1. University of Southern California Center for Systems and Software Engineering Cost Modeling for Commercial Organizations Anandi Hira, USC Graduate Student COCOMO Forum Thursday, November 3, 2011

2. University of Southern California Center for Systems and Software Engineering Outline Cost modeling challenges for large commercial organizations Example of sizing challenges: Fidelity Candidate requirements-level approach: Cockburn –IBM data –eServices data –WellPoint data Next steps November 4, 2011©USC-CSSE2

3. University of Southern California Center for Systems and Software Engineering Cost Modeling Challenges for Large Commercial Organizations Numerous potential cost drivers Diversity of application combinations Reuse, NDI, and interoperability uncertainties Diversity of collected application data Need for early estimates –Sizing based on variable-level requirements –With variable requirements-to-code expansion factors ©USC-CSSE3November 4, 2011

4. University of Southern California Center for Systems and Software Engineering Potential Cost Driver Metadata: WellPoint Business Area (Health Solutions, Mandates) Sponsoring Division (Finance, Human Resources) Operational Capability (Care Mgmt., Claims Mgmt.) Business Capability (Marketing, Enrollment) Need for New Features (Data, Business Processes) Primary Benefits (Higher Retention, Cost Avoidance) Systems Impacted (eBusiness Portals, Call Centers) States Impacted (California, New Hampshire) Business Impact (Actuarial, Legal) Estimated Size ( $5M) ©USC-CSSE4November 4, 2011

5. University of Southern California Center for Systems and Software Engineering 5©USC-CSSE Sizing Challenge: Fidelity November 4, 2011

6. University of Southern California Center for Systems and Software Engineering Reasons for Size Growth Sized just for U.S. part of company –Actually a global company with many different data items, required reports, and laws to comply with –WellPoint similar with many state data items, reports, laws Sized as a computer program and not a system product –Missed product functions such as data validation, user assistance, and required security and privacy –Missed system functions such as interoperability with non-US systems and maintenance and diagnostic functions –Brooks’ Mythical Man Month cites a factor of 3 each to go from a computer program to a program product and then a program system product, or an overall factor of 9 –Early WellPoint estimates may have similar size growth ©USC-CSSE6 November 4, 2011

7. University of Southern California Center for Systems and Software Engineering Outline Cost modeling challenges for large commercial organizations Example of sizing challenges: Fidelity Candidate requirements-level approach: Cockburn –IBM data –eServices data –WellPoint data Next steps ©USC-CSSE7November 4, 2011

8. University of Southern California Center for Systems and Software Engineering Requirement Levels Metaphor: Cockburn 8©USC-CSSENovember 4, 2011

9. University of Southern California Center for Systems and Software Engineering IBM-UK Expansion Factor Experience Business Objectives5Cloud Business Events/Subsystems35 Kite Use Cases/Components250Sea level Main Steps/Main Operations2000 Fish Alt. Steps/Detailed Operations15,000Clam SLOC*1,000K – 1,500KLava (Hopkins & Jenkins, Eating the IT Elephant, 2008) *(70 – 100 SLOC/Detailed Operation) 9©USC-CSSENovember 4, 2011

10. University of Southern California Center for Systems and Software Engineering 25 USC CSCI 577a,b projects –Real-client e-services applications –Similarities and Differences compared to industry projects –Complete information on all requirement levels 10©USC-CSSE Requirement Levels Ratio Study Ali Malik, 2009 November 4, 2011

11. University of Southern California Center for Systems and Software Engineering 11©USC-CSSE Statistic Elaboration Factors Cloud to Kite Kite to Sea Level Sea Level to Fish Fish to Clam Average2.460.897.0666.91 Median2.750.896.5740.72 Standard Deviation 0.940.552.9764.46 Summary of Elaboration Results November 4, 2011

12. University of Southern California Center for Systems and Software Engineering Outline Cost modeling challenges for large commercial organizations Example of sizing challenges: Fidelity Candidate requirements-level approach: Cockburn –IBM data –eServices data –WellPoint data Next steps ©USC-CSSE12November 4, 2011

13. University of Southern California Center for Systems and Software Engineering 3 New Projects with Requirements Levels, Metadata Business Area (Health Solutions, Mandates) Sponsoring Division (Finance, Human Resources) Operational Capability (Care Mgmt., Claims Mgmt.) Business Capability (Marketing, Enrollment) Need for New Features (Data, Business Processes) Primary Benefits (Higher Retention, Cost Avoidance) Systems Impacted (eBusiness Portals, Call Centers) States Impacted (California, New Hampshire) Business Impact (Actuarial, Legal) Estimated Size ( $5M) 4 Finished Projects with Effort Data, Some Requirements Levels, TBD Metadata ©USC-CSSE 13 WellPoint Data to Date November 4, 2011

14. University of Southern California Center for Systems and Software Engineering WellPoint Requirements Level Data IB M WP P# 1 WP P#2 WP P#3 WP FP#1 WP FP#2 WP FP #3 WP FP #4 Cloud to Kite 7.02.031.04.512.3753.625317.3 Kite to Sea Level 7.12.51.0972.61.175TBD0.97TBD 14©USC-CSSENovember 4, 2011

15. University of Southern California Center for Systems and Software Engineering Finished Projects Data and Observations FP #1FP #2FP #3FP #4 Total Hours 51,5841,7240.53,935.57,050.5 Hours/Clo ud 2,149.31,077.53135.711,007.2 Hours/Kite173.68297.2545.23658.269 Hours/Se a Level 147.81TBD46.851TBD 15©USC-CSSENovember 4, 2011

16. University of Southern California Center for Systems and Software Engineering Outline Cost modeling challenges for large commercial organizations Example of sizing challenges: Fidelity Candidate requirements-level approach: Cockburn –IBM data –eServices data –WellPoint data Next steps ©USC-CSSE16November 4, 2011

17. University of Southern California Center for Systems and Software Engineering Next Steps ©USC-CSSE17 Discuss project data similarities, anomalies –Identify additional sources of explanatory data Obtain additional project data where possible –Function point counts –Requirements level clarifications –Partial metadata Obtain data from additional projects November 4, 2011