Success Case | Staff Optimization through Demand Forecasting
Leading fashion retailer in Spain
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The Challenge
The brand plans to size the number of people needed to manage logistics processes based on the demand received and expected revenue in each country where it operates. Although this is a recurring need, it becomes more important during the festive season (Christmas) or sales.
The Solution
From the historical data of unit sales by country, Keepler has built a Machine Learning pipeline for training and inference of the necessary models, including daily monitoring of the results obtained and an alarm system that warns of possible failures in the previous processes.
The Result
Keepler is a full-stack analytics services company specialized in the design, construction, deployment and operation of advanced public cloud analytics custom-made solutions. We bring to the market the Data Product concept, which is a fully automated, public cloud services-based, tailored software that adds advanced analytics, data engineering, massive data processing, and monitoring features. In addition, we help our customers transition to using public cloud services securely and improve data governance to make the organization more data-centric.
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