Abstract
For organizations, the use of Big Data and data analytics provides the opportunity to gain competitive advantages and foster innovation. In most of these data analytics initiatives, it is possible that data from external stakeholders could enrich the internal data assets and lead to enhanced outcomes. Currently, no framework is available that systematically guides practitioners in identifying and evaluating suitable inter-organizational data collaborations at an early stage. This paper closes the gap by following an action design research approach to develop the Data Collaboration Canvas (DCC). The DCC was rigorously evaluated by practitioners from Swiss organizations in six different industries, instantiated in four workshops, and used to guide innovative data collaboration projects. This artifact gives practitioners a guideline for identifying data collaboration opportunities and an insight into the main factors that must be addressed before further pursuing a collaborative partnership.
Paper Number
103
Recommended Citation
Geppert, Tim; Dal Fuoco, Alice; Leikert-Boehm, Ninja; Deml, Stefan; Sturzenegger, David; and Ebert, Nico, "THE DATA COLLABORATION CANVAS: A VISUAL FRAMEWORK FOR SYSTEMATICALLY IDENTIFYING AND EVALUATING ORGANIZATIONAL DATA COLLABORATION OPPORTUNITIES" (2023). Wirtschaftsinformatik 2023 Proceedings. 1.
https://aisel.aisnet.org/wi2023/1
Comments
Track 5: Data Science & Business Analytics