IDEAS home Printed from https://ideas.repec.org/a/aza/ama000/y2021v7i1p47-57.html
   My bibliography  Save this article

How analytics is used in forecasting

Author

Listed:
  • Keating, Barry

    (Professor Emeritus of Finance, University of Notre Dame, USA)

Abstract

Over the last decade, the science of forecasting has adopted the tools of the data scientist. Prediction today combines traditional demand planning models with the standard tools of machine learning. The result is much improved accuracy over the short term and an enhanced ability to account for the effects of major changes in the economic environment. On the flipside, researchers must now sort through much greater volumes of data in order to identify what might be useful to produce accurate forecasts. The application of machine learning solves what could be a major stumbling block here. So-called ‘data consolidators’ are now emerging to support forecasters by providing access to previously unknown data as well as the tools for using such data creatively. This paper will demonstrate how data from data consolidators may be used by analytics algorithms to improve the accuracy of forecasts.

Suggested Citation

  • Keating, Barry, 2021. "How analytics is used in forecasting," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 7(1), pages 47-57, June.
    • Handle: RePEc:aza:ama000:y:2021:v:7:i:1:p:47-57
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/6423/download/
    Download Restriction: Requires a paid subscription for full access.
    File URL: https://hstalks.com/article/6423/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    analytics; forecasting; classification; prediction; supply chain; demand planning;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    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:aza:ama000:y:2021:v:7:i:1:p:47-57. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Henry Stewart Talks (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.