Case Study
Published on 05th January 2022 | By Mate Labs
For
A consumer goods giant
Tags
Demand Forecasting
Rapid Forecasting
Cost Reduction
Before Mate Labs’s solution was implemented, their corporate client used an established legacy tool for demand forecasting that lacked at-scale, advanced analysis capabilities, and failed to measure the impact of promotion and other dynamic features. This also meant a huge wastage of resource time and effort in finalizing demand planning.
Mate Labs’s AutoML platform, Mateverse successfully captured the hidden patterns in forecasting demand via automated feature engineering. In the concerned use case, Mateverse’s feature engineering unpacked and analyzed the impacts of the following features to boost forecast accuracy:
15% jump in forecast accuracy (a total of ~75%) over their traditional method of forecasting which only gave them ~60% accuracy
$530k cost-savings from the forecast accuracy achieved
Procedure digitization
Machine downtime
Manufacturing
Connected machines
Automotive
Industrial automation
Real time monitoring
Manufacturing
Machine utilization
Automotive
