IDEAS home Printed from https://ideas.repec.org/a/jof/jforec/v25y2006i5p303-324.html
   My bibliography  Save this article

The evolution of sales forecasting management: a 20-year longitudinal study of forecasting practices

Author

Listed:
  • DONNA F. DAVIS

    (Texas Tech University, Lubbock, Texas, USA)

  • JOHN T. MENTZER

    (University of Tennessee, Knoxville, Tennessee, USA)

  • TERESA M. MCCARTHY

    (College of Business and Economics, Lehigh University, Bethlehem, Pennsylvania, USA)

  • SUSAN L. GOLICIC

    (University of Oregon, Eugene, Oregon, USA)

Abstract

This paper presents results of a survey designed to discover how sales forecasting management practices have changed over the past 20 years as compared to findings reported by Mentzer and Cox (1984) and Mentzer and Kahn (1995). An up-to-date overview of empirical studies on forecasting practice is also presented. A web-based survey of forecasting executives was employed to explore trends in forecasting management, familiarity, satisfaction, usage, and accuracy among companies in a variety of industries. Results revealed decreased familiarity with forecasting techniques, and decreased levels of forecast accuracy. Implications for managers and suggestions for future research are presented. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Donna F. Davis & John T. Mentzer & Teresa M. Mccarthy & Susan L. Golicic, 2006. "The evolution of sales forecasting management: a 20-year longitudinal study of forecasting practices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(5), pages 303-324.
  • Handle: RePEc:jof:jforec:v:25:y:2006:i:5:p:303-324
    DOI: 10.1002/for.989
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/for.989
    File Function: Link to full text; subscription required
    Download Restriction: no

    References listed on IDEAS

    as
    1. DeRoeck, Richard, 1991. "Is there a gap between forecasting theory and practice? A personal view," International Journal of Forecasting, Elsevier, vol. 7(1), pages 1-2, May.
    2. Klassen, Robert D. & Flores, Benito E., 2001. "Forecasting practices of Canadian firms: Survey results and comparisons," International Journal of Production Economics, Elsevier, vol. 70(2), pages 163-174, March.
    3. Mady, M. Tawfik, 2000. "Sales forecasting practices of Egyptian public enterprises: survey evidence," International Journal of Forecasting, Elsevier, vol. 16(3), pages 359-368.
    4. Barry L. Bayus & William P. Putsis, Jr., 1999. "Product Proliferation: An Empirical Analysis of Product Line Determinants and Market Outcomes," Marketing Science, INFORMS, vol. 18(2), pages 137-153.
    5. Mahmoud, Essam & DeRoeck, Richard & Brown, Robert & Rice, Gillian, 1992. "Bridging the gap between theory and practice in forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 251-267, October.
    6. Scott Armstrong, J., 1988. "Research needs in forecasting," International Journal of Forecasting, Elsevier, vol. 4(3), pages 449-465.
    7. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E. & Fildes, Robert & Goodwin, Paul, 2009. "The effects of integrating management judgement into intermittent demand forecasts," International Journal of Production Economics, Elsevier, vol. 118(1), pages 72-81, March.
    2. repec:pal:jorsoc:v:60:y:2009:i:1:d:10.1057_jors.2008.173 is not listed on IDEAS
    3. Davydenko, Andrey & Fildes, Robert, 2013. "Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 510-522.
    4. Davis, Donna F. & Mentzer, John T., 2007. "Organizational factors in sales forecasting management," International Journal of Forecasting, Elsevier, vol. 23(3), pages 475-495.
    5. Smith, Carlo D. & Mentzer, John T., 2010. "Forecasting task-technology fit: The influence of individuals, systems and procedures on forecast performance," International Journal of Forecasting, Elsevier, vol. 26(1), pages 144-161, January.
    6. Asimakopoulos, Stavros & Dix, Alan, 2013. "Forecasting support systems technologies-in-practice: A model of adoption and use for product forecasting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 322-336.
    7. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    8. Hosoda, Takamichi & Disney, Stephen M., 2009. "Impact of market demand mis-specification on a two-level supply chain," International Journal of Production Economics, Elsevier, vol. 121(2), pages 739-751, October.
    9. Song, Haiyan & Gao, Bastian Z. & Lin, Vera S., 2013. "Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system," International Journal of Forecasting, Elsevier, vol. 29(2), pages 295-310.
    10. Victor Richmond R. Jose, 2017. "Percentage and Relative Error Measures in Forecast Evaluation," Operations Research, INFORMS, vol. 65(1), pages 200-211, February.
    11. Robert Rieg, 2010. "Do forecasts improve over time?: A case study of the accuracy of sales forecasting at a German car manufacturer," International Journal of Accounting and Information Management, Emerald Group Publishing, vol. 18(3), pages 220-236, September.
    12. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    13. Chiang, Chung-Yean & Lin, Winston T. & Suresh, Nallan C., 2016. "An empirically-simulated investigation of the impact of demand forecasting on the bullwhip effect: Evidence from U.S. auto industry," International Journal of Production Economics, Elsevier, vol. 177(C), pages 53-65.
    14. Hong Chen, 2010. "Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 310-331, April.
    15. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    16. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
    17. Ranyard, J.C. & Fildes, R. & Hu, Tun-I, 2015. "Reassessing the scope of OR practice: The Influences of Problem Structuring Methods and the Analytics Movement," European Journal of Operational Research, Elsevier, vol. 245(1), pages 1-13.
    18. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
    19. Williams, Brent D. & Waller, Matthew A. & Ahire, Sanjay & Ferrier, Gary D., 2014. "Predicting retailer orders with POS and order data: The inventory balance effect," European Journal of Operational Research, Elsevier, vol. 232(3), pages 593-600.
    20. Xu, Bing & Ouenniche, Jamal, 2012. "A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices' volatility forecasting models," Energy Economics, Elsevier, vol. 34(2), pages 576-583.
    21. Leeuw, S. de & Vis, I.F.A. & Jonkman, S.N., 2009. "Logistics aspects of emergency preparedness in flood disaster prevention," Serie Research Memoranda 0044, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    22. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jof:jforec:v:25:y:2006:i:5:p:303-324. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.