Airport Business Analytics

The modern airport operator, which has been propelled into a dynamic and competitive landscape, has moved away from being a mere infrastructure provider to a diversified and complex business that operates strategically within the air transport value chain. Consequently, an understanding of economic performance based on statistical and analytical tools as well as robust performance indicators provides valuable business intelligence to decision makers and other stakeholders.

The objective of this course is to introduce participants to some of the essential tools and techniques used to support data-driven decision making in organizations with applications to the airport industry. Seminar themes take a holistic approach to cover key quantitative tools with applications in economics, finance, marketing, operations and other airport functional areas.  Topics include predictive analytics based on regression techniques, airport financial analysis through a battery of key performance indicators as well as the rudiments of air transport demand forecasting.

Participants are requested to bring laptops with Microsoft Excel (English edition) and/or share along with other course participants. General basic knowledge of Excel (e.g. data input, cell formatting, basic formulae and cell referencing, etc.) is required. Depending on the class composition of registered course participants and their collective preferences, session themes may vary beyond the core modules.

Who should attend?

• Airport Analysts, Statisticians and Economists
• Airport Finance Directors and Managers
• Airport Marketing and Research Managers
• Airport Operations Directors and Managers
• Airport Consultants and related professionals
• Civil Aviation Authority Officials
• World Business Partners and other aviation experts

Learning objectives

Upon completing this course, participants will be able to:

• Understand basic statistical nomenclature related to airports and air transport demand;
• Apply analytical techniques  - descriptive statistics, correlations, regression analysis and interpret the results;
• Apply analytical techniques using computer-based applications;
• Develop an understanding of Key Performance Indicators based on financial data to measure business performance;
• Apply standard traffic forecasting tools in Microsoft Excel.

Course content

• Airport statistical nomenclature and concepts for international comparability;
• Getting to know your data with descriptive statistics; Basic marketing research techniques;
• Empirical applications in economic theory: correlation versus causation and interpreting elasticities;
• Measuring business performance: Internal versus external benchmarking;
• Developing and interpreting key performance indicators from economic and financial data;
• Analysing revenue, cost and profitability indicators; constructing the weighted average cost of capital;
• Global analysis of the economic and financial characteristics of the airport industry;
• Measuring seasonality and deseasonalizing time series data;
• Airport traffic forecasting methods for the short medium and long term.