1. Background

A mid-sized retail business specialising in consumer electronics faced significant challenges with inventory management. The company frequently experienced stockouts of high-demand products, leading to lost sales opportunities. At the same time, slow-moving items occupied valuable storage space, increasing holding costs and reducing profitability. The lack of a data-driven approach to inventory forecasting resulted in inefficient purchasing decisions and operational inefficiencies.

2. Analysis & Approach

To identify the root causes of the inventory challenges, a structured analysis was conducted using historical sales data, supplier lead times, and customer demand patterns. The approach involved:

Findings revealed that 30% of storage space was occupied by slow-moving items, while popular products frequently ran out of stock due to inaccurate demand forecasting. Additionally, suppliers had inconsistent lead times, causing unexpected inventory shortages.

3. Solution & Implementation

A data-driven inventory management model was developed to optimise stock levels based on sales performance analysis and demand forecasting. The solution involved:

4. Results & Business Impact

The implementation of the new inventory management approach led to significant improvements in efficiency and profitability: