Building a Connection Between Decision Maker and Data-Driven Decision Process

It is quite common that most of companies’ decisions are made based on feelings, intuitions or personal experiences. The reasons for such patterns have organizational, technical and process oriented backgrounds. For instance, there is no structured way to deal with the analytical results on both sides simultaneously – organizational and technical. Usually, in case of analytics the ones doing analysis (e.g. data scientists) and the ones using results of analytics (e.g. decision makers) are different persons. As a result, such a structure leads to ambiguity and misunderstanding between the involved parties. In order to bridge the existing gap between data scientists and decision makers, we introduced the Data Product Profile which links both data science and data-driven decision processes.

[1]  Tom Fawcett,et al.  Data Science and its Relationship to Big Data and Data-Driven Decision Making , 2013, Big Data.

[2]  Tom Fawcett,et al.  Data science for business , 2013 .

[3]  Carl Anderson Creating a Data-Driven Organization , 2015 .

[4]  Matthias Knoll,et al.  Rezension „Einflüsse auf den Implementierungserfolg von Big Data Systemen“ , 2017, HMD Praxis der Wirtschaftsinformatik.

[5]  Miryung Kim Five steps for success , 2016, Perspectives on Data Science for Software Engineering.

[6]  Erik Brynjolfsson,et al.  Data in Action: Data-Driven Decision Making in U.S. Manufacturing , 2016 .

[7]  T. Davenport,et al.  Data scientist: the sexiest job of the 21st century. , 2012, Harvard business review.

[8]  Ahmed Elragal,et al.  Big Data Analytics in Support of the Decision Making Process , 2016 .

[9]  Guangming Cao,et al.  Understanding the Impact of Business Analytics on Innovation , 2020, ECIS.

[10]  Rüdiger Wirth,et al.  CRISP-DM: Towards a Standard Process Model for Data Mining , 2000 .

[11]  Thomas H. Davenport,et al.  Business Intelligence and Organizational Decisions , 2010, Int. J. Bus. Intell. Res..

[12]  Thilo Stadelmann,et al.  Data Science für Lehre, Forschung und Praxis , 2014, HMD Praxis der Wirtschaftsinformatik.

[13]  Peter Mork,et al.  From Data to Decisions: A Value Chain for Big Data , 2013, IT Professional.

[14]  Erik Brynjolfsson,et al.  The rise of data-driven decision-making is real but uneven , 2017, IEEE Engineering Management Review.

[15]  Peter Buxmann,et al.  Big Data und Informationsverarbeitung in organisatorischen Entscheidungsprozessen , 2014, Wirtschaftsinf..

[16]  Thomas H. Davenport,et al.  Analytics at Work: Smarter Decisions, Better Results , 2010 .