Decision support framework for opening business data

Abstract

Open data movement is gaining widespread attention and spans across a variety of sectors (public, private, academic and civil). The last ten years have seen significant progress in opening of access to government datasets (Davies, 2010). This openness of public data has brought several benefits as: great transparency, innovation and the rise of new business models (i.e. analytics as a service). One of the primary consumers of open public data is the private sector. Private sector companies not only interact with governmental data but also produce a massive amount of data themselves (Herzberg, 2014). Few initiatives to open up data emerged already in the private sector, but are insufficient to provide a benchmark. Businesses are unsure about the associated costs and benefits of such an action (theodi.org, 2015) and a variety a constraints (privacy, security, proprietary interests and data protectionism) hold back this potential (Verhulst, 2014). This research offer guidance for the private sector towards releasing their data, by providing a decision support framework. This framework is composed by seven building blocks: organizational goals, business drivers to open up data, business open data ecosystem, datasets, barriers, and risks, process change and strategies to release data. The novelty of this research consists on the perspective that is given to the “open data”, where private sector organizations are seen as the main suppliers. The main business drivers for companies to open up datasets (community building, promotion, business innovation, business improvement, new revenue stream) are identified. Next to that, key challenges –pertaining to gathering data, opening-up datasets and on the user side regarding business open data are investigated.