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Digitization in Controlling = Foreca...
~
Große Kamphake, Andre.
Digitization in Controlling = Forecasting Processes through Automation /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Digitization in Controlling/ by Andre Große Kamphake.
Reminder of title:
Forecasting Processes through Automation /
Author:
Große Kamphake, Andre.
Description:
XV, 70 p. 17 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Leadership. -
Online resource:
https://doi.org/10.1007/978-3-658-28741-2
ISBN:
9783658287412
Digitization in Controlling = Forecasting Processes through Automation /
Große Kamphake, Andre.
Digitization in Controlling
Forecasting Processes through Automation /[electronic resource] :by Andre Große Kamphake. - 1st ed. 2020. - XV, 70 p. 17 illus.online resource. - BestMasters,2625-3577. - BestMasters,.
The Challenge of Digitalization Projects -- Optimization of Working Capital Management -- Proceeding for Data-Driven Data Mining Forecasts -- Application of the Decision Tree Algorithm C 5.0 -- Implementation of the ARIMA Time Series Model -- Combination of Forecasting Methods Aiming Better Results.
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. Contents The Challenge of Digitalization Projects Optimization of Working Capital Management Proceeding for Data-Driven Data Mining Forecasts Application of the Decision Tree Algorithm C 5.0 Implementation of the ARIMA Time Series Model Combination of Forecasting Methods Aiming Better Results Target Groups Lecturers and students of management, corporate governance, controlling Controllers and data scientists The Author 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.
ISBN: 9783658287412
Standard No.: 10.1007/978-3-658-28741-2doiSubjects--Topical Terms:
562584
Leadership.
LC Class. No.: HD28-70
Dewey Class. No.: 658.4092
Digitization in Controlling = Forecasting Processes through Automation /
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The Challenge of Digitalization Projects -- Optimization of Working Capital Management -- Proceeding for Data-Driven Data Mining Forecasts -- Application of the Decision Tree Algorithm C 5.0 -- Implementation of the ARIMA Time Series Model -- Combination of Forecasting Methods Aiming Better Results.
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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. Contents The Challenge of Digitalization Projects Optimization of Working Capital Management Proceeding for Data-Driven Data Mining Forecasts Application of the Decision Tree Algorithm C 5.0 Implementation of the ARIMA Time Series Model Combination of Forecasting Methods Aiming Better Results Target Groups Lecturers and students of management, corporate governance, controlling Controllers and data scientists The Author 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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