Planning mistakes are costly. If a plan fails to accurately predict demand, then the company could end up with either too little or too much product. If the product isn't available when the customer wants to buy it, then the company risks losing revenue. Excess product sitting around unsold could tie up capital.
That's why a primary focus of demand planning is minimizing forecast error. One way to reduce the number of forecast errors is to employ a new approach called "optimized planning." Eric Lange, director of demand planning and S&OP services for Celestica Supply Chain Services, described this idea at the recent Supply Chain World North America 2014 conference in Nashville, Tenn.
An optimized plan would combine two perspectives to produce a single view of demand. The first is the customer's perspective, formulated by taking data from sales and marketing to get a picture of what the customer thinks will be required. The second is the supply chain perspective, which would use traditional statistical methods to analyze trend data. The "blending" of market knowledge with analytical assessment produces a more accurate picture of demand, according to Celestica. In a white paper it published on the topic, the company said that this hybrid approach greatly simplifies planning and improves forecast accuracy by 20 percent.
As companies adopt more demand-driven supply chains, this hybrid approach will provide a way to marry field input about the market with analytics. And that could help companies more consistently carry the stock that customers are most likely to buy.