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Case Study

Improving the check-in passenger experience:

How Munich Airport reduced up to 64% of queues stretching into flow areas by utilizing space in front of unallocated counters.

Airport

Munich Airport (MUC)

Passengers

47.9 mill. passengers (2019)

Destinations

203 destinations

Client overview: Munich Airport (MUC)

Munich Airport is an international airport serving Munich and Upper Bavaria. It is the second-busiest airport in Germany in terms of passenger traffic after Frankfurt Airport, and the ninth-busiest airport in Europe, handling 47.9 million passengers in 2019. It is the world’s 15th-busiest airport in terms of international passenger traffic, and was the 38th-busiest airport worldwide in 2018.

Airport operations check-in bag drop passenger

Introduction to the collaboration with Munich Airport

Munich Airport (MUC) engaged with Copenhagen Optimization (CopOpt) with the aim of improving the passenger experience at check-in for Terminal 1.

The Challenge:

Munich Airport (MUC) engaged with Copenhagen Optimization (CopOpt) with the aim of improving the passenger experience at check-in for Terminal 1. Terminal 1 has almost 80 airlines operating with the largest airline having less than 20 flights a day. This makes check-in allocation and stakeholder management challenging – especially when it comes to reaping the benefits of self-service baggage drop.

The Solution: A check-in allocation study

An important conclusion from the study is that MUC, as the airport operator, should take a holistic view of the check-in process. This is done by influencing airlines to improve their check-in counter profiles to better match the arrival of passengers.

Additionally, MUC will allocate check-in counters and queue area independently. Through this, use of queue area will be improved, less queues will be stretching into the flow area as well as passenger wait times will be reduced.

Explore Better Check-in

Outcome achieved

Queue management – taking advantage of queue area in front of unallocated counters – can reduce up to
64%
of queues stretching into the flow area.

Building the base for
fact-based performance evaluation.

Demonstrated how operational data can be applied to produce
accurate input parameters.

Outlined how the airport operator should take a larger, more holistic view to the
passenger experience
in check-in to support improvement.

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