Demand Forecasting for Electronics Retail Giant in Dubai

Leading Electronics Retailer in UAE

We initiated the project with a duration of six months at the end of which bi-directional audit needs to be conducted from 3PL.

Business Objective

Our client is among the biggest electronics retailers in Dubai with 30+ stores that offer 15000+ SKUs at competitive prices. Each year the client prepares for the coming Dubai Shopping season and places purchase orders six months in advance. The inventory planning and movement are highly driven by the shopping season with seasonal peak sales ranging from 5X to 20X of BAU sales. In such a scenario, the business often suffered from over- and understocking, which urgently needed to be resolved with an accurate demand forecast.

Challenge

Demand is highly seasonal and 2 week Dubai shopping festivals account for 60% of yearly sales.
Overstocking was a challenge because inventory could not be returned and was difficult to sell until the next season .
Understocking was a challenge because products were sourced directly from China and Adhoc sourcing was not an option.

Solution Methodology

We helped the client predict the future demand for their products using Machine Learning.

We collected and cleaned five years of unstructured historical inventory and sales data.
We modeled the peak sale of the top 100 SKU that contributed to 60% of the sale by revenue. The selected model was then used for demand prediction.
Peak sales were modeled separately from regular sales to increase prediction accuracy.

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Impact

Average forecast accuracy across products improved from 80% to 93%.
In under forecasted weeks, demand was forecasted with 90% accuracy, reducing opportunity loss.
In over forecasted weeks, regular and peak sales weeks were predicted with an average of 80% and 98% accuracy respectively.

Impact in Numbers

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