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Evaluating Heuristics Used When Designing Product Costing Systems


  • Ramji Balakrishnan

    () (Tippie College of Business, University of Iowa, Iowa City, Iowa 52242)

  • Stephen Hansen

    () (School of Business, The George Washington University, Washington, DC 20052)

  • Eva Labro

    () (Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599)


The academic and practitioner literature justifies firms' use of product costs in product pricing and capacity planning decisions as heuristics to address an otherwise intractable problem. However, product costs are the output of a cost reporting system, which itself is the outcome of heuristic design choices. In particular, because of informational limitations, when designing cost systems firms use simple rules of thumb to group resources into cost pools and to select drivers used to allocate the pooled costs to products. Using simulations, we examine how popular choices in costing system design influence the error in reported costs. Taking information needs into account, we offer alternative ways to translate the vague guidance in the literature to implementable methods. Specifically, we compare size-based rules for forming cost pools with more informationally demanding correlation-based rules and develop a blended method that performs well in terms of accuracy. In addition, our analysis suggests that significant gains can be made from using a composite driver rather than selecting a driver based on the consumption pattern for the largest resource only, especially when combined with correlation-based rules to group resources. We vary properties of the underlying cost structure (such as the skewness in resource costs, the traceability of resources to products, the sharing of resources across products, and the variance in resource consumption patterns) to address the generalizability of our findings and to show when different heuristics might be preferred. This paper was accepted by Stefan Reichelstein, accounting.

Suggested Citation

  • Ramji Balakrishnan & Stephen Hansen & Eva Labro, 2011. "Evaluating Heuristics Used When Designing Product Costing Systems," Management Science, INFORMS, vol. 57(3), pages 520-541, March.
  • Handle: RePEc:inm:ormnsc:v:57:y:2011:i:3:p:520-541

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    References listed on IDEAS

    1. Foster, George & Gupta, Mahendra, 1990. "Manufacturing overhead cost driver analysis," Journal of Accounting and Economics, Elsevier, vol. 12(1-3), pages 309-337, January.
    2. Verrecchia, Robert E., 1990. "Information quality and discretionary disclosure," Journal of Accounting and Economics, Elsevier, vol. 12(4), pages 365-380, March.
    3. Jordan, J S, 1989. "The Economics of Accounting Information Systems," American Economic Review, American Economic Association, vol. 79(2), pages 140-145, May.
    4. Marshall Fisher & Kamalini Ramdas & Karl Ulrich, 1999. "Component Sharing in the Management of Product Variety: A Study of Automotive Braking Systems," Management Science, INFORMS, vol. 45(3), pages 297-315, March.
    5. Eva Labro & Mario Vanhoucke, 2008. "Diversity in Resource Consumption Patterns and Robustness of Costing Systems to Errors," Management Science, INFORMS, vol. 54(10), pages 1715-1730, October.
    6. Jayashankar M. Swaminathan & Sridhar R. Tayur, 1998. "Managing Broader Product Lines through Delayed Differentiation Using Vanilla Boxes," Management Science, INFORMS, vol. 44(12-Part-2), pages 161-172, December.
    7. Xavier Vives, 1990. "Trade Association Disclosure Rules, Incentives to Share Information, and Welfare," RAND Journal of Economics, The RAND Corporation, vol. 21(3), pages 409-430, Autumn.
    8. E. Labro & M. Vanhoucke, 2005. "A simulation analysis of interactions between errors in costing system design," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/333, Ghent University, Faculty of Economics and Business Administration.
    9. Langberg, Nisan & Sivaramakrishnan, K., 2008. "Voluntary disclosures and information production by analysts," Journal of Accounting and Economics, Elsevier, vol. 46(1), pages 78-100, September.
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    Cited by:

    1. Sina Hocke & Matthias Meyer & Iris Lorscheid, 2015. "Improving simulation model analysis and communication via design of experiment principles: an example from the simulation-based design of cost accounting systems," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 26(2), pages 131-155, August.
    2. repec:kap:rqfnac:v:51:y:2018:i:2:d:10.1007_s11156-017-0678-1 is not listed on IDEAS
    3. Eva Labro, 2015. "Using simulation methods in accounting research," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 26(2), pages 99-104, August.
    4. Balakrishnan, Ramji & Penno, Mark, 2014. "Causality in the context of analytical models and numerical experiments," Accounting, Organizations and Society, Elsevier, vol. 39(7), pages 531-534.
    5. Stephan Leitner & Friederike Wall, 2015. "Simulation-based research in management accounting and control: an illustrative overview," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 26(2), pages 105-129, August.


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