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Less Is More: Harnessing Product Substitution Information to Rationalize SKUs at Intcomex

Author

Listed:
  • Patxi J. Bernales

    (Intcomex Panama, Panama City, Panama)

  • Yongtao Guan

    (School of Business Administration, University of Miami, Coral Gables, Florida 33146)

  • Harihara Prasad Natarajan

    (School of Business Administration, University of Miami, Coral Gables, Florida 33146)

  • Patricia Souza Gimenez

    (Teva Pharmaceutical Industries, Miami, Florida 33137)

  • Mario Xavier Alvarez Tajes

    (Intcomex Uruguay, Montevideo, 11800 Uruguay)

Abstract

Intcomex, a large global distributor of information technology products, was experiencing severe stress in its supply chain from a rapidly expanding set of products in its catalog. The company proactively partnered with an academic team to develop a data-driven approach to address this issue. Rather than adopt potentially suboptimal rules of thumb for product selection (and exclusion), the project team developed a composite method for rationalizing stock-keeping units (SKUs). This approach allows the company to statistically estimate product demand and product substitution using profit-based optimization of the product selection decision. Intuitively, the approach seeks to leverage the company’s ability to substitute products by eliminating low-profit SKUs for which substitutes are available. It accounts for all costs incurred over a product’s life cycle, incorporates other important contextual considerations, and delivers tailored recommendations for each product category and geographical market. We implemented the composite method as two software modules—one for statistical estimation and one for assortment optimization. Using the software tools of the composite method on a product category in the company’s Uruguay operations, we generated an 18 percent increase in profits from rationalizing the company’s product catalog. Despite the streamlined catalog, more than 97.5 percent of the product demand was served; in addition, revenues increased because of the better match between supply and demand.

Suggested Citation

  • Patxi J. Bernales & Yongtao Guan & Harihara Prasad Natarajan & Patricia Souza Gimenez & Mario Xavier Alvarez Tajes, 2017. "Less Is More: Harnessing Product Substitution Information to Rationalize SKUs at Intcomex," Interfaces, INFORMS, vol. 47(3), pages 230-243, June.
    • Handle: RePEc:inm:orinte:v:47:y:2017:i:3:p:230-243
    DOI: 10.1287/inte.2017.0889
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    References listed on IDEAS

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    1. Ravi Anupindi & Maqbool Dada & Sachin Gupta, 1998. "Estimation of Consumer Demand with Stock-Out Based Substitution: An Application to Vending Machine Products," Marketing Science, INFORMS, vol. 17(4), pages 406-423.
    2. Julie Ward & Bin Zhang & Shailendra Jain & Chris Fry & Thomas Olavson & Holger Mishal & Jason Amaral & Dirk Beyer & Ann Brecht & Brian Cargille & Russ Chadinha & Kathy Chou & Gavin DeNyse & Qi Feng & , 2010. "HP Transforms Product Portfolio Management with Operations Research," Interfaces, INFORMS, vol. 40(1), pages 17-32, February.
    3. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    4. Siddharth Mahajan & Garrett van Ryzin, 2001. "Stocking Retail Assortments Under Dynamic Consumer Substitution," Operations Research, INFORMS, vol. 49(3), pages 334-351, June.
    5. Andrés Musalem & Marcelo Olivares & Eric T. Bradlow & Christian Terwiesch & Daniel Corsten, 2010. "Structural Estimation of the Effect of Out-of-Stocks," Management Science, INFORMS, vol. 56(7), pages 1180-1197, July.
    6. Selçuk Karabati & Bariş Tan & Ömer Öztürk, 2009. "A method for estimating stock-out-based substitution rates by using point-of-sale data," IISE Transactions, Taylor & Francis Journals, vol. 41(5), pages 408-420.
    7. Garrett van Ryzin & Siddharth Mahajan, 1999. "On the Relationship Between Inventory Costs and Variety Benefits in Retail Assortments," Management Science, INFORMS, vol. 45(11), pages 1496-1509, November.
    8. A. Gürhan Kök & Marshall L. Fisher, 2007. "Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application," Operations Research, INFORMS, vol. 55(6), pages 1001-1021, December.
    9. Stephen A. Smith & Narendra Agrawal, 2000. "Management of Multi-Item Retail Inventory Systems with Demand Substitution," Operations Research, INFORMS, vol. 48(1), pages 50-64, February.
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    Cited by:

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    2. Andrade, Xavier & Guimarães, Luís & Figueira, Gonçalo, 2021. "Product line selection of fast-moving consumer goods," Omega, Elsevier, vol. 102(C).

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