Digitization in Controlling: Forecasting Processes through Automation

· Springer Nature
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Andre Große Kamphake deals with the digitization in controlling and focuses in this context on the analysis of automated forecasting processes within a chemical company. He aims at outlining to what extent and how accurate forecasting processes can be automated in the age of digitization and big data. Therefore, the forecast of the working capital is put at the center since it plays a leading role for the cash collection process. Based on data from 2015 to 2018, two different forecasting models are combined to optimally predict the different components contained in the working capital. 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.

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After successfully completing his master's degree in business administration in major Finance at the University of Cologne, Germany, Andre Große Kamphake works as a controller in the field of business development with a focus on reporting and data analysis.

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