What is one key requirement to analyze demand changes in Demand Sensing?

To analyze demand changes effectively in Demand Sensing, it is crucial to implement changes based on historical data analysis. Historical data provides insights into past demand patterns, helping to identify trends, seasonality, and anomalies. By understanding these aspects, businesses can adjust their forecast models to better align with current market conditions, particularly in response to real-time data.

This historical perspective allows for a more informed interpretation of the real-time demand signals, enhancing the accuracy of demand forecasts. It plays a significant role in adjusting planning parameters and improving responsiveness to changing demand patterns, which is essential for successful demand sensing.

Utilizing real-time demand data is important, but it is the context provided by historical analysis that empowers planners to make effective decisions and adaptations in their strategies. This strategic combination helps businesses to anticipate fluctuations and optimize inventory management, ultimately leading to improved service levels and reduced costs.