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
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Winsor Brown, CSSE
Karl Brunson, Lockheed
Sue Koolmanojwong, CSSE
JoAnn Lane, CSSE
Qi Li, CSSE
Lindsay McDonald, BAE
Ramin Moazei, CSSE
Chris Miller
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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 – 1:40 Identify top priority areas for ICM
measurement
1:40 – 3:00 Identify desired outputs for each focus
area
3:00 – 3:30 Break
3:30 – 5:00 Defined 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 15939 (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
The Incremental Commitment Life Cycle Process: Overview
Stage I: Definition
Stage II: Development and Operations
Anchor Point
Milestones
Synchronize, stabilize concurrency via FEDs
Risk patterns
determine life
cycle process
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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
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University of Southern California
Center for Systems and Software Engineering
PSM Information Model
• Level of information
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• Information categories
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Information product
Indicator
Derived measure
Base measures
Attributes
15 July 2008
©USC-CSSE
Schedule and progress
Resources and costs
Product size and stability
Product quality
Process performance
Technology effectiveness
Customer satisfaction
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