Gala Groceries Supply Chain Optimization

This project is part of the Cognizant Artificial Intelligence Program on Forage([https://www.theforage.com/simulations/cognizant/artificial-intelligence-rtbq]). The objective is to optimize the stock levels of Gala Groceries, a technology-led grocery store chain, to minimize waste and avoid stockouts. We analyze sales data, sensor data on stock levels, and storage temperatures to provide actionable insights and predictive models for enhancing supply chain efficiency.

Project Overview

Gala Groceries approached us with a supply chain challenge: how to better stock their items to balance between overstocking and understocking. This project involves:

• Data preprocessing and feature engineering
• Exploratory data analysis
• Building predictive models
• Evaluating model performance
• Providing recommendations based on the findings

Project Tasks

Task One: Exploratory Data Analysis

• Analysed sales data via Python.

Task Two: Data Modelling

• Reviewed a data model diagram.
• Created a plan to answer the client problem statement.
• Created one PowerPoint slide to share plan with my leader.

Task Three: Model Building and Interpretation

• Used Python to build a data model.

Task Four: Machine Learning Production.

• Wrote a Python module to train a model and output performance metrics.