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Strategic Workforce Planning and sales force : a demographic approach to productivity

Author

Listed:
  • Marie Doumic

    (MAMBA - Modelling and Analysis for Medical and Biological Applications - LJLL - Laboratoire Jacques-Louis Lions - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique - Inria Paris-Rocquencourt - Inria - Institut National de Recherche en Informatique et en Automatique)

  • Mathieu Mezache

    (LJLL - Laboratoire Jacques-Louis Lions - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique, MAMBA - Modelling and Analysis for Medical and Biological Applications - LJLL - Laboratoire Jacques-Louis Lions - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique - Inria de Paris - Inria - Institut National de Recherche en Informatique et en Automatique)

  • Benoît Perthame

    (LJLL - Laboratoire Jacques-Louis Lions - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique, MAMBA - Modelling and Analysis for Medical and Biological Applications - LJLL - Laboratoire Jacques-Louis Lions - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique - Inria de Paris - Inria - Institut National de Recherche en Informatique et en Automatique)

  • Edouard Ribes

    (IRSEM - Institut de recherche stratégique de l'Ecole militaire - Ministère des armées)

  • Delphine Salort

    (LCQB - Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology - UPMC - Université Pierre et Marie Curie - Paris 6 - IBPS - Institut de Biologie Paris Seine - UPMC - Université Pierre et Marie Curie - Paris 6 - INSERM - Institut National de la Santé et de la Recherche Médicale - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

Abstract

Sales force Return on Investment (ROI) valuation with marketing mix frameworks is nowadays common. Sizing discussions then generally follow based on market data and business assumptions. Yet, according to our knowledge, little has been done to embed sales force demographic data (age/experience, tenure, gender etc...) as well as dynamics (especially turnover) in order to investigate the impact of the salesforce characteristics on sales. This paper illustrates such an attempt. It shows that sales force ROI valuation can benefit from a correction on turnover and that optimizing a sales rep hiring policy can unleash additional ROI points. The results are yet heavily dependent in the data structure of the study and their generalization would have to be investigated.

Suggested Citation

  • Marie Doumic & Mathieu Mezache & Benoît Perthame & Edouard Ribes & Delphine Salort, 2017. "Strategic Workforce Planning and sales force : a demographic approach to productivity," Working Papers hal-01449812, HAL.
    • Handle: RePEc:hal:wpaper:hal-01449812
    Note: View the original document on HAL open archive server: https://hal.science/hal-01449812
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    References listed on IDEAS

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    1. Marie Doumic & Benoît Perthame & Edouard Ribes & Delphine Salort & Nathan Toubiana, 2016. "Toward an integrated workforce planning framework using structured equations," Working Papers hal-01343368, HAL.
    2. Kremer, Sara T.M. & Bijmolt, Tammo H.A. & Leeflang, Peter S.H. & Wieringa, Jaap E., 2008. "Generalizations on the effectiveness of pharmaceutical promotional expenditures," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 234-246.
    3. Noah Gans & Yong-Pin Zhou, 2002. "Managing Learning and Turnover in Employee Staffing," Operations Research, INFORMS, vol. 50(6), pages 991-1006, December.
    4. Grosse, Eric H. & Glock, Christoph H. & Müller, Sebastian, 2015. "Production economics and the learning curve: A meta-analysis," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 401-412.
    5. John E. Calfee & Clifford Winston & Randolph Stempski, 2002. "Direct-to-Consumer Advertising and the Demand for Cholesterol-Reducing Drugs," Journal of Law and Economics, University of Chicago Press, vol. 45(S2), pages 673-690.
    6. Gerchak, Yigal & Parlar, Mahmut & Sengupta, S. Sankar, 1990. "On manpower planning in the presence of learning," Engineering Costs and Production Economics, Elsevier, vol. 20(3), pages 295-303, December.
    7. Grosse, E. H. & Glock, C. H. & Müller, Seb., 2015. "Production economics and the learning curve: A Meta-Analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 74127, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Puneet Manchanda & Pradeep K. Chintagunta, 2004. "Responsiveness of Physician Prescription Behavior to Salesforce Effort: An Individual Level Analysis," Marketing Letters, Springer, vol. 15(2_3), pages 129-145, July.
    9. Darmon, Rene Y., 2004. "Controlling sales force turnover costs through optimal recruiting and training policies," European Journal of Operational Research, Elsevier, vol. 154(1), pages 291-303, April.
    10. Gary L. Lilien & Ambar G. Rao & Shlomo Kalish, 1981. "Bayesian Estimation and Control of Detailing Effort in a Repeat Purchase Diffusion Environment," Management Science, INFORMS, vol. 27(5), pages 493-506, May.
    11. Marie Doumic & Beno^it Perthame & Edouard Ribes & Delphine Salort & Nathan Toubiana, 2016. "Toward an integrated workforce planning framework using structured equations," Papers 1607.02349, arXiv.org, revised Dec 2016.
    12. Hewitt, Mike & Chacosky, Austin & Grasman, Scott E. & Thomas, Barrett W., 2015. "Integer programming techniques for solving non-linear workforce planning models with learning," European Journal of Operational Research, Elsevier, vol. 242(3), pages 942-950.
    13. Vakratsas, Demetrios & Kolsarici, Ceren, 2008. "A dual-market diffusion model for a new prescription pharmaceutical," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 282-293.
    14. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    15. Stremersch, Stefan, 2008. "Health and marketing: The emergence of a new field of research," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 229-233.
    16. Qin, Ruwen & Nembhard, David A., 2010. "Workforce agility for stochastically diffused conditions--A real options perspective," International Journal of Production Economics, Elsevier, vol. 125(2), pages 324-334, June.
    17. Desiraju, Ramarao & Nair, Harikesh S. & Chintagunta, Pradeep, 2004. "Diffusion of New Pharmaceutical Drugs in Developing and Developed Nations," Research Papers 1950, Stanford University, Graduate School of Business.
    18. Minhi Hahn & Sehoon Park & Lakshman Krishnamurthi & Andris A. Zoltners, 1994. "Analysis of New Product Diffusion Using a Four-Segment Trial-Repeat Model," Marketing Science, INFORMS, vol. 13(3), pages 224-247.
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    Keywords

    Workforce planning; Marketing mix; Learning curve; Optimal policies; Sales force turnover; Structured population dynamics;
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