Information Technology

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.

Challenges

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

Workflow

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)

Tech

Our Tech Stack

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Scikit Learn

Python

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Microsoft SQL Server

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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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