$30
+
+$20
+
+$10
+
+$0
+0
+5
+10
+15
+Resource (BBOE)
+Lower 48
+Canada
+Alaska
+ΕΜΕΝΑ
+Asia Pacific
+
+Costs assume a mid-cycle price environment of $60/BBL WTI.
+Permian
+GKA
+GWA
+GPA WNS
+EMENA
+Norway
+Qatar Libya
+Asia Pacific Canada
+Montney
+APLNG
+20
+Bakken
+Eagle Ford
+Other
+Malaysia China Surmont
+
+ConocoPhillips
+14
+
+--- end page 14
+
+## Strong Track Record of Active Portfolio Management
+
+|                     | 2016            | 2022            |
+|---------------------|-----------------|-----------------|
+| Production          | 1.6 MMBOED      | 1.7 MMBOED      |
+| Resource <$40/BBL WTI | ~10 BBOE        | ~20 BBOE        |
+| Average Cost of Supply | <$40/BBL WTI    | ~$32/BBL WTI    |
+| Resource Life       | >18 years        | >30 years        |
+| Emissions Intensity¹ | ~39 kg CO₂e/BOE | ~22 kg CO2e/BOE |
+
+ | WNS and GKA Working Interest Consolidations |
+ |---|
+ | 2018 |
+ | Montney Acreage Acquisition | Concho and Shell Permian Acquisitions | APLNG Acquisition |
+ |---|---|---|
+ | 2020 | 2021 | 2022 |
+ | 2017 | 2019 |  |
+ |---|---|---|
+ | San Juan Exit Canada Cenovus Transaction | U.K. Exit | Niobrara and Australia-West Exits | Indonesia Exit |
+
+Cost of Supply Framework Drives Disciplined Transactions
+~$25B of Both Acquisitions and Divestitures Since 20162
+
+¹Gross operated GHG emissions (Scope 1 and 2), 2022 is a preliminary estimate. ²Dispositions include contingent payment proceeds and sale of CVE shares.
+
+--- end page 15
+
+## Accelerating Our GHG-Intensity Reduction Target Through 2030
+
+### Emissions Reduction Opportunities
+Pathway to Net-Zero¹
+
+*   Methane Venting and Flaring
+*   Electrification
+*   Optimization and Efficiency
+*   Strategic Pilots and Studies
+
+![Figure 1: Graph illustrates Pathway to Net-Zero Emissions Intensity (kg CO2e/BOE)](image_reference)
+
+Emissions Intensity (kg CO2e/BOE)
+
+*   Near-Term (2025)
+    *   Zero routine flaring by 2025²
+
+*   Medium-Term (2030)
+    *   NEW: Reduce GHG intensity 50-60% (from 40-50%)³
+    *   Near-zero methane intensity target <1.5 kg CO2e/BOE
+
+*   Long-Term (2050)
+    *   Net-zero emissions ambition¹
+
+Progressing Toward Net-Zero Ambition
+
+¹Scope 1 and 2 emissions on a gross operated and net equity basis. ²In line with the World Bank Zero Routine Flaring initiative, ConocoPhillips premise is five years earlier than World Bank 2030 goal.
+³ Reduction from a 2016 baseline.
+
+ConocoPhillips 16
+
+--- end page 16
+
+## LNG: A Crucial Fuel for Energy Transition
+
+### U.S. Electric Power Sector Emissions
+Drop with Shift from Coal to Natural Gas¹
+
+![Figure 1: Line chart showing the percentage share of electricity generation from coal and gas in the US from 2001 to 2021. Coal decreases from 51% to 40%, while gas increases from 17% to 20%.](image_reference)
+
+![Figure 2: Line chart showing CO₂ emissions in millions of metric tons from 2001 to 2021. Total decreases by >30%.](image_reference)
+
+### Global Coal Consumption²
+Has Yet to Definitively Peak
+
+![Figure 3: Line chart showing global coal consumption in MT from 2000 to 2020.](image_reference)
+
+### U.S. LNG Reduces Carbon Intensity of Electricity³
+
+![Figure 4: Bar chart comparing the kg CO₂e per MWh of Germany domestic coal and Germany U.S. Permian LNG. Domestic coal is approximately 1,100 and U.S. Permian LNG is approximately 600.](image_reference)
+
+>40% Reduction
+in lifecycle GHG emissions
+when switching from domestic
+coal to imported LNG
+
+### Strong LNG Growth Outlook4
+
+![Figure 5: Stacked area chart showing strong LNG growth outlook from 2022 to 2050. Operational and under construction are represented. >300 MTPA Supply Gap by 2050](image_reference)
+
+1U.S E.I.A Power Plant Operations Report. 2IEA, Global Coal Consumption, 2000-2025. 3ICF International, Update to the Life-Cycle Analysis of GHG Emissions for US LNG Exports. 4Source Wood Mackenzie Q4 2022.
+
+--- end page 17
+
+## 10-Year Plan Reflects Durable Returns-Focused Value Proposition
+
+### Capital ($B)
+
+![Capital graph]
+
+~$11B
+2023 Capital
+
+12
+
+9
+
+6
+
+3
+
+25
+
+20
+
+15
+
+0
+
+2023E
+
+2024-2028
+Average
+
+2029-2032
+Average
+
+### Production (MBOED)
+
+![Production Graph]
+
+~4-5%
+10-Year
+Production CAGR
+
+2,500
+
+2,000
+
+1,500
+
+1,000
+
+500
+
+0
+
+2023E
+
+2024-2028
+Average
+
+2029-2032
+Average
+
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+### FCF ($B)
+
+![FCF Graph]
+
+10
+
+$80/BBL
+WTI
+Upside Sensitivity
+
+$60/BBL
+WTI
+Mid-Cycle
+Planning Price
+
+0
+
+2023E
+
+2024-2028
+Average
+
+> $115B FCF
+Over the Next 10 Years
+at $60/BBL WTI
+
+2029-2032
+Average
+
+~$35/BBL WTI FCF
+Breakeven
+Average Over the Next 10 Years
+
+ConocoPhillips 18
+
+--- end page 18
+
+## Alaska and International
+
+Andy O'Brien
+SVP, Global Operations
+
+ConocoPhillips
+Alaska and International
+Andy O'Brien
+SVP, Global Operations
+
+--- end page 19
+
+## Alaska and International: Our Unique Diversification Advantage
+
+Portfolio Diversification
+
+*   ~9 BBOE, <$40/BBL WTI Cost of Supply resource base
+*   Leveraging existing infrastructure across conventional assets
+*   Low-decline, low capital-intensity LNG and Surmont
+
+High-Margin Production Growth
+
+*   World-class Qatar LNG resource expansion builds upon 20-year relationship
+*   Progressing Montney unconventional toward development mode
+*   Investing for the future with the high-margin Willow project
+
+$
+
+Significant Free Cash Flow
+
+*   Low reinvestment rate underpins distribution capacity
+*   High-value, Brent-linked production
+*   Delivering value with additional APLNG shareholding interest
+
+Free cash flow (FCF) and reinvestment rate are non-GAAP measures defined in the Appendix.
+
+ConocoPhillips 20
+
+--- end page 20
+
+## Low Capital Intensity Production Growth
+
+### Material Low Cost of Supply Resource Base
+Leveraging Existing Infrastructure
+
+~$30/BBL
+Average
+Cost of Supply
+
+![Figure 1: A cost of supply chart with the x-axis representing resource in BBOE from 0 to 9 and the y-axis representing WTI cost of supply in $/BBL from 0 to 50. There are vertical bars of different colors depicting the resource and cost of supply levels for LNG, Surmont, Montney, Conventional International, and Alaska.](image_reference)
+
+### Capital-Efficient Production Growth
+Underpins Growing Distribution Capacity
+
+*   Production Mix¹
+    *   Oil ~60%
+    *   NGL ~5%
+    *   North American Gas ~5%
+    *   International Gas ~30%
+
+![Figure 2: A production mix chart with the x-axis representing the years 2023E, 2024-2028 Average, and 2029-2032 Average, and the y-axis representing Production in MBOED from 0 to 1,200. There are vertical bars of different colors depicting the production mix for LNG, Surmont, Montney, Conventional International, and Alaska.](image_reference)
+
+4% CAGR at ~40% Reinvestment Rate
+Over the Next 10 Years at $60/BBL WTI
+
+--- end page 21
+
+## LNG: Expanding World-Class Assets
+
+![Figure 1: Image of a large LNG tanker docked at a port facility, with "Qatar" labeled next to the tanker.](image_reference)
+
+### Qatargas 3
+
+*   Legacy position supplying Asian and European markets
+
+### North Field Expansion Projects
+
+*   Building on our 20-year relationship with Qatar
+*   Awarded 2 MTPA net; NFE first LNG in 2026 and NFS in 2027
+*   NFE and NFS add trains 15-20 in Qatar's LNG portfolio
+
+### APLNG
+
+*   90% of volumes under long-term contracts
+*   Increased shareholding interest by 10% in 1Q 2022; expecting to recoup ~50% of purchase price by end of 2Q 2023
+*   Acquiring up to an additional 2.49% shareholding interest and preparing to take over upstream operatorship upon Origin Sale¹
+
+![Graph 1: Bar graph showing Expanding LNG Production for 2023E, 2024-2028 Average, and 2029-2032 Average. Y-axis labeled "Production (MBOED)" from 0 to 300 in increments of 100. Series include APLNG, QG3, and Qatar Expansion.](image_reference)
+
+### Growing Reliable LNG Cash Flows
+
+¹Subject to EIG closing its announced acquisition of Origin Energy (the current upstream operator); EIG's transaction with Origin, as well as ConocoPhillips' shareholding acquisition are subject to
+Australian regulatory approvals and other customary closing conditions. The 2.49% purchase is also subject to shareholder's pre-emptive rights.
+
+ConocoPhillips 22
+
+--- end page 22
+
+## Surmont: Leveraging Low Capital Intensity for Decades of Flat Production
+
+### Optimizing the Machine
+
+*   Record 2H 2022 production
+*   Low sustaining capital requirements
+*   Advantaged operating cost due to top-quartile steam-oil ratio
+
+#### Production (MBOED)1
+
+![Figure 1: Bar chart of Production (MBOED) from 2014 to 2022. X-axis is year, Y-axis is MBOED from 0 to 80 in increments of 20. "LAST NEW PAD" and "RECORD PRODUCTION" are labeled above the 2014 and 2022 bars, respectively.](image_reference)
+
+### First New Pad Drilled Since 2016 Developed at <$15/BBL WTI COS
+24 Well Pairs with 25 MBOED Gross Peak Rate
+
+![Figure 2: Aerial view of an oil drilling site in the snow. The location "Pad 267" is noted on the image.](image_reference)
+
+#### Average Well Cost² ($MM)
+
+![Figure 3: Bar chart of Average Well Cost ($MM) for 2016 Pads and Pad 267. X-axis is Pad type, Y-axis is cost in $MM from 0 to 6 in increments of 2. A downward arrow labeled "Decreased 30%" is between the two bars.](image_reference)
+
+### Transformative Emissions Reduction³ Opportunities
+
+*   1/3 through current technology pilots
+*   1/3 through new technologies
+*   CCS and offsets to achieve net-zero
+
+#### Emissions Reduction Pathway (Net MMTeCO2e)
+
+![Figure 4: Line graph showing the Emissions Reduction Pathway from 2023 to 2050. The line starts at the "CURRENT TECH" level and trends down to the "NEW TECH" level, eventually to the "CCS & OFFSETS" level.](image_reference)
+
+Production Records Achieved
+Through Optimization
+
+Raises Production Plateau
+into 2030s
+
+Multiple Options for
+Emissions Reduction
+
+¹Net before royalty shown to remove price related royalty impacts. ²Includes drill, completions and facilities (excluding pipelines). 3Net equity Scope 1 and 2 emissions.
+
+ConocoPhillips 23
+
+--- end page 23
+
+## Montney: Building Another Core Unconventional Business
+
+### Appraisal Defined Optimal Plan
+
+*   Concluded testing of multiple well configurations and completion designs
+*   Recent strong well results lead to high-graded, two-layer development plan
+
+![Cost of Supply Improvement Chart]
+
+40
+Cost of Supply Improvement
+($/BBL WTI)
+
+Driving to
+Mid-$30s CoS
+0
+Current
+Pads
+Development
+Phase
+
+High-Graded Resource of
+1.8 BBOE at Mid-$30s CoS
+
+### Moving to Development Phase
+
+*   Adding second rig in 2024
+*   Running one continuous frac crew
+*   Refining completion design
+*   CPF2 start-up expected in 3Q 2023
+
+![Figure 1: CPF2](image_reference)
+
+Leveraging
+Unconventional Expertise
+
+### Significant Production Growth
+
+*   60% liquids production, priced off WTI
+*   Long-term commercial offtake secured
+
+![Production Graph]
+
+150
+Production
+(MBOED)
+
+100
+
+50
+
+0
+2023E
+2024-2028
+Average
+2029-2032
+Average
+
+20% CAGR
+Over 10 Years
+
+--- end page 24
+
+## International Conventional: Steady Cash Flow Generator
+
+![Figure 1: Eldfisk](image_reference)
+
+### Brent-Linked Oil and International Gas
+
+#### Norway – 115 MBOED
+
+*   Four subsea tie backs on track for onstream in 2024
+*   Greater Ekofisk Area license extended through 2048
+
+#### Libya – 50 MBOED
+
+*   Increased working interest to ~20% in Waha Concession
+*   Long-term optionality
+
+#### Malaysia – 40 MBOED
+
+*   Low Cost of Supply projects offsetting decline
+
+#### China - 30 MBOED
+
+*   Production sharing contract terms aligned to 2039
+*   Progressing offshore windfarm in China
+
+### ~$1B Per Year Free Cash Flow
+
+Over the Next 10 Years at $60/BBL WTI
+
+[Graph 1: Production (MBOED)]
+
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| :---- | :---- | :---------------- | :---------------- |
+| Value | 213   | 225               | 202               |
+
+Country production numbers quoted are 2023 estimates.
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+--- end page 25
+
+## Alaska Conventional: Legacy World-Class Basin
+
+![Figure 1: Map of Alaska Conventional showing Central Processing Facility (CPF)/Project, ConocoPhillips Interest Acreage, Opportunity Reservoir Extent, Pipeline System, and Future Project](no_image_available)
+
+*   Central Processing Facility (CPF)/Project
+*   ConocoPhillips Interest Acreage
+*   Opportunity Reservoir Extent
+*   Pipeline System
+*   Future Project
+
+**Leveraging Existing Infrastructure**
+
+*   Largest producer, with 40+ years of experience across significant infrastructure
+*   Robust inventory of projects with a ~$25/BBL Cost of Supply for over a decade
+
+**Disciplined Development Plan**
+
+![Figure 2: Disciplined Development Plan Pie Chart](no_image_available)
+
+*   New pads filling existing capacity e.g., Nuna, E News
+*   ~$1B Capex per Year
+*   Drilling from existing pads e.g., Coyote, Fiord West Kuparuk, Torok
+
+![Graph 1: 100% of Production Priced at Brent+](no_image_available)
+
+|         | Production (MBOED) |
+| :------ | :----------------- |
+| 2023E   | 195               |
+| 2024-2028 Average | 214               |
+| 2029-2032 Average | 229               |
+
+40+ Years Later, ~2-3% Production Growth
+Over the Next 10 Years
+
+--- end page 26
+
+## Willow: Building on Our Long History
+
+![Figure 1: Oil field Map and Legends](image_reference)
+
+National Petroleum
+Reserve - Alaska
+
+Western
+North Slope
+2000
+
+Greater
+Kuparuk Area
+1981
+
+Prudhoe Bay
+Non-operated
+1977
+
+Nuna
+
+FWK
+
+ENEWS
+
+CD5
+
+WILLOW
+
+BT2 ▲
+
+Coyote
+
+▲ 1FL NEWS
+
+GMT-1
+
+GMT-2
+
+BT1
+
+BT3
+
+N
+
+0
+10
+20
+Miles
+
+ED8
+
+Alaska State
+Lands
+
+Central Processing
+Facility (CPF)/Project
+
+ConocoPhillips
+Interest Acreage
+
+Opportunity
+Reservoir Extent
+
+Pipeline System
+
+Future CPF/Project
+
+Willow Interest Acreage
+
+### Legacy Infrastructure
+
+**13**
+Central Processing Facilities
+
+**~120**
+Drill Sites
+
+**~410**
+Miles of Corridor
+Road and Pipelines
+
+### Willow
+
+**1**
+Central Processing Facility
+
+**3**
+Drill Sites
+
+**~26**
+Miles of Corridor
+Road and Pipelines
+
+### Significant Opportunity Without "Mega-Project" Risks
+
+**Extensive Definition**
+100% FEED complete at FID
+
+**Simple Governance**
+100% ConocoPhillips owned
+
+**Limited Complexity**
+No "first-of-a-kind" designs
+
+**Proven Execution Model**
+Executed similar drill site, pipeline
+and road scope over past five years
+with proven North Slope contractors
+
+Modular facilities designed and built
+in U.S. by top-tier Gulf Coast contractors
+
+ConocoPhillips 27
+
+--- end page 27
+
+## Willow: Delivering Competitive Returns Into the Next Decade
+
+Capex of $1-1.5B per Year from 2024-2028
+
+*   Drill sites and drilling
+*   Infrastructure, roads, pipelines, power and pads
+*   Central processing facility
+
+$7-7.5B
+to First Oil
+
+### Key Construction Milestones
+
+|        |        |        |        |        |        |        |
+| :----- | :----- | :----- | :----- | :----- | :----- | :----- |
+| 2023   | 2024   | 2025   | 2026   | 2027   | 2028   | 2029   |
+| Winter road and pipeline construction | Central processing facility fabrication and delivery | First Oil |
+| Operation center fabrication and delivery | Complete tie-ins to new drill sites and existing infrastructure |        |
+| Central processing facility procurement | Commence drilling program |        |
+
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+Volume Ramp and Strong Margins Drive FCF
+
+*   Pre-drilling strategy fills facility at startup
+*   Premium-quality light crude compared to current Alaska average
+*   Leverages existing pipeline infrastructure
+
+Production (MBOED)
+
+Willow:
+100% Oil
+
+[Graph 1: Production (MBOED)]
+|        | 2023E | 2024-2028 Average | 2029-2032 Average |
+| :----- | :---- | :---------------- | :---------------- |
+| Legacy Alaska | 200   | 230               | 240               |
+| Willow   | 0     | 0                 | 160               |
+
+--- end page 28
+
+## Alaska and International: Our Unique Diversification Advantage
+
+**Capital** ($B)
+
+[Graph 1: Capital Spending Forecast]
+| Period          | Amount ($B) |
+|-----------------|-------------|
+| 2023E           | 3.5         |
+| 2024-2028 Average | 4.3         |
+| 2029-2032 Average | 3.0         |
+
+**Production** (MBOED)
+
+[Graph 2: Production Forecast]
+| Period          | Amount (MBOED) |
+|-----------------|----------------|
+| 2023E           | 780            |
+| 2024-2028 Average | 870            |
+| 2029-2032 Average | 1,000          |
+
+**FCF** ($B)
+
+[Graph 3: Free Cash Flow Forecast]
+| Period          | Amount ($B) |
+|-----------------|-------------|
+| 2023E           | 5.2          |
+| 2024-2028 Average | 6.2       |
+| 2029-2032 Average | 7.8          |
+
+$80/BBL WTI
+Upside Sensitivity
+
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+
+> $50B FCF and ~40% Reinvestment Rate
+Over the Next 10 Years at $60/BBL WTI
+
+Free cash flow (FCF) and reinvestment rate are non-GAAP measures defined in the Appendix.
+
+ConocoPhillips 29
+
+--- end page 29
+
+## LNG and Commercial
+
+Bill Bullock
+EVP and CFO
+
+ConocoPhillips
+LNG and Commercial
+Bill Bullock
+EVP and CFO
+
+--- end page 30
+
+## LNG Opportunities Underpinned by Strong Commercial Acumen
+
+![Figure 1: LNG image of a ship, LNG tank, and a globe.](image_reference)
+
+*   Rapidly Growing LNG Market
+    *   Robust demand in Asia and Europe driven by energy security and the energy transition
+    *   Qatar and Australia are foundational LNG investments
+    *   North American gas production fuels LNG supply growth
+
+*   Adding North America to Low-Cost LNG Footprint
+    *   Port Arthur is a premier LNG development
+    *   Long-term optionality on the Gulf and West Coasts
+    *   Offtake margins enhanced by diversion capability
+
+*   Extensive Commercial Footprint
+    *   Global market presence
+    *   Second-largest natural gas marketer in North America¹
+    *   60+ years experience with LNG
+
+¹Natural Gas Intelligence North American Marketer Rankings as of Q3 2022, published in December 2022.
+
+--- end page 31
+
+## Attractive Global LNG Portfolio
+
+Key LNG Supply and Demand Markets by 2035
+(ΜΤΡΑ)1
+
+*   Supply Demand
+
+ConocoPhillips Assets at Nexus of Supply and Demand
+
+*   Asia and Europe to remain significant demand centers
+*   Qatar and Australia provide reliable LNG
+*   North America dominates LNG supply growth
+
+ConocoPhillips Global Net LNG Exposure
+(ΜΤΡΑ)
+
+APLNG
+QG3
+NFE/NFS
+PA LNG3
+
+ConocoPhillips Net LNG Capital Spend ($B)
+
+~$3.7B
+Cumulative Capital
+
+[Graph 1: ConocoPhillips Global Net LNG Exposure and Net LNG Capital Spend]
+| Data    | 2023 | 2028 | 2032 |
+| :------ | :--- | :--- | :--- |
+| APLNG   | 5    | 5    | 5    |
+| QG3     | 3    | 3    | 3    |
+| NFE/NFS | 0    | 3    | 3    |
+| PA LNG3 | 0    | 4    | 4    |
+
+| Data              | 2023E | 2024-2028 Average | 2029-2032 Average |
+| :---------------- | :---- | :---------------- | :---------------- |
+| Value             | 7     | 0.3               | 0.4               |
+
+1Wood Mackenzie Q4 2022, North America as marginal supplier. 2Offtake and/or equity at Energia Costa Azul (ECA) Phase 2 and offtake from ECA Phase 1.
+35 MTPA offtake and access to excess cargoes when Phase 1 liquefaction exceeds the 10.5 MTPA contracted under long term SPAs.
+
+--- end page 32
+
+## Port Arthur is a Premier LNG Development
+
+![Figure 1: Map of the United States showing the locations of Permian, Haynesville, Marcellus, PA LNG, and West Coast Optionality. An aerial view of the Port Arthur LNG facility is also shown.](image_reference)
+
+*Permian*
+
+*West Coast
+Optionality¹*
+
+*Haynesville*
+
+*PA LNG*
+
+*Marcellus*
+
+### FID of Port Arthur Phase 1
+
+*   FERC-approved and construction-ready with high-quality operator and EPC contractor
+*   ConocoPhillips to manage gas supply
+*   Near Gulf Coast infrastructure and fastest growing low-cost, low-GHG gas basins
+*   ConocoPhillips participation launched project
+
+### Strategic Optionality
+
+*   Access to low-cost uncontracted excess capacity
+*   Secured long-term optionality on the Gulf and West Coasts¹
+*   Prioritizing market development and offtake over additional equity
+*   Evaluating development of CCS projects at Port Arthur facility
+
+### Low-Cost Offtake Secured
+
+*   5 MTPA offtake from Port Arthur Phase 1²
+*   Top tier liquefaction fee³
+*   Marketing currently underway; receiving significant customer interest
+
+¹Offtake and/or equity on up to six additional trains at Port Arthur, offtake and/or equity at ECA Phase 2, and offtake from ECA Phase 1.
+²20-year agreement. ³Wood Mackenzie Q4 2022, contract fixed liquefaction fees.
+
+ConocoPhillips 33
+
+--- end page 33
+
+## ConocoPhillips Commercial Advantage
+
+Port Arthur LNG Marketing Example: Sale into Germany
+
+European
+Re-Gas
+
+Global Marketing Presence: >10 BCFD and >1 MMBOD¹
+
+*   ConocoPhillips holds re-gas capacity in Germany's first onshore LNG terminal for portion of Port Arthur LNG
+*   Captures Trading Hub Europe (THE) price with diversion capability when other international prices exceed THE
+*   Managed and marketed by experienced ConocoPhillips commercial organization
+
+A
+Global Gas,
+Power and LNG
+
+OPTIMIZED LNG
+CASCADE PROCESS
+Licensing2
+
+1-
+Global Crude
+and NGL
+
+London
+Singapore
+Houston
+Calgary
+Beijing
+Tokyo
+
+9x Equity
+Gas marketed
+globally
+
+6.0 GWh
+Power marketed
+
+~1 ΜΤΡΑ
+Spot sales
+into Asia
+
+113 ΜΤΡΑ
+Utilizing Optimized
+Cascade® Process
+
+2nd Largest
+Global LNG
+technology provider
+
+25 Cargoes
+Marketed globally
+per month
+
+45%
+Brent-linked
+
+180 MBOD
+North American
+export capacity
+
+¹FY2022 data unless otherwise footnoted. ²Based on total global installed production capacity of 113 MTPA associated with 26 licensed LNG trains in operation.
+
+--- end page 34
+
+## Lower 48
+
+Nick Olds
+EVP, Lower 48
+
+ConocoPhillips
+
+Lower 48
+Nick Olds
+EVP, Lower 48
+
+--- end page 35
+
+## Premier Lower 48 Assets Underpin Our Returns-Focused Strategy
+
+Industry Leader Focused
+on Maximizing Returns
+
+*   Largest Lower 48 unconventional producer with deep, durable and diverse unconventional portfolio
+*   Disciplined development optimizing returns and recovery
+
+$
+
+Production and Free Cash Flow
+Growth into the Next Decade
+
+*   Permian premising ~7% production growth, doubling free cash flow by end of decade
+*   Eagle Ford and Bakken delivering material free cash flow
+
+Delivering Continuous
+Improvements
+
+*   Accelerating technology across four core basins to enhance value
+*   Delivering on emissions reductions and sustainable development
+
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+ConocoPhillips 36
+
+--- end page 36
+
+## Deep, Durable and Diverse Portfolio with Significant Growth Runway
+
+### 2022 Lower 48 Unconventional Production¹ (MBOED)
+
+![Production Chart]
+
+1,200
+~$32/BBL
+
+1,000 ConocoPhillips
+800
+600
+400
+200
+0
+WTI Cost of Supply ($/BBL)
+Average
+Cost of Supply
+
+### Net Remaining Well Inventory2
+
+![Well Inventory Chart]
+
+15,000
+ConocoPhillips
+12,000
+9,000
+6,000
+3,000
+0
+$40
+$30
+$20
+$10
+$0
+0
+2
+4
+6
+8
+10
+Resource (BBOE)
+Delaware Basin
+Midland Basin
+Eagle Ford
+Bakken
+Other
+
+Largest Lower 48 Unconventional Producer, Growing into the Next Decade
+
+¹Source: Wood Mackenzie Lower 48 Unconventional Plays 2022 Production. Competitors include CVX, DVN, EOG, FANG, MRO, OXY, PXD and XOM, greater than 50% liquids weight. ²Source: Wood Mackenzie (March 2023), Lower 48
+onshore operated inventory that achieves 15% IRR at $50/BBL WTI. Competitors include CVX, DVN, EOG, FANG, MRO, OXY, PXD, and XOM.
+
+ConocoPhillips 37
+
+--- end page 37
+
+## Delaware: Vast Inventory with Proven Track Record of Performance
+
+![Figure 1: Mapa de Nuevo México y Texas, mapa de la zona de Delaware con zonas de alto y bajo coste de suministro, gráfico circular de inventario operado de Permian a 10 años](image_reference)
+
+### Prolific Acreage Spanning Over ~659,000 Net Acres¹
+
+### 12-Month Cumulative Production³ (BOE/FT)
+
+[Graph 1: Producción acumulada de 12 meses]
+| Months | 2019 | 2020 | 2021 | 2022 |
+|---|---|---|---|---|
+| 1 | 5 | 6 | 7 | 7 |
+| 2 | 9 | 11 | 12 | 13 |
+| 3 | 12 | 14 | 16 | 18 |
+| 4 | 15 | 17 | 20 | 22 |
+| 5 | 18 | 20 | 23 | 26 |
+| 6 | 20 | 23 | 26 | 29 |
+| 7 | 23 | 25 | 29 | 32 |
+| 8 | 25 | 28 | 31 | 35 |
+| 9 | 27 | 30 | 34 | 37 |
+| 10 | 30 | 32 | 36 | 40 |
+| 11 | 32 | 34 | 38 | 41 |
+| 12 | 34 | 36 | 40 | 43 |
+
+~30% Improved Performance from 2019 to 2022
+
+### Delaware Basin Well Capex/EUR4 ($/BOE)
+
+[Graph 2: Capex/EUR de pozos en la cuenca de Delaware]
+|  | ConocoPhillips |  |  |  |  |  |  |  |
+|---|---|---|---|---|---|---|---|---|
+| Capex/EUR | 7.6 | 10.1 | 10.2 | 10.3 | 11.5 | 12.3 | 15.3 | 19.3 | 24.8 |
+
+**High Single-Digit Production Growth**
+
+¹Unconventional acres. ²Source: Enverus and ConocoPhillips (March 2023). ³Source: Enverus (March 2023) based on wells online year. ⁴Source: Enverus (March 2023). Average single well capex/EUR. Top eight public operators based on wells online in years 2021-2022, greater than 50% oil weight. COP based on COP well design. Competitors include: CVX, DVN, EOG, MTDR, OXY, PR and XOM.
+
+--- end page 38
+
+## Midland: Acreage in the Heart of Liquids-Rich Basin
+
+![Figure 1: New Mexico and Texas map with a high-margin play spanning over ~251,000 net acres. Total 10-Year Operated Permian Inventory is 35% Delaware Basin and Midland Basin. A cost of supply map of low and high supplies.](image_reference)
+
+High-Margin Play Spanning Over
+~251,000 Net Acres¹
+
+12-Month Cumulative Production³ (BOE/FT)
+
+![Graph 1: 12-Month Cumulative Production (BOE/FT), with months on the X axis and the rate on the Y axis.](image_reference)
+
+Midland Basin Well Capex/EUR4 ($/BOE)
+
+![Graph 2: Midland Basin Well Capex/EUR, with the company and amount in $/BOE.](image_reference)
+
+Low to Mid Single-Digit Production Growth
+
+¹Unconventional acres. ²Source: Enverus and ConocoPhillips (March 2023). ³Source: Enverus (March 2023) based on wells online year.
+4Source: Enverus (March 2023). Average single well capex/EUR. Top eight public operators based on wells online in years 2021-2022, greater than 50% oil weight. Competitors include FANG, OVV, OXY, PXD, SM, VTLE and XOM.
+
+--- end page 39
+
+## Continuously Optimizing Permian Acreage and Value
+
+### Acreage Trades
+
+#### Illustration
+
+Pre-Trade
+
+Post-Trade
+
+ConocoPhillips Acreage Trade-in Trade-out
+
+#### Trade Area
+LOVING
+
+REEVES
+
+### Permian-Operated Inventory
+
+*   Complementary Positions Enable Trade and Core-Up Opportunities
+*   ~30-40% Cost of Supply Improvement from Lateral-Length Extensions
+
+![Lateral length distribution]
+
+~60%
+2 miles
+or greater
+
+~20%
+1.5 miles
+to 2 miles
+
+### Recent Acreage Trade Metrics
+
+↑2x
+Lateral Length
+
+30%
+Capex/FT
+
+130%
+Cost of Supply
+
+Vast Long-Lateral Inventory Enhances Returns and Durability
+
+ConocoPhillips 40
+
+--- end page 40
+
+## Permian Drives Free Cash Flow in Lower 48
+
+~7%
+10-Year Production CAGR
+
+Production (MBOED)
+
+Growing to Plateau
+in the 2nd Decade
+
+~$50%
