The concept of Demand Sensing uses artificial intelligence to improve the accuracy of your short-term demand plans and create better forecasts at a location, item and day level. These accurate demand plans can then be executed into inventory orders that will reduce your aged inventory and overstocks, increase your on-shelf availability, and reduce lost sales.
When V Net has implemented DS models we have seen, on average, 12% MAPE improvements in the first five weeks over statistical models.
Standard forecasts may use time-series or even basic machine learning algorithms to look back at past sales patterns to determine future need. While these may provide guidance for long-term forecasts, they can be inaccurate when it comes to the erratic nature of day to day demand and the kind of forecasts required for short-window ordering.