CASE STUDY “ Simple and powerful with a quick learning curve, mAdvisor has been exceptional in supporting our data science needs. Reducing model creation time from 6 months to mere weeks with heightened accuracy is our biggest win. ” - Client COO Forecasting demand for buy-on-board food items for an airline caterer Summar y The client is one of the largest airline caterer that provides catering and provisioning solutions for airlines, airport lounges, and related establishments. Challenge The Airline catering industry is struggling to accu- rately predict the demand of in-flight food demand especially on an SKU level. Predicting demand for three meals a day across 2000 routes across hun- dreds of airports using traditional methods was diffi- cult. The long time to build forecas

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