Practical Software Estimation Measurement

Losses Loom Larger Than Gains

Anyone who has gambled (and lost) knows the sting of losing.  In 1979, Daniel Kahneman and Amos Tversky, pioneers in the field of behavioral economics, theorized that losses loom larger than gains; essentially, a person who loses $100 loses more satisfaction that what is gained by someone who wins $100. Behavioral economics weaves psychology and economics together to map the irrational man, the foil of economics' rational man. 

How can I leverage this theory for software development?

According to the QSM IT Software Almanac (2006), worst in class projects took 5.6 times as long to complete and used roughly 15 times as much effort with a median team size of 17, and were less likely to track defects. 

One way you can leverage your worst in class projects would be to use them as history files in SLIM-Estimate, which would adjust PI, defect tuning, etc., to match how you have developed software in the past. Don Beckett recently discussed how to tune effort for best in class analysis and design.

Another way to leverage your worst in class projects would be to build a "project graveyard," that is, a database of your organization's worst projects, and load it into SLIM-Metrics. In SLIM-Metrics, you can analyze duration, peak staff, average staff, and defects to view your own organization's weaknesses. Depending on how well documented your SLIM-DataManager database is, you could analyze some of the custom metrics that ship with SLIM-Metrics, such as reviewing who the project was built for (customer metric) and complexity.

By analyzing your own "project graveyard," you can replicate the QSM Software Almanac's analysis of worst in class projects for your own organization and improve the outcome of future projects.

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