For more than 80 years, Springs Window Fashions has been keeping North America’s windows covered, providing shades, blinds, and residential and commercial window treatments under a variety of brands, including Bali and Graber. The company has grown steadily through the decades thanks to acquisitions, strong sales, and expanded manufacturing capabilities, and today, the Middleton, Wisconsin-based business employs more than 500 people at its corporate location and 9,000 worldwide.
The task of outfitting and decorating windows has also changed over the years; today’s window treatments now span a vast array of styles, colors, textures, dimensions, and functions. And because window styles change frequently—just like fashion trends in the apparel sector—Springs must monitor millions of possible combinations to meet customer demand.
While that wide array of product offerings may make customers happy, it presents a challenge for the company’s supply chain planners, who must ensure that the right materials, products, and labor are available when needed. The planners’ work is complicated by the fact that a significant portion of Springs’ demand is influenced by consumer promotions—a variable that proved tough for its legacy demand-planning system to handle. In the past, demand planners often spent hours using offline analytics and manual entry adjustments to translate forecasts into operational plans.
But as business grew, company leaders realized that the legacy system just wasn’t going to cut it. They needed a solution that would provide more accurate, detailed forecasts to keep the operation running efficiently.
A MATERIAL UPGRADE
To boost its forecasting capabilities, Springs Window Fashions replaced its legacy forecasting solution with a system from Anaplan, a San Francisco-based developer of cloud-based business planning software and operator of a unified platform for modeling and scenario analysis. For help developing a demand-planning system on the platform to fit its specific requirements, Springs turned to Valizant Solutions, a Long Beach, California-based Anaplan partner firm that adapted Anaplan’s real-time calculation engine to run the programs Springs needed.
As a result of the upgrade, Springs now generates its demand plans four times as frequently as before, with 30% better accuracy and far greater detail, Ed Lewis, president and CEO of Valizant, said in a case study posted on Anaplan’s website. “Before this solution, [Springs] had been challenged to build a fresh [forecast] plan in six weeks sometimes. But during the Covid pandemic, the market situation changed every week,” Lewis said. “Now, it can enter the sales history, new product information, [and] changing fabrics and colors, and account for promotions, including the size of discount, competitive pricing, etc.”
The new platform then crunches the data to improve forecasting accuracy and provide more granular detail. “Now, [the planners] don’t have to hedge and order more inventory, since they can trust the forecast. And they can reduce inventory, avoid wasted capacity, and get better revenue planning,” Lewis noted.
Even better, the upgrade process was completed in just six months, Springs leaders said. “Compared [with] other implementations for our exact same business, Valizant Solutions on Anaplan were up and running in a quarter of the time,” Mickey Klicka, Springs Window Fashions’ manager for financial systems, said in the case study. “And the solution delivered is probably three times as complex.”
With Valizant on Anaplan, Springs has now moved from monthly demand-planning reports to a weekly cycle. And the advantages don’t end there. The company says the solution’s benefits extend beyond the demand-planning department to include its manufacturing facilities, purchasing and inventory management groups, and even its material vendors.
