Demand Sensing allows you to incorporate detailed demand data into your short-term forecasts to reduce forecast error by up to 50%, increase inventory performance by up to 20%, and optimally deploy downstream (e.g., Distribution Center) inventory.
Downstream data, such as customer and channel data, is employed to identify demand trends, provide advanced warning of problems, and remove the latency between plan and what is really happening in the supply chain. The quicker deviations can be identified, the quicker and more intelligently a company can respond.
Demand Sensing imports fresh daily demand data, immediately senses demand signal changes compared to a detailed statistical demand pattern, and evaluates the statistical significance of the change. It analyzes partial period actual demand to perform automatic short-term forecast adjustments using probabilistic pattern recognition and predictive analytics to detect patterns in replenishment orders and to identify and rapidly react to sudden changes in customer demand.
Our Demand Sensing can capture and analyze the demand signal from:
- The next downstream step in your demand chain, such as at a Ship-To store or warehouse
- POS data or EDI transactions, expanding the ability to sense the extended supply chain
- More advanced sources of “big data” in Demand Signal Repositories (DSRs), such as macroeconomic trends, social media and customer web behavior.