+Reinvestment Rate¹
+
+< $35/BBL
+Program Cost of Supply
+
+FCF ($B)
+
+~$45B FCF
+Generated Over
+the Next 10 Years
+at $60/BBL WTI
+
+| 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- |
+| 2023E | 2024-2028 Average | 2029-2032 Average |
+| $60/BBL WTI Mid-Cycle Planning Price | $80/BBL WTI Upside Sensitivity |
+
+Top-Tier Permian Position, Growing into the Next Decade
+
+¹Over the next 10 years at $60/bbl.
+Reinvestment rate and free cash flow (FCF) are non-GAAP measures defined in the Appendix.
+
+--- end page 41
+
+## Eagle Ford and Bakken Delivering Material Free Cash Flow
+
+~199,000 Net Acres¹ in Eagle Ford
+~560,000 Net Acres¹ in Bakken
+
+Consistent and Proven Track Record
+in Basin Sweet Spots
+
+Sustains Production
+Over the Decade
+
+![Figure 1: Maps showing Eagle Ford and Bakken with areas shaded according to cost of supply.](image_reference)
+
+Eagle Ford
+
+Bakken
+
+Low
+High
+Cost of Supply²
+
+[Graph 1: Eagle Ford Well Capex/EUR³ ($/BOE)]
+|     | ConocoPhillips |
+| ----------- | ----------- |
+|     | 10 |
+|  | 20 |
+|  | 30 |
+
+[Graph 2: Bakken Well Capex/EUR⁴ ($/BOE)]
+|     | ConocoPhillips |
+| ----------- | ----------- |
+|     | 8 |
+|  | 10 |
+|  | 15 |
+
+[Graph 3: Production (MBOED)]
+| Metric | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+| Bakken | 100 | 100 | 90 |
+| Eagle Ford | 230 | 230 | 240 |
+|     | 300 | 300 | 300 |
+|  | 400 | 400 | 400 |
+
+Delivers ~$20B FCF
+Over the Next 10 Years at $60/BBL WTI
+
+¹Unconventional acres. ²Source: Enverus and ConocoPhillips (March 2023). ³Source: Enverus (March 2023); Average single well capex/EUR; Top eight public operators based on wells online in vintage years 2019-2022, greater than
+50% oil weight; Competitors include: BP, CHK, CPE, DVN, EOG, MGY and MRO. ⁴Source: Enverus (March 2023); Average single well capex/EUR; Top eight operators based on wells online in vintage years 2019-2022, greater than 50%
+oil weight; Competitors include CHRD, Continental, DVN, ERF, HES, MRO and XOM.
+Free cash flow (FCF) is a non-GAAP measure defined in the Appendix.
+
+--- end page 42
+
+## Enhancing Value and Lowering Emissions through Technology
+
+### Drilling
+
+![Figure 1: Permian Real-Time Ops Center](image_reference)
+
+Permian Real-Time Ops Center
+
+*   Real-time analytics improve curve build time by 20% in Eagle Ford
+*   Permian drilling efficiencies¹ improved ~50% since 2019
+
+### Completions
+
+![Figure 2: E-Frac](image_reference)
+
+E-Frac
+
+*   Dual fuel and E-frac reduce emissions ~10% to ~40% compared to diesel
+*   >50% of Permian completions to be Simulfrac'd in 2023
+
+### Operations
+
+![Figure 3: Autonomous Drone Pilot](image_reference)
+
+Autonomous Drone Pilot
+
+*   Real-time intelligent production surveillance, automation and process optimization
+*   Drone-based surveillance increases inspection frequency
+
+Leveraging Operational Wins Across Core Four Basins
+
+¹Permian drilling efficiencies defined as measured depth (feet) per day.
+
+--- end page 43
+
+## Delivering on Emissions Reductions and Sustainable Development
+
+### Lower 48 GHG Intensity¹ (kg CO2e/BOE)
+
+![GHG Emissions intensity chart]
+
+28
+
+2019
+
+~50%
+Reduction
+
+<15
+
+2022²
+
+### Lower 48 Associated Gas Flaring³ (%)
+
+![Lower 48 Associated Gas Flaring chart]
+
+1.7%
+
+~80%
+Reduction
+
+2019
+
+0.3%
+
+2022²
+
+### Permian Recycled Frac Water (%)
+
+![Permian Recycled Frac Water Chart]
+
+52%
+
+>3X
+Increase
+
+2019
+
+11%
+
+2022
+
+### Focused Plans to Further Reduce Emissions and Maximize Water Reuse
+
+*   Reducing Methane and Flaring
+*   Improving Facilities Design
+*   Electrifying Compression
+*   Optimizing D&C Power
+*   Water Conservation
+
+¹Gross operated GHG Emissions (Scope 1 and 2). ²Preliminary estimates. Includes Permian, Eagle Ford and Bakken only. ³Excludes safety, assist gas, pilot gas, tanks and emergency shutdown flaring.
+
+--- end page 44
+
+## Significant Free Cash Flow Growth Over the Decade
+
+### Capital ($B)
+
+[Graph 1: Capital ($B)]
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+|  | 6 | 7 | 8 |
+
+### Production (MBOED)
+
+[Graph 2: Production (MBOED)]
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+|  | 1,100 | 1,300 | 1,450 |
+
+### FCF ($B)
+
+[Graph 3: FCF ($B)]
+|       | 2023E | 2024-2028 Average | 2029-2032 Average |
+| ----------- | ----------- | ----------- | ----------- |
+|  | 6.5 | 8 | 12 |
+
+$80/BBL WTI
+Upside Sensitivity
+
+$60/BBL WTI
+Mid-Cycle Planning Price
+
+~$65B FCF and ~50% Reinvestment Rate
+Over the Next 10 Years at $60/BBL WTI
+
+--- end page 45
+
+## Financial Plan
+
+Bill Bullock
+EVP and CFO
+
+ConocoPhillips
+
+## Financial Plan
+
+Bill Bullock
+EVP and CFO
+
+--- end page 46
+
+## A Financial Plan with Durability of Returns and Cash Flow Growth
+
+Consistent Returns
+on and of Capital
+
+*   Peer-leading ROCE improving through time
+*   CFO-based distribution framework with compelling shareholder returns
+
+Cash Flow Growth
+into the Next Decade
+
+*   ~6% CFO CAGR1 through the plan
+*   Disciplined capital investment accelerates FCF growth
+
+Battle-Tested
+Financial Priorities
+
+*   'A'-rated balance sheet resilient through cycles
+*   Stress-tested financial durability
+
+1CAGR calculated from FY2024 at $60/BBL WTI.
+Return on capital employed (ROCE), cash from operations (CFO) and free cash flow (FCF) are non-GAAP measures defined in the Appendix.
+
+--- end page 47
+
+## Committed to Top-Quartile Returns on Capital
+
+### Five-Year Average ROCE¹
+Peer-Leading ROCE Performance
+
+![Figure 1: A bar chart displays five-year average ROCE. The y-axis is labeled with percentages from 0% to 16%, in increments of 2%. The x-axis displays data for ConocoPhillips, independent peers, and integrated peers. ConocoPhillips is represented by a red bar reaching 14%. Independent peers are represented by a series of grey bars of decreasing height. Integrated peers are represented by a series of darker grey bars, also decreasing in height.](image.png)
+
+### Earnings ($B)
+Low Cost of Supply Investments Fuel Expanding Margins
+
+~10% CAGR
+2024-2032 at $60/BBL WTI
+
+![Figure 2: A bar chart displays earnings in billions of dollars. The y-axis is labeled with values from 0 to 30. The x-axis displays the years 2023E, 2024-2028 Average, and 2029-2032 Average, each with a blue bar rising to around 11, 14, and 18 respectively.](image.png)
+
+### Return on Capital Employed (ROCE)
+Near-Term Delivery of S&P 500 Top-Quartile ROCE
+
+![Figure 3: A bar chart displays the return on capital employed (ROCE). The y-axis displays values from 0% to 40%, in increments of 10%. The x-axis shows 2023E, 2024-2028 Average, and 2029-2032 Average, each with a blue bar, and with a green line indicating the S&P 500 Top Quartile.](image.png)
+
+1Source: Bloomberg Return on Capital 2018 through 2022. 2Integrated peers include CVX and XOM. Independent peers include APA, DVN, EOG, HES, OXY and PXD. 3Represents top quartile of five-year average ROCE (2018-2022)
+for constituents as of December 31, 2022.
+Earnings refers to net income. Return on capital employed (ROCE) is a non-GAAP measure defined in the Appendix.
+
+--- end page 48
+
+## Cash Flow Growth into the Next Decade
+
+### Cash From Operations ($B)
+
+![Graph 1: Cash From Operations ($B)](image_reference)
+
+|                             | 2023E | 2024-2028 Average | 2029-2032 Average |
+| -------------------------- | ----- | ----------------- | ----------------- |
+| $60/BBL WTI Mid-Cycle Planning Price | 22    | 24                | 27                |
+| $80/BBL WTI Upside Sensitivity |       | 3                 | 7                 |
+
+~6% CAGR
+2024-2032 at $60/BBL WTI
+
+### Free Cash Flow ($B)
+
+![Graph 2: Free Cash Flow ($B)](image_reference)
+
+|                             | 2023E | 2024-2028 Average | 2029-2032 Average |
+| -------------------------- | ----- | ----------------- | ----------------- |
+| $60/BBL WTI Mid-Cycle Planning Price | 11    | 13                | 18                |
+| $80/BBL WTI Upside Sensitivity |       | 2                 | 5                 |
+
+~11% CAGR
+2024-2032 at $60/BBL WTI
+
+~$3.5B of Annual CFO is from
+Longer-Cycle Projects¹
+2029-2032 Average at $60/BBL WTI
+
+> $115B FCF Available
+for Distribution
+Over the Next 10 Years at $60/BBL WTI
+
+¹2029-2032 annual average CFO from longer-cycle projects of ~$5B at $80/BBL WTI. Longer-cycle projects are Willow, Port Arthur LNG Phase 1 and North Field Expansions.
+Cash from operations (CFO) and free cash flow (FCF) are non-GAAP measures defined in the Appendix.
+
+--- end page 49
+
+## CFO-Based Framework Delivers Leading Returns of Capital
+
+### Five-Year Distribution as % of CFO1
+Consistent Execution on Our Priorities
+
+![Graph 1: Five-Year Distribution as % of CFO1 Chart](image_reference)
+
+|        |  |
+| ----------- | ----------- |
+| ConocoPhillips | 44%  |
+| Integrated Peers³  | 41%  |
+| Independent Peers³   | 34% |
+
+### Five-Year Distribution Yield2
+Track Record of Leading Distributions
+
+![Graph 2: Five-Year Distribution Yield2 Chart](image_reference)
+
+|        |  |
+| ----------- | ----------- |
+| ConocoPhillips | 7%  |
+| Independent Peers³  | 6%  |
+| Integrated Peers³   | 5% |
+
+### Compelling Shareholder Returns Through Cycles
+
+#### Tier 1
+Ordinary Dividend
+
+S&P Top-Quartile
+Dividend Growth
+
++
+
+#### Tier 2
+Share Buybacks
+
+Reduces Absolute
+Dividend Over Time
+
++
+
+#### Tier 3
+VROC
+
+Flexible Channel for
+Higher Commodity Prices
+
+<sup>1</sup>Source: Bloomberg. 2018-2022 weighted-average of dividend paid and share buybacks as a percentage of CFO. <sup>2</sup>Source: Bloomberg; 2018-2022 average of dividend paid and share buybacks as a percentage of year-end market cap.
+<sup>3</sup>Integrated peers include CVX and XOM. Independent peers include APA, DVN, EOG, HES, OXY and PXD.
+Cash from operations (CFO) is a non-GAAP measure defined in the Appendix.
+
+ConocoPhillips 50
+
+--- end page 50
+
+## Fortress Balance Sheet: A Strategic Asset
+
+### Gross Debt Profile
+
+$20B
+
+$3B
+
+$17B
+
+$2B
+
+$15B
+
+2021
+Debt Reduction
+Achieved
+2022
+Natural
+Maturities
+2026
+
+### On Target
+
+*   $5B debt reduction by 2026
+*   ~$250MM/year interest reduction
+*   Weighted-average maturity extension of three years
+
+### Net Debt/CFO
+Consensus 2023¹
+
+3.0X
+
+2.0X
+
+1.0X
+
+0.0X
+
+Integrated
+Peers²
+ConocoPhillips
+0.3x
+Independent
+Peers ²
+S&P 500
+Energy
+S&P 500
+
+### Net Debt/CFO at $60/BBL WTI
+
+0.3x
+
+0.2x
+
+2024-2028
+Average
+2029-2032
+Average
+
+Source: Bloomberg Net Debt to CFO. As of March 30, 2023. ²Integrated peers include CVX and XOM. Independent peers include APA, DVN, EOG, HES, OXY and PXD.
+Net debt and cash from operations (CFO) are non-GAAP measures defined in the Appendix.
+
+--- end page 51
+
+## Plan Resilient Through Stress Test
+
+Our Rationale for Holding Cash
+
+![NetDebt/CFO stress test]
+
+1.5x
+Two-Year $40/BBL WTI¹ Stress Test
+Net Debt/CFO
+
+Longer-cycle projects
+
+1.0x
+Share buybacks
+
+0.5x
+Strategic
+Cash
+Down-cycle price protection
+
+0.0x
+2023
+Consensus²
+2024
+2025
+2026
+2027
+2028
+Business development
+optionality
+
+$60/BBL WTI (Base Plan) Two-Years at $40/BBL WTI
+Reserve Cash
+~$2-3B
+Maintain near-term
+operating plan even with
+price volatility
+
+Cash and CFO Fund Consistent Execution in Low Price Scenario
+
+*   Maintain capital program, including longer-cycle projects
+*   Meet 30% distribution commitment through ordinary dividend and share buybacks
+
+Operating Cash
+~$1B
+Daily operating and
+working capital
+
+*   <1.5x leverage ratio through the down-cycle
+*   No additional debt required
+
+¹2022 Real, escalating at 2.25% annually. ²Source: Bloomberg Net Debt to CFO. As of March 30, 2023.
+Net debt and cash from operations (CFO) are non-GAAP measures defined in the Appendix.
+
+--- end page 52
+
+## A Powerful Plan with Differential Upside
+
+![10-Year Plan graph]
+
+$350
+
+10-Year Plan ($B)
+2023-2032
+
+$300
+
+CFO at
+$80/BBL WTIUpside Sensitivity
+
+$250
+
+$200
+
+$150
+
+$100
+
+$50
+Additional
+Distributions
+
+CFO at
+$60/BBL WTI
+Mid-Cycle
+Planning Price
+
+30% of CFO
+Distribution
+Commitment
+
+Capital
+
+$0
+Cash 1
+
+Cash¹
+Sources
+Uses
+
+Peer leading ROCE improving through time
+
+Top quartile ordinary dividend growth
+
+>90% market cap² distributed
+
+~$35/BBL WTI FCF Breakeven³
+
+~6% CFO CAGR, ~11% FCF CAGR
+
+Unhedged for price upside
+
+Cash includes cash, cash equivalents, restricted cash and short-term investments. ²Market cap of ~$121B at March 31, 2023 close. ³Average over the next 10 years.
+CAGRs calculated from FY2024 at $60/BBL WTI. Cash from operations (CFO), free cash flow (FCF) and return on capital employed (ROCE) are non-GAAP measures. Definitions are included in the Appendix.
+
+ConocoPhillips 53
+
+--- end page 53
+
+## Closing
+
+Ryan Lance
+Chairman and CEO
+
+ConocoPhillips
+
+## Closing
+
+Ryan Lance
+Chairman and CEO
+
+--- end page 54
+
+## ConocoPhillips Remains the Must-Own E&P Company
+
+### What You Heard Today
+
+We are committed to delivering superior returns **on** and **of** capital through the cycles
+
+We have a **deep, durable** and **diverse** portfolio
+
+We are progressing our **2050 Net-Zero ambition** and accelerating our 2030 GHG emissions intensity reduction target
+
+### Foundational Principles
+
+Balance Sheet
+Strength
+
+Disciplined
+Investments
+
+**RETURNS**
+
+Peer-Leading
+Distributions
+
+ESG
+Excellence
+
+Deliver Superior Returns
+Through Cycles
+
+### A Compelling Returns Focused 10-Year Plan
+
+*Peer leading* ROCE *improving through time*
+
+**Top quartile** ordinary dividend growth
+
+**>90% market cap¹ distributed**
+
+**~$35/BBL** WTI FCF Breakeven²
+
+**~6%** CFO CAGR, **~11%** FCF CAGR
+
+Unhedged for **price upside**
+
+¹Market cap of ~$121B at March 31, 2023 close. ²Average over the next ten years.
+CAGRs calculated from FY2024 at $60/BBL WTI. Cash from operations (CFO), free cash flow (FCF) and return on capital employed (ROCE) are non-GAAP measures defined in the appendix.
+
+ConocoPhillips 55
+
+--- end page 55
+
+# Appendix
+
+Reconciliations, Abbreviations and Definitions
+
+ConocoPhillips
+
+# Appendix
+
+Reconciliations, Abbreviations and Definitions
+
+--- end page 56
+
+## Abbreviations
+
+*   APLNG: Australia Pacific LNG
+*   B: billion
+*   BBL: barrel
+*   BBOE: billions of barrels of oil equivalent
+*   BCFD: billion cubic feet per day
+*   BOE: barrels of oil equivalent
+*   CAGR: compound annual growth rate
+*   CAPEX: capital expenditures and investments
+*   CCS: carbon capture and storage
+*   CFO: cash from operations
+*   CO2: carbon dioxide
+*   CO₂e: carbon dioxide equivalent
+*   CoS: Cost of Supply
+*   CPF: central processing facility
+*   E-FRAC: electric frac
+*   EMENA: Europe, Middle East and North Africa
+*   EPC: engineering procurement and construction
+*   ESG: environmental, social and governance
+*   EUR: estimated ultimate recovery
+*   FEED: front end engineering design
+*   FERC: Federal Energy Regulatory Commission
+*   FCF: free cash flow
+*   FID: final investment decision
+*   FT: foot
+*   G&A: general and administrative
+*   GAAP: generally accepted accounting principles
+*   GHG: greenhouse gas emissions
+
+*   GKA: Greater Kuparuk Area
+*   GPA: Greater Prudhoe Area
+*   GWA: Greater Willow Area
+*   GWh: gigawatt-hour
+*   KG: kilograms
+*   LNG: liquefied natural gas
+*   MBOD: thousands of barrels of oil per day
+*   MBOED: thousands of barrels of oil equivalent per day
+*   MM: million
+*   MMBOD: millions of barrels of oil per day
+*   MMBOED: millions of barrels of oil equivalent per day
+*   MT: million tonnes
+*   MTPA: million tonnes per annum
+*   MWh: megawatt-hour
+*   NFE: North Field East
+*   NFS: North Field South
+*   NGL: natural gas liquids
+*   OPEX: operating expenses
+*   PA LNG: Port Arthur LNG
+*   QG3: Qatargas 3
+*   ROCE: return on capital employed
+*   Te: tonnes
+*   THE: Trading Hub Europe
+*   VROC: variable return of cash
+*   WNS: Western North Slope
+*   WTI: West Texas Intermediate
+
+ConocoPhillips 57
+
+--- end page 57
+
+## Non-GAAP Reconciliations
+
+Use of Non-GAAP Financial Information: ConocoPhillips' financial information includes information prepared in conformity with generally accepted accounting principles (GAAP) as well as non-GAAP information. It is management's intent to provide non-GAAP financial information to enhance understanding of our consolidated financial information as prepared in accordance with GAAP. This non-GAAP information should be considered by the reader in addition to, but not instead of, the financial statements prepared in accordance with GAAP. Each historical non-GAAP financial measure included in this presentation is presented along with the corresponding GAAP measure, so as not to imply that more emphasis should be placed on the non-GAAP measure. The non-GAAP financial information presented may be determined or calculated differently by other companies.
+
+### Reconciliation of Return on Capital Employed (ROCE)
+
+|                                                                  | 2016    | 2019    | 2022    |
+| ---------------------------------------------------------------- | ------- | ------- | ------- |
+| **Numerator**                                                    |         |         |         |
+| Net Income (Loss) Attributable to ConocoPhillips                | (3,615) | 7,189   | 18,680  |
+| Adjustment to Exclude Special Items                              | 307     | (3,153) | (1,340) |
+| Net Income Attributable to Noncontrolling Interests             | 56      | 68      | -       |
+| After-tax Interest Expense                                       | 796     | 637     | 641     |
+| ROCE Earnings                                                    | (2,456) | 4,741   | 17,981  |
+|                                                                  |         |         |         |
+| **Denominator**                                                  |         |         |         |
+| Average Total Equity¹                                            | 37,837  | 33,713  | 48,801  |
+| Average Total Debt²                                              | 28,225  | 14,930  | 17,742  |
+| Average Capital Employed                                         | 66,062  | 48,643  | 66,543  |
+|                                                                  |         |         |         |
+| ROCE (percent)                                                   | -4%     | 10%     | 27%     |
+
+¹Average total equity is the average of beginning total equity and ending total equity by quarter.
+²Average total debt is the average of beginning long-term debt and short-term debt and ending long-term debt and short-term debt by quarter.
+
+--- end page 58
+
+## Non-GAAP Reconciliations – Continued
+
+### Reconciliation of Net Cash Provided by Operating Activities to Cash from Operations to Free Cash Flow
+
+($ Millions, Except as Indicated)
+
+|                                              | 2016  | 2019  | 2022  |
+| -------------------------------------------- | ----- | ----- | ----- |
+| Net Cash Provided by Operating Activities    | 4,403 | 11,104 | 28,314 |
+| Adjustments:                                 |       |       |       |
+| Net Operating Working Capital Changes        | (481) | (579) | (234) |
+| Cash from Operations                         | 4,884 | 11,683 | 28,548 |
+| Capital Expenditures and Investments         | (4,869) | (6,636) | (10,159) |
+| Free Cash Flow                               | 15    | 5,047 | 18,389 |
+
+### Reconciliation of Debt to Net Debt
+
+($ Millions, Except as Indicated)
+
+|                                    | 2016   | 2019   | 2022   |
+| ---------------------------------- | -------- | -------- | -------- |
+| Total Debt                         | 27,275 | 14,895 | 16,643 |
+| Less:                              |        |        |        |
+| Cash and Cash Equivalents¹         | 3,610  | 5,362  | 6,694  |
+| Short-Term Investments             | 50     | 3,028  | 2,785  |
+| Net Debt                             | 23,615 | 6,505  | 7,164  |
+
+¹Includes restricted cash of $0.3B in 2019 and $0.2B in 2022.
+
+--- end page 59
+
+## Non-GAAP Reconciliations – Continued
+
+### Reconciliation of Reinvestment Rate
+
+($ Millions, Except as Indicated)
+
+|                                               | 2012   | 2013   | 2014   | 2015   | 2016   | 2017   | 2018   | 2019   | 2020   | 2021   | 2022   |
+| :-------------------------------------------- | :----- | :----- | :----- | :----- | :----- | :----- | :----- | :----- | :----- | :----- | :----- |
+| Numerator                                     |        |        |        |        |        |        |        |        |        |        |        |
+| Capital Expenditure and Investments           | 14,172 | 15,537 | 17,085 | 10,050 | 4,869  | 4,591  | 6,750  | 6,636  | 4,715  | 5,324  | 10,159 |
+| Denominator                                   |        |        |        |        |        |        |        |        |        |        |        |
+| Net Cash Provided by Operating Activities    | 13,922 | 16,087 | 16,735 | 7,572  | 4,403  | 7,077  | 12,934 | 11,104 | 4,802  | 16,996 | 28,314 |
+| Net Operating Working Capital Changes        | (1,239) | 48     | (505) | (22)   | (481) | 15     | 635    | (579) | (372) | 1,271 | (234) |
+| Cash from Operations                          | 15,161 | 16,039 | 17,240 | 7,594  | 4,884  | 7,062  | 12,299 | 11,683 | 5,174  | 15,725 | 28,548 |
+| Reinvestment Rate                             | 93%    | 97%    | 99%    | 132%   | 100%   | 65%    | 55%    | 57%    | 91%    | 34%    | 36%    |
+
+**104%** Average 2012-2016 Reinvestment Rate
+
+**56%** Average 2017-2022 Reinvestment Rate
+
+Reinvestment rates in 2012-2016 and 2017-2022 columns represent the simple averages of corresponding years.
+
+--- end page 60
+
+## Definitions
+
+### Non-GAAP Measures
+
+Cash from operations (CFO) is calculated by removing the impact from operating working capital from cash provided by operating activities. The company believes that the non-GAAP measure cash from operations is useful to investors to help understand changes in cash provided by operating activities excluding the impact of working capital changes across periods on a consistent basis and with the performance of peer companies in a manner that, when viewed in combination with the Company's results prepared in accordance with GAAP, provides a more complete understanding of the factors and trends affecting the Company's business and performance. Additionally, when the company estimates CFO based on sensitivities, it assumes no operating working capital changes, and therefore CFO equals cash provided by operating activities.
+
+Free cash flow is defined as cash from operations net of capital expenditures and investments. The company believes free cash flow is useful to investors in understanding how existing cash from operations is utilized as a source for sustaining our current capital plan and future development growth. Free cash flow is not a measure of cash available for discretionary expenditures since the company has certain non-discretionary obligations such as debt service that are not deducted from the measure.
+
+Net debt includes total balance sheet debt less cash, cash equivalents and short-term investments. The company believes this non-GAAP measure is useful to investors as it provides a measure to compare debt less cash, cash equivalents and short-term investments across periods on a consistent basis.
+
+Reinvestment rate defined as total capital expenditures divided by cash from operations. Cash from operations is a non-GAAP measure defined in this Appendix. The company believes reinvestment rate is useful to investors in understanding the execution of the company's disciplined and returns-focused capital allocation strategy.
+
+Return on capital employed (ROCE) is a measure of the profitability of the company's capital employed in its business operations compared with that of its peers. The company calculates ROCE as a ratio, the numerator of which is net income, and the denominator of which is average total equity plus average total debt. The net income is adjusted for after-tax interest expense, for the purposes of measuring efficiency of debt capital used in operations; net income is also adjusted for non-operational or special items impacts to allow for comparability in the long-term view across periods. The company believes ROCE is a good indicator of long-term company and management performance as it relates to capital efficiency, both absolute and relative to the company's primary peer group.
+
+--- end page 61
+
+## Definitions
+
+### Other Terms
+
+Cost of Supply is the WTI equivalent price that generates a 10% after-tax return on a point-forward and fully burdened basis. Fully burdened includes capital infrastructure, foreign exchange, price-related inflation, G&A and carbon tax (if currently assessed). If no carbon tax exists for the asset, carbon pricing aligned with internal energy scenarios are applied. All barrels of resource in the Cost of Supply calculation are discounted at 10%.
+
+Distributions is defined as the total of the ordinary dividend, share repurchases and variable return of cash (VROC). Also referred to as return of capital.
+
+Free cash flow breakeven is the WTI price at which cash from operations equals capital expenditures and investments. Also referred to as capital breakeven. Cash from operations is a non-GAAP measure defined in this Appendix.
+
+Leverage ratio refers to net debt divided by cash from operations. Net debt and cash from operations are non-GAAP measures defined in this Appendix.
+
+Optimized Cascade® Process is a ConocoPhillips proprietary licensed process for technology to liquefy natural gas. More information can be found at http://Inglicensing.conocophillips.com/what-we-do/Ing-technology/optimized-cascade-process.
+
+Reserve replacement is defined by the Company as a ratio representing the change in proved reserves, net of production, divided by current year production. The Company believes that reserve replacement is useful to investors to help understand how changes in proved reserves, net of production, compare with the Company's current year production, inclusive of acquisitions and dispositions.
+
+Resources: The company estimates its total resources based on the Petroleum Resources Management System (PRMS), a system developed by industry that classifies recoverable hydrocarbons into commercial and sub-commercial to reflect their status at the time of reporting. Proved, probable and possible reserves are classified as commercial, while remaining resources are categorized as sub-commercial or contingent. The company's resource estimate includes volumes associated with both commercial and contingent categories. The SEC permits oil and gas companies, in their filings with the SEC, to disclose only proved, probable and possible reserves. U.S. investors are urged to consider closely the oil and gas disclosures in our Form 10-K and other reports and filings with the SEC.
+
+Resource life is calculated as total resource under $40 Cost of Supply divided by 2022 production.
+
+Return of capital is defined as the total of the ordinary dividend, share repurchases and variable return of cash (VROC). Also referred to as distributions.
+
+--- end page 62
+

