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Operations risk management by optimally planning the qualified workforce capacity

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  • Fragnière, Emmanuel
  • Gondzio, Jacek
  • Yang, Xi

Abstract

Operational risks are defined as risks of human origin. Unlike financial risks that can be handled in a financial manner (e.g. insurances, savings, derivatives), the treatment of operational risks calls for a "managerial approach". Consequently, we propose a new way of dealing with operational risk, which relies on the well known aggregate planning model. To illustrate this idea, we have adapted this model to the case of a back office of a bank specializing in the trading of derivative products. Our contribution corresponds to several improvements applied to stochastic programming techniques. First, the model is transformed into a multistage stochastic program in order to take into account the randomness associated with the volume of transaction demand and with the capacity of work provided by qualified and non-qualified employees over the planning horizon. Second, as advocated by Basel II, we calculate the probability distribution based on a Bayesian Network to circumvent the difficulty of obtaining data which characterizes uncertainty in operations. Third, we go a step further by relaxing the traditional assumption in stochastic programming that imposes a strict independence between the decision variables and the random elements. Comparative results show that in general these improved stochastic programming models tend to allocate more human expertise in order to hedge operational risks. Finally, we employ the dual solutions of the stochastic programs to detect periods and nodes that are at risk in terms of the expertise availability.

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  • Fragnière, Emmanuel & Gondzio, Jacek & Yang, Xi, 2010. "Operations risk management by optimally planning the qualified workforce capacity," European Journal of Operational Research, Elsevier, vol. 202(2), pages 518-527, April.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:2:p:518-527
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    References listed on IDEAS

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    Cited by:

    1. Sovan Mitra & Andreas Karathanasopoulos, 2019. "Firm Value and the Impact of Operational Management," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(1), pages 61-85, March.
    2. Corominas, Albert & Lusa, Amaia & Olivella, Jordi, 2012. "A detailed workforce planning model including non-linear dependence of capacity on the size of the staff and cash management," European Journal of Operational Research, Elsevier, vol. 216(2), pages 445-458.
    3. Shantia, Ali & Aflaki, Sam & Masini, Andrea, 2021. "Contracting for technology improvement: The effect of asymmetric bargaining power and investment uncertainty," European Journal of Operational Research, Elsevier, vol. 293(2), pages 481-494.
    4. Valeva, Silviya & Hewitt, Mike & Thomas, Barrett W. & Brown, Kenneth G., 2017. "Balancing flexibility and inventory in workforce planning with learning," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 194-207.
    5. Roc'io Paredes & Marco Vega, 2020. "An internal fraud model for operational losses in retail banking," Papers 2002.03235, arXiv.org.
    6. Tahir Ekin & Nicholas G. Polson & Refik Soyer, 2017. "Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 613-627, December.
    7. Mizgier, Kamil J. & Hora, Manpreet & Wagner, Stephan M. & Jüttner, Matthias P., 2015. "Managing operational disruptions through capital adequacy and process improvement," European Journal of Operational Research, Elsevier, vol. 245(1), pages 320-332.
    8. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    9. Ekin, Tahir, 2018. "Integrated maintenance and production planning with endogenous uncertain yield," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 52-61.

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