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

Frank Fuchs-Kittowski (), Paul Schulze (), Andreas Abecker (), Jonas Lachowitzer (), Stefan Lossow (), Heino Rudolf () and Erik Rodner ()
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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

A chapter in Advances and New Trends in Environmental Informatics, 2025, pp 3-19 from Springer

Abstract: 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.

Keywords: Potential analysis; Machine learning; Artificial intelligence; Use cases; State environmental agency (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-85284-8_1

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DOI: 10.1007/978-3-031-85284-8_1

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