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Scorecard models for operations management

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  • Paolo Giudici

Abstract

In this paper, we propose two effective methods to prioritise controls on operations management on the basis of their operational risk. The methods are based on the combination of a sound statistical methodology and an easy to communicate scorecard reporting format. The first method summarises the content of operational self-assessment questionnaires using the idea of a 'Gini rating', thereby producing a simple read ordering of operations performance. The second method introduces a simple non-parametric Bayesian model, able to integrate questionnaire data with observed loss data, thereby producing a combined measure of risk, on which to base capital coverage.

Suggested Citation

  • Paolo Giudici, 2015. "Scorecard models for operations management," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 1(1), pages 96-101.
  • Handle: RePEc:ids:ijdsci:v:1:y:2015:i:1:p:96-101
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    References listed on IDEAS

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    1. Dalla Valle, L. & Giudici, P., 2008. "A Bayesian approach to estimate the marginal loss distributions in operational risk management," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3107-3127, February.
    2. Cornalba, Chiara & Giudici, Paolo, 2004. "Statistical models for operational risk management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 166-172.
    3. Silvia Figini & Lijun Gao & Paolo Giudici, 2013. "Bayesian operational risk models," DEM Working Papers Series 047, University of Pavia, Department of Economics and Management.
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