VANTAGE POINT: All Bets are Off in a Recession
By Robert F. Byrne, President and CEO, Terra Technology
"With the recession, all bets are off. Traditional supply chain processes that rely on historic orders can be thrown out the window" -- Lora Cecere, Vice President, Value Chain Services, AMR Research. May 12, 2009
Consumer spending patterns have changed as cost-conscious consumers react to the unprecedented economic upheaval and continued financial insecurity. Consumer products (CP) companies that rely on historical sales patterns as the basis for forecasting are experiencing increased forecast error because consumers are behaving in new ways. Analysts predict that fewer jobs, falling home values and the biggest loss of household wealth on record may limit consumers' ability to spend for years to come. Cost-conscious consumers are turning to discount retailers and club stores in greater numbers and have become more aggressive about making purchases on deal. Former loyal consumers are beginning to trade down to private label and value brands to save money.
Forecast accuracy is declining and, at the same time, it has become more critical as financial pressures mount: Sales are declining, market share is eroding and costs of materials have increased. Total retail sales for the February through April 2009 period were down 9.2 percent from the same period a year ago, with discount retailers showing increased sales while premium stores cut prices or close stores.
CP manufacturers have the data to increase forecast accuracy and cut costs despite the current economic uncertainty. Advances in technology have made it possible to track daily information about which products are moving through the supply chain, including point-of-sale (POS) data, shipments, channel inventory and warehouse withdrawals. Manufacturers just need to leverage this efficiently.
Lora Cecere, vice president, Consumer Products at AMR Research, recently wrote, "Although bar code scanning is 40 years old, with CP companies having aspired to use POS data for daily replenishment since its inception, the use of POS data to drive CP company forecasts is now more the exception than the rule. As more North American regional retailers increase data sharing and as data cleansing improves, it's slowly becoming a reality."
POS data is a key source of data for CP companies to create more accurate forecasts. Introducing POS data into the forecasting model gives advance notice of future demand and provides real-time information about what is happening at the retail shelf, replacing an estimate with actual facts about products moving off store shelves.
POS data adds a detailed visibility into recent demand but translating that into an accurate forecast of future demand can be difficult because of the amount of data and the complexity of the supply chains involved. Scan one/make one is not likely to become a reality, nor does it really make sense in many situations like seasonal or promoted items. Combining all of their demand signals into a single accurate response is no longer a luxury for best-in-class manufacturers, it a necessity to weather an unforgiving and volatile economy.
About the Author
Robert F. Byrne has been president and CEO of Terra Technology since co-founding the company in March 2001. Prior to establishing Terra, Byrne led the supply chain consulting practices at J.D. Edwards and Numetrix Ltd. and held management positions at James River and Unilever. Byrne has an MBA with Distinction and an MS in Finance from Carnegie Mellon, and a BS in Civil Engineering and Architecture from Princeton University. Byrne was recently named a "Pro to Know" by Supply & Demand Chain Executive magazine.
"With the recession, all bets are off. Traditional supply chain processes that rely on historic orders can be thrown out the window" -- Lora Cecere, Vice President, Value Chain Services, AMR Research. May 12, 2009
Consumer spending patterns have changed as cost-conscious consumers react to the unprecedented economic upheaval and continued financial insecurity. Consumer products (CP) companies that rely on historical sales patterns as the basis for forecasting are experiencing increased forecast error because consumers are behaving in new ways. Analysts predict that fewer jobs, falling home values and the biggest loss of household wealth on record may limit consumers' ability to spend for years to come. Cost-conscious consumers are turning to discount retailers and club stores in greater numbers and have become more aggressive about making purchases on deal. Former loyal consumers are beginning to trade down to private label and value brands to save money.
Forecast accuracy is declining and, at the same time, it has become more critical as financial pressures mount: Sales are declining, market share is eroding and costs of materials have increased. Total retail sales for the February through April 2009 period were down 9.2 percent from the same period a year ago, with discount retailers showing increased sales while premium stores cut prices or close stores.
CP manufacturers have the data to increase forecast accuracy and cut costs despite the current economic uncertainty. Advances in technology have made it possible to track daily information about which products are moving through the supply chain, including point-of-sale (POS) data, shipments, channel inventory and warehouse withdrawals. Manufacturers just need to leverage this efficiently.
Lora Cecere, vice president, Consumer Products at AMR Research, recently wrote, "Although bar code scanning is 40 years old, with CP companies having aspired to use POS data for daily replenishment since its inception, the use of POS data to drive CP company forecasts is now more the exception than the rule. As more North American regional retailers increase data sharing and as data cleansing improves, it's slowly becoming a reality."
POS data is a key source of data for CP companies to create more accurate forecasts. Introducing POS data into the forecasting model gives advance notice of future demand and provides real-time information about what is happening at the retail shelf, replacing an estimate with actual facts about products moving off store shelves.
POS data adds a detailed visibility into recent demand but translating that into an accurate forecast of future demand can be difficult because of the amount of data and the complexity of the supply chains involved. Scan one/make one is not likely to become a reality, nor does it really make sense in many situations like seasonal or promoted items. Combining all of their demand signals into a single accurate response is no longer a luxury for best-in-class manufacturers, it a necessity to weather an unforgiving and volatile economy.
About the Author
Robert F. Byrne has been president and CEO of Terra Technology since co-founding the company in March 2001. Prior to establishing Terra, Byrne led the supply chain consulting practices at J.D. Edwards and Numetrix Ltd. and held management positions at James River and Unilever. Byrne has an MBA with Distinction and an MS in Finance from Carnegie Mellon, and a BS in Civil Engineering and Architecture from Princeton University. Byrne was recently named a "Pro to Know" by Supply & Demand Chain Executive magazine.