How does Data Science Help Inventory Management?

The first step in the ecommerce value chain is to plan and manage inventory stocks. Let’s discuss the problems faced in this step and how are they typically solved.

You saw that there are two basic analytics application in inventory management.

1. Demand forecast

2. Inventory management for the forecasted demand

While time series analysis is used for forecasting demand, this is not done on each product item individually. Products showing a similar demand curve are generally clustered together and a time series analysis is carried out on each of these clusters.

The next step is to manage the inventory for the forecasted demand. So, here again, you can optimise your cost and profit by acquiring, or getting rid of, extra inventory space depending on your forecasted demand.

Additional Reading:

You can read further about inventory analytics from the links given below.

• Using analytics to effectively manage inventory

• Predictive analytics transforms inventory management in retail

• 5 inventory analytics best practices to achieve inventory optimisation