An International home furnishings retailer increases forecasting accuracy leading to higher profits

The Pain Point

The client is an international $2B furniture, housewares and décor retailer with 7500 employees and over 100 stores in 9 countries. Their goal was to automate their forecast and demand management capabilities and enable the use of machine learning for more accurate forecasting.

The Solution

This implementation and customization consisted of three main applications. The first part was the forecast management which used innovative data science and predictive analytics to forecast just-in-time weekly inventory demands. The second part was merchandise financial management. This allowed the client to customize processes that are unique to their company, empowering competitive differentiating. The third part was allocation and markdown optimization which optimized both allocation and markdown processes simultaneously to provide greater revenues and profit. Using a combination of Agile and PMI methodologies, our developers created a flexible development environment which allowed the continuous deployment of new features and customizations according to the client’s requirements. The implementation of these three solutions increased the accuracy of the forecasting leading to higher sales and profitability.

The Results

Softensity Case Study 2

Forecast accuracy increased by 25-50%, increasing their revenue and profit by 20%. In 2019, we supported the client in achieving 3 successful on-time production deployments within one year

Contact: Scott Kirby, Director of Consulting Services / 404.451.7110 /

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