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Enterprise DFA™

Enterprise DFA™. Application of Dynamic Financial Analysis in the Oil Industry. Discussion Outline. Background Oil Company Imperatives Problem Diagnosis The Application of DFA The Opportunities for Actuaries. Background. Stochastic Financial Modeling Not New

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Enterprise DFA™

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

  2. Discussion Outline • Background • Oil Company Imperatives • Problem Diagnosis • The Application of DFA • The Opportunities for Actuaries

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

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

  5. Background • New Focus in Investment Management • Earnings Growth Was Theme • Results Now Handicapped on Risk • New Pressure From the Market • Earnings Predictability • Managing Analysts’ Expectations • Managements Search for Tools to Understand / Manage Earnings Volatility

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

  7. Oil Company Imperatives • Project Undertaken to Evaluate Earnings and Business Risks. • Objectives Included: • Understand Earnings Forecast Failures • Communicate Risks to Board • Change Market’s Perception of Company Risk

  8. Problem Diagnosis - Forecast Failures • EPS 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. Problem Diagnosis - Board • Investment Project vs. Enterprise Focused Analyses - Complex Issues • High Detail - Low Information • Lack of Context and Comparability • No Enterprise Level Conclusions

  10. Problem Diagnosis - Market • Market Perceived Company High Risk v. Competitors • Reinforced by Earnings “Surprises” • Low Appreciation for Risk Hedging Programs • Resulted in Lower than Market P/E

  11. Application of DFA • Project 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

  12. DFA Methodology • Enterprise Model • Common Environmental Assumptions • Economic - Common for All SBU’s • Non Management Controlled Issues • Corporate Financial Leverage • Strategy Based Management Assumptions • Business Unit Based • Probability of Strategy Implementation

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

  14. Common Environmental Assumptions DFA - Methodology • Economic - Non Management Controlled • Energy Price / Demand Drivers • Weather • Economic Growth • Supply Conditions • Capital Markets Conditions • Corporate Financial Structures • Financial Leverage • Hedging / Market Risk Control

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

  16. Business Strategies DFA - Methodology • Chemicals • Reduce Unit Costs • Redesign Major Processes • Commercialize New Technologies • Coal, Minerals & Power • Increase Facility Utilization • Mine Expansions • Expand Electric Power Business

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

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

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

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

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

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

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

  24. Opportunities for Actuaries • Risk Analyses are Central to Industrial Managers • DFA Type Analysis is High Value Added • Actuaries Must Expand beyond Technicians to become Strategists • If Actuaries Don’t - Others Will

  25. Preliminary DFA Results

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