Modelling and Validation of KPIs

Ella Roubtsova, Vaughan Michell


Competition for funding between organizations attracts attention to their Key Performance Indicators (KPIs). KPIs are usually designed with a top-down approach as families of measures for a group of business units and often do not take into account the difference in goals and business processes of organizations at the strategic, tactical and operational level. This results in unreliable, inefficient and sometimes inconsistent KPIs. Validation of KPI properties is typically postponed until the KPI is implemented, and databases are populated with values. The reason is the absence of intuitive and simple methods for KPI modelling that relate the strategic and tactical models and executable operational models. We propose such a method for KPI modelling and validation of their properties. Our method combines ideas of goal, conceptual and executable process modelling. Models at all levels are derived from KPI definitions. The conceptual modelling techniques are used to relate the strategic and tactical models. The synchronous semantics of protocol modelling is used to relate the tactical and the operational models. The executable operational and tactical models enable derivation the KPI values, testing KPIs against the desired properties and identification of ambiguities in KPI definitions that need to be resolved to improve KPIs.


  1. Andrews, P. (2002). An Introduction to Mathematical Logic and Type Theory: To Truth Through Proof. Berlin: Kluwer.
  2. Berler, A., Pavlopoulos, S., and Koutsouris, D. (2005). Using key performance indicators as knowledgemanagement tools at a regional health-care authority level. IEEE Transactions on Information Technology in Biomedicine, 9(2):184-192.
  3. Dardenne, A., van Lamsweerde, A., and Fickas, S. (1993). Goal-directed requirements acquisition. Sci. Comput. Program., 20(1-2):3-50.
  4. Frank, U., Heise, D., and Kattenstroth, H. (2009). Use of a domain specific modeling language for realizing versatile dashboards. In: Tolvanen JP, Rossi M, Gray J, Sprinkle J (eds) Proceedings of the 9th OOPSLA workshop on domain-specific modeling (DSM).
  5. Garengo, P., Biazzo, S., and Bititci, U. S. (2005). Performance measurement systems in SMEs: A review for a research agenda. International Journal of Management Reviews, 7:25-47.
  6. Golfarelli, M. (2009). From User Requirements to Conceptual Design in Data Warehouse Design - a Survey. In Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction. L. Bellatreche (Ed.), pages 1-14.
  7. Gossler, G. and Sifakis, J. (2003). Composition for Component Based Modeling. Springer,LNCS, 2852):443-46.
  8. McNeile, A. and Roubtsova, E. (2010). Aspect-Oriented Development Using Protocol Modeling. LNCS 6210, pages 115-150.
  9. N. (2005).
  10. McNeile, A. and Simons, N. (2006). Protocol Modelling. A Modelling Approach that Supports Reusable Behavioural Abstractions. Software and System Modeling, 5(1):91-107.
  11. Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M., and Kennerley, M. (2000). Performance measurement system design: developing and testing a process-based approach. International Journal of Operations and Production Management, 20(10):1119 - 11452.
  12. OMG (2003). Unified Modeling Language: Superstructure version 2.1.1 formal/2007-02-03.
  13. Parmenter, D. (2010). Key Performance Indicators, Developing, Implementing and Using Winning KPIs. John Wiley & Sons, New Jersey.
  14. Peter Kueng (2000). Process performance measurement system - a tool to support process-based organizations. TOTAL QUALITY MANAGEMENT, 11(1):67-85.
  15. Popova, V. and Sharpanskykh, A. (2010). Modeling organizational performance indicators. Information systems, 35(4):505-527.
  16. Regev, G. and Wegmann, A. (2011). Revisiting GoalOriented Requirements Engineering with a Regulation View. Springer. LNBIP, 109):56-69.
  17. Robert Kaplan, and David Norton (2001). Transforming the Balanced Scorecard from Performance Measurement to strategic management: Part I. Accounting Horizons, pages 87-104.
  18. Roubtsova, E. (2013). Protocol Model of the KPIs from ”The programme ”Improving Access to Psychological Therapies.
  19. Strecker, S., Frank, U., Heise, D., and Kattenstroth, H. (2012). MetricM: A modelling method in support of the reflective design and use of performance measurement systems. Springer, Information Systems and eBusiness Management, 10:241-276.

Paper Citation

in Harvard Style

Roubtsova E. and Michell V. (2013). Modelling and Validation of KPIs . In Proceedings of the Third International Symposium on Business Modeling and Software Design - Volume 1: BMSD, ISBN 978-989-8565-56-3, pages 96-105. DOI: 10.5220/0004774400960105

in Bibtex Style

author={Ella Roubtsova and Vaughan Michell},
title={Modelling and Validation of KPIs},
booktitle={Proceedings of the Third International Symposium on Business Modeling and Software Design - Volume 1: BMSD,},

in EndNote Style

JO - Proceedings of the Third International Symposium on Business Modeling and Software Design - Volume 1: BMSD,
TI - Modelling and Validation of KPIs
SN - 978-989-8565-56-3
AU - Roubtsova E.
AU - Michell V.
PY - 2013
SP - 96
EP - 105
DO - 10.5220/0004774400960105