TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Kiefer, Daniel
A1  - van Dinther, Clemens
A1  - Straub, Tim
T1  - The time has come : application of artificial intelligence in small- and medium-sized enterprises
T2  - Wirtschaftsinformatik 2022 : Proceedings, 21.-23. February 2022, Nuremberg (online)
N2  - 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.
KW  - artificial intelligence
KW  - demand forecasting
KW  - small- and medium-sized enterprises
KW  - supply chain management
KW  - case study
Y1  - 2022
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-38723
UR  - https://aisel.aisnet.org/wi2022/analytics_talks/analytics_talks/1
U6  - https://doi.org/10.34645/opus-3872
DO  - https://doi.org/10.34645/opus-3872
SP  - 4
S1  - 4
PB  - Association for Information Systems
CY  - Atlanta, GA
ER  -