BUSINESS WARGAMING for MANPOWER POLICY ANALYSIS

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BUSINESS WARGAMING forMANPOWER POLICY ANALYSIS

• What is Business Wargaming?
• What is the Underlying Technology?
• NPS-Initiated Projects in Business Wargaming
• USMC Business Wargame

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WHAT IS BUSINESS WARGAMING?

• Management counterpart of combat simulation
• Market (or economy) based vs force-based
• Virtual environment
• Testbed for experimenting with alternative
  management (vice battlefield) decision-making
  policies under pre-specified scenarios
• Business wargames can take the following forms
• - Standalone computer games (e.g., SimCity)
• - Multi-player war room simulations (as in
  combat world)
• - Multi-player distributed (Web-based)
  simulations

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Department of Defense War Gaming Environment
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Live Agent
Live Agent
Live Agent
Live Agent
DoD Agencies, Private Sector Firms
Live Agent
Live Agent
Synthetic
Goods Services
Stock
Labor
Bond
Currency
Economy
Consumers and Workforce
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WHO USES BUSINESS WARGAMING?

• Private Sector
• - McKinsey Company 60 of all US companies
  use some
• form of simulation
• - IBM Strategeer their PC business
• - PriceWaterhouseCoopers, and Booz, Allen,
  Hamilton
• SimCity type systems for specific
  industries
• DoD
• - Information warfare terrorist scenarios (IDA)
• - Army (Firm Handshake) Manpower
• - Navy (ACE) Acquisition

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BENEFITS of BUSINESS WARGAMING

• Insight decision tradeoffs policy
• Experiential Learning
• Team Building
• Leadership Development
• Risk-free Strategy Testing
• Training
• (Note Agent-based simulations are not
  predictive models.)

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SIMULATION TECHNOLOGY

• Agent-Based (Adaptive) Simulation
• - Initiated at Santa Fe Institute
• - Artificial Economies (Brookings Institute)
• - Based on Genetic Algorithms
• - Bottom Up vs Top Down emergent behavior vs
  discrete event
• 
  simulation
• SEAS (Synthetic Environments for Analysis and
  Simulations)
• - State of the Art System Developed at Purdue
  University,
• - Concurrent Multi-player System LAN version
  and Web version
• - Used in DoD and Private Sector Games (e.g.,
  IDA)

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AGENTS and ATTRIBUTES

• Human players govern the actions of agencies and
  firms by making specific decisions from a menu of
  possible actions as the simulation proceeds.
• Software agents are used to simulate the market
  activities within the simulation.
• There may be 1000s of agents within a
  simulation, each of which is programmed with
  rules of engagement.
• Each agent may represent a cohort of such agents
  in the real world, for example a PERSON agent
  who is 17-years old may represent 2,000 17-year
  olds in the marketplace.
• Each agent has a set of attributes, the values of
  which change over time as the agents evolve
  with successive iterations of the simulation.

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RULES OF ENGAGEMENT
INFLUENCE
Human Capital Labor Market
Recruit Incentives
Sell Services
Sell Services
Pay Salary
Recruiting Training Personnel Mgmt Force
Mgmt Acquisition
High Tech Financial Construction Manufacturing Col
lege University
Industry
ATTRITION
RESERVE
INFLUENCE
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HOW THE SIMULATION WORKS

• Teams are presented with decision options they
  can make at various stages within the simulation.
  
• As the game proceeds, each team has a set of
  performance metrics dials that shows them how
  they are doing with respect to each metric. Each
  dial will look something like
• Current Target
  
  
  
  
• 
  Historical
• RETENTION RATE
• Additionally, each team will have an overall
  performance metric gauge by which they
  determine how well the team is performing.

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PLAYER REQUIREMENTS

• For each of the Teams, the following information
  is necessary to set up
• the simulation
• Identification of Policy Decisions Each Team Can
  Control
• E.g., Recruiting may want to increase recruiting
  incentives Force Management (Retention) may want
  to increase re-enlistment bonuses Training may
  want to increase of trainers and facilities
• Identification of Readiness Metrics
• E.g., Recruiting readiness may be
  AvgCostPerContract, Force management readiness
  may be Avg_LOS, Training readiness may be
  _Seats_Filled
• Identification of Overall Performance Metric for
  each Team
• E.g., Recruiting may be OfMission Force
  Management may be MOSFill

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SEAS_MP Game Board
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SEAS Architecture
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SEAS Agent Architecture
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SEAS Web Architecture
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OBJECTIVES OF SIMMARINECORPS

• What we want the participants Aha! experiences
  to be after the game
• INTRACONNECTIVITY Identify issues of
  connectivity within the various USMC manpower
  areas for more detailed analysis. (e.g.,
  recruiting and training)
• INTERCONNECTIVITY Identify issues of
  connectivity between USMC manpower and external
  environments (e.g., the economy, Congress) for
  further investigation.
• RESOURCES-TO-READINESS Identify implications of
  resources-to-readiness pipeline for more
  detailed analysis.
• VALUE OF BUSINESS WARGAMING Recognize the
  value of agent-based simulation as a contingency
  analysis tool for different applications.

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SIMMARINECORPS GAME STRUCURE
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SIMMARINECORPS Scenarios and Moves

• Focus on End Strength
• Two scenarios encompassing 6 (- 1) years each
• Six moves per scenario encompassing one year
  each
• Scenario One Declining Economy (rising energy
  prices, inflation and unemployment)
• Scenario Two Robust Economy (low inflation,
  full employment, high demand for tech skills)
• Questions Did End strength grow, decline, stay
  the same? How much did it cost? Did we grow a
  junior or senior force?

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REFERENCES

• John L. Casti. Would-Be Worlds How Simulation
  Is Changing the Frontiers of Science. 1996.
• A. Chaturvedi and S. Mehta. Synthetic
  Environments for Analysis and Simulations (SEAS).
  1998.
• J. Epstein and R. Axtell. Growing Artificial
  Societies Social Sciences from the Bottom Up.
  MIT Press. 1996.
• J. Holland. Hidden Order How Adaptation Builds
  Complexity. Addison-Wesley, 1995.
• www.thinkingtools.com
• www.santafe.edu (Santa Fe Institute)

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BUSINESS SIMULATION IN PRESS

• Business Week 21, 1998
• Forbes 7 April 1997
• Business Week, 17 March 1997
• Wall Street Journal, 28 March 1997
• Fortune 26 May 1997
• Fast Company, June-July 1996