KPI with Data Flow Analysis for CPFR: A CMC Case Study

The increasingly global operations and supply chains are significant. And the product life cycles are decreasingly shorter. Therefore, to rapidly react to global market immediately and accurately, and to cope with the increase in variability in the supply chains, many enterprises strive to share internal and external information devotedly. CPFR (Collaborative planning, forecasting and replenishment) is one new collaborative commerce model to enable collaborative relationships between buyers and sellers through co-managed processes and shared information. The early adopters of CPFR are retailers and their suppliers to increase the visibility to each other and let the suppliers to exactly replenish goods at right time and accurate quantity. The benefits of developing CPFR for retailers are lower inventory levels, higher fill rates and sales. And the benefits for suppliers are lower order cycle time, better customer service and inventory reductions. CMC is the first one CPFR pilot manufacturer in Taiwan to develop collaboration between CMC and its trading partner, an overseas buyer with well-known brand. The primary products of CMC are optical discs, optical recording media, and compact disc writable. Based on the production environment of CMC, this paper presents the KPI and its data flow for the CPFR system. Before implementing CPFR, the customer demand trends are anticipated from sales interviews with customers, the inventory reports of overseas Hub and factories. And then, develop the master plan according to market demand and historical sales data of each customer. Finally, manufacture and ship the products according to the actual orders. As the demand information is not real time and without customers’ promise, the demand forecast and actual orders are different. Accordingly, unnecessary inventory, inventory carrying costs and warehousing costs are increasing. After implementing CPFR, CMC and buyer can collaborate planning, forecasting and replenishment in accordance with the demand forecast. Besides, in the CPFR process, seller and buyer will resolve exceptions collaboratively. Therefore, the demand forecast is progressively with commitment. This paper also analyzes the CPFR related information systems and then to design the KPI (Key Performance Indicator) information flows. From the KPI information flows, we will comprehend the influence of each KPI and then how to promote these performances.