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A Method for Potential Analysis to Identify Application Scenarios for Machine Learning

In: Advances and New Trends in Environmental Informatics

Author

Listed:
  • Frank Fuchs-Kittowski

    (HTW Berlin, University of Applied Sciences)

  • Paul Schulze

    (HTW Berlin, University of Applied Sciences)

  • Andreas Abecker

    (Disy Informationssysteme GmbH)

  • Jonas Lachowitzer

    (Disy Informationssysteme GmbH)

  • Stefan Lossow

    (Disy Informationssysteme GmbH)

  • Heino Rudolf

    (Simplex4Data GmbH)

  • Erik Rodner

    (HTW Berlin, University of Applied Sciences)

Abstract

This article presents a method for potential analysis for identifying application potentials for application of machine learning (ML) in organizations. This method describes a systematic approach that emphasizes both the requirements of employees and business processes. The structure and artefacts of the method are described in this paper. Furthermore, the application of this method at an environmental agency as pilot user is presented. The results show that this method helped the environmental agencies to quickly develop ML solutions and select beneficial ML solutions effectively.

Suggested Citation

  • Frank Fuchs-Kittowski & Paul Schulze & Andreas Abecker & Jonas Lachowitzer & Stefan Lossow & Heino Rudolf & Erik Rodner, 2025. "A Method for Potential Analysis to Identify Application Scenarios for Machine Learning," Progress in IS, in: Volker Wohlgemuth & Hamdy Kandil & Amna Ramzy (ed.), Advances and New Trends in Environmental Informatics, pages 3-19, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-85284-8_1
    DOI: 10.1007/978-3-031-85284-8_1
    as

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