CPFR Implementation Issues
turban_on_W001-W146-hr
29-01-2009
11:12
Page W-90
Online Brief 10.2
CPFR Implementation Issues
When implementing a CPFR process, the collaborators agree on a standard process, shown in Figure 10.2.1. The process ends with an order forecast. CPFR provides a standard framework for collaborative planning. Retailers and vendors determine the “rules of engagement,” such as how often and at what level information will be provided. Typically, they share greater amounts of more detailed information, such as promotion schedules and item point-of-sale history, and use store-level expectations as the basis for all forecasts. The idea is to improve demand forecasting for all of the partners in the supply chain and then communicate forecasts using information-sharing applications (already developed by technology companies such as Oracle and i2). For the retailer, collaborative forecasting means fewer out-of-stocks and resultant lost sales and less stored inventory. For the manufacturer, collaborative forecasting means fewer expedited shipments, optimal inventory level, and optimally sized production runs. Besides working together to develop production plans and forecasts for stock replenishment, suppliers and retailers also coordinate the related logistics activities (such as shipment or warehousing) using a common language standard and new information methodologies. A 2002 survey found that 67 percent of 43 large food, beverage, and consumer products companies were researching, piloting, or implementing CPFR. About half of the respondents who were looking at CPFR said they planned to go ahead with their initiatives. However, CPFR is not the answer for all trading partners or all types of stock-keeping units (SKUs). According to Tim Paydos, a vice president of marketing at Syncra Systems, CPFR has generated the highest payback with either highly promoted or seasonal goods, whose inventories historically have often been misaligned with demand. “If I’m going to make
29-01-2009
11:12
Page W-90
Online Brief 10.2
CPFR Implementation Issues
When implementing a CPFR process, the collaborators agree on a standard process, shown in Figure 10.2.1. The process ends with an order forecast. CPFR provides a standard framework for collaborative planning. Retailers and vendors determine the “rules of engagement,” such as how often and at what level information will be provided. Typically, they share greater amounts of more detailed information, such as promotion schedules and item point-of-sale history, and use store-level expectations as the basis for all forecasts. The idea is to improve demand forecasting for all of the partners in the supply chain and then communicate forecasts using information-sharing applications (already developed by technology companies such as Oracle and i2). For the retailer, collaborative forecasting means fewer out-of-stocks and resultant lost sales and less stored inventory. For the manufacturer, collaborative forecasting means fewer expedited shipments, optimal inventory level, and optimally sized production runs. Besides working together to develop production plans and forecasts for stock replenishment, suppliers and retailers also coordinate the related logistics activities (such as shipment or warehousing) using a common language standard and new information methodologies. A 2002 survey found that 67 percent of 43 large food, beverage, and consumer products companies were researching, piloting, or implementing CPFR. About half of the respondents who were looking at CPFR said they planned to go ahead with their initiatives. However, CPFR is not the answer for all trading partners or all types of stock-keeping units (SKUs). According to Tim Paydos, a vice president of marketing at Syncra Systems, CPFR has generated the highest payback with either highly promoted or seasonal goods, whose inventories historically have often been misaligned with demand. “If I’m going to make
References: Extreme Networks, “Cybex International Gets Its Network In Shape with Extreme Networks,” 2005, extremenetworks. com/libraries/casestudies/Cybex_CS.asp (accessed October 2006). Sullivan, M., C. Gustke, and N. Hutheesing, “Case Studies: Digital Do-Overs,” Forbes.com, October 7, 2002. W-94