Data Analysis Takes Off

Technology   |   Lori Misenhimer   |   Jul 9, 2020

With more than 250 destinations all over the world and more than 44 million travelers per year, Munich Airport in Germany is among the largest transport hubs. Passengers, however, can only speculate about the complexity and amount of data points and this increases in strategic planning.

“From air traffic operations to restaurants, shops and cleaning personnel, every day airport activities require many different parties to work together seamlessly, like cogs in a gear wheel,” explains Dr. Heike Markus, Senior Consultant for Strategic Planning at Flughafen München GmbH.

“Our analysis focuses on how internal and external factors could affect the future of the entire group — for example, investments, political decisions, or market changes. Since the individual business areas of the airport are interdependent and there are many additional external factors over which we have no influence, the complexity is high,” emphasizes Dr. Markus.

“An important topic was, for example, the decision of the 2015 Paris World Climate Summit. Which CO2 strategy needs to be developed and adopted, and on which areas of operations does this have an impact? To find answers, the team has to calculate the various future scenarios and analyze and compare the sensitivities. This is the only way that airport management can evaluate the effects that the decisions can have on the company.”

Data pioneers are flying high

Together with a team of specialists, Dr. Markus quantifies the relevant issues and also evaluates them qualitatively. “Although we always keep a close eye on the company as a whole, we also collaborate intensively with the individual departments involved and deep-dive into the details when necessary.”

Because they are continually looking toward the future, the strategy team has a pioneering role. “With our work, we also initiate new topics — such as data analyses — which are taken up by other areas in the company,” explains Dr. Markus.

Flexibility, low hurdles and high user-friendliness

However, the complexity of the scenarios and many different data sets overwhelmed the old programs, which is why the team started searching for alternatives two years ago. “At the time, we worked quite intensively with Excel documents, which created significant complexity and limited performance. Moreover, we were unable to connect to any databases. This meant it was quite difficult to track everything,” says Dr. Markus, explaining the challenges at the time. “For this reason, we desperately needed an alternative. In order to consider business models separately, to compare scenarios, and then to evaluate plausibility, we also needed a database-supported solution. At the same time, we didn’t want a classic IT project with an initial requirement of a complicated overall set-up associated combined with a high level of training — only to find out that it was not the right application for our own needs.”

The team’s important decision criteria for the selection were user-friendliness, flexibility and short training time.

“With Alteryx, the hurdles are low: You install the software on your computer and you can start right away. Together with Alteryx partner Woodmark Consulting, we created solution building blocks, one by one, in an agile coaching approach. We then merged them into one homogeneous overall system. In this way we ensured that we received a tailor-made application to meet our needs and we were able to use best practices right from the start. In addition, you can always ask the Alteryx Community for advice when you are stuck — for us, that was another important plus when we made our decision and we often use this opportunity.”

Analysis at the touch of a button

In the meantime, the team has generated the predictive model and specified the internal and external input parameters. “Soon after our first calculations, we realized that we are saving lots of time. Instead of two weeks, we now only need two days in order to update the current data in the forecast model. Instead of two weeks, we now need just two days in order to update the current data in the forecast model. In addition, one person can now take care of two to three projects simultaneously instead of just one. This gives us more time overall for interpreting results and to undertake further detailed examinations.”


See how Munich Airport predicts the future with data. Get the full case study here.


Dr. Heike Markus explains what data analytics can achieve.