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Data Supply for Planning and Budgeting Processes under Uncertainty by Means of Regression Analyses

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Business Intelligence and Performance Management

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

Abstract

Planning and Budgeting (P&B) is an important part of Performance Management (PM). The corresponding processes for medium-sized and large organisations are usually very resource-intensive, time consuming and costly. These issues are mainly caused by uncertainty, which is a big challenge for companies. It is shown that available software and tools do not address this challenge in an appropriate way. Before possible issues and solutions are analysed in detail, an overview of different types of uncertainty is given. Afterwards important steps of the P&B process which suffer from uncertainties are outlined. Quite often it is not really clear which parameters have an impact on the planning object and how strong the planning object is influenced by certain parameters. Additionally, forecasts of the most important parameters which anticipate uncertainties are needed at an early stage of the P&B process. To resolve these issues, the application of different types of regression analyses will be explored. Also, ideas for further processing of fuzzy data in the following P&B steps are given. Furthermore, organisational and cultural prerequisites for the successful application of the outlined approaches will be indicated.

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Authors and Affiliations

  1. Department of Computer Science, Georg Simon Ohm University of Applied Sciences, Kesslerplatz 12, 90489, Nuremberg, Germany

    Peter Rausch

  2. Noris Treuhand Unternehmensberatung GmbH, Virchowstr. 31, 90409, Nuremberg, Germany

    Birgit Jehle

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  1. Peter Rausch
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  2. Birgit Jehle
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Correspondence to Peter Rausch .

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Editors and Affiliations

  1. Department of Computer Science, Georg Simon Ohm Univ. of Applied Science, Philipp-Kittler-Str. 18, Nuremberg, 90480, Germany

    Peter Rausch

  2. Department of Computer Science, Taif University, Makkah, Al-huwayah, Taif, PO888, Saudi Arabia

    Alaa F. Sheta

  3. Faculty of Technology, De Montfort University, The Gateway, Leicester, LE1 9BH, Leicestershire, United Kingdom

    Aladdin Ayesh

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Rausch, P., Jehle, B. (2013). Data Supply for Planning and Budgeting Processes under Uncertainty by Means of Regression Analyses. In: Rausch, P., Sheta, A., Ayesh, A. (eds) Business Intelligence and Performance Management. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-4866-1_11

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  • DOI: https://doi.org/10.1007/978-1-4471-4866-1_11

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4865-4

  • Online ISBN: 978-1-4471-4866-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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