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

Author

Listed:
  • Bastian Stahl

    (Research Center Finance & Information Management
    University of Applied Sciences Augsburg
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

  • Björn Häckel

    (Research Center Finance & Information Management
    University of Applied Sciences Augsburg
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

  • Daniel Leuthe

    (Research Center Finance & Information Management
    University of Applied Sciences Augsburg
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

  • Christian Ritter

    (Research Center Finance & Information Management
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

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.

Suggested Citation

  • Bastian Stahl & Björn Häckel & Daniel Leuthe & Christian Ritter, 2023. "Data or Business First?—Manufacturers’ Transformation Toward Data-driven Business Models," Schmalenbach Journal of Business Research, Springer, vol. 75(3), pages 303-343, September.
    • Handle: RePEc:spr:sjobre:v:75:y:2023:i:3:d:10.1007_s41471-023-00154-2
    DOI: 10.1007/s41471-023-00154-2
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    Cited by:

    1. Marina Fiedler & Thomas Hutzschenreuter & Martin Klarmann & Barbara E. Weißenberger, 2023. "Transformation: Challenges, Impact, and Consequences," Schmalenbach Journal of Business Research, Springer, vol. 75(3), pages 271-279, September.
    2. Daniel Leuthe & Tim Meyer-Hollatz & Tobias Plank & Anja Senkmüller, 2024. "Towards Sustainability of AI – Identifying Design Patterns for Sustainable Machine Learning Development," Information Systems Frontiers, Springer, vol. 26(6), pages 2103-2145, December.

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