Concept for Enabling Customer-oriented Data Analytics via Integration of Production Process Improvement Methods and Data Science Methods

Abstract

Production companies are facing the major challenge of digitization. New technical developments enable new optimization potentials in production that can be leveraged in a highly competitive market. Data analysis is a good example of this, allowing large amounts of data to be used to support production in optimization projects. For data analysis the CRISP-DM approach has become generally accepted in science and practice. This process model offers a good support for data science projects with useful data analysis methods and tools. In practice, however, it can often be observed that aspects such as customer-oriented project definition and the integration of process knowledge in data science projects are difficult to achieve. This paper will present a solution for that challenge. The combination of process optimization methods from the Lean Management and Six Sigma toolbox as well as project management methods for each phase of the CRISP-DM approach support data science projects to customize the project definition and integrate process knowledge.