Returnable Packaging Materials Internship in the Global Supply Chain – Heineken



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head office at Schiphol (BASE) and the Dutch Operating Company office at Leiden

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Community Data2Move
Start Date September 2022
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Company Description

As part of the Supply Planning Capability team, we are looking for an intern to develop better methodologies for the forecasting of expected flows of returnable packaging material (RPM) flows like kegs, crates, bottles, and pallets. A good understanding of the expected available packaging materials is a key input to our production planning and scheduling processes (especially on the short to mid-term).

Currently, we work with different methodologies (time-series based forecasting, and circulation-time based) to estimate the flow of empties coming back from the markets. We believe there is a better methodology through machine learning to come to a more accurate prediction using both historical returns, as well as shipments and forecasted shipments to the market as key inputs.  

Project Description

The project will be focussed on the HEINEKEN Netherlands Supply (HNS) data, but should yield a methodology and/or tool that can easily be applied to other data sets as well. The internship will be coached by a Supply Chain Specialist within the HNS team together with a colleague in the global capability development team. Support from our Global IT and Analytics departments

The internship is based in our global supply chain head office at Schiphol (BASE) and the Dutch Operating Company office at Leiden for the duration of 6 months. 

Your responsibilities

  • Work together with the business team at HNS and Global Planning to understand the requirements and needs.
  • Gain understanding of the dynamics of returnable packaging material flows (internal research available, external research to be determined).
  • Set-up relevant project meetings, interviews, etc.
  • Collect the required data, analyse and develop methodology for forecasting.
  • Create design for a tool that embeds the developed methodology.
  • Ideally: start build of the tool.

Your profile

  • Project is available as Master Thesis project as it is an opportunity to apply theory to a practical business question.
  • Experience in Machine Learning and programming thereof (Python/R).
  • Able to work with large amounts of data, and also with qualitative input from interviews with experts and other stakeholders.
  • Proficient in English (Dutch small plus).
  • Curious about logistics and planning, any experience in the field of planning is a plus.

When you are an intern at HEINEKEN you will:

  • Learn how to apply your theoretical knowledge and to understand business needs.
  • GoPlaces; experience new things and meet colleagues from different cultures along your way.
  • Be challenged and get exciting responsibilities from day one.
  • Be a member of the international team of interns; boosting your professional (and social) network.

P.S. Please note that all interns must be enrolled at a university for the entire duration of the internship. You will need to provide a proof of enrolment with your application. Applications without this will not be considered.


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