Nestlé drives bottom-line improvements with SAS® Demand-Driven Forecasting

Nestlé Direct Store Delivery improved forecasting accuracy four percentage points and increased service levels with help from SAS Demand-Driven Forecasting. Despite growing revenues, the company is able to hold inventory costs flat, and its sales force can better plan profitable sales promotions. Company officials say the savings have exceeded expectations.

Customer Success Video

Check out this video to learn more about Nestle and its successes with SAS.

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Geoff Fisher
Director of Supply Chain

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Arnaud Joliff
Director of Supply Chain Integration

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Bill Grah
Senior Manager for Strategic Sourcing

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Wei Tan
Decision Support Manager

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Based in Oakland, CA, Nestlé Direct Store Delivery is a division of Nestlé USA responsible for distributing its pizza and ice cream products to thousands of stores nationwide. It's the largest US frozen distribution store delivery network, carrying brands like Dreyer's and Edy's Grand ice creams and DiGiorno and Tombstone pizzas to thousands of stores.

Pizza and ice cream are seasonal and promotion-driven, and variety has exploded in recent years. Twenty years ago, consumers could choose from a dozen pizza varieties and similar number of ice cream flavors. Today, there are whole wheat crusts, gourmet toppings, no-sugar-added ice cream blends and seasonal flavors like pumpkin. With so much variety, shelf space is at a premium, making it critical for producers to ship the right amount of product to the right store at the right time. Meanwhile, Nestlé must make sure product doesn't sit too long at distribution centers, not just to reduce carrying costs but also to provide customers with the freshest, best quality products.

Managing a promotion-driven business
The heavy promotional nature of ice cream and pizza also causes demand to wax and wane by store or region. Before using SAS, Nestlé demand planners struggled to factor in the impact of promotions. The NDSD Supply Chain was also guessing at how much product needed to be stocked for special promotions designed to drive volume – and the sales team on what price to select to maximize profit. "Our existing solutions did a poor job of forecasting demand around promotions," explains Geoff Fisher, Director of Demand and Supply Planning for Nestlé.

Data was also scattered in numerous locations. Some of it was sitting in spreadsheets in regional offices and might get sent in once a week, if that. In the division that handles delivery to drugstore chains (a growing business), forecast accuracy was decreasing by the year. "It was driving a lot of service issues and increasing our carrying costs," explains Bill Grah, Senior Manager for Strategic Sourcing.

Choosing a demand-driven solution
Nestlé wanted a robust, scalable and high-speed solution that didn't require planners to spend the majority of their time administering the data, and a user-friendly reporting system. It was also looking for a vendor known for investing in customer success, and a solution that is workable for a demand planner but also sophisticated enough to be used by a statistician. "At that point the vendor list got pretty short," Fisher says, adding that SAS was the only company that could show it had successfully provided complex, demand-driven forecasting solutions to multiple similar-sized enterprises. As part of the selection process, SAS ran a proof of concept that quickly suggested the potential of the solution.

No second-guessing
"When we switched to SAS, we saw our forecast accuracy improve immediately, we saw service take off in a positive way, and our inventories decreased," says Grah. "We actually exceeded our original projections," says Arnaud Joliff, Director of Supply Chain Integration, adding, "Forecast accuracy improvement drives safety stock, inventory days on hand, storage costs and freight costs reduction. By gaining a few points of accuracy at the national level you can generate supply chain savings immediately." The accurate forecasts have even benefited areas such as efficient route planning.

The accuracy is driven by a change from a 50,000-foot view of forecasts to a more detailed look. "We can talk about a particular deal with a retailer and know what kind of lift is generated, and then that drives the supply chain," Grah says. "There is no second-guessing."

Creating synergy between sales and planning
SAS Demand-Driven Forecasting interacts with the Nestlé sales team's promotional planning system. The sales team will enter in its promotion details and SAS will project the associated lifts. These promotional plans are then used to drive the forecast used by the supply chain group to ensure product is available to meet consumer demand. The sales teams have the capability to measure the impact of in-store merchandising vehicles like end cap displays to determine the incremental unit volume impact, as well as revenue impact within designated market channels (e.g., retail grocery channel).

Using SAS, the demand planners can make calculations and let salespeople know, for instance, that there isn't enough pepperoni in the pipeline near their territory to meet the estimated volume that the promotion will generate, and then work with sales to find a better promotion. They can also help sales calculate the lift for a promotion, and whether that sales increase – at that price – will make the promotion profitable. "It takes the subjectivity out of it," Grah says.

Critical to this service is that Fisher's staff doesn't need an entire weekend – or even an afternoon – to compute the data, including tens of thousands of time series calculations. When it took a long time to run data, information was released on a rigid schedule and was sometimes out of date. With SAS, it takes a few minutes to update information, so planners can publish as they update. "It's a better answer that gets out faster," Fisher says.

Achieving lasting ROI
Nestlé wants to use SAS to build additional attributes into its forecasts to further enhance the data visibility to sales and promotions. Having a better understanding of competitor activities, weather and event cannibalization on existing sales are some of the areas under review. "We are trying to understand if our promotions are impacting sales of other products," Grah explains.

Fisher says while overall forecast improvement is at four percentage points, some specific forecasting projects netted forecast accuracy increases of 7 percentage points or better.

With confidence in the forecasts, "People are letting that number drive through the whole organization, affecting what we produce, where we're going to ship, all the way up to our top-line financial commitments. This drives all facets of our business," Fisher says.

"With SAS, we're better able to accomplish our goal of right flavor, right time, right store," Fisher says. "It's hard to put a price tag on it, but it is really invaluable in terms of running the business effectively and better serving the customer."

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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