data/cache/XC9500_CPLD_Family.pdf.md

@@ -0,0 +1,802 @@
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+
+# XC9500 In-System Programmable CPLD Family
+
+Product Specification
+
+DS063 (v6.0) May 17, 2013
+
+# Features
+
+*   High-performance
+*   5 ns pin-to-pin logic delays on all pins
+*   fCNT to 125 MHz
+*   Large density range
+    *   36 to 288 macrocells with 800 to 6,400 usable gates
+*   5V in-system programmable
+    *   Endurance of 10,000 program/erase cycles
+    *   Program/erase over full commercial voltage and temperature range
+*   Enhanced pin-locking architecture
+*   Flexible 36V18 Function Block
+    *   90 product terms drive any or all of 18 macrocells within Function Block
+*   Global and product term clocks, output enables, set and reset signals
+*   Extensive IEEE Std 1149.1 boundary-scan (JTAG) support
+*   Programmable power reduction mode in each macrocell
+*   Slew rate control on individual outputs
+*   User programmable ground pin capability
+*   Extended pattern security features for design protection
+*   High-drive 24 mA outputs
+*   3.3V or 5V I/O capability
+
+*   Advanced CMOS 5V FastFLASH™™ technology
+*   Supports parallel programming of multiple XC9500 devices
+
+# Family Overview
+
+The XC9500 CPLD family provides advanced in-system programming and test capabilities for high performance, general purpose logic integration. All devices are in-system programmable for a minimum of 10,000 program/erase cycles. Extensive IEEE 1149.1 (JTAG) boundary-scan support is also included on all family members.
+
+As shown in Table 1, logic density of the XC9500 devices ranges from 800 to over 6,400 usable gates with 36 to 288 registers, respectively. Multiple package options and associated I/O capacity are shown in Table 2. The XC9500 family is fully pin-compatible allowing easy design migration across multiple density options in a given package footprint.
+
+The XC9500 architectural features address the requirements of in-system programmability. Enhanced pin-locking capability avoids costly board rework. An expanded JTAG instruction set allows version control of programming patterns and in-system debugging. In-system programming throughout the full device operating range and a minimum of 10,000 program/erase cycles provide worry-free reconfigurations and system field upgrades.
+
+Advanced system features include output slew rate control and user-programmable ground pins to help reduce system noise. I/Os may be configured for 3.3V or 5V operation. All outputs provide 24 mA drive.
+
+[Table 1: XC9500 Device Family]
+
+|                | XC9536 | XC9572 | XC95108 | XC95144 | XC95216 | XC95288 |
+| :------------- | :-----: | :-----: | :------: | :-----: | :-----: | :-----: |
+| Macrocells     |   36    |   72    |   108    |   144   |   216   |   288   |
+| Usable Gates   |  800    |  1,600  |  2,400   |  3,200  |  4,800  |  6,400  |
+| Registers      |   36    |   72    |   108    |   144   |   216   |   288   |
+| TPD (ns)       |   5     |   7.5   |   7.5    |   7.5   |   10    |   15    |
+| TSU (ns)       |   3.5   |   4.5   |   4.5    |   4.5   |   6.0   |   8.0   |
+| TCO (ns)       |   4.0   |   4.5   |   4.5    |   4.5   |   6.0   |   8.0   |
+| fCNT (MHz)(1)   |  100    |   125   |   125    |   125   |  111.1  |  92.2   |
+| fSYSTEM (MHz)(2) |  100    |   83.3  |   83.3   |   83.3  |   66.7  |   56.6  |
+
+1.  fCNT = Operating frequency for 16-bit counters.
+2.  fSYSTEM = Internal operating frequency for general purpose system designs spanning multiple FBs.
+
+© 1998-2007, 2013 Xilinx, Inc. All rights reserved. All Xilinx trademarks, registered trademarks, patents, and disclaimers are as listed at http://www.xilinx.com/legal.htm.
+
+All other trademarks and registered trademarks are the property of their respective owners. All specifications are subject to change without notice.
+
+DS063 (v6.0) May 17, 2013
+
+Product Specification
+
+www.xilinx.com
+
+1
+
+
+--- end page 1
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+[Table 2: Available Packages and Device I/O Pins (not including dedicated JTAG pins)]
+|                | XC9536 | XC9572 | XC95108 | XC95144 | XC95216 | XC95288 |
+|----------------|--------|--------|---------|---------|---------|---------|
+| 44-Pin VQFP     | 34     |        |         |         |         |         |
+| 44-Pin PLCC     | 34     | 34     |         |         |         |         |
+| 48-Pin CSP      | 34     |        |         |         |         |         |
+| 84-Pin PLCC     | -      | 69     | 69      |         |         |         |
+| 100-Pin TQFP    | -      | 72     | 81      | 81      |         |         |
+| 100-Pin PQFP    | -      | 72     | 81      | 81      |         |         |
+| 160-Pin PQFP    | -      | -      | 108     | 133     | 133     |         |
+| 208-Pin HQFP    | -      | -      | -       | -       | 166     | 168     |
+| 352-Pin BGA     | -      | -      | -       | -       | 166(2)  | 192     |
+
+1. Most packages available in Pb-Free option. See individual data sheets for more details.
+2. 352-pin BGA package is being discontinued for the XC95216. See XCN07010 for details.
+
+## Architecture Description
+
+Each XC9500 device is a subsystem consisting of multiple
+Function Blocks (FBs) and I/O Blocks (IOBs) fully intercon-
+nected by the Fast CONNECT™™ switch matrix. The IOB
+provides buffering for device inputs and outputs. Each FB
+provides programmable logic capability with 36 inputs and
+18 outputs. The Fast CONNECT switch matrix connects all
+FB outputs and input signals to the FB inputs. For each FB,
+12 to 18 outputs (depending on package pin-count) and
+associated output enable signals drive directly to the IOBs.
+See Figure 1.
+
+--- end page 2
+
+# XILINX
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+XC9500 In-System Programmable CPLD Family
+
+![Figure 1: XC9500 Architecture. The image shows a block diagram of the XC9500 architecture. The key components include JTAG Port, JTAG Controller, In-System Programming Controller, I/O Blocks, Fast CONNECT II Switch Matrix, and Function Blocks (1 to N).  Each Function Block consists of Macrocells (1 to 18). Numbers indicate the number of signals or connections. Note: Function block outputs (indicated by the bold lines) drive the I/O blocks directly.](image_reference)
+
+Note: Function block outputs (indicated by the bold lines) drive the I/O blocks directly.
+
+## Function Block
+
+Each Function Block, as shown in *Figure 2*, is comprised of 18 independent macrocells, each capable of implementing a combinatorial or registered function. The FB also receives global clock, output enable, and set/reset signals. The FB generates 18 outputs that drive the Fast CONNECT switch matrix. These 18 outputs and their corresponding output enable signals also drive the IOB.
+
+Logic within the FB is implemented using a sum-of-products representation. Thirty-six inputs provide 72 true and complement signals into the programmable AND-array to form 90 product terms. Any number of these product terms, up to the 90 available, can be allocated to each macrocell by the product term allocator.
+
+Each FB (except for the XC9536) supports local feedback paths that allow any number of FB outputs to drive into its own programmable AND-array without going outside the FB. These paths are used for creating very fast counters and state machines where all state registers are within the same FB.
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+www.xilinx.com
+3
+
+--- end page 3
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+# XC9500 In-System Programmable CPLD Family
+
+![Figure 2: XC9500 Function Block. The block diagram shows: From Fast CONNECT II Switch Matrix entering a Programmable AND-Array, which connects to Product Term Allocators. This leads to Macrocell 1 through Macrocell 18. Connections show 18 lines to To Fast CONNECT II Switch Matrix, 18 lines to OUT, and 18 lines to To I/O Blocks. Also shows inputs for Global Set/Reset and Global Clocks.](image_reference)
+
+From
+Fast CONNECT II
+Switch Matrix
+36
+
+Macrocell 1
+
+Programmable
+AND-Array
+
+Product
+Term
+Allocators
+
+18
+
+To Fast CONNECT II
+Switch Matrix
+
+18
+OUT
+18
+PTOE
+To I/O Blocks
+
+Macrocell 18
+
+1
+Global
+Set/Reset
+
+3
+Global
+Clocks
+
+Figure 2: XC9500 Function Block
+
+DS063 02 110501
+
+4
+
+[www.xilinx.com](www.xilinx.com)
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+--- end page 4
+
+# XILINX® PRODUCT OBSOLETE / UNDER OBSOLESCENCE XC9500 In-System Programmable CPLD Family
+
+## Macrocell
+
+Each XC9500 macrocell may be individually configured for
+a combinatorial or registered function. The macrocell and
+associated FB logic is shown in Figure 3.
+
+Five direct product terms from the AND-array are available
+for use as primary data inputs (to the OR and XOR gates) to
+implement combinatorial functions, or as control inputs
+including clock, set/reset, and output enable. The product
+term allocator associated with each macrocell selects how
+the five direct terms are used.
+
+The macrocell register can be configured as a D-type or
+T-type flip-flop, or it may be bypassed for combinatorial
+operation. Each register supports both asynchronous set
+and reset operations. During power-up, all user registers
+are initialized to the user-defined preload state (default to 0
+if unspecified).
+
+![Figure 3: XC9500 Macrocell Within Function Block](image_reference)
+
+Figure 3: XC9500 Macrocell Within Function Block
+
+--- end page 5
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+# XC9500 In-System Programmable CPLD Family
+
+All global control signals are available to each individual
+macrocell, including clock, set/reset, and output enable sig-
+nals. As shown in Figure 4, the macrocell register clock
+originates from either of three global clocks or a product
+term clock. Both true and complement polarities of a GCK
+pin can be used within the device. A GSR input is also pro-
+vided to allow user registers to be set to a user-defined
+state.
+
+![Figure 4: Macrocell Clock and Set/Reset Capability](image_reference)
+
+--- end page 6
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+![Figure 1: XILINX® Logo](image_reference)
+
+## Product Term Allocator
+
+The product term allocator controls how the five direct product terms are assigned to each macrocell. For example, all five direct terms can drive the OR function as shown in Figure 5.
+
+Note that the incremental delay affects only the product terms in other macrocells. The timing of the direct product terms is not changed.
+
+![Figure 2: Product Term Allocator with Macrocell Product Term Logic](image_reference)
+
+**Figure 5: Macrocell Logic Using Direct Product Term**
+
+The product term allocator can re-assign other product terms within the FB to increase the logic capacity of a macrocell beyond five direct terms. Any macrocell requiring additional product terms can access uncommitted product terms in other macrocells within the FB. Up to 15 product terms can be available to a single macrocell with only a small incremental delay of TPTA, as shown in Figure 6.
+
+![Figure 3: Product Term Allocation With 15 Product Terms](image_reference)
+
+**Figure 6: Product Term Allocation With 15 Product Terms**
+
+--- end page 7
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+The product term allocator can re-assign product terms
+from any macrocell within the FB by combining partial sums
+of products over several macrocells, as shown in Figure 7.
+In this example, the incremental delay is only 2*TPTA. All 90
+product terms are available to any macrocell, with a maxi-
+mum incremental delay of 8*TPTA.
+
+![Figure 7: Product Term Allocation Over Several Macrocells](image_reference)
+
+Product Term
+Allocator
+
+Macrocell Logic
+With 2
+Product Terms
+
+Product Term
+Allocator
+
+Product Term
+Allocator
+
+Macrocell Logic
+With 18
+Product Terms
+
+Product Term
+Allocator
+
+DS063_07_110501
+
+Figure 7: Product Term Allocation Over Several
+Macrocells
+
+8
+
+www.xilinx.com
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+
+--- end page 8
+
+XILINX®
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+The internal logic of the product term allocator is shown in
+Figure 8.
+
+![Figure 8: Product Term Allocator Logic](image_reference)
+
+Figure 8: Product Term Allocator Logic
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+www.xilinx.com
+9
+
+--- end page 9
+
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+
+# XC9500 In-System Programmable CPLD Family
+
+## Fast CONNECT Switch Matrix
+
+The Fast CONNECT switch matrix connects signals to the FB inputs, as shown in Figure 9. All IOB outputs (corre-
+sponding to user pin inputs) and all FB outputs drive the Fast CONNECT matrix. Any of these (up to a FB fan-in limit
+of 36) may be selected, through user programming, to drive each FB with a uniform delay.
+
+The Fast CONNECT switch matrix is capable of combining multiple internal connections into a single wired-AND output
+before driving the destination FB. This provides additional logic capability and increases the effective logic fan-in of the
+destination FB without any additional timing delay. This capability is available for internal connections originating
+from FB outputs only. It is automatically invoked by the development software where applicable.
+
+![Figure 9: Fast CONNECT Switch Matrix](image_reference)
+
+Wired-AND
+Capability
+
+Fast CONNECT
+Switch Matrix
+
+Function Block
+
+I/O Block
+
+(36).
+
+18
+
+D/T Q
+
+(36).
+
+Function Block
+
+I/O Block
+
+18
+
+D/T Q
+
+1/0
+
+1/0
+
+DS063_09_110501
+
+Figure 9: Fast CONNECT Switch Matrix
+
+10
+
+www.xilinx.com
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+--- end page 10
+
+# XILINX®
+PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+## I/O Block
+
+The I/O Block (IOB) interfaces between the internal logic
+and the device user I/O pins. Each IOB includes an input
+buffer, output driver, output enable selection multiplexer,
+and user programmable ground control. See Figure 10 for
+details.
+
+The input buffer is compatible with standard 5V CMOS, 5V
+TTL, and 3.3V signal levels. The input buffer uses the internal
+5V voltage supply (VCCINT) to ensure that the input thresh-
+olds are constant and do not vary with the Vccio voltage.
+
+The output enable may be generated from one of four
+options: a product term signal from the macrocell, any of the
+global OE signals, always [1], or always [0]. There are two
+global output enables for devices with up to 144 macrocells,
+and four global output enables for the rest of the devices.
+Both polarities of any of the global 3-state control (GTS)
+pins may be used within the device..
+
+![Figure 10: I/O Block and Output Enable Capability](image_reference)
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+www.xilinx.com
+11
+
+--- end page 11
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+Each output has independent slew rate control. Output
+edge rates may be slowed down to reduce system noise
+(with an additional time delay of TSLEW) through program-
+ming. See Figure 11.
+
+Each IOB provides user programmable ground pin capabil-
+ity. This allows device I/O pins to be configured as additional
+ground pins. By tying strategically located programmable
+ground pins to the external ground connection, system
+noise generated from large numbers of simultaneous
+switching outputs may be reduced.
+
+A control pull-up resistor (typically 10K ohms) is attached to
+each device I/O pin to prevent them from floating when the
+device is not in normal user operation. This resistor is active
+during device programming mode and system power-up. It
+is also activated for an erased device. The resistor is deac-
+tivated during normal operation.
+
+The output driver is capable of supplying 24 mA output
+drive. All output drivers in the device may be configured for
+either 5V TTL levels or 3.3V levels by connecting the device
+output voltage supply (Vccio) to a 5V or 3.3V voltage sup-
+
+![Figure 1: Output slew-Rate for (a) Rising and (b) Falling Outputs. The graph shows Output Voltage on the Y axis and Time on the X axis. Figure (a) shows the rising output voltage over time, with annotations for "Standard", "Slew-Rate Limited", and "TSLEW". Figure (b) shows the falling output voltage over time, with annotations for "Standard", "Slew-Rate Limited", and "TSLEW".](image_reference)
+
+![Figure 2: XC9500 Devices in (a) 5V Systems and (b) Mixed 5V/3.3V Systems. Figure (a) shows a diagram of the XC9500 CPLD in a 5V system, with connections for 5V CMOS or 5V TTL, VCCINT, VCCIO, IN, OUT, and GND. Figure (b) shows a diagram of the XC9500 CPLD in a mixed 5V/3.3V system, with connections for 5V CMOS or 5V TTL, VCCINT, VCCIO, IN, OUT, and GND.](image_reference)
+
+ply. Figure 12 shows how the XC9500 device can be used in
+5V only and mixed 3.3V/5V systems.
+
+Pin-Locking Capability
+
+The capability to lock the user defined pin assignments dur-
+ing design changes depends on the ability of the architec-
+ture to adapt to unexpected changes. The XC9500 devices
+have architectural features that enhance the ability to
+accept design changes while maintaining the same pinout.
+
+The XC9500 architecture provides maximum routing within
+the Fast CONNECT switch matrix, and incorporates a flexi-
+ble Function Block that allows block-wide allocation of avail-
+able product terms. This provides a high level of confidence
+of maintaining both input and output pin assignments for
+unexpected design changes.
+
+For extensive design changes requiring higher logic capас-
+ity than is available in the initially chosen device, the new
+design may be able to fit into a larger pin-compatible device
+using the same pin assignments. The same board may be
+used with a higher density device without the expense of
+board rework
+
+
+--- end page 12
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+## XC9500 In-System Programmable CPLD Family
+
+![XILINX®](no_image_available)
+
+## In-System Programming
+XC9500 devices are programmed in-system via a standard
+4-pin JTAG protocol, as shown in Figure 13. In-system pro-
+gramming offers quick and efficient design iterations and
+eliminates package handling. The Xilinx development sys-
+tem provides the programming data sequence using a Xilinx
+download cable, a third-party JTAG development system,
+JTAG-compatible board tester, or a simple microprocessor
+interface that emulates the JTAG instruction sequence.
+
+All I/Os are 3-stated and pulled high by the IOB resistors
+during in-system programming. If a particular signal must
+remain Low during this time, then a pulldown resistor may
+be added to the pin.
+
+## External Programming
+XC9500 devices can also be programmed by the Xilinx
+HW130 device programmer as well as third-party program-
+mers. This provides the added flexibility of using pre-pro-
+grammed devices during manufacturing, with an in-system
+programmable option for future enhancements.
+
+## Endurance
+All XC9500 CPLDs provide a minimum endurance level of
+10,000 in-system program/erase cycles. Each device meets
+all functional, performance, and data retention specifica-
+tions within this endurance limit.
+
+## IEEE 1149.1 Boundary-Scan (JTAG)
+XC9500 devices fully support IEEE 1149.1 boundary-scan
+(JTAG). EXTEST, SAMPLE/PRELOAD, BYPASS, USER-
+CODE, INTEST, IDCODE, and HIGHZ instructions are sup-
+ported in each device. For ISP operations, five additional
+instructions are added; the ISPEN, FERASE, FPGM, FVFY,
+and ISPEX instructions are fully compliant extensions of the
+1149.1 instruction set.
+
+The TMS and TCK pins have dedicated pull-up resistors as
+specified by the IEEE 1149.1 standard.
+
+Boundary Scan Description Language (BSDL) files for the
+XC9500 are included in the development system and are
+available on the Xilinx FTP site.
+
+## Design Security
+XC9500 devices incorporate advanced data security fea-
+tures which fully protect the programming data against
+unauthorized reading or inadvertent device erasure/repro-
+gramming. Table 3 shows the four different security settings
+available.
+
+The read security bits can be set by the user to prevent the
+internal programming pattern from being read or copied.
+When set, they also inhibit further program operations but
+allow device erase. Erasing the entire device is the only way
+to reset the read security bit.
+
+The write security bits provide added protection against
+accidental device erasure or reprogramming when the
+JTAG pins are subject to noise, such as during system
+power-up. Once set, the write-protection may be deacti-
+vated when the device needs to be reprogrammed with a
+valid pattern.
+
+[Table 3: Data Security Options]
+|                               |            |                         Read Security                        |
+| :---------------------------- | :--------- | :----------------------------------------------------------: |
+|                               |            |                           Default                            |                              Set                               |
+| **Write Security**            | **Default**|                   Read Allowed Program/Erase Allowed                   |     Read Inhibited Program Inhibited Erase Allowed      |
+|                               | **Set**    | Read Allowed Program/Erase Inhibited | Program/Erase Inhibited  |
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+[www.xilinx.com](www.xilinx.com)
+
+13
+
+--- end page 13
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+![Figure 13: Diagram showing In-System Programming Operation. (a) Solder Device to PCB showing integrated circuit connected with pins to a circuit board with various components. (b) Program Using Download Cable showing a laptop connected with a cable to an integrated circuit connected with pins to a circuit board with various components.](image_reference)
+
+Figure 13: In-System Programming Operation (a) Solder Device to PCB and (b) Program Using Download Cable
+
+## Low Power Mode
+
+All XC9500 devices offer a low-power mode for individual
+macrocells or across all macrocells. This feature allows the
+device power to be significantly reduced.
+
+Each individual macrocell may be programmed in
+low-power mode by the user. Performance-critical parts of
+the application can remain in standard power mode, while
+other parts of the application may be programmed for
+low-power operation to reduce the overall power dissipation.
+Macrocells programmed for low-power mode incur addi-
+tional delay (TLP) in pin-to-pin combinatorial delay as well as
+register setup time. Product term clock to output and prod-
+uct term output enable delays are unaffected by the macro-
+cell power-setting.
+
+## Timing Model
+
+The uniformity of the XC9500 architecture allows a simpli-
+fied timing model for the entire device. The basic timing
+model, shown in Figure 14, is valid for macrocell functions
+that use the direct product terms only, with standard power
+setting, and standard slew rate setting. Table 4 shows how
+each of the key timing parameters is affected by the product
+term allocator (if needed), low-power setting, and slew-lim-
+ited setting.
+
+The product term allocation time depends on the logic span
+of the macrocell function, which is defined as one less than
+the maximum number of allocators in the product term path.
+If only direct product terms are used, then the logic span is
+0. The example in Figure 6 shows that up to 15 product
+terms are available with a span of 1. In the case of Figure 7,
+the 18 product term function has a span of 2.
+
+Detailed timing information may be derived from the full tim-
+ing model shown in Figure 15. The values and explanations
+for each parameter are given in the individual device data
+sheets.
+
+--- end page 14
+
+# XILINX
+
+## PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+![Figure 14: Basic Timing Model](image_reference)
+
+TPSU
+Combinatorial
+Logic
+
+Propagation Delay = TPD
+(a)
+Combinatorial
+Logic
+P-Term Clock
+Path
+D/T Q
+TPCO
+Combinatorial
+Logic
+D/T Q
+Tco
+Setup Time = Tsu
+(b)
+Clock to Out Time = Tco
+Combinatorial
+Logic
+D/T Q
+Setup Time = TPSU
+(c)
+Clock to Out Time = TPCO
+All resources within FB using local Feedback
+Internal System Cycle Time = TSYSTEM
+(d)
+Combinatorial
+Logic
+D/T Q
+Internal Cycle Time = TCNT
+(e)
+
+![Figure 15: Detailed Timing Model](image_reference)
+
+Pin Feedback
+
+TF
+TIN
+TLOGILP
+TLOGI
+S*TPTA
+TSLEW
+TPDI
+D/T
+Q
+TOUT
+TPTCK
+TSUITCOI
+THI
+EC TAOI
+TRAI
+TGCK
+TPTSR
+SR
+TGSR
+TPTTS
+Macrocell
+TGTS
+TEN
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+www.xilinx.com
+15
+
+--- end page 15
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+## Power-Up Characteristics
+The XC9500 devices are well behaved under all operating
+conditions. During power-up each XC9500 device employs
+internal circuitry which keeps the device in the quiescent
+state until the VCCINT supply voltage is at a safe level
+(approximately 3.8V). During this time, all device pins and
+JTAG pins are disabled and all device outputs are disabled
+with the IOB pull-up resistors (~10K ohms) enabled, as
+shown in Table 5. When the supply voltage reaches a safe
+level, all user registers become initialized (typically within
+100 με for 9536, 95144, 200 μs for 95216, and 300 μs for
+95288), and the device is immediately available for opera-
+tion, as shown in Figure 16.
+
+If the device is in the erased state (before any user pattern
+is programmed), the device outputs remain disabled with
+the IOB pull-up resistors enabled. The JTAG pins are
+enabled to allow the device to be programmed at any time.
+
+If the device is programmed, the device inputs and outputs
+take on their configured states for normal operation. The
+JTAG pins are enabled to allow device erasure or bound-
+ary-scan tests at any time.
+
+## Development System Support
+The XC9500 CPLD family is fully supported by the develop-
+ment systems available from Xilinx and the Xilinx Alliance
+Program vendors.
+
+The designer can create the design using ABEL, schemat-
+ics, equations, VHDL, or Verilog in a variety of software
+front-end tools. The development system can be used to
+
+implement the design and generate a JEDEC bitmap which
+can be used to program the XC9500 device. Each develop-
+ment system includes JTAG download software that can be
+used to program the devices via the standard JTAG inter-
+face and a download cable.
+
+## FastFLASH Technology
+An advanced CMOS Flash process is used to fabricate all
+XC9500 devices. Specifically developed for Xilinx in-system
+programmable CPLDs, the FastFLASH process provides
+high performance logic capability, fast programming times,
+and endurance of 10,000 program/erase cycles.
+
+![Figure 16: Device Behavior During Power-up](no_image)
+VCCINT axis, 3.8V (Typ) label.
+No Power, Quiescent State, User Operation labels along the graph.
+
+[Table 4: Timing Model Parameters]
+| Parameter | Description | Product Term Allocator(1) | Macrocell Low-Power Setting | Output Slew-Limited Setting |
+|---|---|---|---|---|
+| TPD | Propagation Delay | + TPTA * S | + TLP | + TSLEW |
+| Tsu | Global Clock Setup Time | + TPTA * S | + TLP |  |
+| Tco | Global Clock-to-output |  |  | + TSLEW |
+| TPSU | Product Term Clock Setup Time | + TPTA * S | + TLP |  |
+| TPCO | Product Term Clock-to-output |  | - | + TSLEW |
+| TSYSTEM | Internal System Cycle Period | + TPTA* S | + TLP | - |
+Notes:
+1. S = the logic span of the function, as defined in the text.
+
+[Table 5: XC9500 Device Characteristics]
+| Device Circuitry | Quiescent State | Erased Device Operation | Valid User Operation |
+|---|---|---|---|
+| IOB Pull-up Resistors | Enabled | Enabled | Disabled |
+| Device Outputs | Disabled | Disabled | As Configured |
+
+--- end page 16
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+[Table 5: XC9500 Device Characteristics]
+| Device Circuitry         | Quiescent State | Erased Device Operation | Valid User Operation |
+| ------------------------ | --------------- | ----------------------- | -------------------- |
+| Device Inputs and Clocks | Disabled        | Disabled                | As Configured        |
+| Function Block           | Disabled        | Disabled                | As Configured        |
+| JTAG Controller          | Disabled        | Enabled                 | Enabled              |
+
+Warranty Disclaimer
+
+THESE PRODUCTS ARE SUBJECT TO THE TERMS OF THE XILINX LIMITED WARRANTY WHICH CAN BE VIEWED
+AT http://www.xilinx.com/warranty.htm. THIS LIMITED WARRANTY DOES NOT EXTEND TO ANY USE OF THE
+PRODUCTS IN AN APPLICATION OR ENVIRONMENT THAT IS NOT WITHIN THE SPECIFICATIONS STATED ON THE
+THEN-CURRENT XILINX DATA SHEET FOR THE PRODUCTS. PRODUCTS ARE NOT DESIGNED TO BE FAIL-SAFE
+AND ARE NOT WARRANTED FOR USE IN APPLICATIONS THAT POSE A RISK OF PHYSICAL HARM OR LOSS OF
+LIFE. USE OF PRODUCTS IN SUCH APPLICATIONS IS FULLY AT THE RISK OF CUSTOMER SUBJECT TO
+APPLICABLE LAWS AND REGULATIONS.
+
+Revision History
+The following table shows the revision history for this document.
+
+| Date       | Version | Revision                                                                                                                  |
+| ---------- | ------- | ------------------------------------------------------------------------------------------------------------------------- |
+| 12/14/1998 | 3.0     | Revised datasheet to reflect new AC characteristics and Internal Timing Parmeters.                                        |
+| 02/10/1999 | 4.0     | Corrected Figure 3.                                                                                                     |
+| 09/15/1999 | 5.0     | Added -10 speed grade to XC95288.                                                                                       |
+| 09/22/2003 | 5.1     | Minor edits.                                                                                                            |
+| 02/16/2004 | 5.2     | Corrected statement on GTS inputs on page 10. Added links to additional information.                                      |
+| 04/15/2005 | 5.3     | Update to PDF attributes only. No changes to documentation.                                                             |
+| 04/03/2006 | 5.4     | Added Warranty Disclaimer. Added note on Pb-Free packages.                                                                |
+| 06/25/2007 | 5.5     | Change to Table 2, listing discontinuance of 352-pin BGA package for the XC95216. See XCN07010 for details.              |
+| 05/17/2013 | 6.0     | The products listed in this data sheet are obsolete. See XCN11010 for further information.                              |
+
+--- end page 17
+

