Planning - Part 3 - Soup and S&OP

So how does a company overcome the inherent bias that seems to trip up even the best-laid plans? When Mike Mastroianni joined Campbell Soup Co. in 2001, he saw many of the same cultural inhibitors to good forecasts that had stymied Cisco's planners. Brought in to oversee a sales and operations planning (S&OP) initiative at the world's leading soupmaker, he found a supply chain that had become complacent, focused too much on managing internal costs and not enough on customer service.

"For Campbell's, like a lot of companies, manufacturing was king," explains Mastroianni, vice president of North American planning and operations support. Manufacturing was in a position to second-guess the forecasts, thanks largely to the fact that some people had worked in that department for 30 years and had a historical perspective on how the market fluctuated. Mastroianni's mission, however, was to realign the supply chain to facilitate the introduction of new products. "We had become complacent," he says, and to turn things around, forecast accuracy had to get a lot better.

The average error rate of forecasts in the consumer packaged goods industry is about 50 percent, but Campbell's wasn't going to get too far if it merely maintained the status quo. "We decided to focus in on forecast accuracy, which meant we had to change the behavior of bias," Mastroianni explains. "People used to get their heads handed to them" for missing their numbers, so they tended to over-forecast. As a result, they drove inventories up, as well as the costs of obsolescence, warehousing, expedited shipping, and everything else that was affected by overly optimistic forecasts.

How is a forecast created? No, they're not made up out of the thin air, as some wags have observed. Campbell's, like many other companies, uses a traditional S&OP consensus process, which triangulates between sales, marketing, and demand planning. These three groups get together to agree on a number. That forecast number ultimately ends up going to the general manager for endorsement.

"Instead of aiming for a single demand figure, progressive companies have turned to forecasting a range of potential outcomes," explains Yossi Shefli, director of the MIT Center for Transportation & Logistics. "They estimate the likely range of future demand, and use the low end and high end to guide contracting terms and contingency plans." The goal of this range forecasting is to get companies to widen their planning horizons.

Even after consensus planning, though, the odds are pretty good that a company is not going to hit that number, which makes it all the more important that a system of open and ongoing dialogue is in place.

NO TIME LIKE THE REAL TIME

One element driving Campbell's need for better forecasts is its collaborative planning, forecasting, and replenishment (CPFR) efforts with key retail customers. "We were forecasting at a very high level, based on history," Mastroianni says, but to get to a truly collaborative relationship with its customers, the company had to be able to restate its history more frequently than once a month. Because CPFR requires manufacturers and retailers to share point-of-sale data over the Internet in real time, inaccurate forecasts only hasten the distillation of bad information.

"What fuels S&OP is facts," he observes. That meant Campbell's needed to put Key Performance Indicators (KPIs) in place to hold people accountable, as well as measure improvements in forecast accuracy. Mastroianni's team turned to a real-time forecasting tool capable of creating daily, short-term forecasts with 52 weeks of live data. Being able to forecast in real time allows Campbell's to track patterns that used to go undetected. The system might say, for instance, "Forget about the order today as it relates to your forecast. You need to be thinking about the next seven to fourteen days because, based on this current pattern, your next month is going to look like this," he explains. "Or it might say, 'You're holding on to a forecast that just isn't going to happen. So let it go, and produce to this lower number.'"

At National Semiconductor, the production group meets with the demand planning group weekly to review the forecast. "We gauge the effectiveness of forecasting at a high level rather than on each of our 15,000 chips," notes Si Gutierrez. "We also look at how we're scheduling orders compared to how customers requested them and fix any mismatches." Like Campbell's, National Semiconductor looks at a number of KPIs (e.g., how close the company's production matches up with the forecast) and then analyzes the difference between forecast and performance.

National's supply chain planning starts with an annual plan, and once that's in place, the staff looks at forecasting for each month, planning six months ahead, Gutierrez explains. "Sometimes we're surprised. Something we thought would do just okay goes like gangbusters. So we monitor the plan weekly and can revamp it weekly. Each day, we plan factory starts based on what happened the previous day. This allows us to maximize customer service and optimize inventory to maintain customer service levels."

To be continued tomorrow....