Procurement Planning Software Development
Impala Intech developed a procurement planning software solution for an infotech company based on their pre-existing in-house solutions
Client’s Goal - Procurement Planning With ML
The client is a perishable goods supplier who required a solution that could help with planning the procurement of perishable products based on a composition of simple adaptive models for retailers and caterers.
The Challenge for Impala
Business Challenges
The client wanted to receive accurate predictions for the required amount of products they had to buy so they didn’t face losses from losing products as a result of self-life expiration
Technical Challenges
For making shelf-life predictions as well as the number of required products based on client and warehouse data, we had to create a machine learning algorithm to pick up information from different sectors to offer the best predictions
How Impala Intech Made it Possible
Adaptive Prediction Models
The solution is built up of several different adaptive models that process suitable mathematical prediction models for appropriate situations
Updated ERP Systems
After integrating the solution into the ERP, the system was significantly updated and the prediction model provided better calculations and improved reports
Better BI Solutions
The solution brought in improved predictions and detailed reports, offering better Business Insights (BI)
Our Tech Stack
Scikit Learn
Python
Microsoft SQL Server
Microsoft Azure
.NET
The Success of Our Solution
At the time of signing up, the client had a prediction accuracy of 70%. The solution was a big success after testing it in real-life scenarios. The hypothesis was proven and the prediction accuracy increased by more than 10%
Since the model used simple mathematical models for predictions, hardware requirements were also smaller compared to large-scale predictive algorithms.
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