data/cache/XC9500_CPLD_Family.pdf.reformatted.md

@@ -0,0 +1,805 @@
+# XC9500 In-System Programmable CPLD Family
+
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+
+Product Specification
+
+DS063 (v6.0) May 17, 2013
+
+## Features
+
+*   High-performance
+*   5 ns pin-to-pin logic delays on all pins
+*   fCNT to 125 MHz
+*   Large density range
+    *   36 to 288 macrocells with 800 to 6,400 usable gates
+*   5V in-system programmable
+    *   Endurance of 10,000 program/erase cycles
+    *   Program/erase over full commercial voltage and temperature range
+*   Enhanced pin-locking architecture
+*   Flexible 36V18 Function Block
+    *   90 product terms drive any or all of 18 macrocells within Function Block
+*   Global and product term clocks, output enables, set and reset signals
+*   Extensive IEEE Std 1149.1 boundary-scan (JTAG) support
+*   Programmable power reduction mode in each macrocell
+*   Slew rate control on individual outputs
+*   User programmable ground pin capability
+*   Extended pattern security features for design protection
+*   High-drive 24 mA outputs
+*   3.3V or 5V I/O capability
+
+*   Advanced CMOS 5V FastFLASH™™ technology
+*   Supports parallel programming of multiple XC9500 devices
+
+## Family Overview
+
+The XC9500 CPLD family provides advanced in-system programming and test capabilities for high performance, general purpose logic integration. All devices are in-system programmable for a minimum of 10,000 program/erase cycles. Extensive IEEE 1149.1 (JTAG) boundary-scan support is also included on all family members.
+
+As shown in Table 1, logic density of the XC9500 devices ranges from 800 to over 6,400 usable gates with 36 to 288 registers, respectively. Multiple package options and associated I/O capacity are shown in Table 2. The XC9500 family is fully pin-compatible allowing easy design migration across multiple density options in a given package footprint.
+
+The XC9500 architectural features address the requirements of in-system programmability. Enhanced pin-locking capability avoids costly board rework. An expanded JTAG instruction set allows version control of programming patterns and in-system debugging. In-system programming throughout the full device operating range and a minimum of 10,000 program/erase cycles provide worry-free reconfigurations and system field upgrades.
+
+Advanced system features include output slew rate control and user-programmable ground pins to help reduce system noise. I/Os may be configured for 3.3V or 5V operation. All outputs provide 24 mA drive.
+
+### Table 1: XC9500 Device Family
+
+|                | XC9536 | XC9572 | XC95108 | XC95144 | XC95216 | XC95288 |
+| :------------- | :-----: | :-----: | :------: | :-----: | :-----: | :-----: |
+| Macrocells     |   36    |   72    |   108    |   144   |   216   |   288   |
+| Usable Gates   |  800    |  1,600  |  2,400   |  3,200  |  4,800  |  6,400  |
+| Registers      |   36    |   72    |   108    |   144   |   216   |   288   |
+| TPD (ns)       |   5     |   7.5   |   7.5    |   7.5   |   10    |   15    |
+| TSU (ns)       |   3.5   |   4.5   |   4.5    |   4.5   |   6.0   |   8.0   |
+| TCO (ns)       |   4.0   |   4.5   |   4.5    |   4.5   |   6.0   |   8.0   |
+| fCNT (MHz)(1)   |  100    |   125   |   125    |   125   |  111.1  |  92.2   |
+| fSYSTEM (MHz)(2) |  100    |   83.3  |   83.3   |   83.3  |   66.7  |   56.6  |
+
+1.  fCNT = Operating frequency for 16-bit counters.
+2.  fSYSTEM = Internal operating frequency for general purpose system designs spanning multiple FBs.
+
+© 1998-2007, 2013 Xilinx, Inc. All rights reserved. All Xilinx trademarks, registered trademarks, patents, and disclaimers are as listed at http://www.xilinx.com/legal.htm.
+
+All other trademarks and registered trademarks are the property of their respective owners. All specifications are subject to change without notice.
+
+DS063 (v6.0) May 17, 2013
+
+Product Specification
+
+www.xilinx.com
+
+1
+
+--- end page 1
+
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+
+XC9500 In-System Programmable CPLD Family
+
+### Table 2: Available Packages and Device I/O Pins (not including dedicated JTAG pins)
+
+|                | XC9536 | XC9572 | XC95108 | XC95144 | XC95216 | XC95288 |
+|----------------|--------|--------|---------|---------|---------|---------|
+| 44-Pin VQFP     | 34     |        |         |         |         |         |
+| 44-Pin PLCC     | 34     | 34     |         |         |         |         |
+| 48-Pin CSP      | 34     |        |         |         |         |         |
+| 84-Pin PLCC     | -      | 69     | 69      |         |         |         |
+| 100-Pin TQFP    | -      | 72     | 81      | 81      |         |         |
+| 100-Pin PQFP    | -      | 72     | 81      | 81      |         |         |
+| 160-Pin PQFP    | -      | -      | 108     | 133     | 133     |         |
+| 208-Pin HQFP    | -      | -      | -       | -       | 166     | 168     |
+| 352-Pin BGA     | -      | -      | -       | -       | 166(2)  | 192     |
+
+1. Most packages available in Pb-Free option. See individual data sheets for more details.
+2. 352-pin BGA package is being discontinued for the XC95216. See XCN07010 for details.
+
+## Architecture Description
+
+Each XC9500 device is a subsystem consisting of multiple
+Function Blocks (FBs) and I/O Blocks (IOBs) fully intercon-
+nected by the Fast CONNECT™™ switch matrix. The IOB
+provides buffering for device inputs and outputs. Each FB
+provides programmable logic capability with 36 inputs and
+18 outputs. The Fast CONNECT switch matrix connects all
+FB outputs and input signals to the FB inputs. For each FB,
+12 to 18 outputs (depending on package pin-count) and
+associated output enable signals drive directly to the IOBs.
+See Figure 1.
+
+--- end page 2
+
+# XILINX
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+XC9500 In-System Programmable CPLD Family
+
+![Figure 1: XC9500 Architecture. The image shows a block diagram of the XC9500 architecture. The key components include JTAG Port, JTAG Controller, In-System Programming Controller, I/O Blocks, Fast CONNECT II Switch Matrix, and Function Blocks (1 to N).  Each Function Block consists of Macrocells (1 to 18). Numbers indicate the number of signals or connections. Note: Function block outputs (indicated by the bold lines) drive the I/O blocks directly.](image_reference)
+
+Note: Function block outputs (indicated by the bold lines) drive the I/O blocks directly.
+
+## Function Block
+
+Each Function Block, as shown in *Figure 2*, is comprised of 18 independent macrocells, each capable of implementing a combinatorial or registered function. The FB also receives global clock, output enable, and set/reset signals. The FB generates 18 outputs that drive the Fast CONNECT switch matrix. These 18 outputs and their corresponding output enable signals also drive the IOB.
+
+Logic within the FB is implemented using a sum-of-products representation. Thirty-six inputs provide 72 true and complement signals into the programmable AND-array to form 90 product terms. Any number of these product terms, up to the 90 available, can be allocated to each macrocell by the product term allocator.
+
+Each FB (except for the XC9536) supports local feedback paths that allow any number of FB outputs to drive into its own programmable AND-array without going outside the FB. These paths are used for creating very fast counters and state machines where all state registers are within the same FB.
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+www.xilinx.com
+3
+
+--- end page 3
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+# XC9500 In-System Programmable CPLD Family
+
+![Figure 2: XC9500 Function Block. The block diagram shows: From Fast CONNECT II Switch Matrix entering a Programmable AND-Array, which connects to Product Term Allocators. This leads to Macrocell 1 through Macrocell 18. Connections show 18 lines to To Fast CONNECT II Switch Matrix, 18 lines to OUT, and 18 lines to To I/O Blocks. Also shows inputs for Global Set/Reset and Global Clocks.](image_reference)
+
+From
+Fast CONNECT II
+Switch Matrix
+36
+
+Macrocell 1
+
+Programmable
+AND-Array
+
+Product
+Term
+Allocators
+
+18
+
+To Fast CONNECT II
+Switch Matrix
+
+18
+OUT
+18
+PTOE
+To I/O Blocks
+
+Macrocell 18
+
+1
+Global
+Set/Reset
+
+3
+Global
+Clocks
+
+Figure 2: XC9500 Function Block
+
+DS063 02 110501
+
+4
+
+[www.xilinx.com](www.xilinx.com)
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+--- end page 4
+
+# XILINX® PRODUCT OBSOLETE / UNDER OBSOLESCENCE XC9500 In-System Programmable CPLD Family
+
+## Macrocell
+
+Each XC9500 macrocell may be individually configured for
+a combinatorial or registered function. The macrocell and
+associated FB logic is shown in Figure 3.
+
+Five direct product terms from the AND-array are available
+for use as primary data inputs (to the OR and XOR gates) to
+implement combinatorial functions, or as control inputs
+including clock, set/reset, and output enable. The product
+term allocator associated with each macrocell selects how
+the five direct terms are used.
+
+The macrocell register can be configured as a D-type or
+T-type flip-flop, or it may be bypassed for combinatorial
+operation. Each register supports both asynchronous set
+and reset operations. During power-up, all user registers
+are initialized to the user-defined preload state (default to 0
+if unspecified).
+
+![Figure 3: XC9500 Macrocell Within Function Block](image_reference)
+
+Figure 3: XC9500 Macrocell Within Function Block
+
+--- end page 5
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+# XC9500 In-System Programmable CPLD Family
+
+All global control signals are available to each individual
+macrocell, including clock, set/reset, and output enable sig-
+nals. As shown in Figure 4, the macrocell register clock
+originates from either of three global clocks or a product
+term clock. Both true and complement polarities of a GCK
+pin can be used within the device. A GSR input is also pro-
+vided to allow user registers to be set to a user-defined
+state.
+
+![Figure 4: Macrocell Clock and Set/Reset Capability](image_reference)
+
+--- end page 6
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+![Figure 1: XILINX® Logo](image_reference)
+
+## Product Term Allocator
+
+The product term allocator controls how the five direct product terms are assigned to each macrocell. For example, all five direct terms can drive the OR function as shown in Figure 5.
+
+Note that the incremental delay affects only the product terms in other macrocells. The timing of the direct product terms is not changed.
+
+![Figure 2: Product Term Allocator with Macrocell Product Term Logic](image_reference)
+
+**Figure 5: Macrocell Logic Using Direct Product Term**
+
+The product term allocator can re-assign other product terms within the FB to increase the logic capacity of a macrocell beyond five direct terms. Any macrocell requiring additional product terms can access uncommitted product terms in other macrocells within the FB. Up to 15 product terms can be available to a single macrocell with only a small incremental delay of TPTA, as shown in Figure 6.
+
+![Figure 3: Product Term Allocation With 15 Product Terms](image_reference)
+
+**Figure 6: Product Term Allocation With 15 Product Terms**
+
+--- end page 7
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+The product term allocator can re-assign product terms
+from any macrocell within the FB by combining partial sums
+of products over several macrocells, as shown in Figure 7.
+In this example, the incremental delay is only 2*TPTA. All 90
+product terms are available to any macrocell, with a maxi-
+mum incremental delay of 8*TPTA.
+
+![Figure 7: Product Term Allocation Over Several Macrocells](image_reference)
+
+Product Term
+Allocator
+
+Macrocell Logic
+With 2
+Product Terms
+
+Product Term
+Allocator
+
+Product Term
+Allocator
+
+Macrocell Logic
+With 18
+Product Terms
+
+Product Term
+Allocator
+
+DS063_07_110501
+
+Figure 7: Product Term Allocation Over Several
+Macrocells
+
+8
+
+www.xilinx.com
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+--- end page 8
+
+XILINX®
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+The internal logic of the product term allocator is shown in
+Figure 8.
+
+![Figure 8: Product Term Allocator Logic](image_reference)
+
+Figure 8: Product Term Allocator Logic
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+www.xilinx.com
+9
+
+--- end page 9
+
+– PRODUCT OBSOLETE / UNDER OBSOLESCENCE –
+
+# XC9500 In-System Programmable CPLD Family
+
+## Fast CONNECT Switch Matrix
+
+The Fast CONNECT switch matrix connects signals to the FB inputs, as shown in Figure 9. All IOB outputs (corre-
+sponding to user pin inputs) and all FB outputs drive the Fast CONNECT matrix. Any of these (up to a FB fan-in limit
+of 36) may be selected, through user programming, to drive each FB with a uniform delay.
+
+The Fast CONNECT switch matrix is capable of combining multiple internal connections into a single wired-AND output
+before driving the destination FB. This provides additional logic capability and increases the effective logic fan-in of the
+destination FB without any additional timing delay. This capability is available for internal connections originating
+from FB outputs only. It is automatically invoked by the development software where applicable.
+
+![Figure 9: Fast CONNECT Switch Matrix](image_reference)
+
+Wired-AND
+Capability
+
+Fast CONNECT
+Switch Matrix
+
+Function Block
+
+I/O Block
+
+(36).
+
+18
+
+D/T Q
+
+(36).
+
+Function Block
+
+I/O Block
+
+18
+
+D/T Q
+
+1/0
+
+1/0
+
+DS063_09_110501
+
+Figure 9: Fast CONNECT Switch Matrix
+
+10
+
+www.xilinx.com
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+--- end page 10
+
+# XILINX®
+PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+## I/O Block
+
+The I/O Block (IOB) interfaces between the internal logic
+and the device user I/O pins. Each IOB includes an input
+buffer, output driver, output enable selection multiplexer,
+and user programmable ground control. See Figure 10 for
+details.
+
+The input buffer is compatible with standard 5V CMOS, 5V
+TTL, and 3.3V signal levels. The input buffer uses the internal
+5V voltage supply (VCCINT) to ensure that the input thresh-
+olds are constant and do not vary with the Vccio voltage.
+
+The output enable may be generated from one of four
+options: a product term signal from the macrocell, any of the
+global OE signals, always [1], or always [0]. There are two
+global output enables for devices with up to 144 macrocells,
+and four global output enables for the rest of the devices.
+Both polarities of any of the global 3-state control (GTS)
+pins may be used within the device..
+
+![Figure 10: I/O Block and Output Enable Capability](image_reference)
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+www.xilinx.com
+11
+
+--- end page 11
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+Each output has independent slew rate control. Output
+edge rates may be slowed down to reduce system noise
+(with an additional time delay of TSLEW) through program-
+ming. See Figure 11.
+
+Each IOB provides user programmable ground pin capabil-
+ity. This allows device I/O pins to be configured as additional
+ground pins. By tying strategically located programmable
+ground pins to the external ground connection, system
+noise generated from large numbers of simultaneous
+switching outputs may be reduced.
+
+A control pull-up resistor (typically 10K ohms) is attached to
+each device I/O pin to prevent them from floating when the
+device is not in normal user operation. This resistor is active
+during device programming mode and system power-up. It
+is also activated for an erased device. The resistor is deac-
+tivated during normal operation.
+
+The output driver is capable of supplying 24 mA output
+drive. All output drivers in the device may be configured for
+either 5V TTL levels or 3.3V levels by connecting the device
+output voltage supply (Vccio) to a 5V or 3.3V voltage sup-
+
+![Figure 1: Output slew-Rate for (a) Rising and (b) Falling Outputs. The graph shows Output Voltage on the Y axis and Time on the X axis. Figure (a) shows the rising output voltage over time, with annotations for "Standard", "Slew-Rate Limited", and "TSLEW". Figure (b) shows the falling output voltage over time, with annotations for "Standard", "Slew-Rate Limited", and "TSLEW".](image_reference)
+
+![Figure 2: XC9500 Devices in (a) 5V Systems and (b) Mixed 5V/3.3V Systems. Figure (a) shows a diagram of the XC9500 CPLD in a 5V system, with connections for 5V CMOS or 5V TTL, VCCINT, VCCIO, IN, OUT, and GND. Figure (b) shows a diagram of the XC9500 CPLD in a mixed 5V/3.3V system, with connections for 5V CMOS or 5V TTL, VCCINT, VCCIO, IN, OUT, and GND.](image_reference)
+
+ply. Figure 12 shows how the XC9500 device can be used in
+5V only and mixed 3.3V/5V systems.
+
+### Pin-Locking Capability
+
+The capability to lock the user defined pin assignments dur-
+ing design changes depends on the ability of the architec-
+ture to adapt to unexpected changes. The XC9500 devices
+have architectural features that enhance the ability to
+accept design changes while maintaining the same pinout.
+
+The XC9500 architecture provides maximum routing within
+the Fast CONNECT switch matrix, and incorporates a flexi-
+ble Function Block that allows block-wide allocation of avail-
+able product terms. This provides a high level of confidence
+of maintaining both input and output pin assignments for
+unexpected design changes.
+
+For extensive design changes requiring higher logic capас-
+ity than is available in the initially chosen device, the new
+design may be able to fit into a larger pin-compatible device
+using the same pin assignments. The same board may be
+used with a higher density device without the expense of
+board rework
+
+--- end page 12
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+## XC9500 In-System Programmable CPLD Family
+
+![XILINX®](no_image_available)
+
+## In-System Programming
+XC9500 devices are programmed in-system via a standard
+4-pin JTAG protocol, as shown in Figure 13. In-system pro-
+gramming offers quick and efficient design iterations and
+eliminates package handling. The Xilinx development sys-
+tem provides the programming data sequence using a Xilinx
+download cable, a third-party JTAG development system,
+JTAG-compatible board tester, or a simple microprocessor
+interface that emulates the JTAG instruction sequence.
+
+All I/Os are 3-stated and pulled high by the IOB resistors
+during in-system programming. If a particular signal must
+remain Low during this time, then a pulldown resistor may
+be added to the pin.
+
+## External Programming
+XC9500 devices can also be programmed by the Xilinx
+HW130 device programmer as well as third-party program-
+mers. This provides the added flexibility of using pre-pro-
+grammed devices during manufacturing, with an in-system
+programmable option for future enhancements.
+
+## Endurance
+All XC9500 CPLDs provide a minimum endurance level of
+10,000 in-system program/erase cycles. Each device meets
+all functional, performance, and data retention specifica-
+tions within this endurance limit.
+
+## IEEE 1149.1 Boundary-Scan (JTAG)
+XC9500 devices fully support IEEE 1149.1 boundary-scan
+(JTAG). EXTEST, SAMPLE/PRELOAD, BYPASS, USER-
+CODE, INTEST, IDCODE, and HIGHZ instructions are sup-
+ported in each device. For ISP operations, five additional
+instructions are added; the ISPEN, FERASE, FPGM, FVFY,
+and ISPEX instructions are fully compliant extensions of the
+1149.1 instruction set.
+
+The TMS and TCK pins have dedicated pull-up resistors as
+specified by the IEEE 1149.1 standard.
+
+Boundary Scan Description Language (BSDL) files for the
+XC9500 are included in the development system and are
+available on the Xilinx FTP site.
+
+## Design Security
+XC9500 devices incorporate advanced data security fea-
+tures which fully protect the programming data against
+unauthorized reading or inadvertent device erasure/repro-
+gramming. Table 3 shows the four different security settings
+available.
+
+The read security bits can be set by the user to prevent the
+internal programming pattern from being read or copied.
+When set, they also inhibit further program operations but
+allow device erase. Erasing the entire device is the only way
+to reset the read security bit.
+
+The write security bits provide added protection against
+accidental device erasure or reprogramming when the
+JTAG pins are subject to noise, such as during system
+power-up. Once set, the write-protection may be deacti-
+vated when the device needs to be reprogrammed with a
+valid pattern.
+
+### Table 3: Data Security Options
+
+|                               |            |                         Read Security                        |
+| :---------------------------- | :--------- | :----------------------------------------------------------: |
+|                               |            |                           Default                            |                              Set                               |
+| **Write Security**            | **Default**|                   Read Allowed Program/Erase Allowed                   |     Read Inhibited Program Inhibited Erase Allowed      |
+|                               | **Set**    | Read Allowed Program/Erase Inhibited | Program/Erase Inhibited  |
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+[www.xilinx.com](www.xilinx.com)
+
+13
+
+--- end page 13
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+![Figure 13: Diagram showing In-System Programming Operation. (a) Solder Device to PCB showing integrated circuit connected with pins to a circuit board with various components. (b) Program Using Download Cable showing a laptop connected with a cable to an integrated circuit connected with pins to a circuit board with various components.](image_reference)
+
+Figure 13: In-System Programming Operation (a) Solder Device to PCB and (b) Program Using Download Cable
+
+## Low Power Mode
+
+All XC9500 devices offer a low-power mode for individual
+macrocells or across all macrocells. This feature allows the
+device power to be significantly reduced.
+
+Each individual macrocell may be programmed in
+low-power mode by the user. Performance-critical parts of
+the application can remain in standard power mode, while
+other parts of the application may be programmed for
+low-power operation to reduce the overall power dissipation.
+Macrocells programmed for low-power mode incur addi-
+tional delay (TLP) in pin-to-pin combinatorial delay as well as
+register setup time. Product term clock to output and prod-
+uct term output enable delays are unaffected by the macro-
+cell power-setting.
+
+## Timing Model
+
+The uniformity of the XC9500 architecture allows a simpli-
+fied timing model for the entire device. The basic timing
+model, shown in Figure 14, is valid for macrocell functions
+that use the direct product terms only, with standard power
+setting, and standard slew rate setting. Table 4 shows how
+each of the key timing parameters is affected by the product
+term allocator (if needed), low-power setting, and slew-lim-
+ited setting.
+
+The product term allocation time depends on the logic span
+of the macrocell function, which is defined as one less than
+the maximum number of allocators in the product term path.
+If only direct product terms are used, then the logic span is
+0. The example in Figure 6 shows that up to 15 product
+terms are available with a span of 1. In the case of Figure 7,
+the 18 product term function has a span of 2.
+
+Detailed timing information may be derived from the full tim-
+ing model shown in Figure 15. The values and explanations
+for each parameter are given in the individual device data
+sheets.
+
+--- end page 14
+
+# XILINX
+
+## PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+
+XC9500 In-System Programmable CPLD Family
+
+![Figure 14: Basic Timing Model](image_reference)
+
+TPSU
+Combinatorial
+Logic
+
+Propagation Delay = TPD
+(a)
+Combinatorial
+Logic
+P-Term Clock
+Path
+D/T Q
+TPCO
+Combinatorial
+Logic
+D/T Q
+Tco
+Setup Time = Tsu
+(b)
+Clock to Out Time = Tco
+Combinatorial
+Logic
+D/T Q
+Setup Time = TPSU
+(c)
+Clock to Out Time = TPCO
+All resources within FB using local Feedback
+Internal System Cycle Time = TSYSTEM
+(d)
+Combinatorial
+Logic
+D/T Q
+Internal Cycle Time = TCNT
+(e)
+
+![Figure 15: Detailed Timing Model](image_reference)
+
+Pin Feedback
+
+TF
+TIN
+TLOGILP
+TLOGI
+S*TPTA
+TSLEW
+TPDI
+D/T
+Q
+TOUT
+TPTCK
+TSUITCOI
+THI
+EC TAOI
+TRAI
+TGCK
+TPTSR
+SR
+TGSR
+TPTTS
+Macrocell
+TGTS
+TEN
+
+DS063 (v6.0) May 17, 2013
+Product Specification
+
+www.xilinx.com
+15
+
+--- end page 15
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+## Power-Up Characteristics
+The XC9500 devices are well behaved under all operating
+conditions. During power-up each XC9500 device employs
+internal circuitry which keeps the device in the quiescent
+state until the VCCINT supply voltage is at a safe level
+(approximately 3.8V). During this time, all device pins and
+JTAG pins are disabled and all device outputs are disabled
+with the IOB pull-up resistors (~10K ohms) enabled, as
+shown in Table 5. When the supply voltage reaches a safe
+level, all user registers become initialized (typically within
+100 με for 9536, 95144, 200 μs for 95216, and 300 μs for
+95288), and the device is immediately available for opera-
+tion, as shown in Figure 16.
+
+If the device is in the erased state (before any user pattern
+is programmed), the device outputs remain disabled with
+the IOB pull-up resistors enabled. The JTAG pins are
+enabled to allow the device to be programmed at any time.
+
+If the device is programmed, the device inputs and outputs
+take on their configured states for normal operation. The
+JTAG pins are enabled to allow device erasure or bound-
+ary-scan tests at any time.
+
+## Development System Support
+The XC9500 CPLD family is fully supported by the develop-
+ment systems available from Xilinx and the Xilinx Alliance
+Program vendors.
+
+The designer can create the design using ABEL, schemat-
+ics, equations, VHDL, or Verilog in a variety of software
+front-end tools. The development system can be used to
+
+implement the design and generate a JEDEC bitmap which
+can be used to program the XC9500 device. Each develop-
+ment system includes JTAG download software that can be
+used to program the devices via the standard JTAG inter-
+face and a download cable.
+
+## FastFLASH Technology
+An advanced CMOS Flash process is used to fabricate all
+XC9500 devices. Specifically developed for Xilinx in-system
+programmable CPLDs, the FastFLASH process provides
+high performance logic capability, fast programming times,
+and endurance of 10,000 program/erase cycles.
+
+![Figure 16: Device Behavior During Power-up](no_image)
+VCCINT axis, 3.8V (Typ) label.
+No Power, Quiescent State, User Operation labels along the graph.
+
+### Table 4: Timing Model Parameters
+
+| Parameter | Description | Product Term Allocator(1) | Macrocell Low-Power Setting | Output Slew-Limited Setting |
+|---|---|---|---|---|
+| TPD | Propagation Delay | + TPTA * S | + TLP | + TSLEW |
+| Tsu | Global Clock Setup Time | + TPTA * S | + TLP |  |
+| Tco | Global Clock-to-output |  |  | + TSLEW |
+| TPSU | Product Term Clock Setup Time | + TPTA * S | + TLP |  |
+| TPCO | Product Term Clock-to-output |  | - | + TSLEW |
+| TSYSTEM | Internal System Cycle Period | + TPTA* S | + TLP | - |
+Notes:
+1. S = the logic span of the function, as defined in the text.
+
+### Table 5: XC9500 Device Characteristics
+
+| Device Circuitry | Quiescent State | Erased Device Operation | Valid User Operation |
+|---|---|---|---|
+| IOB Pull-up Resistors | Enabled | Enabled | Disabled |
+| Device Outputs | Disabled | Disabled | As Configured |
+
+--- end page 16
+
+# PRODUCT OBSOLETE / UNDER OBSOLESCENCE
+XC9500 In-System Programmable CPLD Family
+
+### Table 5: XC9500 Device Characteristics
+
+| Device Circuitry         | Quiescent State | Erased Device Operation | Valid User Operation |
+| ------------------------ | --------------- | ----------------------- | -------------------- |
+| Device Inputs and Clocks | Disabled        | Disabled                | As Configured        |
+| Function Block           | Disabled        | Disabled                | As Configured        |
+| JTAG Controller          | Disabled        | Enabled                 | Enabled              |
+
+## Warranty Disclaimer
+
+THESE PRODUCTS ARE SUBJECT TO THE TERMS OF THE XILINX LIMITED WARRANTY WHICH CAN BE VIEWED
+AT http://www.xilinx.com/warranty.htm. THIS LIMITED WARRANTY DOES NOT EXTEND TO ANY USE OF THE
+PRODUCTS IN AN APPLICATION OR ENVIRONMENT THAT IS NOT WITHIN THE SPECIFICATIONS STATED ON THE
+THEN-CURRENT XILINX DATA SHEET FOR THE PRODUCTS. PRODUCTS ARE NOT DESIGNED TO BE FAIL-SAFE
+AND ARE NOT WARRANTED FOR USE IN APPLICATIONS THAT POSE A RISK OF PHYSICAL HARM OR LOSS OF
+LIFE. USE OF PRODUCTS IN SUCH APPLICATIONS IS FULLY AT THE RISK OF CUSTOMER SUBJECT TO
+APPLICABLE LAWS AND REGULATIONS.
+
+## Revision History
+
+The following table shows the revision history for this document.
+
+| Date       | Version | Revision                                                                                                                  |
+| ---------- | ------- | ------------------------------------------------------------------------------------------------------------------------- |
+| 12/14/1998 | 3.0     | Revised datasheet to reflect new AC characteristics and Internal Timing Parmeters.                                        |
+| 02/10/1999 | 4.0     | Corrected Figure 3.                                                                                                     |
+| 09/15/1999 | 5.0     | Added -10 speed grade to XC95288.                                                                                       |
+| 09/22/2003 | 5.1     | Minor edits.                                                                                                            |
+| 02/16/2004 | 5.2     | Corrected statement on GTS inputs on page 10. Added links to additional information.                                      |
+| 04/15/2005 | 5.3     | Update to PDF attributes only. No changes to documentation.                                                             |
+| 04/03/2006 | 5.4     | Added Warranty Disclaimer. Added note on Pb-Free packages.                                                                |
+| 04/03/2006 | 5.4     | Added Warranty Disclaimer. Added note on Pb-Free packages.                                                                |
+| 06/25/2007 | 5.5     | Change to Table 2, listing discontinuance of 352-pin BGA package for the XC95216. See XCN07010 for details.              |
+| 05/17/2013 | 6.0     | The products listed in this data sheet are obsolete. See XCN11010 for further information.                              |
+
+--- end page 17

data/cache/deloitte-tech-risk-sector-banking.pdf.md

@@ -0,0 +1,94 @@
+# Deloitte.
+
+# Pushing through undercurrents
+## Technology's impact on systemic risk: A look at banking
+
+As more financial institutions embrace digital innovation, risks emerge that could threaten the stability of the
+financial system. Some of these risks originate from a single sector. Either way, they could proliferate and become
+systemic without appropriate management.
+
+To understand what these technology-driven risks look like, the World Economic Forum (the Forum) and Deloitte
+consulted over 100 financial services and technology experts in the development of a new report, Pushing
+through undercurrents. This group shared more specific perspectives on the forces behind technology-driven
+systemic risk in the banking sector. Here's a summary of what we learned. You can learn more in the full report
+from the Forum, and the executive summary from Deloitte.
+
+### Risk 1: Risk exposure from Banking as a Service offerings
+
+**What could go wrong?**
+
+Banking as a service (BaaS) increasingly relies on application programming interfaces, introducing vulnerabilities
+that can pose risks for banks. The risk is growing because:
+
+- Customers' sensitive data and funds may be at risk from phishing and social engineering attacks
+- Flawed APIs might provide a back door for hackers to penetrate banks' systems
+- Noncompliance with data privacy rules by BaaS providers might expose partner banks to reputational risks
+
+This risk could become systemic if, for example, a malicious actor launches a distributed denial-of-service attack on
+a BaaS provider, keeping customers from accessing their accounts or making transactions.
+
+[Table 1: Risk exposure from Banking as a Service offerings]
+| What sectoral and regional forces could amplify the risk? | How can the industry mitigate it? |
+|---|---|
+| Goal | Mitigation opportunities |
+| - A complex BaaS technology stack<br>- Limited redundancy measures<br>- A lack of input validation, enabling attackers to upload malicious code into a bank's systems through its APIs | Strong security for BaaS platforms and API connectivity | - Use input validation protocols<br>- Apply network segmentation and access control measures |
+|  | Properly vetted BaaS partners | - Improve due diligence on BaaS providers |
+|  | Institutional knowledge transfer from banks to BaaS partners | - Help BaaS and other fintech providers get better at risk management and compliance |
+
+
+--- end page 1
+
+# ! Risk 2: Inadequate stability mechanisms for stablecoin arrangements
+
+What could go wrong?
+Stablecoins mimic fiat currencies but without the backing of a central bank, heightening the probability of a run.
+The risk is growing because:
+• Governance and regulatory gaps could perpetuate illicit activities that might threaten the integrity of the broader
+financial system
+• The novel technologies used for minting and managing stablecoins are exposed to security risks
+• The absence of a stability mechanism like deposit insurance increases the risk of a run
+
+This risk could become systemic if, for example, a significant stablecoin issuer fails to promptly honor large
+customer withdrawal requests, touching off a run and eventually collapsing the stablecoin arrangement.
+
+[Table 1: Information about forces that could amplify the risk and how the industry mitigate it?]
+| What sectoral and regional forces could amplify the risk? | How can the industry mitigate it? |
+|---|---|
+|   | Goal | Mitigation opportunities |
+| • A less mature regulatory environment | Standardization and oversight of stablecoin arrangements | • Requirement for anti-money laundering and "know your customer" processes for stablecoin issuers |
+| • Stringent capital controls, which may encourage individuals in those jurisdictions to park their assets in global stablecoins | Investor and customer protection | • Offer insurance coverage for stablecoin tokens  • Enforce responsible marketing rules and customer education |
+| • Unsecure systems and poorly managed internal processes | Transparency of capital reserves | • Periodically audit and stress-test stablecoin issuers' reserve assets |
+
+To learn more about technology's impact on systemic risk in banking, including examples, please see pages 60-70 of the full report.
+
+Contacts
+
+Neal Baumann
+Financial Services Industry leader
+Deloitte Global
+[email protected]
+
+Rob Galaski
+Vice-Chair and Managing Partner
+Deloitte Canada
+[email protected]
+
+Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (DTTL), its global network of member firms, and their related entities (collectively, the "Deloitte organization"). DTTL (also referred to as
+"Deloitte Global") and each of its member firms and related entities are legally separate and independent entities, which cannot obligate or bind each other in respect of third parties. DTTL and each DTTL
+member firm and related entity is liable only for its own acts and omissions, and not those of each other. DTTL does not provide services to clients. Please see www.deloitte.com/about to learn more.
+
+Deloitte provides industry-leading audit and assurance, tax and legal, consulting, financial advisory, and risk advisory services to nearly 90% of the Fortune Global 500® and thousands of private
+companies. Our people deliver measurable and lasting results that help reinforce public trust in capital markets, enable clients to transform and thrive, and lead the way toward a stronger economy,
+a more equitable society, and a sustainable world. Building on its 175-plus year history, Deloitte spans more than 150 countries and territories. Learn how Deloitte's approximately 415,000 people
+worldwide make an impact that matters at www.deloitte.com.
+
+This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited ("DTTL"), its global network of member firms or their related entities (collectively, the "Deloitte
+organization") is, by means of this communication, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you should
+consult a qualified professional adviser. No representations, warranties or undertakings (express or implied) are given as to the accuracy or completeness of the information in this communication, and
+none of DTTL, its member firms, related entities, employees or agents shall be liable or responsible for any loss or damage whatsoever arising directly or indirectly in connection with any person relying
+on this communication. DTTL and each of its member firms, and their related entities, are legally separate and independent entities.
+
+2023. For information, contact Deloitte Global.
+
+--- end page 2
+

data/cache/deloitte-tech-risk-sector-banking.pdf.reformatted.md

@@ -0,0 +1,92 @@
+# Deloitte.
+
+## Pushing through undercurrents
+### Technology's impact on systemic risk: A look at banking
+
+As more financial institutions embrace digital innovation, risks emerge that could threaten the stability of the
+financial system. Some of these risks originate from a single sector. Either way, they could proliferate and become
+systemic without appropriate management.
+
+To understand what these technology-driven risks look like, the World Economic Forum (the Forum) and Deloitte
+consulted over 100 financial services and technology experts in the development of a new report, Pushing
+through undercurrents. This group shared more specific perspectives on the forces behind technology-driven
+systemic risk in the banking sector. Here's a summary of what we learned. You can learn more in the full report
+from the Forum, and the executive summary from Deloitte.
+
+### Risk 1: Risk exposure from Banking as a Service offerings
+
+**What could go wrong?**
+
+Banking as a service (BaaS) increasingly relies on application programming interfaces, introducing vulnerabilities
+that can pose risks for banks. The risk is growing because:
+
+- Customers' sensitive data and funds may be at risk from phishing and social engineering attacks
+- Flawed APIs might provide a back door for hackers to penetrate banks' systems
+- Noncompliance with data privacy rules by BaaS providers might expose partner banks to reputational risks
+
+This risk could become systemic if, for example, a malicious actor launches a distributed denial-of-service attack on
+a BaaS provider, keeping customers from accessing their accounts or making transactions.
+
+#### Table 1: Risk exposure from Banking as a Service offerings
+
+| What sectoral and regional forces could amplify the risk? | How can the industry mitigate it? |
+|---|---|
+| Goal | Mitigation opportunities |
+| - A complex BaaS technology stack<br>- Limited redundancy measures<br>- A lack of input validation, enabling attackers to upload malicious code into a bank's systems through its APIs | Strong security for BaaS platforms and API connectivity | - Use input validation protocols<br>- Apply network segmentation and access control measures |
+|  | Properly vetted BaaS partners | - Improve due diligence on BaaS providers |
+|  | Institutional knowledge transfer from banks to BaaS partners | - Help BaaS and other fintech providers get better at risk management and compliance |
+
+### Risk 2: Inadequate stability mechanisms for stablecoin arrangements
+
+**What could go wrong?**
+
+Stablecoins mimic fiat currencies but without the backing of a central bank, heightening the probability of a run.
+The risk is growing because:
+• Governance and regulatory gaps could perpetuate illicit activities that might threaten the integrity of the broader
+financial system
+• The novel technologies used for minting and managing stablecoins are exposed to security risks
+• The absence of a stability mechanism like deposit insurance increases the risk of a run
+
+This risk could become systemic if, for example, a significant stablecoin issuer fails to promptly honor large
+customer withdrawal requests, touching off a run and eventually collapsing the stablecoin arrangement.
+
+#### Table 1: Information about forces that could amplify the risk and how the industry mitigate it?
+
+| What sectoral and regional forces could amplify the risk? | How can the industry mitigate it? |
+|---|---|
+|   | Goal | Mitigation opportunities |
+| • A less mature regulatory environment | Standardization and oversight of stablecoin arrangements | • Requirement for anti-money laundering and "know your customer" processes for stablecoin issuers |
+| • Stringent capital controls, which may encourage individuals in those jurisdictions to park their assets in global stablecoins | Investor and customer protection | • Offer insurance coverage for stablecoin tokens  • Enforce responsible marketing rules and customer education |
+| • Unsecure systems and poorly managed internal processes | Transparency of capital reserves | • Periodically audit and stress-test stablecoin issuers' reserve assets |
+
+To learn more about technology's impact on systemic risk in banking, including examples, please see pages 60-70 of the full report.
+
+### Contacts
+
+Neal Baumann
+Financial Services Industry leader
+Deloitte Global
+[email protected]
+
+Rob Galaski
+Vice-Chair and Managing Partner
+Deloitte Canada
+[email protected]
+
+Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (DTTL), its global network of member firms, and their related entities (collectively, the "Deloitte organization"). DTTL (also referred to as
+"Deloitte Global") and each of its member firms and related entities are legally separate and independent entities, which cannot obligate or bind each other in respect of third parties. DTTL and each DTTL
+member firm and related entity is liable only for its own acts and omissions, and not those of each other. DTTL does not provide services to clients. Please see www.deloitte.com/about to learn more.
+
+Deloitte provides industry-leading audit and assurance, tax and legal, consulting, financial advisory, and risk advisory services to nearly 90% of the Fortune Global 500® and thousands of private
+companies. Our people deliver measurable and lasting results that help reinforce public trust in capital markets, enable clients to transform and thrive, and lead the way toward a stronger economy,
+a more equitable society, and a sustainable world. Building on its 175-plus year history, Deloitte spans more than 150 countries and territories. Learn how Deloitte's approximately 415,000 people
+worldwide make an impact that matters at www.deloitte.com.
+
+This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited ("DTTL"), its global network of member firms or their related entities (collectively, the "Deloitte
+organization") is, by means of this communication, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you should
+consult a qualified professional adviser. No representations, warranties or undertakings (express or implied) are given as to the accuracy or completeness of the information in this communication, and
+none of DTTL, its member firms, related entities, employees or agents shall be liable or responsible for any loss or damage whatsoever arising directly or indirectly in connection with any person relying
+on this communication. DTTL and each of its member firms, and their related entities, are legally separate and independent entities.
+
+2023. For information, contact Deloitte Global.
+

