Forecasting demand pattern for iDSpecial using data analytics

Abstract

iDSpecial operates in the ready to cook products division. Flagship products of iDSpecial are idly & dosa batter, chapatti and parota. In 2014 it has registered sales of more than 7 crores. Currently iDSpecial has production plants in 6 cities, with two in Bangalore, one each in Chennai, Mumbai, Hyderabad, Mangalore and Dubai. Due to the busier life styles of the consumer, the demand for Ready to cook products has increased and so has the demand for iDSpecial products. So predicting the demand has become important strategic decision for iDSpecial in order to effectively plan and schedule its operations. Managing the inventory of ready to cook products (perishable) is tedious task for companies like iDSpecial. If not predicted properly, excessive stock will result in loss and understocking will result in lost sales. This situation can be translated into a forecasting problem for iDSpecial where the demand of these SKU’s should be predicted accurately to address the operational problem how many SKU’s to be replenished in each outlet.