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11.18: Forecasting Sales Numbers

  • Page ID
    45188
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    Learning Objectives

    • Explain how retailers forecast probable sales numbers for merchandise categories

    How do retailers forecast sales numbers for merchandise categories?

    One of the concepts we discussed in the previous module in the merchandise planning process was forecasting sales. The retail planning process begins with a sales plan. Besides sales history and statistics, you need to have an understanding of your overall business in order to plan increases or decreases which will then dictate proper inventory levels.

    Forecasting is also important for a few vital functions within the organization such as human resources, marketing, product management, and operations. It is especially important to product management and operations as they need to understand how much product to produce and warehouse capacity needs!

    The merchandise planner helps determine a sales plan based on data from the previous season and the desired sales goals that fall in line with the company strategy. For example, if I am the merchandise planner for women’s swimwear I might decide to plan sales with an increase of 10% over the prior year because I missed sales the previous season and the industry forecasters predict it will be a strong swimwear season. In addition, I might feel my assortment is even more compelling than last year for a number of reasons including better sizing and more desirable styling based on customer feedback.

    We must also consider those external factors that influence how we forecast our sales numbers. Every year the National Retail Federation provides an annual economic forecast to help guide the industry of the impact that the external environment is expected to have. Take a look at the video below to understand how those factors influence the industry. As you watch the video consider how the stock market, gas prices, consumer spending, the job market, wage growth, and debt plays a role. Would you say any of these factors are more important the other and which of these impact your decision to spend?

    Consider what higher gas prices and a declining job market might mean for retailers that carry luxury items such as expensive handbags and shoes? In a down economy you might find that consumers spend more on basic staple items.

    Some categories of business aren’t affected by a downturn in the economy. For example, the beauty industry doesn’t typically see decreased sales patterns during these times. Since the Great Depression the beauty industry has seen sales growth during hard economic times. Why do you believe this is the case? Studies have shown women want to feel good about themselves at all times so they will continue to spend on these “luxury” products that are more like a necessity. So although money might be extremely limited during these times there is always room in a woman’s wallet for those products that will enhance beauty!

    We can also look at specific retailers that emerge during tough economic times. Wal-Mart is a great example as their net income rose from 2008-2010 after the financial crisis and subprime mortgage. By offering a vast assortment of core products at value prices they were able to achieve sales growth.

    Can you think of any other categories or retailers that aren’t impacted by a down trending economy? Why? How does this impact the decisions the retailer makes?

    A link to an interactive elements can be found at the bottom of this page.

    You can view the transcript for “NRF’s 2015 Retail Sales Forecast” (opens in new window).

    Contributors and Attributions

    CC licensed content, Original
    • Forecasting Sales Numbers. Authored by: Robert Danielson. Provided by: Lumen Learning. License: CC BY: Attribution
    All rights reserved content
    • NRFu2019s 2015 retail sales forecast. Authored by: National Retail Federation. Located at: https://youtu.be/-lMtb_rbBJE. License: All Rights Reserved. License Terms: Standard YouTube License

    11.18: Forecasting Sales Numbers is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by LibreTexts.

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