data/cache/dttl-tax-technology-report-2023.pdf.md

@@ -0,0 +1,661 @@
+Deloitte.
+
+Tax in a data-driven world
+More regulations, more data, more technology
+
+--- end page 1
+
+Data and new regulations
+drive tax transformation
+
+Immediate access to reliable, accurate, and fit-for-purpose tax data is essential to be
+able to meet complex tax obligations, real-time reporting requirements, and increasing
+expectations of tax transparency. Recent developments such as the OECD's Pillar
+Two rules, requiring large multinational enterprises to pay a minimum “global tax," the
+introduction of CESOP (Central Electronic System of Payment information) and ViDA rules
+(VAT in a Digital Age) in the EU, e-reporting, and e-invoicing are all examples of initiatives
+which are increasing the compliance requirements for companies and having a significant
+impact on tax strategies and operations. Advances in the way technology is used to
+identify, transform, and manage tax-related data should be an essential component of
+a business's response.
+
+“
+Pillar Two is at the forefront of our mind. We
+are still quantifying any additional liability and
+establishing any impact on our Effective Tax Rate.
+Naturally, there is a huge compliance and systems
+requirement to accommodate Pillar Two.
+Gemma Beck
+Head of Tax, Haleon Plc
+"
+
+Challenges such as version control, manual data collection, or getting the right format
+and level of data can delay accurate reporting and insights—insights from data being
+something the respondents to Deloitte's Tax Transformation Trends 2023 research
+highlighted as of high importance. The impact of these regulatory and digitalization
+changes can vary across companies based on their size, region, or industry. Yet, the
+overall trend has been toward growing workloads and increased complexity.
+
+Tax in a data-driven world | More regulations, more data, more technology
+2
+
+--- end page 2
+
+# 
+
+In addition, many tax authorities are collecting and sharing
+more detailed data about taxes and are requesting direct
+access to large companies' tax-related data. The digitalization
+of tax authorities elevates the need for reliable and automated
+tax models, and generating the right data, in the right format,
+at the right time. Automating data input, validation, and
+cleansing can save time and reduce risk, but is also key to
+enabling the access tax administrations increasingly require.
+
+All this at a time when businesses are starting to explore the
+role and benefits of Generative Al, and having to evaluate how
+trustworthy this technology is, the risks associated with data
+privacy, as well as the consequences for their employees.
+
+Technology can also facilitate greater visibility into tax data
+across the enterprise, which can provide insights that can
+generate value for the business when making strategic
+decisions. In short, tax departments increasingly need
+technology to help them pivot from task completion and
+cost control toward being able to extract outcome-oriented
+business insights from compliance activities through analytics.
+
+[Figure 1. Progress made in implementing tax transformation strategies]
+| Fully implemented |  |  | Plan to implement within 12 months |
+|---|---|---|---|
+| 37% | ERP system customized for tax issues |  | 4% |
+| 37% | Use of tools to monitor relevant developments in tax laws globally |  | 7% |
+| 38% | Tax data management solutions and/or tax professionals in company's data management team |  | 6% |
+| 37% | Use of advanced analytics in monitoring of key controls |  | 4% |
+| 32% | Integrated processes |  | 4% |
+| 41% | Streamlining of processes not appropriate for automation |  | 4% |
+| 41% | Automation of tax compliance and reporting processes |  | 2% |
+
+Yet, when Deloitte asked 300 tax and finance professionals
+what progress they had made in implementing tax
+transformation strategies, 24% stated they intended to
+implement an ERP system customized for tax issues in the next
+12 months (Figure 1). Only 37% of respondents said their tax
+department had fully implemented the use of tools to monitor
+relevant developments in tax laws around the world. Similarly,
+many respondents reported that their tax department
+had not yet fully implemented the data management and
+technology applications required by these changes-
+introduction of tax data management solutions and/or having tax
+professionals in the company's data management team (38%), and
+integrated processes (32%).
+
+Implementing tax technology, or customizing existing ERP systems, requires identifying the appropriate issues to
+customize the system for, involving the right stakeholders internally, obtaining budget when there are competing
+demands, and devising a robust schedule of maintenance.
+
+Tax in a data-driven world | More regulations, more data, more technology 3
+
+
+--- end page 3
+
+# 1. Customizing technology
+for global compliance
+
+Compliance is a top priority for the tax department (Figure 2) but to achieve it, comply
+with Pillar Two, or calculate their global tax liability, tax departments need accurate,
+timely, tax-related data integrated across their organization. However, achieving visibility
+into enterprise-wide tax data has proven difficult for many companies, with respondents
+to Deloitte's Tax Transformation Trends 2023 survey citing integrating tax-related data
+across the company (36%) as their second-most important challenge. More than a fifth of
+respondents found challenges in having limited technology or data management expertise
+(23%), obtaining a comprehensive view of the total tax paid globally (22%), and not having
+sufficient control over technology strategy and investment (22%) (Figure 2). There is a “perfect
+storm" with the compliance challenge at least partly linked to these other factors.
+
+[Graph 2: Challenges for the tax department over the next three to five years]
+
+| Category                                                                   | Percentage   |
+| -------------------------------------------------------------------------- | ------------ |
+| Complying with evolving tax laws and regulations around the world         | 43%          |
+| Integrating tax-related data across the company                            | 36%          |
+| Limited technology/data management expertise                               | 23%          |
+| Lack of sufficient control over technology strategy and investment          | 22%          |
+| Obtaining a comprehensive view of the total tax paid globally             | 22%          |
+| Obtaining adequate budget                                                  | 18%          |
+| Difficulty in aligning with company's technology transformation strategy/approach | 11%          |
+
+Percentage ranked among top 3 challenges
+
+Tax in a data-driven world | More regulations, more data, more technology 4
+
+
+--- end page 4
+
+“
+What we see now is an increasing demand for
+more compliance requirements-I mean from the
+OECD and also coming from local authorities...
+there's demand for more automation.
+Liliane Saiani
+Head of Tax, Mercado Libre
+"
+
+The desire to continue customizing ERP systems for tax is not surprising-being able to incorporate
+flexibility and information to respond to changing tax laws will help companies comply, thereby avoiding
+penalties and costs. Modern ERP systems can provide the accurate, granular data that tax teams
+need at the legal entity level, while still supporting the management-level reporting needed by other
+stakeholders. In this way, the ERP can help support tax analytics so that companies can model the
+impact of changing tax laws in multiple jurisdictions, improving the insights used for decision making.
+
+Companies have been working to put in place the data management and technology capabilities
+demanded by today's tax environment, but many have more work to do.
+
+“
+Our approach was to first work to make ourselves
+more efficient. We're trying to transform our ERP
+landscape. It's always a challenge to wrangle all
+the different technology pieces we have.
+Kristi Doyle
+Global Tax Director, Johnson Controls
+"
+
+Tax in a data-driven world | More regulations, more data, more technology
+5
+
+
+--- end page 5
+
+Many of the challenges appear greater for smaller companies than for larger ones. For example, respondents at companies with revenues of US$5 billion or greater were more likely to
+say that their company had fully implemented introduction of tax data management solutions and/or having tax professionals in the company's data management team (55%) than did those
+at companies with revenues of US$1 billion to US$5 billion (35%) or US$750 million to US$1 billion (25%) (Figure 3).
+
+### Figure 3: Strategies/actions fully implemented by the tax department-by company size
+
+|                                               | Reducing headcount | Implementation of lower-cost delivery model for lower complexity processes | Integrated processes | ERP system customized for tax issues | Processes to allow tax to be adequately considered in corporate decisions | Use of advanced analytics in monitoring of key controls | Use of tools to monitor relevant developments in tax laws globally | Tax data mgmt solutions and/or tax profs. in company's data mgmt team | Streamlining of processes not appropriate for automation | Automation of tax compliance and reporting processes | Ongoing assessment of skills required to identify any gaps | Training programs for skills required in strategic roles |
+|-----------------------------------------------|--------------------|---------------------------------------------------------------------------------|----------------------|---------------------------------------|-----------------------------------------------------------------------------------|-------------------------------------------------------------------|----------------------------------------------------------------------|--------------------------------------------------------------------|-----------------------------------------------------------------|--------------------------------------------------------------------|-------------------------------------------------------------------|-------------------------------------------------------------------|
+| **US$5B+**                                    | 0%                 | 38%                                                                             | 34%                   | 46%                                   | 39%                                                                               | 56%                                                               | 55%                                                                  | 55%                                                                | 49%                                                             | 46%                                                             | 51%                                                               | 56%                                                               |
+| **US$1B - $5B**                               | 0%                 | 30%                                                                             | 33%                   | 45%                                   | 37%                                                                               | 35%                                                               | 38%                                                                  | 35%                                                                | 47%                                                             | 40%                                                             | 51%                                                               | 54%                                                               |
+| **US$750M - $1B**                             | 2%                 | 18%                                                                             | 27%                   | 14%                                   | 20%                                                                               | 24%                                                               | 22%                                                                  | 25%                                                                | 27%                                                             | 29%                                                             | 24%                                                               | 26%                                                               |
+
+Tax in a data-driven world | More regulations, more data, more technology 6
+
+--- end page 6
+
+2. Deciding how to invest
+in technology
+
+Digital transformation is embedded into most companies' agendas, but it is still difficult
+to identify clear returns on technology investment—from determining which actions
+drive the most impact, to which investments yield the highest enterprise value. With
+Generative Al also advancing at pace, it is increasingly difficult for businesses to work out
+the optimum point at which to invest at scale. When resources are constrained, it is worth
+weighing up the investment needed for developing, buying, maintaining, and replacing
+technology versus leveraging the technology of an outsource service provider.
+
+“
+We outsource as much as possible with trusted
+partners. We don't have the resources, nor the
+budget, to develop all those tools ourselves.
+Philippe de Roose
+Senior Vice President for Tax Treasury and Finance Administration,
+Radisson Hospitality Group
+"
+
+Tax in a data-driven world | More regulations, more data, more technology
+7
+
+--- end page 7
+
+Figure 4. Benefit company has received—or could receive—from outsourcing an entire activity or function in the tax department
+
+100%
+
+75%
+26%
+27%
+34%
+37%
+33%
+35%
+30%
+50%
+54%
+51%
+25%
+46%
+45%
+45%
+43%
+40%
+0%
+Access to the
+latest technology
+capabilities
+Reduced
+operating costs
+Access to tax
+subject matter
+expertise
+Reduced need for
+capital investment in
+technology
+Ability to provide flexibility
+and quickly scale tax
+operations as needed
+Major/significant
+Some
+Transfer of risk associated
+with technology systems or
+processes to one or more
+third parties
+Reallocation of current
+tax team to other
+strategic objectives
+
+Respondents to the Tax Transformation Trends 2023 survey cited access to the latest technology capabilities (54%) even more often than reduced operating costs (51%) as a major or
+significant benefit of outsourcing (Figure 4). Reduced need for capital investment in technology (45%) was also named frequently as an important benefit. Outsourcing can provide a
+strategy for tax departments to acquire the technology tools and expertise that the current environment demands without incurring the significant capital investment that would be
+required, upfront and ongoing, if enhancements were developed in-house.
+
+While tax departments may have had discretionary budget for incremental changes, or fixing “broken” systems, wholescale finance transformation has centralized budgets, with IT
+taking a prominent role in deciding where transformation efforts will focus. This has led to a greater need for the tax department to collaborate with IT and other departments.
+
+Tax in a data-driven world | More regulations, more data, more technology
+8
+
+--- end page 8
+
+# $
+3. Internal collaboration
+and obtaining budget
+Data management and IT applications are increasingly important to tax departments.
+However, in Deloitte's Tax Transformation Trends survey, 78% respondents in 2023 said
+technology strategy and planning was largely controlled by Finance or IT; 56% said that
+the tax department has input into the process, while 22% said it had little input (Figure
+5). These findings represent a change from the 2021 survey, in which tax leaders more
+often said their departments had control over technology strategy and budget. This may
+be due to an increased reliance on ERPs, rather than tax-department specific solutions,
+along with the growing need for tax to gather data from across the company-both of
+which would put more control into the hands of IT and Finance.
+
+[Graph 5: Tax function role in technology strategy and planning]
+
+|   | 2021 | 2023 |
+|---|---|---|
+|  | 40% | 15% |
+|  | 23% | 56% |
+|  | 23% | 22% |
+|  | 14% | 7% |
+
+Largely set/controlled
+by Finance or IT, with
+little input from Tax
+
+Largely set/controlled
+by Finance or IT, but
+Tax has input
+
+Tax has significant
+autonomy over
+technology strategy,
+but limited control over
+Capex budget
+
+Tax has significant
+autonomy over both
+technology strategy
+and Capex budget
+
+Tax in a data-driven world | More regulations, more data, more technology 9
+
+
+--- end page 9
+
+There were also significant regional differences. Respondents at North American companies (40%) more often said that the tax department has significant autonomy either over
+technology strategy or over both technology strategy and budget than did those at companies headquartered in Europe (10%) or Asia Pacific (20%) (Figure 6). European and Asian
+companies typically contend with more indirect taxes, requiring complicated integration with supply chain management in ERP systems, led by Finance, while in North America the
+emphasis is on income taxes, requiring the tax department to lead. Historically, Asian companies have been geared more toward managing reporting and compliance in multiple
+jurisdictions in a decentralized manner, and as a result, were not as experienced in having a common ERP platform to solve all jurisdictional issues. This is, however, changing rapidly as
+more tax technology expertise is developing in Asia, enabling common ERP platforms and local customization.
+
+### Figure 6. Tax function role in technology strategy and planning
+By region
+
+|             |      |      |
+| ----------- | ----------- | ----------- |
+| ![Figure 6: Tax function role in technology strategy and planning](image_reference)      |       |       |
+
+[Table 1: Tax function role in technology strategy and planning by region - Europe]
+|                                                                                              | Percentage |
+| :-------------------------------------------------------------------------------------------- | ---------: |
+| Largely set/controlled by Finance or IT, with little input from Tax                         |         6% |
+| Largely set/controlled by Finance or IT, but Tax has input                                 |        51% |
+| Tax has significant autonomy over technology strategy, but limited control over Capex budget |       29% |
+| Tax has significant autonomy over both technology strategy and Capex budget                   |       10% |
+| Total                                                                                        |       100% |
+
+[Table 2: Tax function role in technology strategy and planning by region - North America]
+|                                                                                              | Percentage |
+| :-------------------------------------------------------------------------------------------- | ---------: |
+| Largely set/controlled by Finance or IT, with little input from Tax                         |        8% |
+| Largely set/controlled by Finance or IT, but Tax has input                                 |        22% |
+| Tax has significant autonomy over technology strategy, but limited control over Capex budget |        30% |
+| Tax has significant autonomy over both technology strategy and Capex budget                   |        40% |
+| Total                                                                                        |       100% |
+
+[Table 3: Tax function role in technology strategy and planning by region - Asia Pacific]
+|                                                                                              | Percentage |
+| :-------------------------------------------------------------------------------------------- | ---------: |
+| Largely set/controlled by Finance or IT, with little input from Tax                         |       23% |
+| Largely set/controlled by Finance or IT, but Tax has input                                 |        51% |
+| Tax has significant autonomy over technology strategy, but limited control over Capex budget |       26% |
+| Tax has significant autonomy over both technology strategy and Capex budget                   |       20% |
+| Total                                                                                        |       100% |
+
+Technology plays a key role in many aspects of tax operations and in transforming those operations to meet today's challenges—which was made clear in interviews with respondents.
+
+“
+It's a priority to meet compliance requirements, which are becoming significantly challenging these days, such as
+Pillar Two and e-reporting. All these new kinds of compliance are very connected to technology and digitalization.
+Jesus Bravo Fernandez
+Head of Indirect Tax, Transfer Pricing, and Tax Technology, Coca-Cola Europacific Partners
+"
+
+Tax in a data-driven world | More regulations, more data, more technology 10
+
+--- end page 10
+
+Many respondents said implementing a single, integrated tax platform was a key priority
+for the next few years as they pursue increased efficiency and access to better data. For
+many, there is still work to do on rationalizing fragmented technology landscapes.
+
+“
+We are looking at how do we deal with all the
+various systems, and how do we bring some
+structure and consistency and visibility in that
+chaos-what evolution and trends are happening
+from a technology point of view.
+Dirk Timmermans
+Vice President of Global Statutory Finance and Tax Operations, Johnson Controls
+"
+To make the case for budget, tax departments need to demonstrate the value they
+generate and protect for the company. Companies that have taken the top-down
+company view, managed to explain the impact of tax authority digitalization to the C-suite
+and worked collaboratively with the IT department have typically been more successful in
+building this value case.
+
+Understanding and communicating the aspiration of real-time compliance through
+direct connection between tax authorities and company systems (see the OECD's
+“Tax Administration 3.0" discussion paper) is important for ERP system design as ERP
+systems are where most transactions are handled-thinking about the long term is
+imperative, as finding a point solution now, without thinking through the potential
+requirements in five to 10 years' time, may hinder the tax department from creating
+the environment that will enable being a strategic advisor to the business. Being able to
+identify all the potential outcomes, however, is the difficult part, especially since tax laws
+and regulations still differ significantly between jurisdictions and change frequently.
+
+Tax in a data-driven world | More regulations, more data, more technology 11
+
+--- end page 11
+
+# 4. Finding the optimal
+implementation and
+maintenance program
+
+Tax departments often focus on immediate-need technology. Best practice, however,
+would suggest obtaining budget and developing a road map first to use the technology
+already available, identifying what might be needed in the future, and then making build-
+or-buy decisions. At this point, it's useful to have a holistic view of the tax department's
+operating model—it's not about doing everything now, but looking at increasing speed
+and accuracy, and freeing up tax professionals for more strategic business activity.
+
+Once the technology is chosen, the question is often whether to implement using
+internal resources, appoint an implementation partner, or outsource the entire function
+requiring the technology.
+
+If the decision is made to use in-house resources, tax departments need to develop
+professional teams with the new skills required, especially data management and
+technology expertise. This was evident from Deloitte's Tax Transformation Trends
+research in 2023: When asked where their tax department will have the greatest need
+for skills over the next three to five years, respondents most often named data analytics,
+data-driven strategic insights, and data management (44%)—a reflection of the growing
+importance of data-driven decision making and increased government requirements for
+direct access to companies' tax data (Figure 7 on the next page).
+
+“
+We made the strategic decision to have capable IT
+people within our tax department many years ago,
+and that has allowed us to move much more quickly
+with getting our data needs met.
+
+Dirk Timmermans
+Vice President of Global Statutory Finance and Tax Operations, Johnson Controls
+"
+
+Tax in a data-driven world | More regulations, more data, more technology 12
+
+--- end page 12
+
+Several skill areas were cited less often in 2023 than in 2021, suggesting that some companies may have made progress in addressing their talent requirement in those areas—either
+through recruitment, or by leaning more on outside providers. For example, technology transformation and process redesign was named as a top talent need by 29% of respondents
+in the current survey, compared to 43% in 2021. However, this area still ranked fourth highest among the skills needed in the next few years, indicating that many companies are still
+working to develop or acquire technology talent.
+
+Figure 7. Greatest needs in the tax department for skills over the next one to two years
+
+2021 vs. 2023
+
+[Graph 1: Greatest needs in the tax department for skills over the next one to two years]
+| Skill                                           | 2023 (%) | 2021 (%) |
+|-------------------------------------------------|----------|----------|
+| Data analytics, data-driven strategic insights, and data management | 40       | 44       |
+| Specialist tax technical skills               | 35       | 34       |
+| Transactional tax skills                      | 25       | 33       |
+| Technology transformation and process re-design| 29       | 43       |
+| Risk management                                 | 36       | N/A      |
+| Expertise in emerging areas of regulatory compliance | 27       | 36       |
+| Cross-business advisory skills                | 25       | 34       |
+| External stakeholder management              | 16       | 16       |
+| Business process skills                         | N/A      | 28       |
+| Communications skills                           | N/A      | 10       |
+
+Note: Percentages do not add up to 100% since respondents could make multiple selections. Some items only appeared in the 2023 survey.
+
+Tax in a data-driven world | More regulations, more data, more technology 13
+
+--- end page 13
+
+# What's next?
+
+Strategic management and effective use of data as an asset will be top of mind for tax leaders as
+both global tax reform and primary stakeholders—including boards, finance functions, and financial
+institutions-continue to place data management at the center of the tax function. The tax technology
+landscape, however, is broader than ERP and identifying tax data-tax leaders also need to consider
+how many technologies are really needed to meet their needs, how many are not yet connected to
+each other, and how fast technology is changing, threatening the obsolescence of existing systems.
+
+The pace at which Generative Al technology and tooling is advancing can make it difficult for
+businesses to work out the optimum point at which to invest at scale. Generative Al activity is
+currently predominantly focused on identifying use cases and undertaking a tactical program of
+experimentation as part of a measured approach to understanding the role and impact Generative
+Al can have on a variety of business functions. There should, however, be an expectation that
+over time, Generative Al, combined with broader Al and data analytical techniques, will play an
+increasingly dominant role in the tax technology space, fueled by high levels of fluency, an expansion
+of functionality and, critically, reduced cost of deployment. All of which reinforces the need for a clear
+strategy and focus on data structures.
+
+Today, tax directors are addressing the impact of data within their tax functions and have pivoted
+by introducing new skill sets within their tax function, which is encouraging. This is, however,
+just the first step of a continuous journey in which primary stakeholders use tax data through
+analytics as a strategic enabler to drive investment decisions, often these days using dynamic
+dashboarding and modeling.
+
+The results of Deloitte's Tax Transformation Trends 2023 survey highlighted the need for data-
+driven insight from compliance activities, more agile partnering with other parts of the business,
+and a heightened need to integrate technology across functions and jurisdictions. As digitalization
+continues-accelerated by the introduction of Artificial Intelligence capabilities—tax departments will
+need to ensure their digital strategy meets an ever-changing tax regulatory landscape, is incorporated
+into and aligns with the business's overall digital transformation ambitions, and incorporates efforts
+to prepare their people and processes for accelerated transformation. Tax directors interviewed for
+Deloitte's Tax Transformation Trends research recommend embedding Tax into everyday processes
+and operations. This will lead to tax considerations in transformation efforts becoming “business as
+usual," and making building the business case for technology investment less onerous.
+
+Tax in a data-driven world | More regulations, more data, more technology
+14
+
+
+--- end page 14
+
+# About the research
+
+Deloitte's 2023 Tax Transformation Trends
+survey engaged tax and finance executives
+to understand their strategies for tax
+operations, outsourcing, technology, and
+talent. Deloitte surveyed 300 senior tax
+and finance leaders at companies across
+a range of industries, sizes, and regions to
+understand their future vision for the tax
+function and how they plan to achieve that
+vision. Deloitte also conducted a series
+of qualitative one-on-one interviews with
+senior tax executives at large multinational
+companies to develop deeper insights into
+their tax transformation activities.
+
+# Figure 8. Demographics
+
+## Revenue
+
+|                      |      |
+| -------------------- | ---- |
+| US$750M to 1B      | 43%  |
+| US$1B to 5B         | 28%  |
+| US$5B+              | 29%  |
+
+## Industry
+
+| Industry                      | Percentage |
+| ----------------------------- | ---------- |
+| Life Sciences & Health Care   | 7%         |
+| Consumer                      | 35%        |
+| Financial Services            | 13%        |
+| Technology, Media & Telecommunications | 16%        |
+| Energy, Resources, & Industrials   | 29%        |
+
+## Role
+
+| Role    | Percentage |
+| ------- | ---------- |
+| C-1     | 19%        |
+| C-2     | 35%        |
+| C-suite | 46%        |
+| Finance | 28%        |
+| Tax     | 72%        |
+
+## Headquarters location
+
+| Location        | Percentage |
+| --------------- | ---------- |
+| Asia Pacific    | 30%        |
+| Australia       | 4%         |
+| Japan           | 13%        |
+| China           | 13%        |
+| United Kingdom | 18%        |
+| Europe          | 39%        |
+| United States   | 25%        |
+| North America   | 31%        |
+| Canada          | 6%         |
+| Belgium         | 4%         |
+| Germany         | 7%         |
+| Netherlands     | 5%         |
+| Switzerland     | 5%         |
+
+Survey sample size = 300
+C-suite (e.g., CFO, CAO, CTaxO) = 137
+C-1 (e.g., EVP, SVP of Tax or Finance) = 57
+C-2 (e.g., Directors, VP, Head of
+sub-division) = 106
+
+--- end page 15
+
+# Contacts
+
+Andy Gwyther
+Deloitte Global Operate Leader, Tax & Legal
+[email protected]
+
+North America
+Eric Peel
+Tax Operate Leader
+Deloitte Tax LLP (US)
+[email protected]
+
+Emily VanVleet
+Tax Operate Leader
+Deloitte Tax LLP (US)
+[email protected]
+
+Jeff Butt
+Tax & Legal Operate Leader
+Deloitte Canada
+[email protected]
+
+Arturo Camacho
+Tax & Legal Operate Leader
+Deloitte Spanish-LATAM
+[email protected]
+
+Europe, Middle East, Africa
+Christophe De Waele
+Tax & Legal Operate Leader
+Deloitte North & South Europe
+[email protected]
+
+Ana Santiago Marques
+Tax & Legal Operate Leader
+Deloitte Central Europe
+[email protected]
+
+Patrick Earlam
+Tax & Legal Operate Leader
+Deloitte Africa
+[email protected]
+
+Asia Pacific
+Christopher Roberge
+Tax Operate Leader
+Deloitte Asia Pacific
+[email protected]
+
+Tax in a data-driven world | More regulations, more data, more technology 16
+
+--- end page 16
+
+# Deloitte.
+
+Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (DTTL), its global network of member firms, and their related entities (collectively, the "Deloitte organization"). DTTL (also
+referred to as "Deloitte Global") and each of its member firms and related entities are legally separate and independent entities, which cannot obligate or bind each other in respect of third parties.
+DTTL and each DTTL member firm and related entity is liable only for its own acts and omissions, and not those of each other. DTTL does not provide services to clients. Please see www.deloitte.
+com/about to learn more.
+
+Deloitte provides industry-leading audit and assurance, tax and legal, consulting, financial advisory, and risk advisory services to nearly 90% of the Fortune Global 500® and thousands of private
+companies. Our people deliver measurable and lasting results that help reinforce public trust in capital markets, enable clients to transform and thrive, and lead the way toward a stronger
+economy, a more equitable society, and a sustainable world. Building on its 175-plus year history, Deloitte spans more than 150 countries and territories. Learn how Deloitte's approximately
+457,000 people worldwide make an impact that matters at www.deloitte.com.
+
+This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited ("DTTL"), its global network of member firms or their related entities (collectively, the "Deloitte
+organization") is, by means of this communication, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you
+should consult a qualified professional adviser.
+
+No representations, warranties or undertakings (express or implied) are given as to the accuracy or completeness of the information in this communication, and none of DTTL, its member firms,
+related entities, employees or agents shall be liable or responsible for any loss or damage whatsoever arising directly or indirectly in connection with any person relying on this communication.
+
+2024. For information, contact Deloitte Global.
+
+Designed by CoRe Creative Services. RITM1606967
+
+--- end page 17
+

