From Data to Action - Data-Driven Decision Making in Product Development

Abstract

With increasing amounts of data being available, companies are investing to become data-driven with goals of increased performance, productivity, and profit. However, few companies are able to succeed with their investments. This might be due to a disproportionate focus on data and technology compared to the necessary internal processes and culture needed to leverage it in decision making. Thus, the purpose of this study is to explore the extent to which data-driven decision making can be used in product development. Using a single-case study research design with semi-structured interviewing, this thesis explores data-driven decision making as well as the enabling factors of it. Through a thematic analysis, four major themes emerge. These are the process of data-driven decision making, the collective process of data-driven decision making, enabling factors, and data-driven decision making based on assumptions. This study answers the research question by stating that data-driven decision making can be used in product development to a certain extent. However, to what extent it can be used appears to depend on how well the process of data-driven decision making gets implemented, if a collective effort is made, and to what extent the enabling factors are present.