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The time has come : application of artificial intelligence in small- and medium-sized enterprises

  • Artificial intelligence (AI) is not yet widely used in small- and medium-sized industrial enterprises (SME). The reasons for this are manifold and range from not understanding use cases, not enough trained employees, to too little data. This article presents a successful design-oriented case study at a medium-sized company, where the described reasons are present. In this study, future demand forecasts are generated based on historical demand data for products at a material number level using a gradient boosting machine (GBM). An improvement of 15% on the status quo (i.e. based on the root mean squared error) could be achieved with rather simple techniques. Hence, the motivation, the method, and the first results are presented. Concluding challenges, from which practical users should derive learning experiences and impulses for their own projects, are addressed.

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Metadaten
Author of HS ReutlingenKiefer, Daniel; van Dinther, Clemens; Straub, Tim
URN:urn:nbn:de:bsz:rt2-opus4-38723
URL:https://aisel.aisnet.org/wi2022/analytics_talks/analytics_talks/1
DOI:https://doi.org/10.34645/opus-3872
Erschienen in:Wirtschaftsinformatik 2022 : Proceedings, 21.-23. February 2022, Nuremberg (online)
Publisher:Association for Information Systems (AIS)
Place of publication:Atlanta, GA
Document Type:Conference proceeding
Language:English
Publication year:2022
Tag:artificial intelligence; case study; demand forecasting; small- and medium-sized enterprises; supply chain management
Page Number:4
DDC classes:004 Informatik
Open access?:Ja
Licence (German):License Logo  Open Access