data/cache/dttl-tax-technology-report-2023.pdf.reformatted.md

@@ -0,0 +1,646 @@
+# Tax in a Data-Driven World
+
+Deloitte.
+
+Tax in a data-driven world
+More regulations, more data, more technology
+
+--- end page 1
+
+## Data and New Regulations Drive Tax Transformation
+
+Immediate access to reliable, accurate, and fit-for-purpose tax data is essential to be
+able to meet complex tax obligations, real-time reporting requirements, and increasing
+expectations of tax transparency. Recent developments such as the OECD's Pillar
+Two rules, requiring large multinational enterprises to pay a minimum “global tax," the
+introduction of CESOP (Central Electronic System of Payment information) and ViDA rules
+(VAT in a Digital Age) in the EU, e-reporting, and e-invoicing are all examples of initiatives
+which are increasing the compliance requirements for companies and having a significant
+impact on tax strategies and operations. Advances in the way technology is used to
+identify, transform, and manage tax-related data should be an essential component of
+a business's response.
+
+> Pillar Two is at the forefront of our mind. We
+> are still quantifying any additional liability and
+> establishing any impact on our Effective Tax Rate.
+> Naturally, there is a huge compliance and systems
+> requirement to accommodate Pillar Two.
+> Gemma Beck
+> Head of Tax, Haleon Plc
+
+Challenges such as version control, manual data collection, or getting the right format
+and level of data can delay accurate reporting and insights—insights from data being
+something the respondents to Deloitte's Tax Transformation Trends 2023 research
+highlighted as of high importance. The impact of these regulatory and digitalization
+changes can vary across companies based on their size, region, or industry. Yet, the
+overall trend has been toward growing workloads and increased complexity.
+
+Tax in a data-driven world | More regulations, more data, more technology
+2
+
+--- end page 2
+
+In addition, many tax authorities are collecting and sharing
+more detailed data about taxes and are requesting direct
+access to large companies' tax-related data. The digitalization
+of tax authorities elevates the need for reliable and automated
+tax models, and generating the right data, in the right format,
+at the right time. Automating data input, validation, and
+cleansing can save time and reduce risk, but is also key to
+enabling the access tax administrations increasingly require.
+
+All this at a time when businesses are starting to explore the
+role and benefits of Generative Al, and having to evaluate how
+trustworthy this technology is, the risks associated with data
+privacy, as well as the consequences for their employees.
+
+Technology can also facilitate greater visibility into tax data
+across the enterprise, which can provide insights that can
+generate value for the business when making strategic
+decisions. In short, tax departments increasingly need
+technology to help them pivot from task completion and
+cost control toward being able to extract outcome-oriented
+business insights from compliance activities through analytics.
+
+[Figure 1. Progress made in implementing tax transformation strategies]
+
+| Fully implemented |  |  | Plan to implement within 12 months |
+|---|---|---|---|
+| 37% | ERP system customized for tax issues |  | 4% |
+| 37% | Use of tools to monitor relevant developments in tax laws globally |  | 7% |
+| 38% | Tax data management solutions and/or tax professionals in company's data management team |  | 6% |
+| 37% | Use of advanced analytics in monitoring of key controls |  | 4% |
+| 32% | Integrated processes |  | 4% |
+| 41% | Streamlining of processes not appropriate for automation |  | 4% |
+| 41% | Automation of tax compliance and reporting processes |  | 2% |
+
+Yet, when Deloitte asked 300 tax and finance professionals
+what progress they had made in implementing tax
+transformation strategies, 24% stated they intended to
+implement an ERP system customized for tax issues in the next
+12 months (Figure 1). Only 37% of respondents said their tax
+department had fully implemented the use of tools to monitor
+relevant developments in tax laws around the world. Similarly,
+many respondents reported that their tax department
+had not yet fully implemented the data management and
+technology applications required by these changes-
+introduction of tax data management solutions and/or having tax
+professionals in the company's data management team (38%), and
+integrated processes (32%).
+
+Implementing tax technology, or customizing existing ERP systems, requires identifying the appropriate issues to
+customize the system for, involving the right stakeholders internally, obtaining budget when there are competing
+demands, and devising a robust schedule of maintenance.
+
+Tax in a data-driven world | More regulations, more data, more technology 3
+
+--- end page 3
+
+## 1. Customizing Technology for Global Compliance
+
+Compliance is a top priority for the tax department (Figure 2) but to achieve it, comply
+with Pillar Two, or calculate their global tax liability, tax departments need accurate,
+timely, tax-related data integrated across their organization. However, achieving visibility
+into enterprise-wide tax data has proven difficult for many companies, with respondents
+to Deloitte's Tax Transformation Trends 2023 survey citing integrating tax-related data
+across the company (36%) as their second-most important challenge. More than a fifth of
+respondents found challenges in having limited technology or data management expertise
+(23%), obtaining a comprehensive view of the total tax paid globally (22%), and not having
+sufficient control over technology strategy and investment (22%) (Figure 2). There is a “perfect
+storm" with the compliance challenge at least partly linked to these other factors.
+
+[Graph 2: Challenges for the tax department over the next three to five years]
+
+| Category                                                                   | Percentage   |
+| -------------------------------------------------------------------------- | ------------ |
+| Complying with evolving tax laws and regulations around the world         | 43%          |
+| Integrating tax-related data across the company                            | 36%          |
+| Limited technology/data management expertise                               | 23%          |
+| Lack of sufficient control over technology strategy and investment          | 22%          |
+| Obtaining a comprehensive view of the total tax paid globally             | 22%          |
+| Obtaining adequate budget                                                  | 18%          |
+| Difficulty in aligning with company's technology transformation strategy/approach | 11%          |
+
+Percentage ranked among top 3 challenges
+
+Tax in a data-driven world | More regulations, more data, more technology 4
+
+--- end page 4
+
+> What we see now is an increasing demand for
+> more compliance requirements-I mean from the
+> OECD and also coming from local authorities...
+> there's demand for more automation.
+> Liliane Saiani
+> Head of Tax, Mercado Libre
+
+The desire to continue customizing ERP systems for tax is not surprising-being able to incorporate
+flexibility and information to respond to changing tax laws will help companies comply, thereby avoiding
+penalties and costs. Modern ERP systems can provide the accurate, granular data that tax teams
+need at the legal entity level, while still supporting the management-level reporting needed by other
+stakeholders. In this way, the ERP can help support tax analytics so that companies can model the
+impact of changing tax laws in multiple jurisdictions, improving the insights used for decision making.
+
+Companies have been working to put in place the data management and technology capabilities
+demanded by today's tax environment, but many have more work to do.
+
+> Our approach was to first work to make ourselves
+> more efficient. We're trying to transform our ERP
+> landscape. It's always a challenge to wrangle all
+> the different technology pieces we have.
+> Kristi Doyle
+> Global Tax Director, Johnson Controls
+
+Tax in a data-driven world | More regulations, more data, more technology
+5
+
+--- end page 5
+
+Many of the challenges appear greater for smaller companies than for larger ones. For example, respondents at companies with revenues of US$5 billion or greater were more likely to
+say that their company had fully implemented introduction of tax data management solutions and/or having tax professionals in the company's data management team (55%) than did those
+at companies with revenues of US$1 billion to US$5 billion (35%) or US$750 million to US$1 billion (25%) (Figure 3).
+
+### Figure 3: Strategies/actions fully implemented by the tax department-by company size
+
+|                                               | Reducing headcount | Implementation of lower-cost delivery model for lower complexity processes | Integrated processes | ERP system customized for tax issues | Processes to allow tax to be adequately considered in corporate decisions | Use of advanced analytics in monitoring of key controls | Use of tools to monitor relevant developments in tax laws globally | Tax data mgmt solutions and/or tax profs. in company's data mgmt team | Streamlining of processes not appropriate for automation | Automation of tax compliance and reporting processes | Ongoing assessment of skills required to identify any gaps | Training programs for skills required in strategic roles |
+|-----------------------------------------------|--------------------|---------------------------------------------------------------------------------|----------------------|---------------------------------------|-----------------------------------------------------------------------------------|-------------------------------------------------------------------|----------------------------------------------------------------------|--------------------------------------------------------------------|-----------------------------------------------------------------|--------------------------------------------------------------------|-------------------------------------------------------------------|-------------------------------------------------------------------|
+| **US$5B+**                                    | 0%                 | 38%                                                                             | 34%                   | 46%                                   | 39%                                                                               | 56%                                                               | 55%                                                                  | 55%                                                                | 49%                                                             | 46%                                                             | 51%                                                               | 56%                                                               |
+| **US$1B - $5B**                               | 0%                 | 30%                                                                             | 33%                   | 45%                                   | 37%                                                                               | 35%                                                               | 38%                                                                  | 35%                                                                | 47%                                                             | 40%                                                             | 51%                                                               | 54%                                                               |
+| **US$750M - $1B**                             | 2%                 | 18%                                                                             | 27%                   | 14%                                   | 20%                                                                               | 24%                                                               | 22%                                                                  | 25%                                                                | 27%                                                             | 29%                                                             | 24%                                                               | 26%                                                               |
+
+Tax in a data-driven world | More regulations, more data, more technology 6
+
+--- end page 6
+
+## 2. Deciding How to Invest in Technology
+
+Digital transformation is embedded into most companies' agendas, but it is still difficult
+to identify clear returns on technology investment—from determining which actions
+drive the most impact, to which investments yield the highest enterprise value. With
+Generative Al also advancing at pace, it is increasingly difficult for businesses to work out
+the optimum point at which to invest at scale. When resources are constrained, it is worth
+weighing up the investment needed for developing, buying, maintaining, and replacing
+technology versus leveraging the technology of an outsource service provider.
+
+> We outsource as much as possible with trusted
+> partners. We don't have the resources, nor the
+> budget, to develop all those tools ourselves.
+> Philippe de Roose
+> Senior Vice President for Tax Treasury and Finance Administration,
+> Radisson Hospitality Group
+
+Tax in a data-driven world | More regulations, more data, more technology
+7
+
+--- end page 7
+
+Figure 4. Benefit company has received—or could receive—from outsourcing an entire activity or function in the tax department
+
+100%
+
+75%
+26%
+27%
+34%
+37%
+33%
+35%
+30%
+50%
+54%
+51%
+25%
+46%
+45%
+45%
+43%
+40%
+0%
+Access to the
+latest technology
+capabilities
+Reduced
+operating costs
+Access to tax
+subject matter
+expertise
+Reduced need for
+capital investment in
+technology
+Ability to provide flexibility
+and quickly scale tax
+operations as needed
+Major/significant
+Some
+Transfer of risk associated
+with technology systems or
+processes to one or more
+third parties
+Reallocation of current
+tax team to other
+strategic objectives
+
+Respondents to the Tax Transformation Trends 2023 survey cited access to the latest technology capabilities (54%) even more often than reduced operating costs (51%) as a major or
+significant benefit of outsourcing (Figure 4). Reduced need for capital investment in technology (45%) was also named frequently as an important benefit. Outsourcing can provide a
+strategy for tax departments to acquire the technology tools and expertise that the current environment demands without incurring the significant capital investment that would be
+required, upfront and ongoing, if enhancements were developed in-house.
+
+While tax departments may have had discretionary budget for incremental changes, or fixing “broken” systems, wholescale finance transformation has centralized budgets, with IT
+taking a prominent role in deciding where transformation efforts will focus. This has led to a greater need for the tax department to collaborate with IT and other departments.
+
+Tax in a data-driven world | More regulations, more data, more technology
+8
+
+--- end page 8
+
+## 3. Internal Collaboration and Obtaining Budget
+
+Data management and IT applications are increasingly important to tax departments.
+However, in Deloitte's Tax Transformation Trends survey, 78% respondents in 2023 said
+technology strategy and planning was largely controlled by Finance or IT; 56% said that
+the tax department has input into the process, while 22% said it had little input (Figure
+5). These findings represent a change from the 2021 survey, in which tax leaders more
+often said their departments had control over technology strategy and budget. This may
+be due to an increased reliance on ERPs, rather than tax-department specific solutions,
+along with the growing need for tax to gather data from across the company-both of
+which would put more control into the hands of IT and Finance.
+
+[Graph 5: Tax function role in technology strategy and planning]
+
+|   | 2021 | 2023 |
+|---|---|---|
+|  | 40% | 15% |
+|  | 23% | 56% |
+|  | 23% | 22% |
+|  | 14% | 7% |
+
+Largely set/controlled
+by Finance or IT, with
+little input from Tax
+
+Largely set/controlled
+by Finance or IT, but
+Tax has input
+
+Tax has significant
+autonomy over
+technology strategy,
+but limited control over
+Capex budget
+
+Tax has significant
+autonomy over both
+technology strategy
+and Capex budget
+
+Tax in a data-driven world | More regulations, more data, more technology 9
+
+--- end page 9
+
+There were also significant regional differences. Respondents at North American companies (40%) more often said that the tax department has significant autonomy either over
+technology strategy or over both technology strategy and budget than did those at companies headquartered in Europe (10%) or Asia Pacific (20%) (Figure 6). European and Asian
+companies typically contend with more indirect taxes, requiring complicated integration with supply chain management in ERP systems, led by Finance, while in North America the
+emphasis is on income taxes, requiring the tax department to lead. Historically, Asian companies have been geared more toward managing reporting and compliance in multiple
+jurisdictions in a decentralized manner, and as a result, were not as experienced in having a common ERP platform to solve all jurisdictional issues. This is, however, changing rapidly as
+more tax technology expertise is developing in Asia, enabling common ERP platforms and local customization.
+
+### Figure 6. Tax function role in technology strategy and planning By region
+
+|             |      |      |
+| ----------- | ----------- | ----------- |
+| ![Figure 6: Tax function role in technology strategy and planning](image_reference)      |       |       |
+
+#### Europe
+
+[Table 1: Tax function role in technology strategy and planning by region - Europe]
+|                                                                                              | Percentage |
+| :-------------------------------------------------------------------------------------------- | ---------: |
+| Largely set/controlled by Finance or IT, with little input from Tax                         |         6% |
+| Largely set/controlled by Finance or IT, but Tax has input                                 |        51% |
+| Tax has significant autonomy over technology strategy, but limited control over Capex budget |       29% |
+| Tax has significant autonomy over both technology strategy and Capex budget                   |       10% |
+| Total                                                                                        |       100% |
+
+#### North America
+
+[Table 2: Tax function role in technology strategy and planning by region - North America]
+|                                                                                              | Percentage |
+| :-------------------------------------------------------------------------------------------- | ---------: |
+| Largely set/controlled by Finance or IT, with little input from Tax                         |        8% |
+| Largely set/controlled by Finance or IT, but Tax has input                                 |        22% |
+| Tax has significant autonomy over technology strategy, but limited control over Capex budget |        30% |
+| Tax has significant autonomy over both technology strategy and Capex budget                   |        40% |
+| Total                                                                                        |       100% |
+
+#### Asia Pacific
+
+[Table 3: Tax function role in technology strategy and planning by region - Asia Pacific]
+|                                                                                              | Percentage |
+| :-------------------------------------------------------------------------------------------- | ---------: |
+| Largely set/controlled by Finance or IT, with little input from Tax                         |       23% |
+| Largely set/controlled by Finance or IT, but Tax has input                                 |        51% |
+| Tax has significant autonomy over technology strategy, but limited control over Capex budget |       26% |
+| Tax has significant autonomy over both technology strategy and Capex budget                   |       20% |
+| Total                                                                                        |       100% |
+
+Technology plays a key role in many aspects of tax operations and in transforming those operations to meet today's challenges—which was made clear in interviews with respondents.
+
+> It's a priority to meet compliance requirements, which are becoming significantly challenging these days, such as
+> Pillar Two and e-reporting. All these new kinds of compliance are very connected to technology and digitalization.
+> Jesus Bravo Fernandez
+> Head of Indirect Tax, Transfer Pricing, and Tax Technology, Coca-Cola Europacific Partners
+
+Tax in a data-driven world | More regulations, more data, more technology 10
+
+--- end page 10
+
+Many respondents said implementing a single, integrated tax platform was a key priority
+for the next few years as they pursue increased efficiency and access to better data. For
+many, there is still work to do on rationalizing fragmented technology landscapes.
+
+> We are looking at how do we deal with all the
+> various systems, and how do we bring some
+> structure and consistency and visibility in that
+> chaos-what evolution and trends are happening
+> from a technology point of view.
+> Dirk Timmermans
+> Vice President of Global Statutory Finance and Tax Operations, Johnson Controls
+
+To make the case for budget, tax departments need to demonstrate the value they
+generate and protect for the company. Companies that have taken the top-down
+company view, managed to explain the impact of tax authority digitalization to the C-suite
+and worked collaboratively with the IT department have typically been more successful in
+building this value case.
+
+Understanding and communicating the aspiration of real-time compliance through
+direct connection between tax authorities and company systems (see the OECD's
+“Tax Administration 3.0" discussion paper) is important for ERP system design as ERP
+systems are where most transactions are handled-thinking about the long term is
+imperative, as finding a point solution now, without thinking through the potential
+requirements in five to 10 years' time, may hinder the tax department from creating
+the environment that will enable being a strategic advisor to the business. Being able to
+identify all the potential outcomes, however, is the difficult part, especially since tax laws
+and regulations still differ significantly between jurisdictions and change frequently.
+
+Tax in a data-driven world | More regulations, more data, more technology 11
+
+--- end page 11
+
+## 4. Finding the Optimal Implementation and Maintenance Program
+
+Tax departments often focus on immediate-need technology. Best practice, however,
+would suggest obtaining budget and developing a road map first to use the technology
+already available, identifying what might be needed in the future, and then making build-
+or-buy decisions. At this point, it's useful to have a holistic view of the tax department's
+operating model—it's not about doing everything now, but looking at increasing speed
+and accuracy, and freeing up tax professionals for more strategic business activity.
+
+Once the technology is chosen, the question is often whether to implement using
+internal resources, appoint an implementation partner, or outsource the entire function
+requiring the technology.
+
+If the decision is made to use in-house resources, tax departments need to develop
+professional teams with the new skills required, especially data management and
+technology expertise. This was evident from Deloitte's Tax Transformation Trends
+research in 2023: When asked where their tax department will have the greatest need
+for skills over the next three to five years, respondents most often named data analytics,
+data-driven strategic insights, and data management (44%)—a reflection of the growing
+importance of data-driven decision making and increased government requirements for
+direct access to companies' tax data (Figure 7 on the next page).
+
+> We made the strategic decision to have capable IT
+> people within our tax department many years ago,
+> and that has allowed us to move much more quickly
+> with getting our data needs met.
+>
+> Dirk Timmermans
+> Vice President of Global Statutory Finance and Tax Operations, Johnson Controls
+
+Tax in a data-driven world | More regulations, more data, more technology 12
+
+--- end page 12
+
+Several skill areas were cited less often in 2023 than in 2021, suggesting that some companies may have made progress in addressing their talent requirement in those areas—either
+through recruitment, or by leaning more on outside providers. For example, technology transformation and process redesign was named as a top talent need by 29% of respondents
+in the current survey, compared to 43% in 2021. However, this area still ranked fourth highest among the skills needed in the next few years, indicating that many companies are still
+working to develop or acquire technology talent.
+
+Figure 7. Greatest needs in the tax department for skills over the next one to two years
+
+2021 vs. 2023
+
+[Graph 1: Greatest needs in the tax department for skills over the next one to two years]
+| Skill                                           | 2023 (%) | 2021 (%) |
+|-------------------------------------------------|----------|----------|
+| Data analytics, data-driven strategic insights, and data management | 40       | 44       |
+| Specialist tax technical skills               | 35       | 34       |
+| Transactional tax skills                      | 25       | 33       |
+| Technology transformation and process re-design| 29       | 43       |
+| Risk management                                 | 36       | N/A      |
+| Expertise in emerging areas of regulatory compliance | 27       | 36       |
+| Cross-business advisory skills                | 25       | 34       |
+| External stakeholder management              | 16       | 16       |
+| Business process skills                         | N/A      | 28       |
+| Communications skills                           | N/A      | 10       |
+
+Note: Percentages do not add up to 100% since respondents could make multiple selections. Some items only appeared in the 2023 survey.
+
+Tax in a data-driven world | More regulations, more data, more technology 13
+
+--- end page 13
+
+## What's Next?
+
+Strategic management and effective use of data as an asset will be top of mind for tax leaders as
+both global tax reform and primary stakeholders—including boards, finance functions, and financial
+institutions-continue to place data management at the center of the tax function. The tax technology
+landscape, however, is broader than ERP and identifying tax data-tax leaders also need to consider
+how many technologies are really needed to meet their needs, how many are not yet connected to
+each other, and how fast technology is changing, threatening the obsolescence of existing systems.
+
+The pace at which Generative Al technology and tooling is advancing can make it difficult for
+businesses to work out the optimum point at which to invest at scale. Generative Al activity is
+currently predominantly focused on identifying use cases and undertaking a tactical program of
+experimentation as part of a measured approach to understanding the role and impact Generative
+Al can have on a variety of business functions. There should, however, be an expectation that
+over time, Generative Al, combined with broader Al and data analytical techniques, will play an
+increasingly dominant role in the tax technology space, fueled by high levels of fluency, an expansion
+of functionality and, critically, reduced cost of deployment. All of which reinforces the need for a clear
+strategy and focus on data structures.
+
+Today, tax directors are addressing the impact of data within their tax functions and have pivoted
+by introducing new skill sets within their tax function, which is encouraging. This is, however,
+just the first step of a continuous journey in which primary stakeholders use tax data through
+analytics as a strategic enabler to drive investment decisions, often these days using dynamic
+dashboarding and modeling.
+
+The results of Deloitte's Tax Transformation Trends 2023 survey highlighted the need for data-
+driven insight from compliance activities, more agile partnering with other parts of the business,
+and a heightened need to integrate technology across functions and jurisdictions. As digitalization
+continues-accelerated by the introduction of Artificial Intelligence capabilities—tax departments will
+need to ensure their digital strategy meets an ever-changing tax regulatory landscape, is incorporated
+into and aligns with the business's overall digital transformation ambitions, and incorporates efforts
+to prepare their people and processes for accelerated transformation. Tax directors interviewed for
+Deloitte's Tax Transformation Trends research recommend embedding Tax into everyday processes
+and operations. This will lead to tax considerations in transformation efforts becoming “business as
+usual," and making building the business case for technology investment less onerous.
+
+Tax in a data-driven world | More regulations, more data, more technology
+14
+
+--- end page 14
+
+## About the Research
+
+Deloitte's 2023 Tax Transformation Trends
+survey engaged tax and finance executives
+to understand their strategies for tax
+operations, outsourcing, technology, and
+talent. Deloitte surveyed 300 senior tax
+and finance leaders at companies across
+a range of industries, sizes, and regions to
+understand their future vision for the tax
+function and how they plan to achieve that
+vision. Deloitte also conducted a series
+of qualitative one-on-one interviews with
+senior tax executives at large multinational
+companies to develop deeper insights into
+their tax transformation activities.
+
+### Figure 8. Demographics
+
+#### Revenue
+
+|                      |      |
+| -------------------- | ---- |
+| US$750M to 1B      | 43%  |
+| US$1B to 5B         | 28%  |
+| US$5B+              | 29%  |
+
+#### Industry
+
+| Industry                      | Percentage |
+| ----------------------------- | ---------- |
+| Life Sciences & Health Care   | 7%         |
+| Consumer                      | 35%        |
+| Financial Services            | 13%        |
+| Technology, Media & Telecommunications | 16%        |
+| Energy, Resources, & Industrials   | 29%        |
+
+#### Role
+
+| Role    | Percentage |
+| ------- | ---------- |
+| C-1     | 19%        |
+| C-2     | 35%        |
+| C-suite | 46%        |
+| Finance | 28%        |
+| Tax     | 72%        |
+
+#### Headquarters Location
+
+| Location        | Percentage |
+| --------------- | ---------- |
+| Asia Pacific    | 30%        |
+| Australia       | 4%         |
+| Japan           | 13%        |
+| China           | 13%        |
+| United Kingdom | 18%        |
+| Europe          | 39%        |
+| United States   | 25%        |
+| North America   | 31%        |
+| Canada          | 6%         |
+| Belgium         | 4%         |
+| Germany         | 7%         |
+| Netherlands     | 5%         |
+| Switzerland     | 5%         |
+
+Survey sample size = 300
+C-suite (e.g., CFO, CAO, CTaxO) = 137
+C-1 (e.g., EVP, SVP of Tax or Finance) = 57
+C-2 (e.g., Directors, VP, Head of
+sub-division) = 106
+
+--- end page 15
+
+## Contacts
+
+Andy Gwyther
+Deloitte Global Operate Leader, Tax & Legal
+[email protected]
+
+### North America
+
+Eric Peel
+Tax Operate Leader
+Deloitte Tax LLP (US)
+[email protected]
+
+Emily VanVleet
+Tax Operate Leader
+Deloitte Tax LLP (US)
+[email protected]
+
+Jeff Butt
+Tax & Legal Operate Leader
+Deloitte Canada
+[email protected]
+
+Arturo Camacho
+Tax & Legal Operate Leader
+Deloitte Spanish-LATAM
+[email protected]
+
+### Europe, Middle East, Africa
+
+Christophe De Waele
+Tax & Legal Operate Leader
+Deloitte North & South Europe
+[email protected]
+
+Ana Santiago Marques
+Tax & Legal Operate Leader
+Deloitte Central Europe
+[email protected]
+
+Patrick Earlam
+Tax & Legal Operate Leader
+Deloitte Africa
+[email protected]
+
+### Asia Pacific
+
+Christopher Roberge
+Tax Operate Leader
+Deloitte Asia Pacific
+[email protected]
+
+Tax in a data-driven world | More regulations, more data, more technology 16
+
+--- end page 16
+
+## Deloitte.
+
+Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (DTTL), its global network of member firms, and their related entities (collectively, the "Deloitte organization"). DTTL (also
+referred to as "Deloitte Global") and each of its member firms and related entities are legally separate and independent entities, which cannot obligate or bind each other in respect of third parties.
+DTTL and each DTTL member firm and related entity is liable only for its own acts and omissions, and not those of each other. DTTL does not provide services to clients. Please see www.deloitte.
+com/about to learn more.
+
+Deloitte provides industry-leading audit and assurance, tax and legal, consulting, financial advisory, and risk advisory services to nearly 90% of the Fortune Global 500® and thousands of private
+companies. Our people deliver measurable and lasting results that help reinforce public trust in capital markets, enable clients to transform and thrive, and lead the way toward a stronger
+economy, a more equitable society, and a sustainable world. Building on its 175-plus year history, Deloitte spans more than 150 countries and territories. Learn how Deloitte's approximately
+457,000 people worldwide make an impact that matters at www.deloitte.com.
+
+This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited ("DTTL"), its global network of member firms or their related entities (collectively, the "Deloitte
+organization") is, by means of this communication, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you
+should consult a qualified professional adviser.
+
+No representations, warranties or undertakings (express or implied) are given as to the accuracy or completeness of the information in this communication, and none of DTTL, its member firms,
+related entities, employees or agents shall be liable or responsible for any loss or damage whatsoever arising directly or indirectly in connection with any person relying on this communication.
+
+2024. For information, contact Deloitte Global.
+
+Designed by CoRe Creative Services. RITM1606967
+
+--- end page 17
+

data/cache/life-sciences-smart-manufacturing-services-peak-matrix-assessment-2023.pdf.md

