On Advancing the Field of Organizational Diagnosis based on Insights from EntropyMotivating the Need for Constructional Models

Gilles Oorts, Philip Huysmans, Peter De Bruyn

Abstract

In this paper, we explore how the field of organizational diagnosis can benefit from lessons learned from entropy reduction in other fields. In an organizational context, entropy is related to the lack of knowledge concerning the way of how management-level KPIs (observable system macrostate) are brought about by operational elements (which are considered to be the causing microstate). Because of this lack of knowledge, the goal and scope of projects to remedy problematic KPIs cannot be determined unambiguously. Organizational diagnosis aims to further the insight in these decisions by providing conceptual models to find causal explanations between observations and their causes. In related fields, reduction of entropy is achieved by introducing and analyzing structure in a system, which is described in a constructional perspective. However, we will show in this paper that many diagnostic approaches do not support this constructional perspective adequately.

References

  1. Alderfer, C. P. (2010). The Practice of Organizational Diagnosis: Theory and Methods. Oxford University Press, USA; 1 edition.
  2. Boltzmann, L. (1995). Lectures on Gas Theory. Dover Publications.
  3. Box, G. E. P. and Liu, P. Y. T. (1999). Statistics as a catalyst to learning by scientific method. Journal of Quality Technology, 31(1):1-15.
  4. Craver, C. F. (2006). When mechanistic models explain. Synthese, 153(3):355-376.
  5. de Mast, J. and Bisgaard, S. (2007). The science in six sigma. The American Heart Hospital Journal, 40(1):25-29.
  6. Dietz, J. L. (2010). Enterprise engineering manifesto. Online available at: http://www.ciaonetwork.org/ publications/EEManifesto.pdf.
  7. Dietz, J. L. G. (2006). Enterprise Ontology: Theory and Methodology. Springer.
  8. Ettema, R. (2011). Diagnosing the enterprise, towards a true causal claim. In Proceedings of the 2011 CIAO DC.
  9. Gero, J. S. and Kannengiesser, U. (2004). The situated function-behaviour-structure framework. Design Studies, 25(4):373-391.
  10. Harrison, M. I. (1994). Diagnosing Organizations: Methods, Models, and Processes. Sage.
  11. Harry, M. (1988). The nature of six sigma quality. Motorola University Press.
  12. Hevner, A. and Chatterjee, S. (2010). Design Research in Information Systems: Theory and Practice, volume 22 of Integrated Series in Information Systems. Springer.
  13. Horowitz, I. (1970). Employment concentration in the common market: An entropy approach. Journal of the Royal Statistical Society, 133(3):463-479.
  14. Jacquemin, A. P. and Berry, C. H. (1979). Entropy measure of diversification and corporate growth. The Journal of Industrial Economics, 27(4):359-369.
  15. Janow, R. (2004). Shannon entropy and productivity: Why big organizations can seem stupid. Journal of the Washington Academy of Sciences, 90(1):39-50.
  16. Katz, D. and Kahn, R. (1978). The social psychology of organizations. Wiley.
  17. Palepu, K. (1985). Diversification strategy, profit performance and the entropy measure. Strategic Management Journal, 6(3):pp. 239-255.
  18. Russo, F. (2008). Causality and Causal Modelling in the Social Sciences: Measuring Variations (Methodos Series). Springer.
  19. Senge, P. M. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization. Doubleday.
  20. Shannon, C. (1948). A mathematical theory of communication. Bell System Technical Journal, 27:379-423.
  21. Sitkin, S. B., Sutcliffe, K. M., and Schroeder, R. G. (1994). Distinguishing control from learning in total quality management: A contingency perspective. The Academy of Management Review, 19(3):537-564.
  22. Weinberg, G. M. (1975). An Introduction to General Systems Thinking. Wiley-Interscience.
Download


Paper Citation


in Harvard Style

Oorts G., Huysmans P. and De Bruyn P. (2012). On Advancing the Field of Organizational Diagnosis based on Insights from EntropyMotivating the Need for Constructional Models . In Proceedings of the Second International Symposium on Business Modeling and Software Design - Volume 1: BMSD, ISBN 978-989-8565-26-6, pages 138-143. DOI: 10.5220/0004462001380143


in Bibtex Style

@conference{bmsd12,
author={Gilles Oorts and Philip Huysmans and Peter De Bruyn},
title={On Advancing the Field of Organizational Diagnosis based on Insights from EntropyMotivating the Need for Constructional Models},
booktitle={Proceedings of the Second International Symposium on Business Modeling and Software Design - Volume 1: BMSD,},
year={2012},
pages={138-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004462001380143},
isbn={978-989-8565-26-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Symposium on Business Modeling and Software Design - Volume 1: BMSD,
TI - On Advancing the Field of Organizational Diagnosis based on Insights from EntropyMotivating the Need for Constructional Models
SN - 978-989-8565-26-6
AU - Oorts G.
AU - Huysmans P.
AU - De Bruyn P.
PY - 2012
SP - 138
EP - 143
DO - 10.5220/0004462001380143