Planning and Forecasting 4 – The Truth Plays Out

As Campbell's Soup learned, no matter how capable and experienced its planners are, their plan is only as good as the information that feeds it. The big "a-ha!" moment at Campbell's Soup came when the S&OP process illustrated exactly how broken many of the company's processes were throughout the organization—from finance to commercialization to label design, custom pack planning, and transportation. S&OP provides a heightened level of transparency to the extent that, over time, as Mastroianni puts it, "the truth plays out." By bringing all of Campbell's business plans into a single, integrated set of plans—the end game of an S&OP initiative—the company was ultimately able to fix a dozen or more major processes.

Sales and operations planning (S&OP) aligns all of a company's business plans (customers, sales and marketing, research and development, production, sourcing, and financial) into a single, integrated set of plans. The end goal is a plan that more accurately forecasts supply and demand.

For instance, Campbell's has improved by as much as 50 percent the weekly accuracy of the item-level signals sent to its manufacturing plants, which resulted in an immediate benefit: The company can now better plan how many trucks it needs to replenish its distribution centers with product. That increased level of accuracy has also paid off by reducing how often Campbell's has to use expedited shipping to make up for not having the right products at its customers at the right time.

Taking it a step further, Campbell's has leveraged its precision of accuracy to provide improved visibility to its warehouses and manufacturing plants. The company has used its long-range planning capabilities to prebuy transportation with some of its carriers. It's also used those forecasts for labor management, specifically in determining when to add extra crews to its warehouses and when to cut back.

There's one last benefit to the best practices Campbell's uses for its supply chain planning: "It makes me sleep real good at night," Mastroianni says. "It's no fun getting your head handed to you."

END-TO-END INTEGRATION

The key to Campbell's S&OP program was being able to integrate all of those different departments and processes into one central plan, and that strategy can be applied in any company in any industry. At computer giant IBM Corp., for instance, integration is not only a key best practice for the company, it's included in the very name of its supply chain organization, the Integrated Supply Chain (ISC).

In 2003, IBM completed an end-to-end integration project that connects all of its business processes and supporting systems into the ISC, an organization employing 19,000 people at more than 50 locations worldwide. The ISC comprises manufacturing, procurement, logistics, distribution, customer ordering, and planning and scheduling— the whole nine yards of supply chain processes.

"There are many factors in supply chain planning," observes Rich Hume, vice president of operations and strategy with the ISC. "Every proposed idea or change at IBM must meet certain criteria. Initiatives must improve customer satisfaction, increase the flexibility of the supply chain, improve economics, and improve functional excellence. Proposals must be executable and include measurable economic results."

Most of IBM's supply chain planning is done internally, involving such departments as logistics, fulfillment, manufacturing, and manufacturing engineering, as well as functional experts in the company's business consulting and business transformation groups.

"In other companies, these professionals are typically aligned with corporate functions like procurement or logistics," Hume notes. "Having them in one organization allows us to take advantage of their expertise within each function, while also benefiting from their integration across the supply chain."

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....

Planning and Forecasting - Part 2 - A Bias Against Smart Planning

Cisco's supply chain planning suffered from a common malady that afflicts many companies—bias. It's a pattern of behavior within a company where different departments focus on their own individual priorities, often disregarding the overall health of the company in favor of propping up their own fiefdoms. A good supply chain plan will fail every time, for instance, if employees are being given incentives to avoid stock-outs, and as a result keep building up the safety stock. Because employees are not being penalized for making too much—in some companies, the only unpardonable sin is to be caught short—the importance of the overall supply chain plan ends up taking a backseat to the size of one's weekly paycheck. When it comes to protecting and keeping their jobs, employees learned long ago that management will rarely punish those who tell them what they want to hear.

In Cisco's case, forecasting growth had been the right answer for more than 10 years, so it seemed the most natural thing in the world to keep going forward, even when it started to look like the boom days were over.

"There's a growth bias built into the business of forecasting," explains Ajay Shah, a former director of Solectron Corp., one of Cisco's major suppliers and one of the companies that got caught up in the undertow when too many unwanted electronics products started to flood the marketplace. "People see a shortage and intuitively they forecast higher." That kind of growth bias leads to the unwritten rule of forecasting demand that says, "Err on the side of needing more, not less."

Forecasts need to make sense, adds Si Gutierrez, vice president of central planning and production control with chipmaker National Semiconductor Corp. A big part of forecasting at National involves an analysis of general economic conditions. He uses the cell phone industry as an example: "If the forecast says we'll need 20 percent more chips, we ask, 'Does that make sense, given current market conditions?' Everyone can agree that's a reasonable expectation for total market growth. The challenge comes in meeting with major players in the industry. Everyone wants to win and everyone's planning for success, so they add 30 percent. But not everyone wins. If you add up all the players in the industry, you might double a realistic forecast," he explains.

Ultimately, in the wake of the economic downturn in 2001, Cisco ended up with far more products than it could ever sell. How much more? The company wrote off $2.2 billion worth of unsaleable, unusable inventory and reported a $2.6 billion quarterly loss. Although Cisco had gained the reputation of being the supply chain poster child for the New Economy, it reacted to the supply chain glitch in a typically Old Economy fashion: The company laid off 8,500 employees.

More to come tomorrow...