Case Study: Sales Forecasting

Background: A key retail client houses over 2000 SKUs, needs to provide accurate sales forecasts to it's vendors who supply the SKUs. Inaccurate forecasts lead to either loss of sales or over stocking

Approach: A time series based forecasting model was built in SAS to account for various factors like seasonality, holidays, trends, special events, promotion. For new SKUs forecasts were built by studying the sales of sister SKUs

Impact: Accurate forecasts along with a sound Inventory Planning model helped significantly reduced stock outs as well as over stocking. Increased sales & lower stock holding costs increased the net margins for the company