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Sales-Force Decision Models: Insights from 25 Years of Implementation

Author

Listed:
  • Prabhakant Sinha

    (ZS Associates, 1800 Sherman Avenue, Evanston, Illinois 60201)

  • Andris A. Zoltners

    (J. L. Kellogg Graduate School of Management, Northwestern University, Evanston, Illinois 60208, and ZS Associates)

Abstract

Over 25 years, we have developed many sales-force and modeling insights through over 2,000 projects with several hundred selling organizations in over 50 countries. Content insights are useful in making sales-force decisions. Examples are that profitability is flat for a wide range of sales-force sizes; phased sales-force growth is rarely optimal; focused strategies dominate scattered strategies; most sales territories (55 percent) are too large or too small; and no compensation plan satisfies everyone. Implementation insights concern model building, use, and implementation, for example, a model's economic value can come from such sources as reduced uncertainty, accuracy, increased speed, objectivity, and stakeholder involvement; theory and practice have different and complementary perspectives; experience and wisdom are sometimes better than models; and models provide insights, while people make decisions.

Suggested Citation

  • Prabhakant Sinha & Andris A. Zoltners, 2001. "Sales-Force Decision Models: Insights from 25 Years of Implementation," Interfaces, INFORMS, vol. 31(3_supplem), pages 8-44, June.
    • Handle: RePEc:inm:orinte:v:31:y:2001:i:3_supplement:p:s8-s44
    DOI: 10.1287/inte.31.3s.8.9675
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    References listed on IDEAS

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    1. Haofeng Jin & Zhentong Lu, 2021. "Measuring the Effectiveness of Salespeople: Evidence from a Cold-Drink Market," Staff Working Papers 21-40, Bank of Canada.
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    5. Sumitro Banerjee & Alex P. Thevaranjan, 2013. "How to deal with unprofitable customers? A salesforce compensation perspective," ESMT Research Working Papers ESMT-13-05, ESMT European School of Management and Technology.
    6. Meredith B. Rosenthal & Ernst R. Berndt & Julie M. Donohue & Arnold M. Epstein & Richard G. Frank, 2003. "Demand Effects of Recent Changes in Prescription Drug Promotion," NBER Chapters, in: Frontiers in Health Policy Research, Volume 6, pages 1-26, National Bureau of Economic Research, Inc.
    7. Edward I. Brody, 2001. "Marketing Engineering at BBDO," Interfaces, INFORMS, vol. 31(3_supplem), pages 74-81, June.
    8. Du, Shaofu & Wang, Lei & Hu, Li & Zhu, Yangguang, 2019. "Platform-led green advertising: Promote the best or promote by performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 115-131.
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    11. Gahler, Daniel & Hruschka, Harald, 2016. "Resource Allocation Heuristics for Unknown Sales Response Functions with Additive Disturbances," University of Regensburg Working Papers in Business, Economics and Management Information Systems 488, University of Regensburg, Department of Economics.
    12. Milind G. Sohoni & Achal Bassamboo & Sunil Chopra & Usha Mohan & Nuri Sendil, 2010. "Threshold incentives over multiple periods and the sales hockey stick phenomenon," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(6), pages 503-518, September.
    13. Fruchter, Gila E. & Van den Bulte, Christophe, 2011. "Why the Generalized Bass Model leads to odd optimal advertising policies," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 218-230.
    14. Raghuram Iyengar & Christophe Van den Bulte & Jae Young Lee, 2015. "Social Contagion in New Product Trial and Repeat," Marketing Science, INFORMS, vol. 34(3), pages 408-429, May.
    15. Gary L. Lilien & Arvind Rangaswamy & Gerrit H. Van Bruggen & Katrin Starke, 2004. "DSS Effectiveness in Marketing Resource Allocation Decisions: Reality vs. Perception," Information Systems Research, INFORMS, vol. 15(3), pages 216-235, September.
    16. Harikesh S. Nair & Sanjog Misra & William J. Hornbuckle IV & Ranjan Mishra & Anand Acharya, 2017. "Big Data and Marketing Analytics in Gaming: Combining Empirical Models and Field Experimentation," Marketing Science, INFORMS, vol. 36(5), pages 699-725, September.
    17. Xiaojing Dong & Pradeep Chintagunta & Puneet Manchanda, 2011. "A new multivariate count data model to study multi-category physician prescription behavior," Quantitative Marketing and Economics (QME), Springer, vol. 9(3), pages 301-337, September.
    18. Germann, Frank & Lilien, Gary L. & Rangaswamy, Arvind, 2013. "Performance implications of deploying marketing analytics," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 114-128.
    19. Claro, Danny P. & Ramos, Carla & Gonzalez, Gabriel R. & Palmatier, Robert W., 2020. "Dynamic effects of newcomer salespersons' peer relational exchanges and structures on performance," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 74-92.
    20. Daniel Gahler & Harald Hruschka, 2022. "Resource allocation procedures for unknown sales response functions with additive disturbances," Journal of Business Economics, Springer, vol. 92(6), pages 997-1034, August.

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