# The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development

## TL;DR

This study explores agile software practitioners' perspectives on data-driven decision making, revealing limited current use but optimistic views on its future potential across different decision levels.

## Contribution

It provides empirical insights into practitioners' experiences and attitudes towards DDDM in agile environments, highlighting gaps and opportunities.

## Key findings

- Few practitioners currently use DDDM extensively.
- Positive outlook on DDDM for high-level and requirements decisions.
- Less enthusiasm for DDDM at the team level.

## Abstract

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.