Simulation Toolset for Experimental Environment Research STEER

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Simulation Toolset for Experimental Environment
Research (STEER)

• PI CDR Tom Jones
• May 2008

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CapabilitiesEnhanced, Integrated HR
Decision-making
MPTE HQ
Richer description of total force and work
requirements
Policy, process and resource allocation analysis
Integrated career-span assessments
Total Force (AC, RC, Civ, Cont)
Enterprises
Readiness
Units
Career planning
Job negotiation
Optimal person-team-organization matching
Unit level decision making
Unit planning
Right PersonRight Place/WorkRight TeamRight
Cost
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Technical ObjectiveIT Framework Simulation
Environment
STEER
Corporate Data Inputs
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Modeling Simulation Approach

• STEER modeling and simulation approach
• Agent-Based Modeling and Simulation (ABMS)
• Allows dynamic individual interactions between
  agents
• Agent-based Computational Economics (ACE)
• A bottom-up economic modeling approach which uses
  individual behavioral characteristics to
  instantiate the agents
• Dynamic individual agent interactions will modify
  the individual and group economic behavior

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Technical Approach / RD

• Experimental design for the Behavioral Economics
  experiments
• Structural IT approach
• Services Oriented Architecture (SOA)
• SOA data coordination with BUPERS CIO, FUTURE
  and PISCES teams
• Data Standardization
• Data Element Dictionary

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Capabilities SOAEnhanced, Integrated HR
Decision-making
MPTE HQ
Richer description of total force and work
requirements
Policy, process and resource allocation analysis
Integrated career-span assessments
Total Force (AC, RC, Civ, Cont)
Enterprises
Readiness
Units
Career planning
Job negotiation
Optimal person-team-organization matching
Unit level decision making
Unit planning
Right PersonRight Place/WorkRight TeamRight
Cost
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Solutions Offered by STEER

• Visibility of the cost drivers for readiness
• (Understand the tradeoffs) Visibility of
  tradeoffs between readiness, cost, and risk
• (Forecast) Improve understanding how a policy
  changes impact individual, unit and enterprise
  readiness, cost and risk
• Testing the principles of decentralization by
  pushing resource allocation decisions down to the
  most efficient level of decision making
• Increased understanding of labor substitution and
  the incentives needed for resource efficiency
• Enhanced DSTs for unit personnel negotiation to
  allow optimized resource allocation decisions

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Risks, Barriers and Mitigation Plans

• Building a quantitative measure of readiness - a
  key metric for the proposed effort
• Working with FFC / N1 to define an individuals
  contribution to readiness
• Creating flexibility within the model to allow
  changes to the model if/when future readiness
  metrics change
• Identifying costs incentives at the individual
  unit level
• Developing alternative approaches to individual
  cost to be evaluated in the simulation
  environment
• The design complexity of Agent-Based Simulation

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Anticipated Payoff

• Cost avoidance by correcting poor or asymmetric
  policy adoption or implementation procedures
• Cost savings with respect to resource allocation
• Situational awareness across integrated
  functionalities (e.g., optimization and tradeoff
  analyses across functions) and in aggregation
  across the enterprise

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STEER Project Team
NPRST Team CDR Tom Jones, PI Tanja Blackstone,
PhD Randy Brou, PhD Rodney Myers Kimberly
Crayton Ricky Hall Jerry Crabb LT Don Britton
Customer Team ONR- Resource Sponsor CNP N10
Functional Sponsor
Proposed Contractor Team IcoSystems
Serco OptTek WBB
Proposed Academic Team Appalachian State
University George Mason University University of
Northern Alabama Michigan State
University University of Memphis University of
Colorado Boulder University of Colorado
Denver University of Missouri - St. Louis
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Questions?
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