Background:

A Dubai-based cosmetics company reached out to us for guidance on managing inventory levels and accurately predicting inventory turnover. The company had suffered from a loss of revenue due to inadequate inventories of some products. Inventory management is a crucial aspect for small and medium-sized businesses since any material/product wastage can have a detrimental impact on the business’ financial performance. The fundamental aspect of inventory management is demand forecasting. Being able to predict demand helps the company to ascertain the level of inventory needed to fulfill the demand. Accurate demand predictions result from artificial intelligence that can learn and provide solutions using existing data.

What did Solvexis suggest?

After careful consideration of the problem and the business model, our analysts agreed on using machine learning for demand prediction and hence, better inventory management. A machine learning software can learn from the inventory movements and thus suggest a minimum inventory required to meet demand over the months. Machine learning enables the software to learn from the data and make amendments to the inventory levels. The company reported almost 150% cost savings following this solution. Product wastage also decreased tremendously. It reduced manual labour and allowed the company to prioritize other aspects of business operations