A continuación, te explicamos cómo puedes analizar estratégicamente los datos como gestor de aeropuertos.

As a airport manager, we should keep data as clear as possible and as data would be huge and each things should be observed closely. Arrival and departure of flights is the key thing to be managed. And the maintenance and logistics in the airport. We could use excel and powerBI to for dashboard and data visibility

Establishing robust data collection protocols is crucial for effective airport operations. Once key metrics like passenger flow, flight punctuality, and baggage handling efficiency are identified, implement advanced data analytics tools to process and analyze this information. Leveraging real-time data analytics provides actionable insights, optimizing scheduling and improving passenger experience. Integrating predictive analytics can help anticipate and mitigate potential issues, ensuring smooth operations and future-proofing your airport's strategy.

A lot of airport data comes from legacy operational systems. There is a wealth of data in there that you may not be aware of - the airport may not mandate that airlines must provide certain key datasets (e.g. PTMs) for every flight. Second, those airport systems are typically focused on specific airport operations - aircraft movement or ticket presentation. Where are the gaps in the passenger or bag journey where there are blind spots? Video analytics, LiDAR or Wi-Fi Analytics can generate new datasets to help to plug those gaps and build a more complete picture of the operation.

Data is the new crude oil which has to be refined in order to be meaningful. As a manager, we need to firstly ensure data integrity and good governance. Irrespective of how good a data analyst is, if the data you are working on is messy or lack integrity, all the insights drew out of it will be misleading. Having worked with the data integrity, then proper domain knowledge is essential to know the KPI of the organization you are managing. Apply appropriate analytics tools is also key for better data performance. Data can talk if you understand its language.

As an airport manager, I can leverage data analytics to optimize flight scheduling, gate management, and resource allocation, enhancing operational efficiency and reducing delays. Analyzing passenger flow and feedback helps improve the customer experience, while predictive analytics ensures safety and security by forecasting potential issues. Additionally, data-driven insights into retail, parking, and environmental impact enable revenue optimization and sustainable practices.

Once data is collected, integrating it into a single platform is crucial. Utilize advanced software solutions that consolidate data from disparate sources into a unified system. This integration allows for a holistic view of airport operations, facilitating better decision-making. For example, combining passenger flow data with flight schedules can help optimize staffing levels at security checkpoints. Effective data integration also enhances collaboration among different departments, ensuring everyone has access to accurate and timely information.

Data integration is the process of combining data from different sources to provide a unified view. For an airport manager, effective data integration is essential for comprehensive analysis, operational efficiency, and strategic decision-making.

In data integration you understand different perspectives of the clients and make sense of what works well going forward or where to enhance capacity of the resources for efficiency

Data integration as an airport manager involves consolidating data from various sources to ensure seamless operations, enhance decision-making, and improve passenger experience. #Benefits of Data Integration - Enhanced Operational Efficiency: Streamline operations by having a unified view of all activities. - Improved Decision-Making: Make informed decisions based on comprehensive, real-time data. - Better Customer Experience: Enhance passenger experience through better information flow and service coordination. - Cost Savings: Reduce redundancies and optimize resource allocation. By integrating data effectively, an airport manager can significantly enhance the efficiency, safety, and overall performance of the airport.

Analyzing integrated data is where insights are born. Use data analytics tools to identify patterns and trends. For instance, analyzing passenger traffic can reveal peak times, allowing for better resource allocation. Predictive analytics can forecast delays and suggest proactive measures. Encourage your team to delve deep into the data, looking for anomalies or outliers that could indicate potential issues. By thoroughly understanding the data, you can make informed decisions that enhance efficiency and passenger satisfaction.

As an airport manager, data analysis is where raw information is transformed into strategic insights. Start with exploratory data analysis (EDA) to uncover trends such as peak passenger volumes or bottlenecks in service areas. Leverage statistical methods and machine learning algorithms to dive deeper into the data. For example, using cluster analysis to segment passengers can help tailor services to different groups. Cultivating a data-savvy culture within your team is vital, empowering them to explore and derive actionable insights from the data.

With a centralised data repository, the data scientists can get to work testing hypotheses and identifying those big opportunities for step changes in efficiency, revenue and service. Data also needs to be cleaned, validated and properly governed so that it can be promoted to the Gold layer where data products can be built and curated, allowing business intelligence reporting. This builds trust in the data across the business - an essential first step to achieving the holy grail of self-service analytics.

Data analysis is a critical process that involves examining, cleaning, transforming, and modeling data to derive useful information, support decision-making, and enhance operational efficiency. As an airport manager, data analysis can help optimize airport operations, improve passenger experiences, and drive strategic initiatives.

It brings about comparison and coming up with decisions from the hypothesis looking at significance in variables in the design

Setting and monitoring performance metrics is vital for continuous improvement. Identify key performance indicators (KPIs) such as on-time departures, security wait times, and baggage handling efficiency. Regularly review these metrics to gauge your airport's performance. Implement a dashboard that provides real-time updates on these KPIs, allowing you to quickly address any deviations. Sharing these metrics with your team fosters a culture of transparency and accountability, motivating everyone to strive for excellence.

Performance metrics are quantifiable measures used to evaluate the success and efficiency of an organization's operations. For an airport manager, performance metrics are essential for assessing various aspects of airport operations, identifying areas for improvement, and making informed decisions

As an airport manager, defining and tracking performance metrics is critical for assessing and driving operational success. Identify key performance indicators (KPIs) that align with your strategic goals, such as on-time departure rates, average security wait times, and passenger satisfaction scores. Implement dashboards that provide real-time updates on these metrics, allowing for prompt responses to any issues. Regularly review and refine these KPIs to ensure they continue to reflect your airport’s operational priorities and challenges.

