Forecasting Demand with Point of Sales Data-A Case Study of Fashion Products

By Sichel, Bill | The Journal of Business Forecasting, Winter 2008 | Go to article overview

Forecasting Demand with Point of Sales Data-A Case Study of Fashion Products


Sichel, Bill, The Journal of Business Forecasting


The retail industry is faced with increasingly shorter lead times due to changing customer-supplier relationships and overall competitive and profitability pressures. Many retailers utilize weekly POS data to improve forecasting accuracy of their products by store location. In this article we describe methods to improve weekly demand forecasts by using the Point of Sales (POS) data. This data, which represents retail store sales to their final consumers, are captured electronically from retail accounts. In forecasting consumer demand trends, POS data represents the most current indicator of actual consumer demand; in fact, it is the first indicator of changes in consumer demand patterns. In consideration of lead times and the potential short duration of trends, the fashion industry requires a weekly forecasting technique, which detects early changes in consumer demand so that it can quickly respond by revising forecasts, as well as production plans.

The Monet Group, acquired by Liz Claiborne, is the world leader in the design, production, and distribution of costume jewelry. End customers include most large retailers such as Macy's (USA), Breuninger (Germany), Harrods (UK), Galeries Lafayette (France), and De Bijenkorf (Holland), as well as many other smaller retail outlets.

METHODOLOGY

POS data is transferred via EDI (Electronic Data Interchange), which is to say, it is transferred by way of computer-to-computer data transfers. Retail POS data is transmitted from retail stores to our computer facility once each week. The POS data is modeled for seasonality patterns and then an annual (single number) forecast of expected sales to POS accounts is produced which is then broken down into 52 weekly periods. The derived annual forecast of retail POS sales is inflated for non-POS customers, suchas international and military customers. Due to the difference in seasonality between retail POS sales and shipments from the distribution facility, the inflated annual estimate of POS sales is re-seasonalized into monthly buckets based on seasonality patterns derived from historical shipping patterns.

EXPECTATIONS FROM IMPROVED FORECASTS

The expectations from improved forecasts both by vendors and customers are:

* Lower Inventory Cash Flow, which will allow for increased expenditures in areas such as advertising and in-store displays to further promote sales.

* Minimum store-level stock outs (lost sales) with a rapid vendor replenishment system.

* Maximum resource utility under constrained production environment by producing the right product at the right time.

HANDLING THE SEASONAL COMPONENT OF A FORECAST

There are five components of a forecast: baseline, seasonality, promotions, events, and outliers. This article, however, discusses only the seasonality component of the entire forecast process. The procedure discussed here can be easily programmed into an automated system - particularly if it is written in a user-friendly programming language.

The costume jewelry business is a highly seasonal business. Therefore, the first step here should be to aggregate POS data to a highest product level by adding up all product items with similar characteristics. In the costume jewelry industry, products are categorized by pierced earrings, clip earrings, necklaces, bracelets, color pierced earrings, etc. This is called category level categorization (in comparison to the brand level, which would be a higher level, or the subcategory level, which would be lower). After aggregation along the product line, the weekly POS data needs to be aggregated into monthly buckets. Figure 1 gives the monthly seasonal indexes of POS data of two categories - Metal Pierced Earrings and Color Pierced Earrings. …

The rest of this article is only available to active members of Questia

Sign up now for a free, 1-day trial and receive full access to:

  • Questia's entire collection
  • Automatic bibliography creation
  • More helpful research tools like notes, citations, and highlights
  • A full archive of books and articles related to this one
  • Ad-free environment

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items

Items saved from this article

This article has been saved
Highlights (0)
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

Citations (0)
Some of your citations are legacy items.

Any citation created before July 30, 2012 will labeled as a “Cited page.” New citations will be saved as cited passages, pages or articles.

We also added the ability to view new citations from your projects or the book or article where you created them.

Notes (0)
Bookmarks (0)

You have no saved items from this article

Project items include:
  • Saved book/article
  • Highlights
  • Quotes/citations
  • Notes
  • Bookmarks
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Sign up now to cite pages or passages in MLA, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

1

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited article

Forecasting Demand with Point of Sales Data-A Case Study of Fashion Products
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Help
Full screen

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Sign up now to cite pages or passages in MLA, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    Thanks for trying Questia!

    Please continue trying out our research tools, but please note, full functionality is available only to our active members.

    Your work will be lost once you leave this Web page.

    For full access in an ad-free environment, sign up now for a FREE, 1-day trial.

    Already a member? Log in now.