Software Development

Forecasting demand at bol.com during the COVID-19 pandemic | Blog | bol.com


Bol.com is a retail platform with over 12 million customers in the Netherlands and Belgium. To serve the needs of these customers, it is essential that our team provides accurate forecasts to empower business decisions on a day to day basis. With the outbreak of the COVID-19 pandemic, online shopping behaviour went through a major shift and demand for essential and non-essential products swiftly increased (see cbs).

After months of struggling with producing any reasonable forecasts, we managed to design a feature which is able to describe the dynamic changes associated with the COVID-19 pandemic. The addition of this feature allows us to provide reliable forecasts in the short term and roll-out scenario forecasting for the long term, supporting different domains across the business. Our approach is easily interpretable and explainable to stakeholders, leading to better data driven decisions.

In our forecasting landscape, we provide different types of sales forecasting, both on total level and also on product level. These forecasts are then used on their own for different purposes across the organisation but also used by our team as the main drivers for operational planning forecasting. The different forecasts rely on different time-series modelling techniques, from linear models to gradient boosting algorithms. As such, it was important for us to have an one-size-fits-all solution which could scale across the different modelling approaches.

We started with an extensive data analysis and reading on the information regarding COVID-19 restrictions to contain the spread of the virus. With this information we developed a severity index that translated the impact of the pandemic on our sales patterns. Our severity index ranges between 0 and 12, where a 0 represents no COVID-19 related restrictions and a 12 represents the tightest restrictions we encountered during the pandemic. Figure 1. shows a representation of the COVID-19 severity index.