A tool for airline network planning business users to consistently and quickly analyze the effects of future flight schedule changes.


Airplanes are expensive! Therefore network planning decisions like where to fly, how often to fly there, and at which times, are fundamentally important for any airline.

However, the evaluation of any future strategic flight schedule change, requires on one hand, various historic data sources and, on the other hand, mathematical modelling to project historic pax and revenue figures into the future.

Hence without automation the technical process to evaluate a business scenario is only possible for technical experts with specialized software, involving manual efforts and a long and complex pipeline until the analysis arrives on the screen of the network planning end user.

Furthermore, different group airlines, planning teams or even individual users might apply different underlying data sources, modelling or planning assumptions, rendering comparisons and an actual informed decision-making almost impossible.

A convenient tool enabling network planners to consistently and comfortably analyze schedule changes was needed.


First, zeroG started by conducting a design sprint with actual network planning end users. Our aviation and modeling experts together with the users came up with a plan for an easy to use graphical web interface that provides all required KPIs, overwrite possibilities and report export.

Next, together with the customer the required data sources and the mathematical model for predicting the planning period were defined. Colleagues from Lufthansa Systems Budapest provided the backend and the graphical user interface very closely to what was drafted in the design sprint.

In parallel at zeroG we implemented a lean Python-module of the data-driven model for schedule change evaluations, delivering KPIs to the web user interface. Furthermore, we set up a Business intelligence module based on Microsoft Power BI to enable the user to create customized reports.


At the click of a button, a network planner can quickly evaluate a schedule change. Within minutes (instead of days) a network planner will see an accurate forecast for market shares, revenues, cost and effects on the whole network and is able to transparently incorporate case-based assumptions.

Customized reports can be generated easily. Finally, the consistent data and modelling foundation enables a harmonized evaluation throughout different network planning teams, automated spill-and-recapture forecasts, and a data driven base for decision making.