Digitalization Canvas - Towards Identifying Digitalization Use Cases and Projects

Andreas Heberle (Karlsruhe University of Applied Sciences, Germany)

Welf Löwe (Linnaeus University and Softwerk AB, Sweden)

Anders Gustafsson (Södra Skog, Sweden)

Örjan Vorrei (Södra Skog, Sweden)

Abstract: Nowadays, many companies are running digitalization initiatives or are planning to do so. There exist various models to evaluate the digitalization potential of a company and to define the maturity level of a company in exploiting digitalization technologies summarized under buzzwords such as Big Data, Artificial Intelligence (AI), Deep Learning, and the Industrial Internet of Things (IIoT). While platforms, protocols, patterns, technical implementations, and standards are in place to adopt these technologies, small- to medium-sized enterprises (SME) still struggle with digitalization. This is because it is hard to identify the most beneficial projects with manageable cost, limited resources and restricted know-how. In the present paper, we describe a real-life project where digitalization use cases have been identified, evaluated, and prioritized with respect to benefits and costs. This effort led to a portfolio of projects, some with quick and easy wins and some others with mid- to long-term benefits. From our experiences, we extracted a general approach that could be useful for other SMEs to identify concrete digitalization activities and to define projects implementing their digital transformation. The results are summarized in a Digitalization Canvas.

Keywords: big data, business process management, digitalization, machine learning

Categories: E.m, H.4.m