Towards Design Principles for Data-Driven Decision Making: An Action Design Research Project in the Maritime Industry

Tiemo Thiess, Oliver Müller

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Data-driven decision making (DDD) refers to organizational decision-making practices that emphasize the use of data and statistical analysis instead of relying on human judgment only. Various empirical studies provide evidence for the value of DDD, both on individual decision maker level and the organizational level. Yet, the path from data to value is not always an easy one and various organizational and psychological factors mediate and moderate the translation of data-driven insights into better decisions and, subsequently, effective business actions. The current body of academic literature on DDD lacks prescriptive knowledge on how to successfully employ DDD in complex organizational settings. Against this background, this paper reports on an action design research study aimed at designing and implementing IT artifacts for DDD at one of the largest ship engine manufacturers in the world. Our main contribution is a set of design principles highlighting, besides decision quality, the importance of model comprehensibility, domain knowledge, and actionability of results.
Original languageEnglish
Title of host publicationECIS 2018 Proceedings
PublisherAIS Electronic Library (AISeL)
Publication date28 Nov 2018
ISBN (Electronic)978-1-86137-667-1
Publication statusPublished - 28 Nov 2018

Keywords

  • Data-Driven Decision Making
  • Design Principles
  • Action Design Research

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