Data or Business First?—Manufacturers’ Transformation Toward Data-driven Business Models

Bastian Stahl (), Björn Häckel, Daniel Leuthe and Christian Ritter
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Bastian Stahl: Research Center Finance & Information Management
Björn Häckel: Research Center Finance & Information Management
Daniel Leuthe: Research Center Finance & Information Management
Christian Ritter: Research Center Finance & Information Management

Schmalenbach Journal of Business Research, 2023, vol. 75, issue 3, 303-343

Abstract: Abstract Driven by digital technologies, manufacturers aim to tap into data-driven business models, in which value is generated from data as a complement to physical products. However, this transformation can be complex, as different archetypes of data-driven business models require substantially different business and technical capabilities. While there are manifold contributions to research on technical capability development, an integrated and aligned perspective on both business and technology capabilities for distinct data-driven business model archetypes is needed. This perspective promises to enhance research’s understanding of this transformation and offers guidance for practitioners. As maturity models have proven to be valuable tools in capability development, we follow a design science approach to develop a maturity model for the transformation toward archetypal data-driven business models. To provide an integrated perspective on business and technology capabilities, the maturity model leverages a layered enterprise architecture model. By applying and evaluating in use at two manufacturers, we find two different transformation approaches, namely ‘data first’ and ‘business first’. The resulting insights highlight the model’s integrative perspective’s value for research to improve the understanding of this transformation. For practitioners, the maturity model allows a status quo assessment and derives fields of action to develop the capabilities required for the aspired data-driven business model.

Keywords: Data-driven business models; Data-driven services; Data analytics; Manufacturing; Enterprise architecture.; L60; O14; O32 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s41471-023-00154-2

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