The potential ramifications of errors in a company's forecast are clear: A company may face declining customer satisfaction, loss of revenue, and, sometimes as a consequence, additional cost stemming from carrying increased inventory used as safety stock. The resulting pressure to improve forecasting accuracy is perhaps most keenly felt by companies in the often volatile consumer products market...
The potential ramifications of errors in a company’s forecast are clear: A company may face declining customer satisfaction, loss of revenue, and, sometimes as a consequence, additional cost stemming from carrying increased inventory used as safety stock. The resulting pressure to improve forecasting accuracy is perhaps most keenly felt by companies in the often volatile consumer products market where consumer allegiance can shift quickly.
While consumer products manufacturers typically employ sophisticated forecasting solutions, there are additional ways they can further improve forecast accuracy. For instance, last spring, Procter & Gamble and Unilever both announced they will deploy a demand sensing solution from Terra Technology, a supplier of demand sensing and inventory optimization solutions used by consumer products companies. The Demand Sensing solution uses pattern recognition mathematics to decipher daily data streams to determine which information may be used to predict actual demand, as well as more accurately predict retailer requirements.
"Unilever selected Terra Technology’s Demand Sensing solution to gain supply chain visibility and improve manufacturing planning," says Doug Sloan, director, supply chain operations support for Unilever U.S., Englewood Cliffs, N.J. "In these volatile times, it’s important to respond quickly to shifts in consumer preferences and control costs. Improving forecast accuracy enables Unilever to produce the right product mix, decrease costs, and better serve our customers."
One of the reasons Unilever has been able to build such a strong reputation as a consumer products leader is because it has adopted best-in-class technologies to respond quickly and efficiently to market changes, says Robert F. Byrne, president and CEO of Terra Technology. By implementing Demand Sensing, Byrne says, Unilever will gain visibility into real-time shifts in consumer demand, and therefore be able to quickly respond to demand fluctuation—reducing costs significantly in the process.
While the company is still rolling out the Terra solution, Unilever—a leading supplier of food, home, and personal care products known for brands ranging from Axe, Caress, and Q-Tips, to Ben & Jerry’s, Hellmann’s, Lipton, Popsicle, and Skippy—did conduct a pilot with Demand Sensing a few years ago. Based on that experience, along with reported results from other Terra customers, Unilever expects to reduce forecast error by roughly 25 percent, Sloan says.
"That type of improvement will dramatically reduce both inventory and costs," Sloan says.
Unilever’s plan calls for using the Terra solution to fine-tune its tactical horizon—or the next roughly four weeks, Sloan says. That’s possible because Demand Sensing takes into account a combination of historical data, the existing forecast, and current orders. It then recalculates the forecast every night, allowing Unilever to further smooth out production.
Use of Demand Sensing at Unilever is expected to impact two specific areas targeted for improvement, says Sloan. The first is that the company will be able to carry less inventory, which of course, will improve Unilever’s bottom line.
"The second significant benefit stems from further reducing cost of distribution. When the forecast is more accurate, we’ll be able to more closely match production with demand, so, for example, we won’t need to expedite products from one DC to another to meet local demand," Sloan says. "Instead, we’ll be able to ship directly from a local DC as needed—eliminating the cost of expediting products."
