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Assessing Transition of Security Operations in Afghanistan. Progress Report 4 March 2010. Agenda. Problem Statement Methodology System Design Update Values and Metrics Update Preliminary Results Friction Points Earned Value Management. Problem Statement.
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Assessing Transition of SecurityOperations in Afghanistan Progress Report 4 March 2010
Agenda • Problem Statement • Methodology • System Design Update • Values and Metrics Update • Preliminary Results • Friction Points • Earned Value Management
Problem Statement • The goal of the research is to develop a value model that assesses the transition of security lead from the International Security Assistance Force (ISAF) and US Forces Afghanistan (USFOR-A) to the Afghani government and Afghanistan National Security Forces (ANSF) • Deputy Director, Force Integration and Training (CJ7) / CSTC-A defined five lines of operation (LOOs) that support the goal of transferring security operations • Accelerate ANSF growth • Achieve security for the Afghan population • Marginalize malign actors • Achieve legitimate, responsive, and accountable governance • Facilitate community development • Develop metrics and an accompanying decision support tool to measure progress against the five LOOs • Stakeholders • Force Integration and Training cell of NTM-A/CSTC-A (sponsor) • NTM-A/CSTC-A • Coalition military leadership • U.S. government leadership
Methodology Project group organized into two subgroups • Values and Metrics • Research values and metrics • “Requirements” to win a counter-insurgency conflict • Assessments of ANSF, security, Afghani government, and community • Develop value model with sponsor • System Design • Development of user interface, input forms, storage, usable output • Integrate values, metrics, and value model from other team into the system
Technical Approach – System Design System Input: the quantitative portion of the value model in a standardized survey format, completed by military units System Processing and Storage: completed survey templates are configuration controlled and ingested into data storage. User querying capabilities allow the retrieval of data (by unit and/or AOR and/or date range) to research trends Analysis Output: Condensed and easily understood presentation for decision makers 5
Concept of Operation • Surveys from 5 main military regions • CJ7 processes surveys and requests status report CJ7 Processes Surveys Requests Status Report Military Regions
System Design Update • Past Week Progress • Finalize Functional and Non-Functional Requirements (Data, Maintenance) • Data Compiler Prototype • Finalize Concept of Operation • Way Ahead • Refine interface and status report requirements • Expand Compiler Capacity
Technical Approach – Value Model Qualitative Value Model: the identification of an objective hierarchy relating fundamental and means objectives Quantitative Value Model: the articulation of the decision maker’s preferences towards the attributes, and the means of measuring each attribute V(x) = ∑wivi(xi) where wi = weight of attribute i vi = value of attribute i at score xi 13
Values and Metrics Update • Past Week Progress • Refined value structure • Removed overlapping parameters • Removed or modified parameters with problematic metrics • Sent to sponsor for feedback • Researched range of variation • Near Term Goals • Complete range of variation analysis • Elicit weights and utility funtions • Personal meeting unlikely • Elicit by phone / email
Value Function Status • 54 values identified • 56 metrics developed • 56 possible ranges of variation determined • Theoretical where data unavailable • Awaiting data or feedback to strengthen • Awaiting partial or complete data for 43 of the identified metrics
Range of Variation (ROV)aka “Range of a value measure” • Definition: “The possible variation of the scores of a value measure” -Gregory S. Parnell • Important precursor to determining DM value (or utility) function *OR681, GMU
Sports Car .7 .3 Performance Reliability .1 .35 .25 .3 Braking Acceleration Handling Top Speed Elicitation of Weights and Utility (1 of 3) • Weight is the relative importance of a value and are elicited from DM; must sum to one at each level under each node • Weight of values under Sports Car must equal 1 • Weight of values under both Performance and Reliability must each equal 1
Elicitation of Weights and Utility(2 of 3) • Several methods to elicit weights • Direct weights • Swing weights • Rank Sum • Utility is the value the DM assigns to a specific point along a range of variation • How much better is a Top Speed of 150 mph than 120 mph? 90 mph? • Often used to assess risk attitude
Weights and Utility Curves(3 of 3) • Elicit utility through lottery or certainty equivalence • Weights and utility can be linear, piecewise, exponential, or an S-curve *OR681, GMU
Preliminary Results • Functioning test system using input forms
Friction Points • No approval from JIEDDO to work with classified material • Portions of data and final project expected to be classified • Can use fabricated data to demonstrate function and sponsor can populate with correct information in secure environment • Distance and interaction of sponsor • No face-to-face meetings possible • Flow of information is sporadic • Use local point of contact for weight elicitation and fabricate unavailable data
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