What's the best way to prioritize your airline data analytics questions?

1 Define your business goals

The first step to prioritize your airline data analytics questions is to define your business goals and align them with your data sources. What are the key performance indicators (KPIs) that matter most to your airline? How do you measure them and track them over time? What are the data sources that can provide you with the relevant information and insights? By clarifying your business goals and data sources, you can narrow down your data analytics questions to the ones that directly support your objectives and can be answered with the data you have.

2 Use the SMART framework

The second step to prioritize your airline data analytics questions is to use the SMART framework. SMART stands for Specific, Measurable, Achievable, Relevant, and Time-bound. These are the criteria that can help you evaluate and rank your data analytics questions based on their feasibility and value. For example, a SMART question could be: How can we increase the average ticket price by 10% in the next quarter by adjusting our pricing strategy based on demand and seasonality? A non-SMART question could be: How can we make more money from our flights? By using the SMART framework, you can filter out vague or unrealistic questions and focus on the ones that are clear, actionable, and impactful.

3 Prioritize by impact and effort

The third step to prioritize your airline data analytics questions is to prioritize them by impact and effort. Impact refers to the potential benefit or value that answering a question can bring to your airline, such as increased revenue, reduced costs, or improved customer loyalty. Effort refers to the amount of time, resources, and complexity that answering a question requires, such as data collection, analysis, visualization, and communication. By prioritizing by impact and effort, you can identify the questions that have the highest impact and the lowest effort, which are the ones that you should tackle first. You can also avoid the questions that have low impact and high effort, which are the ones that you should drop or defer.

4 Validate and iterate

The fourth step to prioritize your airline data analytics questions is to validate and iterate. Validation means checking the accuracy, reliability, and relevance of your data and your analysis. You can validate your data by ensuring that it is complete, consistent, and clean. You can validate your analysis by testing your assumptions, hypotheses, and methods. You can also validate your results by comparing them with other sources, benchmarks, or feedback. Iteration means refining and improving your data analytics questions and answers based on new data, insights, or feedback. You can iterate your questions by asking follow-up or deeper questions that can reveal more details, patterns, or trends. You can iterate your answers by updating or modifying your analysis, visualization, or communication based on new data, insights, or feedback. By validating and iterating, you can ensure that your data analytics questions and answers are accurate, reliable, and relevant to your airline.

5 Communicate and act

The fifth step to prioritize your airline data analytics questions is to communicate and act. Communication means sharing your data analytics questions and answers with the relevant stakeholders, such as your managers, colleagues, or customers. You can communicate your data analytics questions and answers by using clear, concise, and compelling language and visuals. You can also communicate your data analytics questions and answers by using the right channels, formats, and frequency. For example, you can use dashboards, reports, or presentations to communicate your data analytics questions and answers. Action means using your data analytics questions and answers to inform and guide your decisions and actions. You can use your data analytics questions and answers to identify and implement the best solutions, strategies, or policies for your airline. You can also use your data analytics questions and answers to monitor and measure the outcomes and impacts of your decisions and actions. By communicating and acting, you can turn your data analytics questions and answers into value for your airline.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?