Traditional project control requires the collection of different types of data. These types include frequency counts, raw numbers, subject numeric ratings, and indicator and surrogate measures. But where do we find these in Agile managed projects?
Let’s examine a software project managed using Agile principles via Scrum processes. Note that a sprint is a two to four week cycle of product development over which time the desired result is a deliverable product. The product may not meet any minimum requirement but it will be demonstrable.
A frequency count compiled during every sprint is the number of features per week developed per contributing team member.
A raw number generated during the sprint would be the number of features developed by a single team member during the sprint.
Subjective numeric ratings are collected during sprint planning when members assign relative levels of difficulty to each feature in the sprint backlog.
An indicator of team performance is the velocity, or number of features developed in the last sprint.
As all of these data collections feature heavily in the Scrum process, the applicability of traditional project control and measurement under less traditional management methods shows clearly.