Master Competitive Analytics with Oracle Endeca Information Discovery by Helen Sun

Author:Helen Sun
Language: eng
Format: epub
Publisher: McGraw-Hill Education
Published: 2015-01-04T05:00:00+00:00

Demand Forecast

Demand forecast is another area where retailers are trying to better understand customers through the smart use of new data sources. As we discussed earlier in this chapter, a surge in online shopping during the 2013 holiday season left stores breaking promises to deliver packages by Christmas, suggesting that retailers and shipping companies still don’t fully understand consumers’ buying patterns in the Internet era. In addition, new business models are making accurate and timely demand forecast an even more critical success factor.

For example, one well-known sports apparel manufacturer and retailer is changing its go-to-market approach from selling individual items to assortment-based merchandising. In other words, instead of selling shoes and T-shirts separately, they are switching to a model that sells an entire outfit, including matching shoes, socks, hats, shirts, and pants or shorts. The assortments could be sports themed, location based, and season oriented. This changes what, where, and how data is to be sourced and applied in the business processes. A variety of new data sources will be integrated into the system, including social media and survey feedback on new product and assortment development, store layout maps for efficient display planning as well as foot traffic analysis, weather information, and location data with residents’ demographics, local sports teams, and event schedule, all of which to help determine and maximize the operational efficiency for inventory, manufacturing, and logistics planning and management.

Figure 5-5 describes the demand forecast model used at a CPG company to predict the success of various digital initiatives and launches of new products.

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