Key performance metrics for airport management encompass a wide range of operational, financial, and customer-centric indicators. Operational metrics include on-time performance, measuring the percentage of flights departing and arriving within scheduled times; Passenger-related metrics focus on aspects like average security wait times, check-in queue lengths, and baggage delivery times. Financial metrics encompass revenue per passenger, non-aeronautical revenue share, and operating margin. Customer satisfaction scores, derived from surveys and feedback, provide insights into the overall passenger experience. Environmental metrics, such as carbon emissions per passenger and waste recycling rates, are increasingly important.

After implementing the business logic now you can visualise the exact performance on the basis of required KPIs.You can use dashboard for this as it is a very good platform to showcase the performance.

By analysing the KPIs you can work on analytics part with the use of AI/ML models as it can affect the business exponentially.

Regularly reviewing and updating data analysis strategies to adapt to changing industry trends and technologies. Implementing feedback loops to incorporate insights from data analysis into operational processes. Conducting periodic audits of data collection and analysis methods to ensure accuracy and relevance. Benchmarking against industry best practices and seeking opportunities for innovation. Engaging in collaborative efforts with airlines, ground handlers, and other stakeholders to share data and insights for mutual benefit. Regularly soliciting feedback from passengers and staff to identify areas for improvement. Implementing agile methodologies to quickly test and iterate on improvement initiatives.

Continuous improvement is an ongoing effort to enhance products, services, or processes over time. In the context of airport management, it involves consistently seeking ways to improve operational efficiency, passenger experience, safety, and financial performance.

As an airport manager, fostering a culture of continuous improvement is essential for staying competitive. Use insights from data analysis to refine processes and implement new strategies. For instance, if data shows frequent delays during peak times, optimize staff schedules or enhance check-in procedures. Encourage feedback and innovative ideas from all team members, promoting a culture where continuous refinement is the norm. This approach ensures your airport operations are consistently evolving to meet changing demands and expectations.

Para um ambiente de melhoria contínua funcionar, é necessário contar com uma "bancada de especialistas de negócio". Após uma análise de dados, é possível identificar diversas oportunidades de melhoria, mas nem todas podem ser consideradas melhorias completas de imediato. É necessário considerar a política e objetivo atual da empresa, bem como os projetos em andamento para evitar retrabalho ou "piorias". Em outras palavras, é fundamental avaliar se a melhoria realmente traz valor ao negócio, e isso deve ser feito com a colaboração de pessoas especializadas que tenham uma visão geral das operações

Simulating the flow of aircraft, passengers and bags enables the AirPort Operations Centre (APOC) to advise teams in the terminals of the correct proactive interventions to minimise disruption. It enables complex decision support that cannot be done in isolation by individuals managing individual parts of the operation. In particular, the impact of elements like stand allocation on diverse areas such as ground handling operations, short-connecting passengers/bags Immigration queues and PRS services can be far better anticipated through predictive modelling.

Model optimization and Model Monitoring are two aspects which is to be considered as important part of the Model development cycle. Most of the time Model identifies the patterns/trends for shorter time frame but it degrades as the time frame increases. Better to tune your Model before putting it on production and monitor the performance closely with data drifts and identify the change in trends prior by using the latest methodologies.

Leveraging predictive modeling can significantly enhance your airport's operational efficiency. Use historical data to create models that forecast future events, such as passenger flow during holidays or potential delays due to weather conditions. Predictive models can also assist in maintenance planning, anticipating when equipment might fail and scheduling preventative maintenance accordingly. By proactively addressing potential issues before they arise, you can minimize disruptions and maintain a smooth operation.

Predictive modeling is a statistical technique used to forecast future events or outcomes by analyzing historical data and identifying patterns. In airport management, predictive modeling can be leveraged to improve operational efficiency, enhance passenger experience, optimize resource allocation, and support strategic decision-making.

As an airport manager, leveraging predictive modeling allows you to anticipate and prepare for future challenges. Develop models using historical data to forecast passenger traffic, predict weather-related disruptions, and plan for maintenance needs. Implement machine learning algorithms that adapt to new data, enhancing their predictive accuracy over time. This proactive strategy helps mitigate risks, optimize resource allocation, and maintain seamless airport operations, keeping your airport one step ahead of potential issues.

It is also important to note the connection flight information and the volume of passengers travelling with a connection. It is important to consider if the passenger can go through security check if any, passport control if any and baggage transfer if any required during these connections. These all along with the terminal changes are very common for international flights. This will also help with the layout of the gates and evaluate the minimum connection time that will reduce the number of passengers missing the connections.

Above all, data-driven airport operations are enabled through buy-in to the data strategy at the highest level of the organisation, so that the data transformation can include People, Process and Technology and create a data team that is empowered to deliver insight and drive business value.

You could analyse the fundamental factors of the data analysed, for example, the reasons for the decisions made behind the data collected. This can include the reasons for cancellations, travelling to different destinations, class of travel or the recruitment of skills based staff members. This can be combined with the initial data to produce a correlation of the covariance between the data and the fundamental analysis above.

Hello everyone! I would add to the suggestions you noted in each step of how should be the organization, planning, operation and evaluation of flights at an airport, that before carrying out each of the stages, you should know in detail the related laws that are in force both nationally, internationally, as well as international agreements -if applicable- on the subject. Without these regulations and the manuals of positions and functions that the control centers at each airport must have, it will be difficult to propose adequate ways for their efficient and risk-free operation.