Forecasting

We developed a platform that combines traditional forecasting techniques with the latest in Machine Learning and Artificial Intelligence to predict different business variables. With that, our customers have improved their sales throughput by 20%-30% through superior sales predictions and optimized manpower planning. Our solution has the versatility to be deployed in small retail chains as well as large retailers. Our Agile approach can deliver tangible results within 6 to 8 weeks, shortening the payback period and generating a significant ROI.

PHYSICAL STORES

By feeding our innovative solution with internal historical data and external data (weather, public and school holidays, etc.), we can improve short-term sales forecast error by up to 50% when compared to traditional methods. A more accurate prediction leads to better sizing of personnel, increased customer satisfaction with reduced queues and increased sales throughput.

E-COMMERCE

In e-commerce, where under-staffing leads to revenue loss, planners need to carefully balance the cost of over-staffing with the risk of losing revenues. Planning the right number of pickers for each time slot is critical to ensure a high sales throughput. Our Solution combines superior sales drivers prediction with optimized pickers’ planning, which can lead to an 85% reduction in the risk of revenue loss.

WAREHOUSE

Aggregating SKU predictions for all POS leads to accurate forecasts at the warehouse level. Focusing on the most critical SKUs (e.g. perishable, high rotation) allows to significantly reduce waste and stockouts. By applying optimized workforce planning, it is also possible to significantly increase workforce productivity.