The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development
This addresses the gap in understanding practitioner perspectives on DDDM in agile contexts, but it is incremental as it primarily reports survey results without proposing new methods.
The study investigated the use of data-driven decision making (DDDM) in agile software development through a survey of 84 industry practitioners, finding that few currently use DDDM widely but they see potential for future application, especially at higher levels.
With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a widespread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled.