Buyer Analytics

What would improving forecast error by 50% be worth? Better production planning, resource utilization and significant inventory reduction to name a few. Demand Sensing validates daily demand data from multiple sources in the supply chain, including point-of-sale data, customer warehouse and outlet inventory, and forecasts. Demand Sensing uses pattern recognition mathematics to decipher which information can be forecasted accurately.

Here is an example of a demand sensing initiative at P&G:

"In the current economic climate -- with ever increasing volatility in demand -- it is crucial to extend the supply chain visibility as close to our customers as possible," explains Mueller. In the near term, he is therefore now focusing on integrating customer demand data into Procter & Gamble's demand sensing application, which is expected to further improve forecast accuracy in order to achieve superior customer service.  Speed today is of the essence," says Mueller. "Only those companies that can respond quickly to customer and consumer needs will stay ahead. At Procter & Gamble, one key focus area is on dramatically simplifying our operations. For technology professionals this is a major opportunity. We are well positioned to empower the company to turn external crisis into opportunity."