ML-ready-data for out-of-stock detection

Velocity and consistency to the ingestion of disparate data, until machine learning can do its magic.

Machine learning unlocks a vast potential for data detection automation. By scanning data sources, organizations can retrieve useful new information to create clarity on obscure matters and ultimately improve their processes.

It was an exciting task for the IT department of an industry-leading personal care manufacturer to leverage machine learning to automate their out-of-stock detection. Their objective was to give recommendations on how local business units could improve the pitfalls of their supply chain and the management of their inventory to maximize in-store presence and sales.

The analysis could be performed much faster than they thought, because they could rely on harmonized data from Redslim. In just a few meetings, the two teams were able to align on the desired data format, and in a matter of a days the IT department had ingested data from more than 40 countries and 4 categories into their systems.

From there, it was an easier job to test and run the algorithms for out-of-stock detection. The company HQ was able to identify key issues with their stock across a whole region and give recommendations for an improvement plan. Redslim’s quick support and the enrichment layer we provided allowed them to perform this analysis quickly and consistently across their markets.

Want to go over your opportunities?

Eric Bensimon
eric.bensimon@redslim.net
+33 6 23 89 73 85