DISRE - Data Driven Innovation in Specialized Retail Ecosystems

There is limited tradition for research-driven innovation in the Norwegian retail sector that is now facing increasing competition from international platform companies. An example is Amazon with its extensive experience from big data analytics, research driven algorithms and cloud-based data storage services. To address this competition, the DISRE project is exploring how data sharing between Norwegian specialty retailers can create alternative advantages. Instead of adopting a strictly regulated platform model, the retailers can collaborate within an ecosystem aimed at developing shared capabilities for value creation and data sharing for value capture. The initiative is organized in a novel and alternative "triple helix"-collaboration between speciality retailers Voice, Happy Homes and Jernia, the knowledge provider inFuture, researchers from University of Southeastern-Norway (USN), University of Oslo, NIFU, Luleå University of Technology (the IMIT foundation), and the employer organization Virke, and is structured around three data driven innovation concepts. Appropriate work methods, collaboration frameworks, techniques, and data foundations have been established. The project has hired a postdoctoral researcher with expertise in network analysis and a PhD candidate with extensive experience in data-driven innovation, particularly in retail. A comprehensive assessment of the regulatory, cultural, and technological prerequisites for data-driven innovation in the specialty retail sector has been conducted. Privacy regulations pose a significant challenge, and few specialty retailers have privacy policies that are equipped for such innovation. Cultural prerequisites also vary widely and differ significantly from those in sectors like grocery retail. Technologically, there is considerable variation in the readiness for data-driven innovation among the specialty retailers involved in the project. Together with each retail partner and their ecosystem collaborators, the project has identified and developed concepts for data-driven innovation. The project has actively employed service design methodologies for insights, idea generation, and prototyping. The project is also testing whether customers and providers are interested in adopting the proposed concepts.

The retail sector in Norway has limited tradition for research-driven innovation. This is particularly evident for speciality retailers that are currently challenged by platform company entry. However, speciality retailers can match the competitive advantages of platform companies by aggregating and sharing data in their ecosystem, but this is a “wicked innovation problem" where individual retailers lack the incentives to release value from positive production externalities. The DISRE project aims to corrects this market failure by organizing a novel and alternative "triple helix"-collaboration between speciality retailers Voice, Happy Homes and Jernia, KIBS provider inFuture and university researchers from USN, UiO, NIFU and Luleå. We develop the knowledge required for data driven innovation in speciality retail ecosystems through work packages (WPs) that explore three service concepts for data driven insight in cycles of service ecosystem design and applied research. Generic WPs support these cycles through more basic consumer, business model, culture, regulatory and innovation research. A novel research framework and governance form is used to link basic and applied research and engage retail research users. In addition to the speciality retailers' improved competitiveness against platform companies, the outcomes of DISRE will enable them to better support consumer journeys across retailers and service providers, for example during important consumer life events. This will increase consumer well-being and enable retail to retain its function as a supplier of ecosystem services in local cities and communities and reduce goods- and consumer transport. Results from DISRE will be disseminated to the scientific-, speciality- and generic retail, policy maker- and student audiences through a rich set of activities, including the extension of the Digitalization School of Retail with particular focus on the integration of big data analytics and business competence.