Case studies

Datadriven placement of red letterboxes in Ghent (Belgium)

Bpost, the company responsible for the delivery of mail in Belgium, wants to raise efficiency and reduce costs by removing some of the red letter boxes in Ghent. The city of Ghent received a list (in pdf) with the addresses of the letterboxes that are staying and the ones that are being removed. Other datasets included the network of roads  and the “bevolkingsregister”.

The first idea as to see how many citizens are within the service area of the letterboxes before and after removal. It was assumed that a citizen could reach a letterbox if they were within 400m of their home. Before removal 75% of the citizens (and 72.1% of citizens aged over 65 years old) lived within 400m of a letter box. After removal this was merely 54.3% (and 50.6% for 65+ citizens).

In a second step mobility patterns of citizens were taken into account. If the mobility patterns are optimized service can become more centralized. The city of Ghent developed 3 different scenario’s of positioning the letter boxes, each with specific advantages and disadvantages, and will take this information to open the discussion with bpost.

Challenges encountered:

  • The data was send as text in a pdf file. First conversion and data cleaning was necessary before visualization was possible.
  • Defining the exact question and needs of the different stakeholders (reduce cost, raise efficience, vs. ensure maximum service) is challenging

Stakeholders:

  • City of Ghent
  • bpost

Actions steps:

Discuss different ways of looking at the data and defining service reach of a letter box with bpost

Lessons learned:

  • Share data in appropriate formats
  • Define goal early on and find common goal between stakeholders

Links:

It is too early to assess the outcome impact


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