Practical Management Science
Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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How does a food company forecast demand for its meat snack and sausage products? Oberto Sausage, an 85-year-old family business in Washington State, sells beef jerky and other packaged meat products, such as pork rinds and smoked sausage sticks, directly  to

 mass merchandisers and supermarket chains. Oberto has been enjoying double-digit growth. The company has also been expanding its consumer marketing efforts into the digital realm; it recently concluded a successful sweepstakes promotion that invited participants to text in their entries from their cell phones. Growing demand means accurate forecasting is critical to Oberto’s ability to provide a steady supply of fresh products to the right places at the right time. Forecasting also ensures Oberto has the necessary ingredients and packaging available to fill orders on time. In its recent search for a new computer-based forecasting system, the company looked for a way to create a model of routine and ongoing “base” demand, incorporate and keep track of changes it made to the model, forecast general demand and demand for specific market segments, input human judgment, and finally keep costs for the new system in line with the quality of forecasting the company desired. The company chose a suite of software programs from a forecasting software company called Forecast Pro headquartered in Massachusetts. The programs serve as “the main foundation of our demand forecasting process,” says the company’s director of forecasting and planning. “It’s where the forecast is generated and maintained. After we establish the forecast, it is fed into our ERP [enterprise resource planning] system where it drives procurement, planning/scheduling, and plant execution. One of our biggest forecasting challenges is really understanding what our true baseline demand is. We start by creating a relatively conservative base forecast that’s statistically driven off history. … To accommodate abnormal conditions in history, things that happened that aren’t expected to happen again in the future—promotions, weather, outliers—we use event models. That’s our starting point.” Despite its reliance on computer models, however, Oberto still brings a big dose of human judgment into its forecasting process at critical points. The company’s demand manager, as well as its customer service representatives, review the computer-generated forecast and make changes their experience and information suggest. “The forecast team interfaces directly with the sales team and often has knowledge of unusual conditions, things that wouldn’t be reflected in the history,” says Oberto’s forecasting director. “Their job is to make sure the forecasting process captures this ‘business as usual.’ … We use our sales team to provide intelligence only when history doesn’t tell us what’s happening—and this approach has worked well. Next, Oberto’s forecast analysts look at what they know about important customers and add available consumption data to the model. They also add unusual events like the sweepstakes promotion. “The forecast analysts concentrate on the 20% of our customers and events that drive 80% of our volume,” says Oberto’s forecasting director. Oberto is getting full value from its forecasting process. Its forecasting director reports, “We’ve been able to sustain years of doubledigit growth while inventory value has remained constant. We’ve also been able to strategically identify potential gaps in our plans where we may have shortfalls with important customers and move proactively to fill those gaps. Our forecasts are used for everything from planning/scheduling all the way up to revenue projection by the executive team.

Questions for Critical Thinking

1. Why do you think it was important for Oberto to have a computer-based forecasting program that could accept human input and even overrides?

2. What other factors in the company’s external environment, in addition to the ones mentioned in the case, should its executives consider in preparing their demand forecasts?

 

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