University of Southern California Center for Systems and Software Engineering Next Generation Estimation Methods and Management Metrics: Working Group Outbrief Jo Ann Lane October 29, 2008

University of Southern California Center for Systems and Software Engineering Attendees Winsor Brown, CSSE Karl Brunson, Lockheed Sue Koolmanojwong, CSSE JoAnn Lane, CSSE Qi Li, CSSE Lindsay McDonald, BAE Ramin Moazei, CSSE Chris Miller Warren Reid Arlene Ross, r2Estimation Frank Sisti, Aerospace Peter Suk, Boeing Ye Yang, ISCAS

University of Southern California Center for Systems and Software Engineering Workshop Format WEDNESDAY AFTERNOON 1:10 – 1:40Identify top priority areas for ICM measurement 1:40 – 3:00Identify desired outputs for each focus area 3:00 – 3:30Break 3:30 – 5:00Defined decision/information needs for ICM phases Homework:Identify measures to support information needs THURSDAY MORNING 8:00 – 9:30 Integrate results for outbriefs

University of Southern California Center for Systems and Software Engineering Candidate Estimation and Measurement Challenges for Next-Generation Processes Emergent requirements –Example: Virtual global collaboration support systems –Need to manage early concurrent engineering Rapid change –In competitive threats, technology, organizations, environment Net-centric systems of systems –Incomplete visibility and control of elements Model-driven, service-oriented, Brownfield systems –New phenomenology, counting rules Always-on, never-fail systems –Need to balance agility and discipline

University of Southern California Center for Systems and Software Engineering Candidate Estimation and Measurement Challenges (continued) DoD acquisition changes Competitive prototyping Hardware, software and systems engineering integration Human factors, software and systems engineering integration Complex systems Process changes (new activities, less/more emphasis on traditional activities, etc.) that impact current estimation methods –Historical data –Engineering judgment –Parametric model size drivers and cost factors What is most important to measure/monitor for program success in next generation processes

University of Southern California Center for Systems and Software Engineering Results Captured general philosophy for defining measures based on –Practical Software Measurement Guidance (see backup) –ISO (Systems and software engineering measurement process standard) –Measurement analysis in Capability Maturity Model Integrated (CMMI) –Goal/Question/Metric (GQM) –Try to keep guidance domain independent Developed list of Decision/Information Needs for each phase of ICM –Exploration: 28  Development: 8 –Valuation: 15  Operations: 8 –Foundations: 14 Had team members identify measures for each need (as part of homework)

University of Southern California Center for Systems and Software Engineering 15 July 2008©USC-CSSE7 The Incremental Commitment Life Cycle Process: Overview Stage I: DefinitionStage II: Development and Operations Anchor Point Milestones Synchronize, stabilize concurrency via FEDs Risk patterns determine life cycle process

University of Southern California Center for Systems and Software Engineering Longer Term Goal Incorporate general measurement guidance in current ICM draft Collect homework inputs and integrate/refine identified measures Follow up with an invited set of measurement experts to review and critique measures Incorporate comments and integrate into the ICM guidebook

University of Southern California Center for Systems and Software Engineering Backup Charts 15 July 2008©USC-CSSE9

University of Southern California Center for Systems and Software Engineering PSM Information Model Level of information –Information product –Indicator –Derived measure –Base measures –Attributes Information categories –Schedule and progress –Resources and costs –Product size and stability –Product quality –Process performance –Technology effectiveness –Customer satisfaction ©USC-CSSE July 2008