University of Southern California Center for Systems and Software Engineering ©USC-CSSE1 Ray Madachy USC Center for Systems and Software Engineering 22nd International Forum on COCOMO and Systems/Software Cost Modeling November 1, 2007 Business Valuation with Software Cost Modeling – A Case Study

University of Southern California Center for Systems and Software Engineering ©USC-CSSE2 Introduction A business valuation was undertaken to quantify the intellectual property value of a software product for an acquisition investment analysis –Product is a financial application that supports banks in auditing specialized accounts A parametric cost modeling approach was used to answer the question “How much would it cost to reproduce the software”. –We also performed an organization productivity analysis to crosscheck the evaluation and provide more background for potential investors Multiple independent sizing and estimation models were used

University of Southern California Center for Systems and Software Engineering ©USC-CSSE3 Intellectual Property Valuation Per Reifer’s guidelines in Value-Based Software Engineering [Biffl et al. 2005] –The standard of value was defined as an acquisition value –The chosen valuation approach was a cost approach to predict how much an investor would pay to replace or reproduce the software asset

University of Southern California Center for Systems and Software Engineering ©USC-CSSE4 Cost Modeling Method Cost models can be used to support business investment decisions that don’t involve software development or process improvement per se Best approach to software cost estimation is iteratively using a combination of methods –Used COCOMO in conjunction with function point models The software value estimate was derived by distilling the essential, invariant product characteristics and abstracting out factors unique to the client

University of Southern California Center for Systems and Software Engineering ©USC-CSSE5 Cost Modeling Method (cont.) Used the effort multiplier term in COCOMO to separate out two groups of significant cost factors –1) Core attributes of product functionality. E.g. What would someone have to develop to compete against this product? –2) Organizational differentiators of the client for comparison analysis. E.g. What are the environmental cost factors that indicate unique productivity advantages/disadvantages, quality or risk profiles? Stuck with conservative assumptions at every turn

University of Southern California Center for Systems and Software Engineering ©USC-CSSE6 Software Metrics and Models Data collected consisted of size, cost driver ratings, and effort –ASP and HTML code –Size measured in both source lines of code and function points Function points used for –Backfiring to lines of code –Independent estimates based on function point sizing alone Function point gearing factors from public tables used to convert function points to lines of code as a crosscheck –Produced considerably larger prediction compared to measured logical lines of code COCOMO calibration was performed to validate our estimates and indicate whether a local calibration was needed (only 5% error using default calibration)

University of Southern California Center for Systems and Software Engineering ©USC-CSSE7 Software Metrics and Models (cont.) Independent estimates were done with COCOMO II and the International Software Benchmarking Standards Group (ISBSG) proprietary database of projects by application type –ISBSG predictions are based on simple regression of effort against size in function points –Project data samples in the ISBSG database are Accounting (7), Banking (34) and Financial (9) Final valuation converted software effort to labor costs with variable ranges of compensation for labor grades

University of Southern California Center for Systems and Software Engineering ©USC-CSSE8 Estimates with Ranges

University of Southern California Center for Systems and Software Engineering ©USC-CSSE9 Conclusions The range of different estimates is typical and came from alternative, crosschecking estimation methods with different sources of uncertainty The major sources of uncertainties were due to sizing and the backfiring method, the applicability of domain-specific function point data, and assumed compensation rates –However, the iterative cost modeling approach was able to narrow down the range of estimates and provide a good enough estimate for the client to proceed with –Stuck with conservative assumptions throughout A more comprehensive valuation would consider infrastructure and possible start-up costs depending on the corporate perspective –The actual “cost to reproduce” when considering more aspects would be higher. We strongly recommended further analysis to refine the data and assumptions, and to undertake a more comprehensive business valuation including an income-based approach considering revenues derived from the software

University of Southern California Center for Systems and Software Engineering ©USC-CSSE10 References B. Boehm, C. Abts, W. Brown, S. Chulani, B. Clark, E. Horowitz, R. Madachy, D. Reifer, B. Steece, Software Cost Estimation with COCOMO II, Prentice-Hall, 2000 Biffl S, Aurum A, Boehm B, Erdogmus H, Grünbacher P (eds.), Value-Based Software Engineering, Springer, 2005 QSM, Function Point Programming Languages Table,