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Decision Analysis and Its Applications to Systems Engineering INCOSE/SCEA November 18, 2009

Navy Aircraft Carrier Gap Analysis Justin Hornback & Robin Smith Decision Analysis and Its Applications to Systems Engineering INCOSE/SCEA November 18, 2009

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Decision Analysis and Its Applications to Systems Engineering INCOSE/SCEA November 18, 2009

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  1. Navy Aircraft Carrier Gap Analysis Justin Hornback & Robin Smith Decision Analysis and Its Applications to Systems Engineering INCOSE/SCEA November 18, 2009

  2. The Naval Aviation Enterprise (NAE) Carrier Readiness Team (CRT)required holistic view for assessing strategic plans for futureaircraft carrier availability • Problem: The NAE CRT required a holistic understanding of the risks associated with the looming aircraft carrier availability gap and how best to handle these risks. • Reduction in number of aircraft carriers from 11 to 10, planned retirement of USS Enterprise 2012 • Demand for aircraft carrier deployment unchanged • Several important questions needed to be addressed: • How does risk impact aircraft carrier operational availability (Ao)? • What are the cost and schedule impacts of risk? • How should mitigation dollars be prioritized against high-impact risks? • Is historical data useful for future planning? • How does one carrier in the enterprise(portfolio) impact the others? • Previous attempts to address this problem were largely qualitative in nature and lacked a rigorous analytical framework and incorporated no uncertainty or risk. • Applied the operational RISC-IQTM methodology to this problem to address these challenges. Constrained Resources and Emphasis on Efficiency Makes Understanding Risks Essential to Carrying Out Strategic Objectives

  3. NAE Risk Methodology Risk ID & Foundational Efforts Aircraft Carrier Operations (Initial Data Gathering & Formulation; Risks Identified from a Variety of Sources) Historical Data Analyses (Data Gathered, Trends & Outliers Analyzed) Definitions Definitions Stakeholder Collaboration Risk Modeling Constraints Constraints Risk Modeling Survey Results Objectives Objectives Assumptions Assumptions Stakeholder Survey (Key Inputs Discussed & Reviewed) DRAFT FINAL Cost Schedule Cost Schedule Risk Mapping Risk Risk A Risk B (Discrete Risks Mapped to Cost Elements & Schedule Tasks)

  4. 600 500 FY08$M 400 300 200 100 0 2009 2010 2011 2012 2013 2014 2015 2016 NAE Risk Methodology (cont’d) Schedule Cost Risk Risk Modeling (Simulations Run to Evaluate Risk Impacts on Cost & Schedule) Translation to Availability Metrics Ao Metrics (Simulation Results Compiled, Aggregate Ao Metrics Calculated) Sensitivity Analyses Risk Modeling Risk Modeling (Simulation Data Analyzed, Excursions Run, “What If” Cases Developed) Cost/ Schedule Drivers Recommendations Strategic Focus Areas: - A, B, C Maintenance Schedules During Months D, E, F - System Dependency G - Bottleneck Point H - Costs of I, J, K - Stakeholder L (Results Compiled & Recommendations Formulated)

  5. Schedules were overlaid upon another to create the “S” curve from the Monte Carlo simulations Likelihood (Percentage) Months achieving desired readiness level (48 max) = • Multiple Scenario generation • Slope of S curve relates the amount of risk associated with a scenario

  6. Client’s first application of this methodology Politically charged environment Potential conflict with previous Congressional Briefings Diverse stakeholders World-wide implications Initial resistance due to client’s unfamiliarity with the process Report Card of performance Client used to stand-alone (i.e., stoplight chart) risk management that did not reveal the range of potential outcomes Optimistic Schedules Complex environment with intricate interdependencies Cyclical critical path Resource constraints, industrial complex Key Challenges

  7. Applying the RISC- IQ methodology supplied the client with information required to make informed decisions • This process was beneficial in that it.. • Quantified the intuition of industry stakeholders • Specified availability of assets • Examined the root cause of schedule divergences • Allowed the client to build confidence in their ‘go forward’ plan • Built a foundation from which further analyses can be conducted • Expansion outside of Aircraft Carriers • Generated a portfolio of risk models • Each risk model represented a unique compilation of data which created… Quantifiable and Defendable Results

  8. Aircraft Carrier Maintenance Stack-Up • September 2009, four carriers in carrier maintenance at Northrop Grumman Shipbuilding, Newport News (NGSB NN) creating work capacity risks across all four carriers. • 36% of aircraft carrier fleet • 2004 CV/CVN Maintenance Availability Schedule projected 1 carrier at NGSB – September 2009 • CVN 65 EDSRA • Risk Analysis of 2004 CV/CVN Maintenance Schedule projects potential of 3 carriers - September 2009 • CVN 65 EDSRA (>90%) • CVN 70 PSA/SRA (50%) • CVN 77 PSA/SRA (80%) • (% likelihood/potential of CVN maintenance event occurring at NGSB NN - September 2009) • CVN 71 RCOH was not projected due to the 2004 scheduled RCOH start date of 11/2009. This date was moved up to 9/2/2009 during CVN 71 RCOH planning in 2007.

  9. Questions? • Justin Hornback hornback_justin@bah.com • Robin Smith smith_robin_k@bah.com

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