Data-Driven Business Models - Building the Bridge between Data and Value.

Abstract

In the wake of an ongoing digital transformation organizations are seeking to understand and generate new data-driven business models. While data is a key resource, generating value from data is a key challenge for innovating data-driven business models. Extant tools for business model representation offer little help. In this paper, we propose the design of a Data Insight Generator (DIG) artefact that can support the design process of data-driven business models at a crucial step: connecting data to value propositions. The artefact is positioned as a complement to the Business Model Canvas, the most widely used tool for business model representation. The DIG connects two key elements of the business model, namely key resources and value proposition through six data-specific elements. Further, the DIG supports an iterative process of discovery for these elements as a boundary object between business and data science/IT participants of business model innovation. Based on a formative evaluation we demonstrate the usability and utility of the DIG.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 42 citations exist upstream.