A Case Study on Entropy Generation during Business Process ExecutionA Monte Carlo Simulation of the Custom Bikes Case

Peter De Bruyn, Philip Huysmans, Herwig Mannaert

2013

Abstract

Contemporary organizations require high-quality information to design and manage their business processes. Important challenges in this context comprise (1) the decision regarding which information should be stored and in what way, and (2) the need to allow adequate reporting for different organizational perspectives. To tackle these issues, we proposed in previous work applying the concept of entropy as defined in statistical thermodynamics to the domain of business process management. In this paper, we further elaborate on this idea by performing a Monte Carlo simulation of the Custom Bikes case to show how guidelines are necessary to control this entropy. In doing so, we extend previous theoretical contributions by releasing some simplifying assumptions made earlier, while simultaneously proving its practical relevance in a case. Finally, this paper discusses the important challenge for the need of adequate reporting from different organizational perspectives.

References

  1. Boltzmann, L. (1995). Lectures on Gas Theory. Dover Publications.
  2. De Bruyn, P. (2011). Towards designing enterprises for evolvability based on fundamental engineering concepts. In On the Move to Meaningful Internet Systems: OTM 2011 Workshops, volume 7046 of Lecture Notes in Computer Science, pages 11-20. Springer, Berlin, Heidelberg.
  3. De Bruyn, P., Huysmans, P., Mannaert, H., and Verelst, J. (2013). Understanding entropy generation during the execution of business process instantiations: An illustration from cost accounting. In Advances in Enterprise Engineering VII, Lecture Notes in Computer Science. Springer Berlin Heidelberg. in press.
  4. De Bruyn, P., Huysmans, P., Oorts, G., and Mannaert, H. (2012). On the applicability of the notion of entropy for business process analysis. In Shishkov, B., editor, Proceedings of the second international symposium on Business Modeling and Software Design, pages 128-137.
  5. De Bruyn, P. and Mannaert, H. (2012). On the generalization of normalized systems concepts to the analysis and design of modules in systems and enterprise engineering. International journal on advances in systems and measurements, 5(3&4):216-232.
  6. Drury, C. (2007). South-Western.
  7. Ethiraj, S. K. and Levinthal, D. (2004). Bounded rationality and the search for organizational architecture: An evolutionary perspective on the design of organizations and their evolvability. Administrative Science Quarterly, 49(3):404 - 437.
  8. Hevner, A. R., March, S. T., Park, J., and Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1):75-105.
  9. Jacquemin, A. P. and Berry, C. H. (1979). Entropy measure of diversification and corporate growth. The Journal of Industrial Economics, 27(4):359-369.
  10. Jung, J.-Y., Chin, C.-H., and Cardoso, J. (2011). An entropy-based uncertainty measure of process models. Information Processing Letters, 111(3):135-141.
  11. Kaplan, R. S. and Anderson, S. R. (2004). Time-driven activity-based costing. Harvard business review, 82(11):131-8.
  12. Mannaert, H., De Bruyn, P., and Verelst, J. (2012). Exploring entropy in software systems: towards a precise definition and design rules. In Proceedings of the Seventh International Conference on Systems (ICONS) 2012, pages 93-99.
  13. Mannaert, H. and Verelst, J. (2009). Normalized SystemsRe-creating Information Technology Based on Laws for Software Evolvability. Koppa.
  14. Mannaert, H., Verelst, J., and Ven, K. (2011). The transformation of requirements into software primitives: Studying evolvability based on systems theoretic stability. Science of Computer Programming, 76(12):1210-1222.
  15. Oorts, G., Huysmans, P., and De Bruyn, P. (2012). On advancing the field of organizational diagnosis based on insights from entropy - motivating the need for constructional models. In Shishkov, B., editor, Proceedings of the second international symposium on Business Modeling and Software Design, pages 138-143.
  16. Regev, G., Hayard, O., and Wegmann, A. (2012). Homeostasis - the forgotten enabler of business models. In Shishkov, B., editor, Proceedings of the second international symposium on Business Modeling and Software Design, pages 13-24.
  17. Tumay, K. (1996). Business process simulation. In Charnes, J., Morrice, D., Brunner, D., and Swain, J., editors, Proceedings of the 1996 Winter Simulation Conference, pages 93-98. ACM Press.
  18. Van Nuffel, D. (2011). Towards Designing Modular and Evolvable Business Processes. PhD thesis, University of Antwerp.
Download


Paper Citation


in Harvard Style

De Bruyn P., Huysmans P. and Mannaert H. (2013). A Case Study on Entropy Generation during Business Process ExecutionA Monte Carlo Simulation of the Custom Bikes Case . In Proceedings of the Third International Symposium on Business Modeling and Software Design - Volume 1: BMSD, ISBN 978-989-8565-56-3, pages 187-197. DOI: 10.5220/0004775301870197


in Bibtex Style

@conference{bmsd13,
author={Peter De Bruyn and Philip Huysmans and Herwig Mannaert},
title={A Case Study on Entropy Generation during Business Process ExecutionA Monte Carlo Simulation of the Custom Bikes Case},
booktitle={Proceedings of the Third International Symposium on Business Modeling and Software Design - Volume 1: BMSD,},
year={2013},
pages={187-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004775301870197},
isbn={978-989-8565-56-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Symposium on Business Modeling and Software Design - Volume 1: BMSD,
TI - A Case Study on Entropy Generation during Business Process ExecutionA Monte Carlo Simulation of the Custom Bikes Case
SN - 978-989-8565-56-3
AU - De Bruyn P.
AU - Huysmans P.
AU - Mannaert H.
PY - 2013
SP - 187
EP - 197
DO - 10.5220/0004775301870197