Supply chain forecast based on customer forecasts – PostNL

 Overview

Company Description

One of PostNL’s most important service is to transport parcels ordered at web shops to consumers. To enable a sustainable growth PostNL is involved in a digital transformation of the supply chain, where capacity planning and steering is endorsed by both historic and realtime data sources. This transformation poses many challenges in the field of operational research and data science.

Project Description

In order to plan sorter capacity and test whether interventions are required in the ongoing process we need a forecast of the (remainder) of the supply line. For several reasons we would like to build up this forecast from contributions of the individual customers. This poses methodological challenges because customers vary greatly in size, sensitivity for external factors and they have different week patterns.

Goals of the Project
Find out whether a customer based supply line forecast is a feasible route to obtain better supply line predictions.

Deliverables

• Python code for large scale customer predictions
• Recommendations for further research based on given data and own explorations. 

Essential Student Knowledge 

Python, time series analysis, clustering, factor analysis.

More information: escf@tue.nl