Looking Back on Previous Estimation Error as a Method to Improve the Uncertainty Assessment of Benefits and Costs of Software Development Projects

摘要

Knowing the uncertainty of estimates of benefits and costs is useful when planning, budgeting and pricing projects. The traditional method for assessing such uncertainty is based on prediction intervals, e.g., asking for minimum and maximum values believed to be 90% likely to include the actual outcome. Studies report that the traditional method typically results in too narrow intervals and intervals that are too symmetric around the estimated most likely outcome when compared with the actual uncertainty of outcomes. We examine whether an uncertainty assessment method based on looking back on the previous estimation error of similar projects leads to wider and less symmetric prediction intervals. Sixty software professionals, with experience from estimating software project costs and benefits, were randomly divided into a group with a traditional or a group with a looking back-based uncertainty assessment method. We found that those using the looking back-based method had much wider prediction intervals for both costs and benefits. The software professionals of both groups provided uncertainty assessment values suggesting a left-skewed distribution for benefits and a right-skewed distribution for cost, but with much more skew among those using the looking back-based method. We argue that a looking back-based method is promising for improved realism in uncertainty assessment of benefits and costs of software development projects.