Abstract
In the following contribution, an innovative artificial intelligence technology will be introduced. It was developed by international top-level researchers and has found successful application in retail for years now. Future events in complex business environments can be recognized and precisely assessed by this artificial intelligence, and the insights can serve as basis for founded decisions. Further, a high degree of automatization can serve to reduce strain on business operations, while simultaneously creating more efficient processes.
This contribution highlights the implementation of statistical models and procedures that take all influencing factors and their interdependencies into account to calculate forecasts. In addition, the economic advantage by including variable costs and business targets into the optimization will be portrayed in particular. The area of application, the replenishment sector, as well as many other examples will be introduced.
This contribution aims at an audience consisting replenishment, purchase, marketing, and sales experts and responsible persons, as well as all those that are interested in an individual assessment of their customers, but do not have the necessary experience or methods to process the data at their disposal.
An adaption of this contribution has been originally printed as Clasen, M., Milnik, M.: Vom Urknall zur Prognose, Buttkus, M., Neugebauer, A., Kaland, A. (2016), Controlling in Handel: Innovative Ansätze und Praxisbeispiele, pp. 177–192, Springer Gabler, Wiesbaden.
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Clasen, M., Milnik, M. (2019). Big Bang Based Decision Automation. In: Buttkus, M., Eberenz, R. (eds) Performance Management in Retail and the Consumer Goods Industry. Springer, Cham. https://doi.org/10.1007/978-3-030-12730-5_11
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DOI: https://doi.org/10.1007/978-3-030-12730-5_11
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