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Obtaining Key Performance Indicators by Using Data Mining Techniques

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Advances in Conceptual Modeling (ER 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9382))

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Abstract

Currently dashboards are the preferred tool across organizations to monitor business performance. Dashboards are often composed by different data visualization techniques, amongst which Key Performance Indicators (KPIs) play a crucial role in facilitating quick and precise information by comparing current performance against a target required to fulfill business objectives. It is however the case that not always KPIs are well known, and sometimes it is difficult to find an adequate KPI to associate with each business objective. On the other hand, data mining techniques are often used for forecasting trends and visualizing data correlations. In this paper, we present a novel approach to combine these two aspects in order to drive data mining techniques into obtaining specific KPIs for business objectives in a semi-automatic way. The main benefit of our approach, is that organizations do not need to rely on existing KPI lists, such as APQC, nor test KPIs on a cycle, as they can analyze their behaviour using existing data. In order to show the applicability of our approach, we apply our proposal to the novel field of MOOC courses in order to identify additional KPIs to the ones being currently used.

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Notes

  1. 1.

    UniMOOC can be accessed at http://unimooc.com/landing/.

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Acknowledgments

This work has been funded by the Spanish Ministry of Economy and Competitiveness under the project Grant GEODAS-BI (TIN2012-37493-C03-03) and the University of Alicante, within the program of support for official master studies and research initiation (BOUA of 30/07/2013) and within the program of support for research, under project GRE14-10 (BOUA of 03/06/2014).

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Authors and Affiliations

  1. Lucentia Research Group, Department of Software and Computing Systems, University of Alicante, Alicante, Spain

    Roberto Tardío & Jesús Peral

Authors
  1. Roberto Tardío
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  2. Jesús Peral
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Correspondence to Jesús Peral .

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Editors and Affiliations

  1. University of Skövde, Skövde, Sweden

    Manfred A. Jeusfeld

  2. Indian Institute of Technology, Gujarat, India

    Kamalakar Karlapalem

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Tardío, R., Peral, J. (2015). Obtaining Key Performance Indicators by Using Data Mining Techniques. In: Jeusfeld, M., Karlapalem, K. (eds) Advances in Conceptual Modeling. ER 2015. Lecture Notes in Computer Science(), vol 9382. Springer, Cham. https://doi.org/10.1007/978-3-319-25747-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-25747-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25746-4

  • Online ISBN: 978-3-319-25747-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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