Demand Sensing is an advanced forecasting method using real-time data and AI to predict near-term demand within hours to days. Unlike traditional planning based on historical sales, it uses Big Data, IoT, and Deep Learning to analyze high-frequency signals such as real-time POS data, weather, and social media trends.
This approach reduces the bullwhip effect, which magnifies small consumer demand changes into large upstream swings in volatile markets. By turning passive data into actionable insights, firms can optimize inventory and cut waste.
The main challenge is managing data latency and integrating diverse sources into a unified, agile supply chain response.