Challenges in Data Science Project Management: A Case Study in a European OEM

Abstract

In today's world, the immense amount of data generated led to the emergence of Data Science (DS) as an integral discipline to extract knowledge and value from data. As DS projects suffer from high failure rates, new approaches for DS project management need to be developed and evaluated. In this paper, the Data Science Lifecycle (DSLC) process model is applied in a real-world DS undertaking at a European Original Equipment Manufacturer to support the initiation and planning of a project concerning the product development process. In this course, challenges in the application of the DSLC and the project at hand are identified and discussed. As this study only focuses on the initial Situation Assessment activity, in the future, the extension of the research to the remaining project phases and the inclusion of additional cases are needed to generalize the findings.