Titlebook: Digitization in Controlling; Forecasting Processe Andre Gro?e Kamphake Book 2020 Springer Fachmedien Wiesbaden GmbH, part of Springer Natur

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Results,, first, the dates for net due date are sorted from oldest to newest for the respective monthly data, and secondly, the sum of ACTs of the respective month to be predicted is calculated. This BM rests on the assumption that the customers pay exactly on the net due date of their invoices.

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Introduction, business purposes, this development is currently leading to a trend shift towards the use of predictive analytics in companies. With the help of modern statistical algorithms and their utilization within corporate management, patterns, trends, and structures can be found more accurately, particular

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Digitalization in Controlling,y of working. This term differs from digitization which describes the action or process of digitizing analogue data into digital form and is understood as a trend reversal in the use of this thesis. Especially controllers face the challenge of digitalization projects to improve and accelerate decisi

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Results,, first, the dates for net due date are sorted from oldest to newest for the respective monthly data, and secondly, the sum of ACTs of the respective month to be predicted is calculated. This BM rests on the assumption that the customers pay exactly on the net due date of their invoices.

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2625-3577 al. The author manages to prove that both a trained forecasting algorithm achieves a prediction accuracy of 92.49 % and statistical methods in machine learning lead to a significant increase in forecasts compared to naive forecasting models..978-3-658-28740-5978-3-658-28741-2Series ISSN 2625-3577 Series E-ISSN 2625-3615