RESUMEN

One software product company found that its project duration estimation accuracy followed a lognormal distribution and the uncertainty range was nearly identical at all stages in the project life cycle. This conflicts with popular interpretation of the "cone of uncertainty" concept.

Previous approaches to understanding software dynamics and costs include building systems dynamics models or detailed cost equations. Although they can be enlightening, these models are complex, they focus on cost rather than value, and they typically don't consider uncertainty. The model features a set OT functions and parameters that can be applied in a spreadsheet. One can obtain data curves in many ways, including using industry data, historical metrics, or from the team's subjective assessments. Other models use net present value to focus on value and uncertainty. The author has developed a relatively simple project dynamics model to use in conjunction with market sensitivity and economic analysis to help optimize profitability. The time required for application testing depends on both testing new features and regression-testing existing features. Authors have assumed that developed material has created value; those who make business decisions are interested in understanding how to translate that into value captured.