@@ -0,0 +1,513 @@
+Everest Group®
+
+Everest Group Life Sciences Smart Manufacturing Services PEAK Matrix®
+Assessment 2023
+
+Focus on Deloitte
+August 2023
+
+Everest Group
+PEAK
+MATRIX®
+
+Copyright © 2023 Everest Global, Inc.
+This document has been licensed to Deloitte
+
+--- end page 1
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Introduction
+
+Historically, the traditional manufacturing industry was primarily focused on designing standardized manufacturing procedures and managing labor and mechanical systems, but with the
+emergence of Industry 4.0, technology adoption has become widespread across industries, unlocking numerous benefits. However, the life sciences industry has been slow in adopting
+technology to modernize manufacturing setups. Nevertheless, the pandemic, regulatory frameworks, and the urge to achieve operational excellence are now driving the adoption of smart
+manufacturing services.
+
+Life sciences enterprises aim to unlock benefits such as cost optimization, increased productivity, visibility, and efficiency by investing in critical use cases, including digital twins, predictive
+maintenance, etc. They are also exploring high-growth opportunities such as sustainable manufacturing, batch-to-continuous manufacturing, and manufacturing of personalized medicines.
+As the industry experiences investments in smart manufacturing, service providers are taking on the role of end-to-end digital transformation partners by co-developing solutions to assist
+enterprises in their digital journeys.
+
+In the full report, we present an assessment of 16 life sciences service providers featured on the Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023.
+The assessment is based on Everest Group's annual RFI process for the calendar year 2023, interactions with leading life sciences service providers, client reference checks, and an
+ongoing analysis of the life sciences smart manufacturing services market.
+
+The full report includes the profiles of the following 16 leading life sciences service providers featured on the Life Sciences Smart Manufacturing Services PEAK Matrix:
+* Leaders: Accenture, Cognizant, Deloitte, HCLTech, and TCS
+* Major Contenders: Capgemini, Tech Mahindra, LTIMindtree, Wipro, NTT DATA, Innova Solutions, Birlasoft, and Infosys
+* Aspirants: Atos, HARMAN DTS, and NNIT
+
+Scope of this report
+
+![Figure 1: Icons representing Geography (Global), Industry (Life sciences (biopharmaceuticals and medical devices)), and Services (Life sciences smart manufacturing services)](image_reference)
+
+
+--- end page 2
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+Life Sciences Smart Manufacturing Services PEAK Matrix® characteristics
+
+**Leaders**
+Accenture, Cognizant, Deloitte, HCLTech, and TCS
+- Leaders have positioned themselves as digital transformation partners for enterprises with end-to-end capabilities, and offer a balanced breadth of offerings across the life sciences
+manufacturing value chain
+- They demonstrate flexibility and innovation while pitching engagement models and commercial constructs, and possess a distinct talent pool specializing in the life sciences smart
+manufacturing space
+- There is a presence of a robust partnership ecosystem and investments aligned with the demand of the enterprises in the areas of digital twins, IoT-enabled analytics, cybersecurity, etc.,
+as well as high-growth opportunity areas such as specialty drugs manufacturing, sustainable manufacturing, and batch-to-continuous manufacturing
+- They showcase a clear future roadmap to better supplement their internal capabilities and fill in the gaps in their existing portfolio of services through the development of IP, CoEs, and
+strategic initiatives
+
+**Major Contenders**
+Capgemini, Tech Mahindra, LTIMindtree, Wipro, NTT DATA, Innova Solutions, Birlasoft, and Infosys
+- Major Contenders comprise a varied mix of midsize and large firms. They possess a relatively less balanced portfolio compared to Leaders and are inclined toward specialization in
+certain specific areas of the value chain. Additionally, they offer limited solutions around high-growth opportunity areas such as specialty drugs manufacturing, sustainable
+manufacturing, and batch-to-continuous manufacturing
+- Major Contenders have shortcomings in certain areas of the manufacturing value chain; the prevalent approach to address smart manufacturing use cases is by harnessing
+cross-industry intellectual property, talent, and partnerships
+- They have substantiated their position within the mid-tier segment of clients by pursuing active client management and ramping up/down resources commensurate to the ask of buyers
+
+**Aspirants**
+Atos, HARMAN DTS, and NNIT
+- When it comes to their services portfolio, Aspirants have restricted their focus to specific areas in the life sciences manufacturing value chain, with limited digital service capabilities
+- They have a limited partnership ecosystem and place more focus on leveraging horizontal capabilities to cater to the needs of life sciences enterprises rather than developing
+domain-specific services through CoEs and strategic alliances
+- They have a dedicated focus on capturing the market share in the small and midsize buyer segment
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+3
+
+--- end page 3
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+# Everest Group PEAK Matrix®
+Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023 |
+Deloitte is positioned as a Leader
+
+Everest Group Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 20231,2,3
+
+![Figure 1: Everest Group Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023. The image is a two-dimensional matrix. The X-axis is titled "Vision & capability - Measures ability to deliver services successfully". The Y-axis is titled "Market impact - Measures impact created in the market". Companies are positioned in the matrix, divided into four quadrants: Aspirants, Major Contenders, and Leaders. Deloitte is positioned as a Leader. Other companies include Accenture, TCS, HCLTech, Cognizant, Capgemini, Wipro, NTT DATA, LTIMindtree, Innova Solutions, Tech Mahindra, Birlasoft, NNIT, HARMAN DTS, and Atos.](image_reference)
+
+*   Leaders
+*   Major Contenders
+*   Aspirants
+
+1 Assessments for Atos, Capgemini, Infosys, and NTT DATA exclude provider inputs and are based on Everest Group's proprietary Transaction Intelligence (TI) database, provider public disclosures, and Everest Group's interactions with enterprise buyers
+2 Assessment for Birlasoft, HARMAN DTS, and NNIT is based on partial primary inputs (briefings only)
+3 The assessment of Atos is completed prior to its acquisition by Eviden
+Confidentiality: Everest Group takes its confidentiality pledge very seriously. Any information we collect that is contract specific will only be presented back to the industry in an aggregated fashion
+Source: Everest Group (2023)
+
+--- end page 4
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+# Deloitte profile (page 1 of 6)
+
+Overview
+
+Company mission
+Deloitte's Life Sciences Smart Manufacturing practice partners with life sciences enterprises in reimagining and
+reconfiguring their value chains to ensure the reliable and efficient supply of affordable and accessible therapies
+and medical products to the end customers, resulting in enhanced well-being of patients. It supports clients in
+their digital transformation journey and pushes life sciences manufacturing into the next generation of digital
+evolution. This is achieved through substantial investments in expanding global smart manufacturing
+capabilities, fostering robust partnerships, developing proprietary IP-based assets, leveraging smart factory
+technology, and nurturing talent.
+
+Overview of the client base
+Among its diverse customer base, Deloitte's life science smart manufacturing practice engages with the top 10
+largest global pharmaceutical enterprises, top 10 largest BioTech enterprises, 9 out of the top 10 medical device
+enterprises, and 18 out of the 21 largest life sciences enterprises.
+
+[Table 1: Revenue by line of business¹]
+|                       | Low (<10%) | Medium (10-35%) | High (>35%) |
+| :-------------------- | :---------- | :--------------- | :----------- |
+| Biopharmaceuticals    |             |                  | ■            |
+| Medical devices       |             |                  |              |
+| Others                | ■           |                  |              |
+
+[Table 2: Revenue by buyer size¹]
+|                                            | Low (<20%) | Medium (20-40%) | High (>40%) |
+| :----------------------------------------- | :---------- | :--------------- | :----------- |
+| Small (annual revenue <US$1 billion)        |             | ■                |              |
+| Midsize (annual revenue US$1-10 billion)    | ■           |                  |              |
+| Large (annual revenue >US$10 billion)       |             |                  | ■            |
+
+[Table 3: Revenue by geography¹]
+|                       | Low (<15%) | Medium (15-40%) | High (>40%) |
+| :-------------------- | :---------- | :--------------- | :----------- |
+| North America         |             |                  | ■            |
+| Rest of Europe        |             |                  |              |
+| United Kingdom        |             | ■                |              |
+| Asia Pacific          |             |                  |              |
+| Middle East & Africa  | ■           |                  |              |
+| South America         |             |                  | ■            |
+
+¹ All the revenue components add up to a total of 100%
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+5
+
+
+--- end page 5
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+Deloitte profile (page 2 of 6)
+Case studies
+Case study 1
+Transformation of Quality Management System (QMS) for a global
+pharmaceutical manufacturer
+Case study 2
+NOT EXHAUSTIVE
+Developing a global security standard for the manufacturing sites of a global
+pharmaceutical enterprise
+
+Business challenge
+The client faced challenges with high costs of quality and the regulatory risks in managing compliance. It had
+basic and disconnected platforms for quality processes, and lacked integration and traceability. To address
+this, the client identified a QMS platform and set ambitious timelines to deploy multiple Quality System
+Elements (QSEs) across more than five sites.
+
+Solution
+Deloitte assisted the client in their QMS transformation journey by assessing the current state of QSEs and
+conducting a process design exercise. Additionally, it built solutions tailored to client requirements, including
+customization with next-generation functionalities, performed detailed validation and system testing, and
+supported the change management process through a training program strategy.
+
+Impact
+- Assisted the clients in realizing benefits worth US$30 million by eliminating non-value-added work, thereby
+reducing overhead expenses
+- Deployed more than 10 QSEs in 14 months across five manufacturing sites
+- Ensured QMS process adoption for more than 700 employees globally
+Business challenge
+The client recognized the necessity of developing and implementing a global security standard across all
+manufacturing and R&D sites to enhance the security maturity of Internet of Things (IoT), Industrial Control
+Systems (ICS), and Operational Technology (OT).
+
+Solution
+Deloitte implemented a tailored OT cybersecurity framework, conducted detailed site security assessments,
+and deployed monitoring solutions to enhance OT asset security monitoring, visibility, and situational
+awareness. It also deployed threat intelligence and analytics for detecting OT cybersecurity threats and
+established standards, communication plans, playbooks, and workflows for incident response and recovery.
+
+Impact
+- Deployed 14 OT security controls
+- Remediated 42 manufacturing and R&D sites
+- Identified and monitored more than 30,000 OT digital assets
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+6
+
+--- end page 6
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+# Deloitte profile (page 3 of 6)
+
+# Offerings
+
+NOT EXHAUSTIVE
+
+Proprietary smart manufacturing solutions – such as IP, platforms, accelerators, and tools (representative list)
+
+[Table 1: Proprietary smart manufacturing solutions]
+| Solution | Details |
+| --- | --- |
+| Supply chain control tower platform | It is an end-to-end platform solution that assists clients by providing prescriptive insights, monitoring transaction-level data, and offering analytical capabilities across the manufacturing and supply chain processes. |
+| CentralSight | It has the capabilities to effectively visualize a multi-tier deep supplier ecosystem, helping enterprises identify and address the associated risks within the ecosystem in a timely manner. |
+| Smart factory capability compass | It is an application that assists clients in assessing the current manufacturing maturity and readiness of their sites for smart factory investments and initiatives. |
+| CognitiveSpark for manufacturing | It is a cloud-based, Al-powered solution designed to assist biopharma and MedTech manufacturers with insights that help optimize manufacturing processes and improve product quality. |
+| Turnkey IoT | It is a suite of pre-configured solution accelerators tailored to high-potential manufacturing use cases. |
+| Managed Extended Detection and Response (MXDR) | It is a SaaS-based, modular cybersecurity solution designed to protect enterprises from internal and external cyber threats. |
+| Greenlight | This is a decarbonization solution designed to achieve net-zero emissions. It includes a package of dashboard modules that can ingest Green House Gas (GHG) emissions and reduce project data, enabling clients to visualize and analyze their aggregate carbon footprint. |
+| IDEA | It is an loT-based application that helps clients manage real-time energy consumption from different sources, combining the loT approach with traditional Energy Management Systems (EMS). |
+| Digital IoT | It is a preconfigured Siemens MindSphere application that offers a cloud-based, open loT operating system connecting products, plants, systems, and machines. This application unifies data from Digital Product Lifecycle Management (DPLM), Data Acquisition and Management System (DAMS), Digital Manufacturing Execution System (DMES), and IoT systems onto an integrated dashboard, thereby enabling actionable insights. |
+
+Everest Group Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+7
+
+
+--- end page 7
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 4 of 6)
+
+### Offerings
+
+[Table 1: Proprietary smart manufacturing solutions – such as IP, platforms, accelerators, and tools (representative list)]
+| Solution | Details |
+| ----------- | ----------- |
+| SupplyHorizon | It enables enterprises to proactively identify and mitigate supply chain issues. It leverages internal and external data, risk profiling, mitigation planning, persona-based visualizations, and Al to enable a visibility of multi-tier supply networks and sense any upcoming risks in order to mitigate disruptions. |
+| Smart manufacturing platform | This is a platform solution that enables the comprehensive view of manufacturing operations across the organization with connected data from disparate systems to create dynamic data visualizations that provide useful insights and recommended actions. It assists in predictive analytics, quality analytics, planning and management, shop floor tracking and serialization, etc. |
+| Supplier 360 | It is an end-to-end management solution that improves supplier relationships by consolidating data from various disparate sources to generate actionable insights on supplier performance, connecting stakeholders, and more. |
+
+NOT EXHAUSTIVE
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+
+--- end page 8
+
+Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+# Deloitte profile (page 5 of 6)
+## Recent developments
+
+[Table 1: Key events - related to smart manufacturing services (representative list)]
+| Event name | Type of event | Year | Details |
+|---|---|---|---|
+| Industrial data fabric | Alliance | 2023 | Forged a multi-party partnership with AWS, HighByte, and Element to help manufacturers connect, structure, and manage industrial data at scale through an open industrial data framework; supports Deloitte's smart manufacturing platform and services, offering data analytics, predictive insights, and faster time-to-value for manufacturers |
+| Nubik | Acquisition | 2022 | Acquired to strengthen its presence and leadership in the Salesforce practice and firm up its relationships and offerings for mid-market clients; it will assist clients with advanced solutions in manufacturing and distribution |
+| OCT Emissions Solutions | Acquisition | 2022 | Acquired to assist clients with an end-to-end offering across the climate change and decarbonization life cycle. It provides solutions for hydrogen, carbon sequestration and offsets, and carbon dioxide cleanup |
+| AE Cloud Consultant | Acquisition | 2022 | Acquired to deploy front-end and back-end solutions for order management, production management, supply chain management, warehouse and fulfillment, procurement, etc., for enterprises |
+| Smart factories spread across global locations | Investment | 2022 | The smart factories that are spread across the globe serve as an ecosystem of smart manufacturing capabilities built on advanced technologies such as loT, cybersecurity, and digital twins; also acts as a platform that brings together solution providers, technology innovators, and academic researchers to drive innovation |
+| Check Point | Alliance | 2021 | Alliance with Check Point, a leading provider of cybersecurity solutions, to assist Deloitte in strengthening Industry 4.0 technologies by securing the enterprise manufacturing and supply chain infrastructure |
+| Syncronic | Acquisition | 2021 | Acquired to enhance its supply chain practice in the Nordics region |
+| aeCyberSolutions | Acquisition | 2021 | Acquired to strengthen its cybersecurity offerings |
+| Digital Immunity | Alliance | 2020 | Alliance with Digital Immunity to leverage Deloitte's multiple OT lab environments, such as the Smart Factory in Wichita, to accelerate deployment testing by utilizing configuration and deployment guidelines from the lab environment |
+| Nozomi | Alliance | 2020 | Alliance with Nozomi Networks to deliver IT, OT, and IoT security services in the EMEA region. This collaboration aims to assist enterprises in enhancing their threat detection capabilities and implementing effective cyber risk solutions |
+| Beelogix | Acquisition | 2019 | Acquired to expand its capabilities and leadership in SAP digital supply chain solution |
+
+--- end page 9
+
+Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+# Deloitte profile (page 6 of 6)
+# Everest Group assessment – Leader
+
+Measure of capability: Low High
+
+## Market impact
+| Market   | Portfolio  | Value     | Overall   | Vision and | Scope of    | Vision & capability | Innovation and  | Delivery   | Overall  |
+| :------- | :--------- | :-------- | :-------- | :--------- | :---------- | :------------------ | :-------------- | :--------- | :------- |
+| adoption | mix        | delivered |           | strategy   | services offered |                     | investments   | footprint |          |
+
+## Strengths
+* Deloitte has made substantial investments in developing manufacturing solutions
+throughout the life sciences value chain, focusing on futuristic domain use cases such as
+cell and gene therapy manufacturing and sustainable manufacturing. It is further
+reinforced by its dedicated investments in building the Wichita smart factory, which
+strengthens its capabilities in loT, cybersecurity, digital twins, robotics, etc.
+* While clients highlight the premium pricing points, they acknowledge the innovative
+commercial constructs offered by Deloitte and perceive the dollar value per service
+provided to be better compared to peers
+* Clients view Deloitte as a reliable strategic partner as it addresses both the existing and
+emerging business problems, even by engaging third-party providers if necessary
+* Clients appreciate the high quality of the talent deployed and the strong technical domain
+knowledge they possess
+
+## Limitations
+* Although clients appreciate the technical and domain expertise of the talent deployed,
+they expect better attrition management to ensure seamless project delivery
+* Deloitte's tendency to consistently agree with clients without conducting thorough
+evaluations can reveal a lack of critical assessment and hinder their ability to make
+decisions that align with the enterprise's expertise and best interests
+* While clients appreciate Deloitte's strategic inputs, they look for better transparency and
+alignment with the enterprise stakeholders
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+10
+
+--- end page 10
+
+Appendix
+
+Everest Group®
+11
+
+--- end page 11
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+Everest Group PEAK Matrix® is a proprietary framework for assessment of
+market impact and vision & capability
+
+Everest Group PEAK Matrix
+
+![Figure 1: A matrix is shown with 'Market impact' as the vertical axis and 'Vision & capability' as the horizontal axis.  The matrix is divided into four quadrants: Aspirants, Major Contenders, and Leaders. The arrow demonstrates the movement towards the top right of the matrix, indicating growth in both vision and market impact.](image.png)
+
+--- end page 12
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+Services PEAK Matrix® evaluation dimensions
+
+Measures impact created in the market –
+captured through three subdimensions
+
+Market adoption
+Number of clients, revenue base,
+YoY growth, and deal value/volume
+
+Portfolio mix
+Diversity of client/revenue base across
+geographies and type of engagements
+
+Value delivered
+Value delivered to the client based
+on customer feedback and
+transformational impact
+
+Market impact
+Aspirants
+Major Contenders
+Leaders
+
+Vision & capability
+Measures ability to deliver services successfully.
+This is captured through four subdimensions
+
+![Figure 1: The PEAK Matrix graph is plotted with "Market Impact" on the vertical axis and "Vision & Capability" on the horizontal axis. The graph is divided into three zones from left to right: Aspirants, Major Contenders, and Leaders. An arrow spans diagonally across the chart.](image_reference)
+
+Vision and strategy
+Vision for the client and itself; future
+roadmap and strategy
+
+Scope of services offered
+Depth and breadth of services portfolio
+across service subsegments/processes
+
+Innovation and investments
+Innovation and investment in the enabling
+areas, e.g., technology IP, industry/domain
+knowledge, innovative commercial
+constructs, alliances, M&A, etc.
+
+Delivery footprint
+Delivery footprint and global sourcing mix
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+13
+
+--- end page 13
+
+# FAQs
+
+Does the PEAK Matrix® assessment incorporate any subjective criteria?
+Everest Group's PEAK Matrix assessment takes an unbiased and fact-based approach that leverages provider / technology vendor RFIs and Everest Group's proprietary databases containing providers' deals
+and operational capability information. In addition, we validate/fine-tune these results based on our market experience, buyer interaction, and provider/vendor briefings.
+
+Is being a Major Contender or Aspirant on the PEAK Matrix, an unfavorable outcome?
+No. The PEAK Matrix highlights and positions only the best-in-class providers / technology vendors in a particular space. There are a number of providers from the broader universe that are assessed and do
+not make it to the PEAK Matrix at all. Therefore, being represented on the PEAK Matrix is itself a favorable recognition.
+
+What other aspects of the PEAK Matrix assessment are relevant to buyers and providers other than the PEAK Matrix positioning?
+A PEAK Matrix positioning is only one aspect of Everest Group's overall assessment. In addition to assigning a Leader, Major Contender, or Aspirant label, Everest Group highlights the distinctive capabilities
+and unique attributes of all the providers assessed on the PEAK Matrix. The detailed metric-level assessment and associated commentary are helpful for buyers in selecting providers/vendors for their specific
+requirements. They also help providers/vendors demonstrate their strengths in specific areas.
+
+What are the incentives for buyers and providers to participate/provide input to PEAK Matrix research?
+* Enterprise participants receive summary of key findings from the PEAK Matrix assessment
+* For providers
+    - The RFI process is a vital way to help us keep current on capabilities; it forms the basis for our database – without participation, it is difficult to effectively match capabilities to buyer inquiries
+    - In addition, it helps the provider/vendor organization gain brand visibility through being in included in our research reports
+
+What is the process for a provider / technology vendor to leverage its PEAK Matrix positioning?
+* Providers/vendors can use their PEAK Matrix positioning or Star Performer rating in multiple ways including:
+    - Issue a press release declaring positioning; see our [citation policies](citation policies)
+    - Purchase a customized PEAK Matrix profile for circulation with clients, prospects, etc. The package includes the profile as well as quotes from Everest Group analysts, which can be used in PR
+    - Use PEAK Matrix badges for branding across communications (e-mail signatures, marketing brochures, credential packs, client presentations, etc.)
+* The provider must obtain the requisite licensing and distribution rights for the above activities through an agreement with Everest Group; please contact your CD or [contact us](contact us)
+
+Does the PEAK Matrix evaluation criteria change over a period of time?
+PEAK Matrix assessments are designed to serve enterprises' current and future needs. Given the dynamic nature of the global services market and rampant disruption, the assessment criteria
+are realigned as and when needed to reflect the current market reality and to serve enterprises' future expectations.
+
+--- end page 14
+
+# Everest Group®
+With you on the journey
+
+Everest Group is a leading research firm helping business leaders make confident decisions. We guide clients through
+today's market challenges and strengthen their strategies by applying contextualized problem-solving to their unique
+situations. This drives maximized operational and financial performance and transformative experiences. Our deep
+expertise and tenacious research focused on technology, business processes, and engineering through the lenses of
+talent, sustainability, and sourcing delivers precise and action-oriented guidance. Find further details and in-depth content
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+
+Stay connected
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+* in @Everest Group
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+"as is" and "as available" without any warranty of any kind, including any
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+and nothing provided by Everest Group is legal, tax, financial, or investment advice. Nothing Everest Group
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+Nothing from Everest Group may be used or relied upon in evaluating the merits of any investment. Do not base
+any investment decisions, in whole or part, on anything provided by Everest Group.
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+or representation as to past, present, or future performance of a business or a market. The information contained
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+
+
+--- end page 15
+

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+# Everest Group® Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+Everest Group
+PEAK
+MATRIX®
+
+Copyright © 2023 Everest Global, Inc.
+This document has been licensed to Deloitte
+
+--- end page 1
+
+## Introduction
+
+Historically, the traditional manufacturing industry was primarily focused on designing standardized manufacturing procedures and managing labor and mechanical systems, but with the
+emergence of Industry 4.0, technology adoption has become widespread across industries, unlocking numerous benefits. However, the life sciences industry has been slow in adopting
+technology to modernize manufacturing setups. Nevertheless, the pandemic, regulatory frameworks, and the urge to achieve operational excellence are now driving the adoption of smart
+manufacturing services.
+
+Life sciences enterprises aim to unlock benefits such as cost optimization, increased productivity, visibility, and efficiency by investing in critical use cases, including digital twins, predictive
+maintenance, etc. They are also exploring high-growth opportunities such as sustainable manufacturing, batch-to-continuous manufacturing, and manufacturing of personalized medicines.
+As the industry experiences investments in smart manufacturing, service providers are taking on the role of end-to-end digital transformation partners by co-developing solutions to assist
+enterprises in their digital journeys.
+
+In the full report, we present an assessment of 16 life sciences service providers featured on the Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023.
+The assessment is based on Everest Group's annual RFI process for the calendar year 2023, interactions with leading life sciences service providers, client reference checks, and an
+ongoing analysis of the life sciences smart manufacturing services market.
+
+The full report includes the profiles of the following 16 leading life sciences service providers featured on the Life Sciences Smart Manufacturing Services PEAK Matrix:
+* Leaders: Accenture, Cognizant, Deloitte, HCLTech, and TCS
+* Major Contenders: Capgemini, Tech Mahindra, LTIMindtree, Wipro, NTT DATA, Innova Solutions, Birlasoft, and Infosys
+* Aspirants: Atos, HARMAN DTS, and NNIT
+
+Scope of this report
+
+![Figure 1: Icons representing Geography (Global), Industry (Life sciences (biopharmaceuticals and medical devices)), and Services (Life sciences smart manufacturing services)](image_reference)
+
+--- end page 2
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Life Sciences Smart Manufacturing Services PEAK Matrix® characteristics
+
+### Leaders
+Accenture, Cognizant, Deloitte, HCLTech, and TCS
+- Leaders have positioned themselves as digital transformation partners for enterprises with end-to-end capabilities, and offer a balanced breadth of offerings across the life sciences
+manufacturing value chain
+- They demonstrate flexibility and innovation while pitching engagement models and commercial constructs, and possess a distinct talent pool specializing in the life sciences smart
+manufacturing space
+- There is a presence of a robust partnership ecosystem and investments aligned with the demand of the enterprises in the areas of digital twins, IoT-enabled analytics, cybersecurity, etc.,
+as well as high-growth opportunity areas such as specialty drugs manufacturing, sustainable manufacturing, and batch-to-continuous manufacturing
+- They showcase a clear future roadmap to better supplement their internal capabilities and fill in the gaps in their existing portfolio of services through the development of IP, CoEs, and
+strategic initiatives
+
+### Major Contenders
+Capgemini, Tech Mahindra, LTIMindtree, Wipro, NTT DATA, Innova Solutions, Birlasoft, and Infosys
+- Major Contenders comprise a varied mix of midsize and large firms. They possess a relatively less balanced portfolio compared to Leaders and are inclined toward specialization in
+certain specific areas of the value chain. Additionally, they offer limited solutions around high-growth opportunity areas such as specialty drugs manufacturing, sustainable
+manufacturing, and batch-to-continuous manufacturing
+- Major Contenders have shortcomings in certain areas of the manufacturing value chain; the prevalent approach to address smart manufacturing use cases is by harnessing
+cross-industry intellectual property, talent, and partnerships
+- They have substantiated their position within the mid-tier segment of clients by pursuing active client management and ramping up/down resources commensurate to the ask of buyers
+
+### Aspirants
+Atos, HARMAN DTS, and NNIT
+- When it comes to their services portfolio, Aspirants have restricted their focus to specific areas in the life sciences manufacturing value chain, with limited digital service capabilities
+- They have a limited partnership ecosystem and place more focus on leveraging horizontal capabilities to cater to the needs of life sciences enterprises rather than developing
+domain-specific services through CoEs and strategic alliances
+- They have a dedicated focus on capturing the market share in the small and midsize buyer segment
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+3
+
+--- end page 3
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Everest Group PEAK Matrix®
+Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023 |
+Deloitte is positioned as a Leader
+
+Everest Group Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 20231,2,3
+
+![Figure 1: Everest Group Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023. The image is a two-dimensional matrix. The X-axis is titled "Vision & capability - Measures ability to deliver services successfully". The Y-axis is titled "Market impact - Measures impact created in the market". Companies are positioned in the matrix, divided into four quadrants: Aspirants, Major Contenders, and Leaders. Deloitte is positioned as a Leader. Other companies include Accenture, TCS, HCLTech, Cognizant, Capgemini, Wipro, NTT DATA, LTIMindtree, Innova Solutions, Tech Mahindra, Birlasoft, NNIT, HARMAN DTS, and Atos.](image_reference)
+
+*   Leaders
+*   Major Contenders
+*   Aspirants
+
+1 Assessments for Atos, Capgemini, Infosys, and NTT DATA exclude provider inputs and are based on Everest Group's proprietary Transaction Intelligence (TI) database, provider public disclosures, and Everest Group's interactions with enterprise buyers
+2 Assessment for Birlasoft, HARMAN DTS, and NNIT is based on partial primary inputs (briefings only)
+3 The assessment of Atos is completed prior to its acquisition by Eviden
+Confidentiality: Everest Group takes its confidentiality pledge very seriously. Any information we collect that is contract specific will only be presented back to the industry in an aggregated fashion
+Source: Everest Group (2023)
+
+--- end page 4
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 1 of 6)
+
+### Overview
+
+#### Company mission
+Deloitte's Life Sciences Smart Manufacturing practice partners with life sciences enterprises in reimagining and
+reconfiguring their value chains to ensure the reliable and efficient supply of affordable and accessible therapies
+and medical products to the end customers, resulting in enhanced well-being of patients. It supports clients in
+their digital transformation journey and pushes life sciences manufacturing into the next generation of digital
+evolution. This is achieved through substantial investments in expanding global smart manufacturing
+capabilities, fostering robust partnerships, developing proprietary IP-based assets, leveraging smart factory
+technology, and nurturing talent.
+
+#### Overview of the client base
+Among its diverse customer base, Deloitte's life science smart manufacturing practice engages with the top 10
+largest global pharmaceutical enterprises, top 10 largest BioTech enterprises, 9 out of the top 10 medical device
+enterprises, and 18 out of the 21 largest life sciences enterprises.
+
+#### Revenue Breakdown
+
+[Table 1: Revenue by line of business¹]
+|                       | Low (<10%) | Medium (10-35%) | High (>35%) |
+| :-------------------- | :---------- | :--------------- | :----------- |
+| Biopharmaceuticals    |             |                  | ■            |
+| Medical devices       |             |                  |              |
+| Others                | ■           |                  |              |
+
+[Table 2: Revenue by buyer size¹]
+|                                            | Low (<20%) | Medium (20-40%) | High (>40%) |
+| :----------------------------------------- | :---------- | :--------------- | :----------- |
+| Small (annual revenue <US$1 billion)        |             | ■                |              |
+| Midsize (annual revenue US$1-10 billion)    | ■           |                  |              |
+| Large (annual revenue >US$10 billion)       |             |                  | ■            |
+
+[Table 3: Revenue by geography¹]
+|                       | Low (<15%) | Medium (15-40%) | High (>40%) |
+| :-------------------- | :---------- | :--------------- | :----------- |
+| North America         |             |                  | ■            |
+| Rest of Europe        |             |                  |              |
+| United Kingdom        |             | ■                |              |
+| Asia Pacific          |             |                  |              |
+| Middle East & Africa  | ■           |                  |              |
+| South America         |             |                  | ■            |
+
+¹ All the revenue components add up to a total of 100%
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+5
+
+--- end page 5
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 2 of 6)
+
+### Case studies
+
+#### Case study 1
+Transformation of Quality Management System (QMS) for a global
+pharmaceutical manufacturer
+
+Business challenge
+The client faced challenges with high costs of quality and the regulatory risks in managing compliance. It had
+basic and disconnected platforms for quality processes, and lacked integration and traceability. To address
+this, the client identified a QMS platform and set ambitious timelines to deploy multiple Quality System
+Elements (QSEs) across more than five sites.
+
+Solution
+Deloitte assisted the client in their QMS transformation journey by assessing the current state of QSEs and
+conducting a process design exercise. Additionally, it built solutions tailored to client requirements, including
+customization with next-generation functionalities, performed detailed validation and system testing, and
+supported the change management process through a training program strategy.
+
+Impact
+- Assisted the clients in realizing benefits worth US$30 million by eliminating non-value-added work, thereby
+reducing overhead expenses
+- Deployed more than 10 QSEs in 14 months across five manufacturing sites
+- Ensured QMS process adoption for more than 700 employees globally
+
+#### Case study 2
+NOT EXHAUSTIVE
+Developing a global security standard for the manufacturing sites of a global
+pharmaceutical enterprise
+
+Business challenge
+The client recognized the necessity of developing and implementing a global security standard across all
+manufacturing and R&D sites to enhance the security maturity of Internet of Things (IoT), Industrial Control
+Systems (ICS), and Operational Technology (OT).
+
+Solution
+Deloitte implemented a tailored OT cybersecurity framework, conducted detailed site security assessments,
+and deployed monitoring solutions to enhance OT asset security monitoring, visibility, and situational
+awareness. It also deployed threat intelligence and analytics for detecting OT cybersecurity threats and
+established standards, communication plans, playbooks, and workflows for incident response and recovery.
+
+Impact
+- Deployed 14 OT security controls
+- Remediated 42 manufacturing and R&D sites
+- Identified and monitored more than 30,000 OT digital assets
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+6
+
+--- end page 6
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 3 of 6)
+
+### Offerings
+
+NOT EXHAUSTIVE
+
+Proprietary smart manufacturing solutions – such as IP, platforms, accelerators, and tools (representative list)
+
+[Table 1: Proprietary smart manufacturing solutions]
+| Solution | Details |
+| --- | --- |
+| Supply chain control tower platform | It is an end-to-end platform solution that assists clients by providing prescriptive insights, monitoring transaction-level data, and offering analytical capabilities across the manufacturing and supply chain processes. |
+| CentralSight | It has the capabilities to effectively visualize a multi-tier deep supplier ecosystem, helping enterprises identify and address the associated risks within the ecosystem in a timely manner. |
+| Smart factory capability compass | It is an application that assists clients in assessing the current manufacturing maturity and readiness of their sites for smart factory investments and initiatives. |
+| CognitiveSpark for manufacturing | It is a cloud-based, Al-powered solution designed to assist biopharma and MedTech manufacturers with insights that help optimize manufacturing processes and improve product quality. |
+| Turnkey IoT | It is a suite of pre-configured solution accelerators tailored to high-potential manufacturing use cases. |
+| Managed Extended Detection and Response (MXDR) | It is a SaaS-based, modular cybersecurity solution designed to protect enterprises from internal and external cyber threats. |
+| Greenlight | This is a decarbonization solution designed to achieve net-zero emissions. It includes a package of dashboard modules that can ingest Green House Gas (GHG) emissions and reduce project data, enabling clients to visualize and analyze their aggregate carbon footprint. |
+| IDEA | It is an loT-based application that helps clients manage real-time energy consumption from different sources, combining the loT approach with traditional Energy Management Systems (EMS). |
+| Digital IoT | It is a preconfigured Siemens MindSphere application that offers a cloud-based, open loT operating system connecting products, plants, systems, and machines. This application unifies data from Digital Product Lifecycle Management (DPLM), Data Acquisition and Management System (DAMS), Digital Manufacturing Execution System (DMES), and IoT systems onto an integrated dashboard, thereby enabling actionable insights. |
+
+Everest Group Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+7
+
+--- end page 7
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 4 of 6)
+
+### Offerings
+
+[Table 1: Proprietary smart manufacturing solutions – such as IP, platforms, accelerators, and tools (representative list)]
+| Solution | Details |
+| ----------- | ----------- |
+| SupplyHorizon | It enables enterprises to proactively identify and mitigate supply chain issues. It leverages internal and external data, risk profiling, mitigation planning, persona-based visualizations, and Al to enable a visibility of multi-tier supply networks and sense any upcoming risks in order to mitigate disruptions. |
+| Smart manufacturing platform | This is a platform solution that enables the comprehensive view of manufacturing operations across the organization with connected data from disparate systems to create dynamic data visualizations that provide useful insights and recommended actions. It assists in predictive analytics, quality analytics, planning and management, shop floor tracking and serialization, etc. |
+| Supplier 360 | It is an end-to-end management solution that improves supplier relationships by consolidating data from various disparate sources to generate actionable insights on supplier performance, connecting stakeholders, and more. |
+
+NOT EXHAUSTIVE
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+
+--- end page 8
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 5 of 6)
+
+### Recent developments
+
+[Table 1: Key events - related to smart manufacturing services (representative list)]
+| Event name | Type of event | Year | Details |
+|---|---|---|---|
+| Industrial data fabric | Alliance | 2023 | Forged a multi-party partnership with AWS, HighByte, and Element to help manufacturers connect, structure, and manage industrial data at scale through an open industrial data framework; supports Deloitte's smart manufacturing platform and services, offering data analytics, predictive insights, and faster time-to-value for manufacturers |
+| Nubik | Acquisition | 2022 | Acquired to strengthen its presence and leadership in the Salesforce practice and firm up its relationships and offerings for mid-market clients; it will assist clients with advanced solutions in manufacturing and distribution |
+| OCT Emissions Solutions | Acquisition | 2022 | Acquired to assist clients with an end-to-end offering across the climate change and decarbonization life cycle. It provides solutions for hydrogen, carbon sequestration and offsets, and carbon dioxide cleanup |
+| AE Cloud Consultant | Acquisition | 2022 | Acquired to deploy front-end and back-end solutions for order management, production management, supply chain management, warehouse and fulfillment, procurement, etc., for enterprises |
+| Smart factories spread across global locations | Investment | 2022 | The smart factories that are spread across the globe serve as an ecosystem of smart manufacturing capabilities built on advanced technologies such as loT, cybersecurity, and digital twins; also acts as a platform that brings together solution providers, technology innovators, and academic researchers to drive innovation |
+| Check Point | Alliance | 2021 | Alliance with Check Point, a leading provider of cybersecurity solutions, to assist Deloitte in strengthening Industry 4.0 technologies by securing the enterprise manufacturing and supply chain infrastructure |
+| Syncronic | Acquisition | 2021 | Acquired to enhance its supply chain practice in the Nordics region |
+| aeCyberSolutions | Acquisition | 2021 | Acquired to strengthen its cybersecurity offerings |
+| Digital Immunity | Alliance | 2020 | Alliance with Digital Immunity to leverage Deloitte's multiple OT lab environments, such as the Smart Factory in Wichita, to accelerate deployment testing by utilizing configuration and deployment guidelines from the lab environment |
+| Nozomi | Alliance | 2020 | Alliance with Nozomi Networks to deliver IT, OT, and IoT security services in the EMEA region. This collaboration aims to assist enterprises in enhancing their threat detection capabilities and implementing effective cyber risk solutions |
+| Beelogix | Acquisition | 2019 | Acquired to expand its capabilities and leadership in SAP digital supply chain solution |
+
+--- end page 9
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Deloitte profile (page 6 of 6)
+
+### Everest Group assessment – Leader
+
+Measure of capability: Low High
+
+## Market impact
+| Market   | Portfolio  | Value     | Overall   | Vision and | Scope of    | Vision & capability | Innovation and  | Delivery   | Overall  |
+| :------- | :--------- | :-------- | :-------- | :--------- | :---------- | :------------------ | :-------------- | :--------- | :------- |
+| adoption | mix        | delivered |           | strategy   | services offered |                     | investments   | footprint |          |
+
+### Strengths
+* Deloitte has made substantial investments in developing manufacturing solutions
+throughout the life sciences value chain, focusing on futuristic domain use cases such as
+cell and gene therapy manufacturing and sustainable manufacturing. It is further
+reinforced by its dedicated investments in building the Wichita smart factory, which
+strengthens its capabilities in loT, cybersecurity, digital twins, robotics, etc.
+* While clients highlight the premium pricing points, they acknowledge the innovative
+commercial constructs offered by Deloitte and perceive the dollar value per service
+provided to be better compared to peers
+* Clients view Deloitte as a reliable strategic partner as it addresses both the existing and
+emerging business problems, even by engaging third-party providers if necessary
+* Clients appreciate the high quality of the talent deployed and the strong technical domain
+knowledge they possess
+
+### Limitations
+* Although clients appreciate the technical and domain expertise of the talent deployed,
+they expect better attrition management to ensure seamless project delivery
+* Deloitte's tendency to consistently agree with clients without conducting thorough
+evaluations can reveal a lack of critical assessment and hinder their ability to make
+decisions that align with the enterprise's expertise and best interests
+* While clients appreciate Deloitte's strategic inputs, they look for better transparency and
+alignment with the enterprise stakeholders
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+10
+
+--- end page 10
+
+## Appendix
+
+Everest Group®
+11
+
+--- end page 11
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Everest Group PEAK Matrix® is a proprietary framework for assessment of
+market impact and vision & capability
+
+Everest Group PEAK Matrix
+
+![Figure 1: A matrix is shown with 'Market impact' as the vertical axis and 'Vision & capability' as the horizontal axis.  The matrix is divided into four quadrants: Aspirants, Major Contenders, and Leaders. The arrow demonstrates the movement towards the top right of the matrix, indicating growth in both vision and market impact.](image.png)
+
+--- end page 12
+
+# Life Sciences Smart Manufacturing Services PEAK Matrix® Assessment 2023
+
+## Services PEAK Matrix® evaluation dimensions
+
+Measures impact created in the market –
+captured through three subdimensions
+
+Market adoption
+Number of clients, revenue base,
+YoY growth, and deal value/volume
+
+Portfolio mix
+Diversity of client/revenue base across
+geographies and type of engagements
+
+Value delivered
+Value delivered to the client based
+on customer feedback and
+transformational impact
+
+Market impact
+Aspirants
+Major Contenders
+Leaders
+
+Vision & capability
+Measures ability to deliver services successfully.
+This is captured through four subdimensions
+
+![Figure 1: The PEAK Matrix graph is plotted with "Market Impact" on the vertical axis and "Vision & Capability" on the horizontal axis. The graph is divided into three zones from left to right: Aspirants, Major Contenders, and Leaders. An arrow spans diagonally across the chart.](image_reference)
+
+Vision and strategy
+Vision for the client and itself; future
+roadmap and strategy
+
+Scope of services offered
+Depth and breadth of services portfolio
+across service subsegments/processes
+
+Innovation and investments
+Innovation and investment in the enabling
+areas, e.g., technology IP, industry/domain
+knowledge, innovative commercial
+constructs, alliances, M&A, etc.
+
+Delivery footprint
+Delivery footprint and global sourcing mix
+
+Everest Group® Proprietary © 2023, Everest Global, Inc. | this document has been licensed to Deloitte
+13
+
+--- end page 13
+
+## FAQs
+
+Does the PEAK Matrix® assessment incorporate any subjective criteria?
+Everest Group's PEAK Matrix assessment takes an unbiased and fact-based approach that leverages provider / technology vendor RFIs and Everest Group's proprietary databases containing providers' deals
+and operational capability information. In addition, we validate/fine-tune these results based on our market experience, buyer interaction, and provider/vendor briefings.
+
+Is being a Major Contender or Aspirant on the PEAK Matrix, an unfavorable outcome?
+No. The PEAK Matrix highlights and positions only the best-in-class providers / technology vendors in a particular space. There are a number of providers from the broader universe that are assessed and do
+not make it to the PEAK Matrix at all. Therefore, being represented on the PEAK Matrix is itself a favorable recognition.
+
+What other aspects of the PEAK Matrix assessment are relevant to buyers and providers other than the PEAK Matrix positioning?
+A PEAK Matrix positioning is only one aspect of Everest Group's overall assessment. In addition to assigning a Leader, Major Contender, or Aspirant label, Everest Group highlights the distinctive capabilities
+and unique attributes of all the providers assessed on the PEAK Matrix. The detailed metric-level assessment and associated commentary are helpful for buyers in selecting providers/vendors for their specific
+requirements. They also help providers/vendors demonstrate their strengths in specific areas.
+
+What are the incentives for buyers and providers to participate/provide input to PEAK Matrix research?
+* Enterprise participants receive summary of key findings from the PEAK Matrix assessment
+* For providers
+    - The RFI process is a vital way to help us keep current on capabilities; it forms the basis for our database – without participation, it is difficult to effectively match capabilities to buyer inquiries
+    - In addition, it helps the provider/vendor organization gain brand visibility through being in included in our research reports
+
+What is the process for a provider / technology vendor to leverage its PEAK Matrix positioning?
+* Providers/vendors can use their PEAK Matrix positioning or Star Performer rating in multiple ways including:
+    - Issue a press release declaring positioning; see our [citation policies](citation policies)
+    - Purchase a customized PEAK Matrix profile for circulation with clients, prospects, etc. The package includes the profile as well as quotes from Everest Group analysts, which can be used in PR
+    - Use PEAK Matrix badges for branding across communications (e-mail signatures, marketing brochures, credential packs, client presentations, etc.)
+* The provider must obtain the requisite licensing and distribution rights for the above activities through an agreement with Everest Group; please contact your CD or [contact us](contact us)
+
+Does the PEAK Matrix evaluation criteria change over a period of time?
+PEAK Matrix assessments are designed to serve enterprises' current and future needs. Given the dynamic nature of the global services market and rampant disruption, the assessment criteria
+are realigned as and when needed to reflect the current market reality and to serve enterprises' future expectations.
+
+--- end page 14
+
+## Everest Group®
+With you on the journey
+
+Everest Group is a leading research firm helping business leaders make confident decisions. We guide clients through
+today's market challenges and strengthen their strategies by applying contextualized problem-solving to their unique
+situations. This drives maximized operational and financial performance and transformative experiences. Our deep
+expertise and tenacious research focused on technology, business processes, and engineering through the lenses of
+talent, sustainability, and sourcing delivers precise and action-oriented guidance. Find further details and in-depth content
+at www.everestgrp.com.
+
+### Stay connected
+
+Dallas (Headquarters)
+[email protected]
++1-214-451-3000
+
+Bangalore
+[email protected]
++91-80-61463500
+
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+[email protected]
++91-124-496-1000
+
+London
+[email protected]
++44-207-129-1318
+
+Toronto
+[email protected]
++1-214-451-3000
+
+Website
+everestgrp.com
+
+Social Media
+* @EverestGroup
+* in @Everest Group
+* + @Everest Group
+* @Everest Group
+
+Blog
+everestgrp.com/blog
+
+This document is for informational purposes only, and it is being provided
+"as is" and "as available" without any warranty of any kind, including any
+warranties of completeness, adequacy, or fitness for a particular purpose.
+Everest Group is not a legal or investment adviser; the contents of this
+document should not be construed as legal, tax, or investment advice.
+This document should not be used as a substitute for consultation with
+professional advisors, and Everest Group disclaims liability for any
+actions or decisions not to act that are taken as a result of any material
+in this publication.
+
+NOTICE AND DISCLAIMERS
+IMPORTANT INFORMATION. PLEASE REVIEW THIS NOTICE CAREFULLY AND IN ITS ENTIRETY.
+THROUGH YOUR ACCESS, YOU AGREE TO EVEREST GROUP'S TERMS OF USE.
+
+Everest Group's Terms of Use, available at www.everestgrp.com/terms-of-use/, is hereby incorporated by
+reference as if fully reproduced herein. Parts of these terms are pasted below for convenience; please refer
+to the link above for the full version of the Terms of Use.
+
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+provides is an offer to sell or a solicitation of an offer to purchase any securities or instruments from any entity.
+Nothing from Everest Group may be used or relied upon in evaluating the merits of any investment. Do not base
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+
+Products and/or Services represent research opinions or viewpoints, not representations or statements of fact.
+Accessing, using, or receiving a grant of access to an Everest Group Product and/or Service does not constitute
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+(2) enter into a particular transaction. Nothing from Everest Group will be relied upon or interpreted as a promise
+or representation as to past, present, or future performance of a business or a market. The information contained
+in any Everest Group Product and/or Service is as of the date prepared, and Everest Group has no duty or
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+other way, including, without limitation, participating in Everest Group research activities.
+
+--- end page 15

