Demand Sensing Solution Utilizes Real-Time Data to Predict Near-Term Demand

Fast-moving trends and changes in consumer behavior make it critical to track demand closely.

Traditional demand planning techniques were developed decades ago when distribution channels were few and history was a relevant predictor of future events. Today this method is insufficient, and there are a number of obstacles to predicting near-term demand:

• Volatility driven by changes in consumer preferences and social sentiment
• Growth-through-innovation strategies and rapid stockkeeping unit (SKU) proliferation
• Promotions and marketing programs designed to shape consumer behavior and change buying patterns
• Omni-channel and e-commerce strategies that disrupt traditional distribution and make historical orders even less relevant to future demand

Instead of relying on historical information, E2open Demand Sensing uses real-time data across the supply chain to accurately predict near-term demand for make-to-stock products.

The result is a 30 to 40 percent improvement in short-term forecast accuracy compared to traditional time series approaches. Field-proven with more than a decade of use in over 180 countries for $250 billion in annual sales volume, the solution is a core part of the demand-driven digital transformation strategies of leading global companies.