Moving to reduce inventory while maintaining customer service levels, agribusiness Syngenta needed accurate demand forecasts. But first the company had to put a forecasting process in place.
Forecasting demand, as much an art as a science, is never easy in the best of circumstances. But Greensboro, N.C.-based Syngenta Crop Protection faced at least one major hurdle in forecasting North American demand for its fungicides, herbicides and insecticides, according to Richard Herrin, manager for NAFTA planning and forecasting at the company: "We didn't have a forecasting process."
Now the company has undertaken an initiative to implement just such a process and to provide its employees with the necessary forecasting tools as part of Syngenta's drive to maintain its customer service levels while driving down its working-capital requirements.
Mostly Seasonal, With Variable Demand
Syngenta Crop Protection is a $2.3 billion business in North America, based on 2002 sales, and a $6.2 billion business globally. With 19,000 employees in 90 countries, including 4,300 in the North American Free Trade Agreement (NAFTA) region, the company is headquartered in Basel, Switzerland. Syngenta sells its fungicides, herbicides and insecticides to distributors and dealers, who then sell to growers.
The agribusiness market, and Syngenta's segment of that market in particular, offers a challenging environment for demand forecasters. Syngenta produces the active ingredients (AIs) with a two-year lead-time. The company distributes these AIs to various regional divisions, which formulate and package local variations of its products (stock keeping units — SKUs) in accordance with the local requirements and regulations. The challenge for the local units has been to manufacture enough of each particular product to meet demand, even though, absent a formal forecasting process, the production side of the business did not have a clear picture of actual demand.
In the past, Syngenta employed a "top down" business planning process for generating sales goals and production targets. The company's finance group would generate quarterly sales estimates and set targets for the sales staff. On the manufacturing side, the company's production planners would blow out those targets to determine how much of each SKU to produce. The catch, of course, was that without accurate demand forecasts, the company found itself making to stock and loading up on inventory to ensure that they could meet fluctuations in customer demand and minimize orders lost due to out-of-stock product. Inevitably, the mix of goods that Syngenta produced in line with the sales goals would not be the mix of goods that wound up selling, and at the end of the January-May production cycle, the company typically found itself with excess inventory. "We had huge inventories out there," Herrin says, adding that the company's inventory turns were about one-and-a-half per year. And it's no wonder, given the highly seasonal nature of the company's sales and production cycle, the agricultural market's perennially high demand variability and customer delivery expectations of less than one week (and frequent cases in which two-day delivery had to be guaranteed).
On top of these challenges, Syngenta, like other companies in this extremely competitive segment, faced the imperative to minimize its working capital needs while maintaining its high customer service levels. To get better control of its inventories, Syngenta elected to undertake a major sales and operations planning (S&OP) initiative. Trouble was, S&OP uses inventory control models to affect working capital requirements, and the basic inputs into the inventory control models are accurate demand forecasts, but, as noted above, Syngenta did not have in place a forecasting process to gather those inputs.
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