Airline Revenue Management - How to improve forecast accuracy in an unstable operating environment?
Himanka, Mia (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202402163056
https://urn.fi/URN:NBN:fi:amk-202402163056
Tiivistelmä
Revenue Management plays a key role in any airline’s financial success. As the industry has low profit margins, maximising revenue and profits is critical. During recent years the airline industry has suffered from many unexpected events such as the Covid-19 pandemic followed by Russian airspace closure commencing in February 2022. This double crisis has made forecasting and revenue maximisation increasingly challenging with constant changes in both the network and customer behaviour.
Considering the recent challenges within the airline industry, this master’s thesis aims at finding solutions to improve demand forecast accuracy for the case airline. The measures undertaken to improve forecast accuracy are examined as well as potential future development items discovered. The aim of the thesis is to give concrete recommendations on how to improve forecast accuracy from different perspectives.
In the beginning of the thesis an introduction to airline revenue management is given including information regarding revenue management systems, artificial intelligence in revenue management and forecasting. Also, the impacts of the double crisis on the airline industry are discussed in more detail.
This research was conducted as a qualitative case study as this research method supports the goals of this study in the best way. The empirical evidence was collected from semi-structured interviews with seven employees from the case company who work closely with forecasting activities. All seven respondents work within the revenue management department in different teams. Additionally, document analysis was used to study current forecasting processes further.
The study indicates that the company has proactively sought solutions to help forecasting work in a challenging environment. Actions that have been taken include the creation of additional reporting, closer teamwork and finding solutions to help working with the Network Revenue management system. Overall, ensuring revenue maximization during recent years has required resilience and commitment from the team.
Recommendations include improving understanding of the NRM system functionality, increasing sharing of knowledge and best ways of working within the team and clarification of existing fore-casting processes. Additionally, the recommendations include a list of improvement suggestions related to the NRM system.
Considering the recent challenges within the airline industry, this master’s thesis aims at finding solutions to improve demand forecast accuracy for the case airline. The measures undertaken to improve forecast accuracy are examined as well as potential future development items discovered. The aim of the thesis is to give concrete recommendations on how to improve forecast accuracy from different perspectives.
In the beginning of the thesis an introduction to airline revenue management is given including information regarding revenue management systems, artificial intelligence in revenue management and forecasting. Also, the impacts of the double crisis on the airline industry are discussed in more detail.
This research was conducted as a qualitative case study as this research method supports the goals of this study in the best way. The empirical evidence was collected from semi-structured interviews with seven employees from the case company who work closely with forecasting activities. All seven respondents work within the revenue management department in different teams. Additionally, document analysis was used to study current forecasting processes further.
The study indicates that the company has proactively sought solutions to help forecasting work in a challenging environment. Actions that have been taken include the creation of additional reporting, closer teamwork and finding solutions to help working with the Network Revenue management system. Overall, ensuring revenue maximization during recent years has required resilience and commitment from the team.
Recommendations include improving understanding of the NRM system functionality, increasing sharing of knowledge and best ways of working within the team and clarification of existing fore-casting processes. Additionally, the recommendations include a list of improvement suggestions related to the NRM system.