Service centers served.
Historical data processed.
A global logistics company with overall 900 distribution centers in India, catering to various Indian e-commerce companies.
The client wanted reliable demand forecasts for each of its service centers to obtain more efficient staff capacity planning and meet demand more effectively, thus boosting revenue and meeting customer expectations.
The client engaged SG Analytics to help create predictions of the daily demand for 100+ service centers across India for up to 12 weeks in advance.
SG Analytics helped the client’s team to understand and consolidate the historical data trends from its existing sales database for the past 5 years while taking into account factors such as weekday, monthly seasonality, holidays, and locality and beyond etc.
Post the exploratory data analysis, SG Analytics' team helped the client to build predictive linear models to accurately predict the future demands based on observed historical trends. Then, using advanced classification models, SG Analytics' data scientists divided the client's service centers into categories and created buckets of homogenous service centers. The modeling exercise was repeated for each service center category and the factors were tweaked separately as per their specific requirements.
SG Analytics' models delivered accurate demand forecasts for all the distribution centers.
The models helped the client's organization to create effective staff schedules.
The improved and more efficient schedules helped increase the client's staff productivity and motivation.