data/pdfs/2023-conocophillips-aim-presentation.pdf

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data/pdfs/XC9500_CPLD_Family.pdf

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data/pdfs/deloitte-tech-risk-sector-banking.pdf

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data/pdfs/dttl-tax-technology-report-2023.pdf

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+size 2733823

data/pdfs/gx-iif-open-data.pdf

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data/pdfs/life-sciences-smart-manufacturing-services-peak-matrix-assessment-2023.pdf

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data/storage_metadata/processed_docstore_storage.json

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+size 966216

requirements.txt

@@ -1,6 +1,2 @@
-faicons
 shiny
-shinywidgets
-plotly
-pandas
-ridgeplot
+llama-index-core

shared.py

@@ -1,6 +0,0 @@
-from pathlib import Path
-
-import pandas as pd
-
-app_dir = Path(__file__).parent
-tips = pd.read_csv(app_dir / "tips.csv")

structure_parsers.py

@@ -0,0 +1,179 @@
+from collections import deque
+from pathlib import Path
+import logging
+from typing import Iterator, Self
+import re
+
+from llama_index.core.schema import BaseNode
+
+logger = logging.getLogger(__name__)
+
+DOCUMENT_NODE_NUMBER: int = -1
+
+
+class TreeNode:
+    def __init__(self, name: str, number: int | None = None):
+        self.name = name
+        self.number = number
+        self.children: list[Self] = []
+        self.parent: Self | None = None
+
+    def add_child(self, child: Self) -> None:
+        self.children.append(child)
+
+    def set_parent(self, parent: Self) -> None:
+        if self.parent is not None:
+            raise ValueError("parent has already been set")
+        else:
+            self.parent = parent
+
+    def remove_parent(self) -> None:
+        self.parent = None
+
+    def __str__(self, level: int = 0) -> str:
+        ret = "  " * level + self.name
+        if self.number is not None:
+            ret += f" [{self.number}]"
+        ret += "\n"
+        for child in self.children:
+            ret += child.__str__(level + 1)
+        return ret
+
+    def bfs(self) -> Iterator[Self]:
+        """Perform Breadth-First traversal of the tree."""
+        queue = deque([self])
+        while queue:
+            node = queue.popleft()
+            yield node
+            queue.extend(node.children)
+
+    def remove_child(self, child: Self) -> bool:
+        if child in self.children:
+            child.remove_parent()
+            self.children.remove(child)
+            return True
+        return False
+
+    def __iter__(self):
+        return self.bfs()
+
+
+def parse_landscape_structure(document: BaseNode) -> TreeNode:
+    page_pattern = re.compile(r"^-\s*Page\s+(\d+)\s*:\s*(.+)$")
+    header_pattern = re.compile(r"^(#+)\s+(.+)$")
+    format = document.metadata.get("format", "")
+    if format != "landscape":
+        raise ValueError(f"Unsupported format {format}")
+    number_pages = document.metadata.get("nb_pages", None)
+    structure = document.metadata.get("structure", "")
+    filename = document.metadata.get("filename", "")
+    assert number_pages and structure and filename
+    lines = structure.splitlines()
+    filestem = Path(filename).stem
+    root = TreeNode(name=filestem, number=DOCUMENT_NODE_NUMBER)
+    stack = [(root, 0)]  # (node, level) pairs
+    abstract_node_number = DOCUMENT_NODE_NUMBER - 1
+    processed_page_numbers = set()
+    for line in lines:
+        line = line.strip()
+        if not line:
+            continue
+        # Check if it's a header
+        header_match = header_pattern.match(line)
+        if header_match:
+            level = len(header_match.group(1))
+            title = header_match.group(2).strip()
+            new_node = TreeNode(name=title, number=abstract_node_number)
+            abstract_node_number -= 1
+            # Adjust stack for header level
+            while stack and stack[-1][1] >= level:
+                stack.pop()
+            if stack:
+                stack[-1][0].add_child(new_node)
+                new_node.set_parent(stack[-1][0])
+            stack.append((new_node, level))
+            continue
+        # Check if it's a page entry
+        page_match = page_pattern.match(line)
+        if page_match:
+            page_num = int(page_match.group(1))
+            title = page_match.group(2).strip()
+            if page_num in processed_page_numbers:
+                logger.warning(f"Filename {filename} Page {page_num} already processed. Skipping {title}.")
+            elif page_num > number_pages:
+                logger.warning(
+                    f"Filename {filename} Page number {page_num} is greater than the number of pages in the document. Skipping {title}."
+                )
+            else:
+                processed_page_numbers.add(page_num)
+                new_node = TreeNode(name=title, number=page_num)
+                # Add to last header in stack
+                if stack:
+                    stack[-1][0].add_child(new_node)
+                    new_node.set_parent(stack[-1][0])
+
+    leftout_page_numbers = set(range(1, number_pages + 1)) - processed_page_numbers
+    if leftout_page_numbers:
+        logger.warning(f"Filename {filename} Page numbers {leftout_page_numbers} are not processed.")
+        uncategorized_node = TreeNode(name="Uncategorized", number=abstract_node_number)
+        abstract_node_number -= 1
+        root.add_child(uncategorized_node)
+        uncategorized_node.set_parent(root)
+        for page_num in leftout_page_numbers:
+            new_node = TreeNode(name=f"Page number {page_num}", number=page_num)
+            uncategorized_node.add_child(new_node)
+            new_node.set_parent(uncategorized_node)
+
+    return root
+
+
+def parse_portrait_structure(document: BaseNode) -> TreeNode:
+    header_pattern = re.compile(r"(#+)\s+(.*?)\s+\[line\s+(\d+)\]")
+    format = document.metadata.get("format", "")
+    if format != "portrait":
+        raise ValueError(f"Unsupported format {format}")
+    structure = document.metadata.get("structure", "")
+    filename = document.metadata.get("filename", "")
+    created_toc = document.metadata.get("created_toc", "")
+    assert structure and filename and created_toc
+    lines = structure.splitlines()
+    filestem = Path(filename).stem
+    root = TreeNode(name=filestem, number=DOCUMENT_NODE_NUMBER)
+    stack = [(root, 0)]  # (node, level) pairs
+    processed_line_numbers = list()
+    for line in lines:
+        line = line.strip()
+        if not line:
+            continue
+        # Check if it's a header
+        header_match = header_pattern.match(line)
+        if header_match:
+            level = len(header_match.group(1))
+            title = header_match.group(2).strip()
+            line_number = int(header_match.group(3))
+            processed_line_numbers.append(line_number)
+            new_node = TreeNode(name=title, number=line_number)
+            # Adjust stack for header level
+            while stack and stack[-1][1] >= level:
+                stack.pop()
+            if stack:
+                stack[-1][0].add_child(new_node)
+                new_node.set_parent(stack[-1][0])
+            stack.append((new_node, level))
+            continue
+
+    assert processed_line_numbers[0] == 0 and all(
+        processed_line_numbers[i] <= processed_line_numbers[i + 1] for i in range(len(processed_line_numbers) - 1)
+    )
+    return root
+
+
+def parse_structure(document: BaseNode) -> TreeNode:
+    format = document.metadata.get("format", "")
+    match format:
+        case "landscape":
+            return parse_landscape_structure(document)
+        case "portrait":
+            return parse_portrait_structure(document)
+        case _:
+            raise ValueError(f"Unsupported format {format}")

styles.css

@@ -1,12 +0,0 @@
-:root {
-  --bslib-sidebar-main-bg: #f8f8f8;
-}
-
-.popover {
-  --bs-popover-header-bg: #222;
-  --bs-popover-header-color: #fff;
-}
-
-.popover .btn-close {
-  filter: var(--bs-btn-close-white-filter);
-}

tips.csv

@@ -1,245 +0,0 @@
-total_bill,tip,sex,smoker,day,time,size
-16.99,1.01,Female,No,Sun,Dinner,2
-10.34,1.66,Male,No,Sun,Dinner,3
-21.01,3.5,Male,No,Sun,Dinner,3
-23.68,3.31,Male,No,Sun,Dinner,2
-24.59,3.61,Female,No,Sun,Dinner,4
-25.29,4.71,Male,No,Sun,Dinner,4
-8.77,2.0,Male,No,Sun,Dinner,2
-26.88,3.12,Male,No,Sun,Dinner,4
-15.04,1.96,Male,No,Sun,Dinner,2
-14.78,3.23,Male,No,Sun,Dinner,2
-10.27,1.71,Male,No,Sun,Dinner,2
-35.26,5.0,Female,No,Sun,Dinner,4
-15.42,1.57,Male,No,Sun,Dinner,2
-18.43,3.0,Male,No,Sun,Dinner,4
-14.83,3.02,Female,No,Sun,Dinner,2
-21.58,3.92,Male,No,Sun,Dinner,2
-10.33,1.67,Female,No,Sun,Dinner,3
-16.29,3.71,Male,No,Sun,Dinner,3
-16.97,3.5,Female,No,Sun,Dinner,3
-20.65,3.35,Male,No,Sat,Dinner,3
-17.92,4.08,Male,No,Sat,Dinner,2
-20.29,2.75,Female,No,Sat,Dinner,2
-15.77,2.23,Female,No,Sat,Dinner,2
-39.42,7.58,Male,No,Sat,Dinner,4
-19.82,3.18,Male,No,Sat,Dinner,2
-17.81,2.34,Male,No,Sat,Dinner,4
-13.37,2.0,Male,No,Sat,Dinner,2
-12.69,2.0,Male,No,Sat,Dinner,2
-21.7,4.3,Male,No,Sat,Dinner,2
-19.65,3.0,Female,No,Sat,Dinner,2
-9.55,1.45,Male,No,Sat,Dinner,2
-18.35,2.5,Male,No,Sat,Dinner,4
-15.06,3.0,Female,No,Sat,Dinner,2
-20.69,2.45,Female,No,Sat,Dinner,4
-17.78,3.27,Male,No,Sat,Dinner,2
-24.06,3.6,Male,No,Sat,Dinner,3
-16.31,2.0,Male,No,Sat,Dinner,3
-16.93,3.07,Female,No,Sat,Dinner,3
-18.69,2.31,Male,No,Sat,Dinner,3
-31.27,5.0,Male,No,Sat,Dinner,3
-16.04,2.24,Male,No,Sat,Dinner,3
-17.46,2.54,Male,No,Sun,Dinner,2
-13.94,3.06,Male,No,Sun,Dinner,2
-9.68,1.32,Male,No,Sun,Dinner,2
-30.4,5.6,Male,No,Sun,Dinner,4
-18.29,3.0,Male,No,Sun,Dinner,2
-22.23,5.0,Male,No,Sun,Dinner,2
-32.4,6.0,Male,No,Sun,Dinner,4
-28.55,2.05,Male,No,Sun,Dinner,3
-18.04,3.0,Male,No,Sun,Dinner,2
-12.54,2.5,Male,No,Sun,Dinner,2
-10.29,2.6,Female,No,Sun,Dinner,2
-34.81,5.2,Female,No,Sun,Dinner,4
-9.94,1.56,Male,No,Sun,Dinner,2
-25.56,4.34,Male,No,Sun,Dinner,4
-19.49,3.51,Male,No,Sun,Dinner,2
-38.01,3.0,Male,Yes,Sat,Dinner,4
-26.41,1.5,Female,No,Sat,Dinner,2
-11.24,1.76,Male,Yes,Sat,Dinner,2
-48.27,6.73,Male,No,Sat,Dinner,4
-20.29,3.21,Male,Yes,Sat,Dinner,2
-13.81,2.0,Male,Yes,Sat,Dinner,2
-11.02,1.98,Male,Yes,Sat,Dinner,2
-18.29,3.76,Male,Yes,Sat,Dinner,4
-17.59,2.64,Male,No,Sat,Dinner,3
-20.08,3.15,Male,No,Sat,Dinner,3
-16.45,2.47,Female,No,Sat,Dinner,2
-3.07,1.0,Female,Yes,Sat,Dinner,1
-20.23,2.01,Male,No,Sat,Dinner,2
-15.01,2.09,Male,Yes,Sat,Dinner,2
-12.02,1.97,Male,No,Sat,Dinner,2
-17.07,3.0,Female,No,Sat,Dinner,3
-26.86,3.14,Female,Yes,Sat,Dinner,2
-25.28,5.0,Female,Yes,Sat,Dinner,2
-14.73,2.2,Female,No,Sat,Dinner,2
-10.51,1.25,Male,No,Sat,Dinner,2
-17.92,3.08,Male,Yes,Sat,Dinner,2
-27.2,4.0,Male,No,Thur,Lunch,4
-22.76,3.0,Male,No,Thur,Lunch,2
-17.29,2.71,Male,No,Thur,Lunch,2
-19.44,3.0,Male,Yes,Thur,Lunch,2
-16.66,3.4,Male,No,Thur,Lunch,2
-10.07,1.83,Female,No,Thur,Lunch,1
-32.68,5.0,Male,Yes,Thur,Lunch,2
-15.98,2.03,Male,No,Thur,Lunch,2
-34.83,5.17,Female,No,Thur,Lunch,4
-13.03,2.0,Male,No,Thur,Lunch,2
-18.28,4.0,Male,No,Thur,Lunch,2
-24.71,5.85,Male,No,Thur,Lunch,2
-21.16,3.0,Male,No,Thur,Lunch,2
-28.97,3.0,Male,Yes,Fri,Dinner,2
-22.49,3.5,Male,No,Fri,Dinner,2
-5.75,1.0,Female,Yes,Fri,Dinner,2
-16.32,4.3,Female,Yes,Fri,Dinner,2
-22.75,3.25,Female,No,Fri,Dinner,2
-40.17,4.73,Male,Yes,Fri,Dinner,4
-27.28,4.0,Male,Yes,Fri,Dinner,2
-12.03,1.5,Male,Yes,Fri,Dinner,2
-21.01,3.0,Male,Yes,Fri,Dinner,2
-12.46,1.5,Male,No,Fri,Dinner,2
-11.35,2.5,Female,Yes,Fri,Dinner,2
-15.38,3.0,Female,Yes,Fri,Dinner,2
-44.3,2.5,Female,Yes,Sat,Dinner,3
-22.42,3.48,Female,Yes,Sat,Dinner,2
-20.92,4.08,Female,No,Sat,Dinner,2
-15.36,1.64,Male,Yes,Sat,Dinner,2
-20.49,4.06,Male,Yes,Sat,Dinner,2
-25.21,4.29,Male,Yes,Sat,Dinner,2
-18.24,3.76,Male,No,Sat,Dinner,2
-14.31,4.0,Female,Yes,Sat,Dinner,2
-14.0,3.0,Male,No,Sat,Dinner,2
-7.25,1.0,Female,No,Sat,Dinner,1
-38.07,4.0,Male,No,Sun,Dinner,3
-23.95,2.55,Male,No,Sun,Dinner,2
-25.71,4.0,Female,No,Sun,Dinner,3
-17.31,3.5,Female,No,Sun,Dinner,2
-29.93,5.07,Male,No,Sun,Dinner,4
-10.65,1.5,Female,No,Thur,Lunch,2
-12.43,1.8,Female,No,Thur,Lunch,2
-24.08,2.92,Female,No,Thur,Lunch,4
-11.69,2.31,Male,No,Thur,Lunch,2
-13.42,1.68,Female,No,Thur,Lunch,2
-14.26,2.5,Male,No,Thur,Lunch,2
-15.95,2.0,Male,No,Thur,Lunch,2
-12.48,2.52,Female,No,Thur,Lunch,2
-29.8,4.2,Female,No,Thur,Lunch,6
-8.52,1.48,Male,No,Thur,Lunch,2
-14.52,2.0,Female,No,Thur,Lunch,2
-11.38,2.0,Female,No,Thur,Lunch,2
-22.82,2.18,Male,No,Thur,Lunch,3
-19.08,1.5,Male,No,Thur,Lunch,2
-20.27,2.83,Female,No,Thur,Lunch,2
-11.17,1.5,Female,No,Thur,Lunch,2
-12.26,2.0,Female,No,Thur,Lunch,2
-18.26,3.25,Female,No,Thur,Lunch,2
-8.51,1.25,Female,No,Thur,Lunch,2
-10.33,2.0,Female,No,Thur,Lunch,2
-14.15,2.0,Female,No,Thur,Lunch,2
-16.0,2.0,Male,Yes,Thur,Lunch,2
-13.16,2.75,Female,No,Thur,Lunch,2
-17.47,3.5,Female,No,Thur,Lunch,2
-34.3,6.7,Male,No,Thur,Lunch,6
-41.19,5.0,Male,No,Thur,Lunch,5
-27.05,5.0,Female,No,Thur,Lunch,6
-16.43,2.3,Female,No,Thur,Lunch,2
-8.35,1.5,Female,No,Thur,Lunch,2
-18.64,1.36,Female,No,Thur,Lunch,3
-11.87,1.63,Female,No,Thur,Lunch,2
-9.78,1.73,Male,No,Thur,Lunch,2
-7.51,2.0,Male,No,Thur,Lunch,2
-14.07,2.5,Male,No,Sun,Dinner,2
-13.13,2.0,Male,No,Sun,Dinner,2
-17.26,2.74,Male,No,Sun,Dinner,3
-24.55,2.0,Male,No,Sun,Dinner,4
-19.77,2.0,Male,No,Sun,Dinner,4
-29.85,5.14,Female,No,Sun,Dinner,5
-48.17,5.0,Male,No,Sun,Dinner,6
-25.0,3.75,Female,No,Sun,Dinner,4
-13.39,2.61,Female,No,Sun,Dinner,2
-16.49,2.0,Male,No,Sun,Dinner,4
-21.5,3.5,Male,No,Sun,Dinner,4
-12.66,2.5,Male,No,Sun,Dinner,2
-16.21,2.0,Female,No,Sun,Dinner,3
-13.81,2.0,Male,No,Sun,Dinner,2
-17.51,3.0,Female,Yes,Sun,Dinner,2
-24.52,3.48,Male,No,Sun,Dinner,3
-20.76,2.24,Male,No,Sun,Dinner,2
-31.71,4.5,Male,No,Sun,Dinner,4
-10.59,1.61,Female,Yes,Sat,Dinner,2
-10.63,2.0,Female,Yes,Sat,Dinner,2
-50.81,10.0,Male,Yes,Sat,Dinner,3
-15.81,3.16,Male,Yes,Sat,Dinner,2
-7.25,5.15,Male,Yes,Sun,Dinner,2
-31.85,3.18,Male,Yes,Sun,Dinner,2
-16.82,4.0,Male,Yes,Sun,Dinner,2
-32.9,3.11,Male,Yes,Sun,Dinner,2
-17.89,2.0,Male,Yes,Sun,Dinner,2
-14.48,2.0,Male,Yes,Sun,Dinner,2
-9.6,4.0,Female,Yes,Sun,Dinner,2
-34.63,3.55,Male,Yes,Sun,Dinner,2
-34.65,3.68,Male,Yes,Sun,Dinner,4
-23.33,5.65,Male,Yes,Sun,Dinner,2
-45.35,3.5,Male,Yes,Sun,Dinner,3
-23.17,6.5,Male,Yes,Sun,Dinner,4
-40.55,3.0,Male,Yes,Sun,Dinner,2
-20.69,5.0,Male,No,Sun,Dinner,5
-20.9,3.5,Female,Yes,Sun,Dinner,3
-30.46,2.0,Male,Yes,Sun,Dinner,5
-18.15,3.5,Female,Yes,Sun,Dinner,3
-23.1,4.0,Male,Yes,Sun,Dinner,3
-15.69,1.5,Male,Yes,Sun,Dinner,2
-19.81,4.19,Female,Yes,Thur,Lunch,2
-28.44,2.56,Male,Yes,Thur,Lunch,2
-15.48,2.02,Male,Yes,Thur,Lunch,2
-16.58,4.0,Male,Yes,Thur,Lunch,2
-7.56,1.44,Male,No,Thur,Lunch,2
-10.34,2.0,Male,Yes,Thur,Lunch,2
-43.11,5.0,Female,Yes,Thur,Lunch,4
-13.0,2.0,Female,Yes,Thur,Lunch,2
-13.51,2.0,Male,Yes,Thur,Lunch,2
-18.71,4.0,Male,Yes,Thur,Lunch,3
-12.74,2.01,Female,Yes,Thur,Lunch,2
-13.0,2.0,Female,Yes,Thur,Lunch,2
-16.4,2.5,Female,Yes,Thur,Lunch,2
-20.53,4.0,Male,Yes,Thur,Lunch,4
-16.47,3.23,Female,Yes,Thur,Lunch,3
-26.59,3.41,Male,Yes,Sat,Dinner,3
-38.73,3.0,Male,Yes,Sat,Dinner,4
-24.27,2.03,Male,Yes,Sat,Dinner,2
-12.76,2.23,Female,Yes,Sat,Dinner,2
-30.06,2.0,Male,Yes,Sat,Dinner,3
-25.89,5.16,Male,Yes,Sat,Dinner,4
-48.33,9.0,Male,No,Sat,Dinner,4
-13.27,2.5,Female,Yes,Sat,Dinner,2
-28.17,6.5,Female,Yes,Sat,Dinner,3
-12.9,1.1,Female,Yes,Sat,Dinner,2
-28.15,3.0,Male,Yes,Sat,Dinner,5
-11.59,1.5,Male,Yes,Sat,Dinner,2
-7.74,1.44,Male,Yes,Sat,Dinner,2
-30.14,3.09,Female,Yes,Sat,Dinner,4
-12.16,2.2,Male,Yes,Fri,Lunch,2
-13.42,3.48,Female,Yes,Fri,Lunch,2
-8.58,1.92,Male,Yes,Fri,Lunch,1
-15.98,3.0,Female,No,Fri,Lunch,3
-13.42,1.58,Male,Yes,Fri,Lunch,2
-16.27,2.5,Female,Yes,Fri,Lunch,2
-10.09,2.0,Female,Yes,Fri,Lunch,2
-20.45,3.0,Male,No,Sat,Dinner,4
-13.28,2.72,Male,No,Sat,Dinner,2
-22.12,2.88,Female,Yes,Sat,Dinner,2
-24.01,2.0,Male,Yes,Sat,Dinner,4
-15.69,3.0,Male,Yes,Sat,Dinner,3
-11.61,3.39,Male,No,Sat,Dinner,2
-10.77,1.47,Male,No,Sat,Dinner,2
-15.53,3.0,Male,Yes,Sat,Dinner,2
-10.07,1.25,Male,No,Sat,Dinner,2
-12.6,1.0,Male,Yes,Sat,Dinner,2
-32.83,1.17,Male,Yes,Sat,Dinner,2
-35.83,4.67,Female,No,Sat,Dinner,3
-29.03,5.92,Male,No,Sat,Dinner,3
-27.18,2.0,Female,Yes,Sat,Dinner,2
-22.67,2.0,Male,Yes,Sat,Dinner,2
-17.82,1.75,Male,No,Sat,Dinner,2
-18.78,3.0,Female,No,Thur,Dinner,2