Handling Uncertainty in Agile Requirement Prioritization and Scheduling Using Statistical Simulation

In the creation of a release plan developers must attempt to maximise business value while maintaining a high degree of certainty that the product will be completed on time and to budget. As a result of these constraints management is often forced to make the difficult decision as to which stories to complete and which to ignore. The difficulty of this decision is compounded by a high degree of uncertainty within the business value of each story, the story size and also the resources available. This paper proposes a relatively simple statistical methodology that allows for uncertainty in these areas. In so doing it provides key stakeholders with the opportunity to manage uncertainty in the planning of what functionality to include in upcoming releases. The technique is lightweight in nature and consistent with existing agile planning practices. A case study is provided to demonstrate how the method may be used.