Demand Forecasting and Inventory Management in Retail
To predict product-level demand at the unit store/kiosk. Stocking inventory of products higher than its actual demand results in increased cost of inventory as well as opportunity lost in terms of fulfilling demand of some other product. At the same time, falling short of demand will result in lost revenue and poor customer service.
With AI enhanced time series forecasting, retailers know the demand for a given period at each kiosk for the product. This not only enables retailers to reduce the inventory cost of an over-supplied product but also allows them to replace that inventory with the product which is likely to be in greater demand in the upcoming period.
Our models make the best use of both Neural Networks and Time-series specific models to make the prediction. This enables us to achieve more accurate results in even a volatile market with seasonal spikes.