Sales Forecasting

This was a project started as an experiment to see whether using covariates like weather and economic indicators provide better forecasts than simply using historical data.

Eventually it evolved to the point the team designed its own forecasting algorithm and making a pipeline to provide better forecasts than IBP.

I focused on developing a new algorithm to perform Time Series Forecasting in general, as well as automating a pipeline to get latest actual data and IBP forecasts every month, perform the forecasting on the new data, compare the accuracy with IBP forecasts and present the results on a dashboard.

The algorithm I developed integrated the baseline algorithm used by Sahil Rajpal and Sejal Anand with conventional time series forecasting techniques like trend, seasonality and lags. This algorithm is full encapsulated in a library - tsf