Reduction in food wastage
Million savings per month
Improvement in model accuracy
The customer’s legacy statistical-based modeling approach forecasts demand in terms of dollars earned, and item quantities sold at a daily and sub-hourly level. The forecast has to be made several weeks in advance to cater to the business requirements. Legacy methods, however, struggled to perform in a dynamic and fast changing environment.
AWS Lambda
Amazon S3
Amazon Athena
Amazon EMR
Amazon Aurora
Amazon Sagemaker
TensorFlow
Jenkins
The customer wanted a state of the art demand forecasting solution with a dashboard to receive updates on a periodic basis to have better control on demand fluctuations in order to have an efficient supply chain, which in turn would reduce costs, food wastage, and optimize available warehouse space.
Quantiphi built a forecasting engine to predict sales at a daily and intra day basis for multiple different time horizons. Our flexible models helped the client with efficient warehouse management and manpower scheduling. The solution also improved the estimates of the suggested quantities of ingredients to be ordered from the distribution centers. The solution was scaled to more than 2000 stores.
