- 1 - OMP 1 Enterprise DFA™ Application of Dynamic Financial Analysis in the Oil Industry

- 2 - OMP 2 Discussion Outline FBackground FOil Company Imperatives FProblem Diagnosis FThe Application of DFA FThe Opportunities for Actuaries

- 3 - OMP 3 Background FStochastic Financial Modeling Not New  Significant Academic Interest  Standard in 1970’s Finance Texts  Promoted Heavily by IBM et a FDid Not Gain Wide Acceptance in Practice  Miscast as Predictive Tool  Difficult and Expensive to Implement  Measuring / Understanding Risk Not Valued

- 4 - OMP 4 Background Considered Evidence that Long Term Forecasting Was Not Practical Time Results

- 5 - OMP 5 Background FNew Focus in Investment Management  Earnings Growth Was Theme  Results Now Handicapped on Risk FNew Pressure From the Market  Earnings Predictability  Managing Analysts’ Expectations FManagements Search for Tools to Understand / Manage Earnings Volatility

- 6 - OMP 6 Oil Company Imperatives FLarge Oil Company’s Stock Under Performing  Management Believed It Undervalued  Earnings “Surprises” Had Hurt Values  Perceived as High Risk Company FBoard Losing Confidence in Management  Huge Bets on High Risk Projects  Unsure How Risks Managed  “We Going to Lose the Ranch?”

- 7 - OMP 7 Oil Company Imperatives FProject Undertaken to Evaluate Earnings and Business Risks. FObjectives Included:  Understand Earnings Forecast Failures  Communicate Risks to Board  Change Market’s Perception of Company Risk

- 8 - OMP 8 Problem Diagnosis - Forecast Failures FEPS Forecasts Only Compiled by Corporate  No True Enterprise Model  Roll Up Of Divisional Forecasts  Tied to Business Planning / Challenge Process  Significantly Different Risk Levels / Drivers  Each Used its Own Economic Assumptions  Forecasts were Deterministic Point Estimates

- 9 - OMP 9 Problem Diagnosis - Board FInvestment Project vs. Enterprise Focused Analyses - Complex Issues FHigh Detail - Low Information FLack of Context and Comparability FNo Enterprise Level Conclusions

OMP 10 Problem Diagnosis - Market FMarket Perceived Company High Risk v. Competitors FReinforced by Earnings “Surprises” FLow Appreciation for Risk Hedging Programs FResulted in Lower than Market P/E

OMP 11 Application of DFA FProject to Address Issues Using DFA Type Analysis  Enterprise Level Financial Model Developed - Tied to Corporate Plans  High Impact Variables Identified  Assumption Variability from Key Executives  Disaggregation Analysis  Competitive Analysis  Board Presentations

OMP 12 DFA Methodology FEnterprise Model FCommon Environmental Assumptions  Economic - Common for All SBU’s  Non Management Controlled Issues  Corporate Financial Leverage FStrategy Based Management Assumptions  Business Unit Based  Probability of Strategy Implementation

OMP 13 DFA - Methodology Exploration / Production Coal / Power Refining / Marketing Chemicals Economic Environment - Weather - Economic Growth - Supply Constraints - Spot Market Prices Management Interventions Enterprise Model Structure

OMP 14 DFA - Methodology FEconomic - Non Management Controlled  Energy Price / Demand Drivers »Weather »Economic Growth »Supply Conditions  Capital Markets Conditions FCorporate Financial Structures  Financial Leverage  Hedging / Market Risk Control Common Environmental Assumptions

OMP 15 DFA - Methodology FExploration / Production  Profitability of Existing Production  Success of Exploration Opportunities  Project Selection / New Market Growth FRefining & Marketing  Sales Growth in High Value Fuels  Expansion in High Growth Markets  Shut Refining in Low Growth Markets  Reduce Unit Expenses Business Strategies

OMP 16 DFA - Methodology FChemicals  Reduce Unit Costs  Redesign Major Processes  Commercialize New Technologies FCoal, Minerals & Power  Increase Facility Utilization  Mine Expansions  Expand Electric Power Business Business Strategies

OMP 17 DFA Results Revenues Earnings per Share x Consolidated Forecast Earnings Forecast Failures

OMP 18 DFA Results Revenues Earnings Per Share x Consolidated Forecast 0 } Capital Requirement 100 Earnings Forecast Failures 95% Confidence Level x Expected Value Aggressive vs. Most Likely Assumptions Used in Forecasts

OMP 19 DFA Results Revenues Earnings per Share Expected Value x With Leverage Without Leverage x Communicate Risks to Board Financial Leverage Added High Risk and Small Earnings Gain

OMP 20 DFA Results Revenues Earnings per Share x x x Refining / Marketing Chemicals Exploration/ Production 0 Communicate Risks to Board x Coal Businesses Differ in Risk - Exploration Forecasts Aggressive

OMP 21 DFA Results Revenues net of Hedge Earnings per Share x Base Strategy x Hedge All Price Risk 0 Communicate Risks to Board Energy Market Price Greatest Risk Source

OMP 22 DFA Results Unit Operating Costs Earnings per Share x 0 Communicate Risks to Board Strategies to Lower Costs Had Small Impact on Risk

OMP 23 DFA Results Revenues Earnings % of Revenue 0 Market Perception of Risk Client Had Lower Risk than Most Competitors Client Comp. C Competitor A Competitor B

OMP 24 Opportunities for Actuaries FRisk Analyses are Central to Industrial Managers FDFA Type Analysis is High Value Added FActuaries Must Expand beyond Technicians to become Strategists FIf Actuaries Don’t - Others Will

OMP 25 Preliminary DFA Results