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COSYSMO: Parametric Cost Estimation Model for System Engineering

Learn about COSYSMO, a parametric model estimating engineering costs, collaborating with industry and organizations like BAE Systems and NAVAIR. Discover how data drives model evolution and lifecycle.

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COSYSMO: Parametric Cost Estimation Model for System Engineering

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  1. INCOSE CAB Crystal City, VA June 28, 2003 Ricardo Valerdi University of Southern California Center for Software Engineering

  2. Outline • COSYSMO Drivers • Data collection process • Data safeguarding procedures • Schedule & Critical Path

  3. COSYSMO Introduction • Parametric model to estimate system engineering costs • Includes 4 size & 14 cost drivers • Covers full system engineering lifecycle • Developed with USC-CSE Corporate Affiliate and INCOSE participation

  4. Update since Feb briefing in Tampa • Collaboration with: • SECOE/Eric Honour • DAU SoS effort/Rob Flowe & Martha Spurlock • Finalized new driver definitions • # of recursive levels in the design • Technology Maturity • Length of life cycle • Three potential data points • BAE Systems: Mission Solutions/Information Systems Sector (Jim Cain) • Raytheon: Strategic Imaging Systems/Intelligence & Information Systems (John Rieff, Gary Thomas) • NAVAIR: 4.X (Dave Burgess, Donald Allen)

  5. Organizations actively involved with COSYSMO • Commercial Industry (1) • Galorath • Aerospace Industry (5) • BAE, Lockheed Martin, Northrop Grumman, Raytheon, SAIC • Government (2) • NAVAIR, US Army Research Labs • FFRDC’s and Consortia (2) • Aerospace, SPC • Technical Societies (3) • INCOSE, ISPA, PSM HELP! DATA!

  6. Data will drive the Evolution Path & Scope of the Model Operate, Maintain, or Enhance Transition to Operation Replace or Dismantle Oper Test & Eval Conceptualize Develop Global Command and Control System 1. COSYSMO-IP 2. COSYSMO-C4ISR Satellite Ground Station 3. COSYSMO-Machine Joint Strike Fighter 4. COSYSMO-SoS Future Combat Systems

  7. 4 Size Drivers • Number of System Requirements • Number of Major Interfaces • Number of Operational Scenarios • Number of Critical Algorithms • Each weighted by complexity, volatility, and degree of reuse

  8. 14 Cost Drivers Application Factors (8) • Requirements understanding • Architecture complexity • Level of service requirements • Migration complexity • Technology Maturity • Documentation Match to Life Cycle Needs • # and Diversity of Installations/Platforms • # of Recursive Levels in the Design

  9. 14 Cost Drivers (cont.) Team Factors (6) • Stakeholder team cohesion • Personnel/team capability • Personnel experience/continuity • Process maturity • Multisite coordination • Tool support

  10. Data Collection Process • Project & people are identified • Systems engineer • Cost estimator/data base manager • Job/task codes in accounting system are • mapped to COSYSMO • Meta data is collected • System scope • Life cycle • Application domain • Cost drivers are rated • Interaction between SE, Cost, USC • Data is entered into secure repository at USC

  11. Safeguarding Procedures • Data identification • Only affiliate & Dr. Boehm know the OID (XXX) and only affiliate knows PID (YYY) • Data storage • Stand-alone computer at USC with one-way access to the network • In a room with cypher lock & limited access • Data access • Non-disclosure agreements signed • Controlled access to data by researchers (US Citizens only)

  12. How can the CAB help?(Assumptions from the Project Plan) • Identify potential sources for Systems Engineering data • Identify additional commercial INCOSE members for Working Group • Commit resources to assist with: • Driver definition and refinement • Review of outputs • Delphi survey participation • Data from projects • Help in obtaining lead participants from other INCOSE Corporate Members • Establish COSYSMO “owner” within INCOSE • Measurement Working Group willing • Assist USC in finding additional funding support for a COSYSMO dedicated graduate student performer

  13. Parametric Cost Model Critical Path Usual # Months* Critical Path Task 6 Converge on cost drivers, WBS 6 Converge on detailed definitions and rating scales 12 Obtain initial exploratory dataset (5-10 projects) 6 Refine model based on data collection & analysis experience 12+ Obtain IOC calibration dataset (30 projects) 9 Refine IOC model and tool *Can be shortened and selectively overlapped

  14. Calendar of Activities: 2003 USC CSE Annual Research Review (Los Angeles, CA) INCOSE/SCEA Meeting (Chantilly, VA) INCOSE 2003 (Washington, DC) COCOMO Forum (Los Angeles, CA) J F M A M J J A S O N D 2003 2004 Practical Software & Systems Measurement Workshop (Keystone, CO) INCOSE IW (Tampa, FL) Conference on Systems Integration (Hoboken, NJ) Working Group Meeting

  15. Don’t be left out!

  16. Contact Information Ricardo Valerdi rvalerdi@sunset.usc.edu Dr. Barry Boehm boehm@sunset.usc.edu Dr. Elliot Axelband axelband@usc.edu Don Reifer dreifer@earthlink.net Websites http://sunset.usc.edu http://valerdi.com/cosysmo

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