Tura Eyewear Sees Big Savings Using SmartForecasts for New Product Introductions and Reverse Logistics

“Eyewear is a fashion item,” says John Weir, general manager at Tura Eyewear, an eyewear distributor based in Lake Success, New York. “Our products are changing all the time.” Needless to say this business, with its frequent new product introductions and seasonal fluctuations, poses some interesting demand forecasting challenges for Weir and his brand managers at Tura.

Tura, a 100-year-old company, organizes its product inventory into “collections” and sells them to retail outlets through a network of manufacturer’s representatives. Most of its collections are manufactured in Europe and have a three to six month lead-time. In the eyewear business, retailers expect a 100 percent credit on returns. The challenge for Tura is to introduce new collections to its customers without cannibalizing sales of the old ones. The consequences of not doing this properly are a lot of unusable inventory, an unacceptable level of merchandise credits, and a reduction in profits

The Challenge
“Our biggest challenge,” Weir says, “is to forecast the ‘sell-in’ at the start of a new collection.” Retailers, he explains, have limited shelf space. New collections must replace old ones without cannibalizing sales. To solve the problem, Tura phases in new collections by delivering them to only a portion of its customers at a time. As customers return old product, the impact is netted against ongoing requirements. This process, known as “reverse logistics,” puts a premium on successfully predicting the amount of returned inventory available to meet demand and the timing of its flow. “Our goal is to ensure a soft landing at the end of the product life cycle,” Weir says.

Before using SmartForecasts, Tura was forced to rely on detailed spreadsheets and a fair amount of “dead reckoning” to create its forecasts. The number of variables—SKUs, sizes, colors, seasonal fluctuations, trade promotions—made the job of developing an accurate forecast impractical, if not impossible.

Trade promotions offered to retailers are also an important part of Tura’s business, and generating a demand forecast that adequately reflects their effects adds to the challenge of planning new product introductions. Tura uses SmartForecasts to accurately model the effects of trade promotions. “Promotions are an important part of our business,” Weir says. “If we overlook or incorrectly estimate their impact, we could get into big trouble.”

The Solution
Smart Software worked with Tura to develop special customized procedures, using SmartForecasts’ multidimensional data management and Multiseries forecasting capabilities, to plan the future demand for entire product lines and particularly for “sell-ins.” To generate a forecast, SmartForecasts uses demand data stored in Excel spreadsheets that are generated by brand managers, along with several sets of data in Tura’s SQL Server host database. SmartForecasts is linked directly to the host database, and forecast results produced in SmartForecasts are automatically transferred back to the database where they are placed in SQL Server data tables. From there they can be easily used by other parts of Tura’s planning system. Among other things, the forecast results enable Tura to anticipate which of the older products might be cannibalized by new ones and make appropriate inventory management adjustments.

The Results
SmartForecasts can handle all of Tura’s complex forecasting needs with push-button ease. Weir says that SmartForecasts “has totally revamped the forecasting process, enabling us to adjust for seasonality, offset historical peaks and valleys, and compensate for lead times.”

The financial payoff to Tura from using SmartForecasts has been impressive. Weir estimates that the company has generated annual inventory savings of almost $1.8 million by using SmartForecasts to help plan new product introductions and manage its reverse logistics process.

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