Zusammenfassung
Die zunehmende Digitalisierung sowie die allgegenwärtige Verfügbarkeit von Daten verändern das Wirtschaftsleben, den Alltag des Einzelnen und die Gesellschaft als Ganzes. Vor diesem Hintergrund wird der Einsatz von maschinellen Lernverfahren in vielen Bereichen von Wirtschaft und Gesellschaft zum Teil kontrovers diskutiert. Mit Hilfe des Einsatzes solcher Algorithmen lassen sich beispielsweise Prognosen verbessern sowie Entscheidungen bzw. Entscheidungsprozesse automatisieren. In diesem Artikel geben wir zum einen einen Überblick über die Grundprinzipien maschinellen Lernens. Zum anderen diskutieren wir Anwendungsmöglichkeiten sowie Wirtschaftlichkeitspotenziale am Beispiel von Kundenbindungsprozessen.
Abstract
The increasing digitalization, as well as the ubiquitous availability of data, are currently transforming the economy, the lives of consumers, and society in general. In this context, the use of machine learning is often controversially debated by businesses and the public. For example, these algorithms can help improve making predictions and help automate decisions and decision making processes. In this paper, we first provide an overview of the basic concepts of machine learning and secondly, we will examine selected use cases and efficiency potentials within the customer retention processes.
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Notes
Vgl. starke künstliche Intelligenz bzw. „Artificial General Intelligence“ (Pennachin und Goertzel 2007).
Durchführung der Studie im Jahr 2017.
Vgl. hierzu „Durchschnittliche Beratungszeit“, typische Bandbreite von 1,95–8,7 min bei Erichsen (2007).
Konservative Annahme für zwei API-Calls (Kategorisierung und Lösungsvorschlag) bedingt durch eventuelle Latenz und Verarbeitungsdauer; basierend auf Test via SAP API Business Hub (SAP 2017c).
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Welsch, A., Eitle, V. & Buxmann, P. Maschinelles Lernen. HMD 55, 366–382 (2018). https://doi.org/10.1365/s40702-018-0404-z
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DOI: https://doi.org/10.1365/s40702-018-0404-z