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Industrial Conference on Data Mining

ICDM 2015: Advances in Data Mining: Applications and Theoretical Aspects pp 3–16Cite as

Improving the Predictive Power of Business Performance Measurement Systems by Constructed Data Quality Features? Five Cases

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9165))

Abstract

Predictive power is an important objective for current business performance measurement systems and it is based on metrics design, collection and preprocessing of data and predictive modeling. A promising but less studied preprocessing activity is to construct additional features that can be interpreted to express the quality of data and thus provide predictive models not only data points but also their quality characteristics. The research problem addressed in this study is: can we improve the predictive power of business performance measurement systems by constructing additional data quality features? Unsupervised, supervised and domain knowledge approaches were used to operationalize eight features based on elementary data quality dimensions. In the case studies five corporate datasets Toyota Material Handling Finland, Innolink group, 3StepIt, Papua Merchandising and Lempesti constructed data quality features performed better than minimally processed data sets in 29/38 and equally in 9/38 tests. Comparison to a competing method of preprocessing combinations with the first two datasets showed that constructed features had slightly lower prediction performance, but they were clearly better in execution time and easiness of use. Additionally, constructed data quality features helped to visually explore high dimensional data quality patterns. Further research is needed to expand the range of constructed features and to map the findings systematically to data quality concepts and practices.

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Acknowledgements

Professor emeritus Pertti Järvinen, professor Martti Juhola and Dr. Kati Iltanen University of Tampere, Finland. After sales director Jarmo Laamanen Toyota Material Handling Finland, managing director Marko Kukkola Innolink Group, sales director Mika Karjalainen 3StepIt, managing director Olli Vaaranen Papua Merchandising and managing director Sirpa Kauppila Lempesti.

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  1. University of Tampere, Tampere, Finland

    Markus Vattulainen

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  1. Markus Vattulainen
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Correspondence to Markus Vattulainen .

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  1. IBaI, Leipzig, Germany

    Petra Perner

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Vattulainen, M. (2015). Improving the Predictive Power of Business Performance Measurement Systems by Constructed Data Quality Features? Five Cases. In: Perner, P. (eds) Advances in Data Mining: Applications and Theoretical Aspects. ICDM 2015. Lecture Notes in Computer Science(), vol 9165. Springer, Cham. https://doi.org/10.1007/978-3-319-20910-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-20910-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20909-8

  • Online ISBN: 978-3-319-20910-4

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