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More Observations, More Variables or More Quality? - Data Acquisition Strategies to Enhance Uncertainty Analytics for Industrial Service Contracting

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Exploring Services Science (IESS 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 279))

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Abstract

Service business models expose industrial service providers to an increasing amount of uncertainties. In order to design profitable offerings, providers need to understand how uncertainties affect contract profitability. Both, access to data and algorithms are key requirements for accurate analyses.

While current research focuses on developing algorithms to derive insights from data that already exist, the need for strategically acquiring relevant data sets has been neglected so far. In this article, we develop a method for defining data acquisition strategies to improve uncertainty analyses for industrial service contracting. We explain how lacking observations, variables and quality of data affect uncertainty analyses, propose data acquisition strategies as a systematic plan to acquire relevant data and develop an approach for ranking acquisition strategies by measuring their acquisition effort and business benefit.

The method is applied in an industrial use case to demonstrate its benefit for assessing cost uncertainties in full-service repair contracts.

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Author information

Authors and Affiliations

  1. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Björn Schmitz & Gerhard Satzger

  2. ABB Corporate Research, Ladenburg, Germany

    Ralf Gitzel

Authors
  1. Björn Schmitz
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  2. Gerhard Satzger
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  3. Ralf Gitzel
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Correspondence to Björn Schmitz .

Editor information

Editors and Affiliations

  1. Faculty of Economics, eCampus University, Rome, Italy

    Stefano Za

  2. Department of Automatic Control and System Engineering, University Politehnica of Bucharest, Bucharest, Romania

    Monica Drăgoicea

  3. Università Cattolica del Sacro Cuore, Milan, Italy

    Maurizio Cavallari

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Schmitz, B., Satzger, G., Gitzel, R. (2017). More Observations, More Variables or More Quality? - Data Acquisition Strategies to Enhance Uncertainty Analytics for Industrial Service Contracting. In: Za, S., Drăgoicea, M., Cavallari, M. (eds) Exploring Services Science. IESS 2017. Lecture Notes in Business Information Processing, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-319-56925-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-56925-3_13

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  • Print ISBN: 978-3-319-56924-6

  • Online ISBN: 978-3-319-56925-3

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