Demand sensing

Demand sensing is a demand forecasting method that uses data mining and real-time data capture to create a forecast of demand based on the current realities of the supply chain.{{Cite journal|last=Byrne|first=Robert F.|date=Summer 2012|title=Beyond Traditional Time-Series: Using Demand Sensing to Improve Forecasts in Volatile Times|url=|journal=Journal of Business Forecasting|volume=31|issue=2|pages=13–19}}{{Cite journal|last=Folinas|first=Dimitris|last2=Rabi|first2=Samuel|date=2012-12-01|title=Estimating benefits of Demand Sensing for consumer goods organisations|url=https://doi.org/10.1057/dbm.2012.22|journal=Journal of Database Marketing & Customer Strategy Management|language=en|volume=19|issue=4|pages=245–261|doi=10.1057/dbm.2012.22|issn=1741-2447|doi-access=free}}

Traditionally, forecasting accuracy was based on time series techniques which create a forecast based on prior sales history and draws on several years of data to provide insights into predictable seasonal patterns. Demand sensing uses a broader range of demand signals, (including current data from the supply chain) and different mathematics to create a forecast that responds to real-world events such as market shifts, weather changes, natural disasters and changes in consumer buying behavior.