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Planning under Uncertainty —without Paralysis!

Planning under Uncertainty —without Paralysis!. PAUL K. DAVIS RAND CORPORATION AND PARDEE RAND GRADUATE SCHOOL THE HAGUE DECEMBER, 2008. References. 1994. 2005. 2008. 2008. 2002. Order or download at www.rand.org/pubs. Core Themes. Core Theme: Seeking FAR Strategies.

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Planning under Uncertainty —without Paralysis!

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  1. Planning under Uncertainty —without Paralysis! PAUL K. DAVIS RAND CORPORATION AND PARDEE RAND GRADUATE SCHOOL THE HAGUE DECEMBER, 2008

  2. References 1994 2005 2008 2008 2002 Order or download at www.rand.org/pubs

  3. Core Themes

  4. Core Theme: Seeking FAR Strategies • Flexibility for different missions • Adaptiveness to unexpected circumstances • Robustness in coping with or recovering from adverse shock • Imperfect shorthands: • Planning for adaptiveness • Robust adaptive planning • Planning for agility • …

  5. Uncertainty Sensitive Planning in Brief Characterize no-surprises environment Identify branches and shocks Develop strategy for no-surprises environment Develop strategy to improve odds of desirable future Core strategy Develop contingent strategies Develop capabilities to help with shocks Environment shaping Branches of strategy for what can be anticipated Hedge capabilities for the unexpected

  6. Given Options, Even Simplest Decent Decision Structure is Hard

  7. Given Options To Evaluate, Even the Simplest Decent Decision Structure is Different, and Hard

  8. What Makes It Hard? • What are best and worst plausible cases? • Who does the assessing (perspectives) • Defining option suitably (scale) • “Net assessment” across categories • Linear weighted sums is often wrong • Subjective: risk taking? risk averse? faith-based? • Recommendation: leave net assessment until last, for “tidying up” after decisions are made • “Costs are sometimes uncertain, untrue, or very dependent on scale

  9. Portfolio Analysis • Many objectives; several time scales • Many instruments • Many options • Portfolio options correspond to strategies and attend to objectives in different ways: • Different relative emphasis, risk management, costs,… Very different from seeing “strategy” as way to win two simultaneous wars in particular scenarios

  10. Methods and Tools

  11. Capabilities-Based Planning Capabilities-based planning (CPB) is planning, under uncertainty, to provide capabilities suitable for a wide range of modern-day challenges and circumstances while working within an economic framework that necessitates choice • Poor implementations: • Avoid named threats • Find shortfalls and solutions; defer economics • Pretend any cut anywhere raises risk • Avoid choice; ask for blank check

  12. Assessing Capabilities in a Scenario Space (Assumptions Space) Objectives and strategies Pol-MilContext A particular case (scenario) Forces Model assumptions Force capabilities Type environment

  13. Exploratory Analysis Across Scenario Space • Analogy: a aircraft designer’s “envelopes” • Airplane will behave well within envelope • If problem can be modeled, run cases throughout scenario space • Result: characterize when results are good, bad, or indifferent Designers aren’t paralyzed: this is fun But poor defense analysts may complain bitterly

  14. Simplify after Scenario-Space Analysis • Observe that options fare differently by “region” of scenario space • Define representative cases for each region • Set of such cases is a spanning set • Use these as community-wide test set • “Spanning sets” are quite different from usual official scenario sets

  15. Official Spanning Sets Should Be Early Decision Output

  16. Examples of Applications • 1997 QDR • Late-1990s Strategic Discussion of Transformation • 2005-2007 Acquisition work • 2007 Strategy work

  17. A Then-New Way of Viewing Defense Strategy (for 1997 QDR) Strategic Portfolio of Defense Investments For Environment Shaping (by theater) (Shape) For Strategic Adaptiveness For Responding to Diverse Contingencies (Prepare) (Respond) Threat SSCs Allies, bases MTWs • Overseas presence • MOOTW activities • Alliances and coalitions • Economic activities • Military infrastructure • Military security assistance • Sizable forces-in-being to back up commitments Budget, priorities, costs Tech. (Informed by scenario- space analysis)

  18. Four Options To Stimulate Transformation(presented to senior leaders, 1997-2000) • Evolve current forces • Selected, experimental transformation • Some smaller units (e.g., brigades), fast-deploying, precision weapons, exploit information technology • Across-board transformation • Skip-a-generation reengineering

  19. Evaluation of Strategic Options, 1997 (for 2010)

  20. Evaluation of Strategic Options, 1997 (for 2010)

  21. Notional Depiction for Ballistic Missile Defense, Circa 2005

  22. Global Strike Options (2008-2008)Spanning Set • Attack of Mobile Missiles Country X and US are in crisis; country X generates nuclear-armed mobile missiles; US wants to destroy them • Terrorist Leaders • High-ranking terrorists will be meeting briefly at a house in known city, but location won’t be known until shortly before • WMD FacilitiesCountry Y is developing nuclear weapon capability; US decides to impede development by destroying facilities Not included: cyberwar, psyops…

  23. The Set Stresses Capabilities Systematically Stress depends on parameter values!

  24. Multiresolution Parameterization:Essential, Not Mere Nice-to-Have Others: number of attacks, number of targets, time between attacks,regional and terrain issues,…

  25. An Experiment in Massive Scenario Generation in Terrorism Analysis Davis, Bankes, and Egner, 2007 (?)

  26. Massive Scenario Generation (2006-2007) CARs and a model being exercised 2, 4 Scenarios,statistics, Other data Black-Boxmodel External outputs Post processing External inputs 1 Requests 3

  27. Visualizing Results from n-Space Is Hard 3 dim. 2 dim.

  28. A First “Dot Plot” from Exploratory Analysis in n-Dimensions: Incomprehensible One dot per scenario. Color , not Y axis, indicates outcome. Ten thousand scenarios chosen by sampling scenario space for other parameters, and for random events Cluttered, inconsistent landscape.

  29. After Filtering, Lumping, Data Mining, Rotating,… Results Take Shape

  30. Surprisingly, a Crude Motivated Meta Model Is Rather Good Full Model Motivated Metamodel Agreement depends on small non-zero values of some C’s

  31. Conclusions • Core principles are obvious but profound • More often ignored than followed • High leverage is in first steps • Many techniques exist • Capabilities-based planning (RAND style) • Portfolio analysis • Massive scenario generation for exploratory analysis • Robust adaptive planning (related) • … (by lots of names)

  32. Enemies of Sound Planning • Simple-minded priority lists and extreme first-things first attitudes • False choices, such as choose among modernization, maintaining global missions, or controlling budget • Idealized, orthogonal options • Real options are not just cowardly compromises • Waving flag of risk to protect status quo • Easy money: budget-imposed choice is often the friend of reform

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