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Explore the application of Dynamic Financial Analysis (DFA) in the oil industry to address forecasting failures, communicate risks to stakeholders, and enhance financial leverage strategies.
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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 • 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
Results Time Background Considered Evidence that Long Term Forecasting Was Not Practical
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
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?”
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
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
Problem Diagnosis - Board • Investment Project vs. Enterprise Focused Analyses - Complex Issues • High Detail - Low Information • Lack of Context and Comparability • No Enterprise Level Conclusions
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
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
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
Management Interventions Enterprise Model Structure DFA - Methodology Exploration / Production Refining / Marketing Economic Environment - Weather - Economic Growth - Supply Constraints - Spot Market Prices Chemicals Coal / Power
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
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
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
Consolidated Forecast x Revenues Earnings per Share Earnings Forecast Failures DFA Results
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
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
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
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
Communicate Risks to Board DFA Results Strategies to Lower Costs Had Small Impact on Risk x Unit Operating Costs 0 Earnings per Share
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
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