The primary use case of an airline operations real-time dashboard is about visualizing information an KPIs. No doubt about it. However, a dashboard infrastructure —at least when talking about our product setup— collects a vast amount of data from different sources (flight data, passenger data, airport data, etc.).
Based on that three use cases can be realized. All of them providing a huge potential without substantial additional investment.
Let’s starts with the basics first
To present real-time KPIs and information, an infrastructure is required that collects, processes, and stores data. For example, with our product, the A:Wall, we operate a data warehouse that is tailored to these tasks.
That data warehouse is tailored to collecting data from different sources/systems, to process it and to archive it in a structured way. Displaying the information within the dashboard or on your mobile is finally only the icing on the cake.
Most of the effort is linked to collecting and processing data but not to visualizing it.
When discussing the setup with clients some years ago, we identified the possibility of using this data also for other use cases — instead of showing it on dashboards only.
Accordingly, that means we are not talking about alternative use cases of a dashboard, but use cases the infrastructure —mainly a required data warehouse— brings with It.
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The importance of data analytics is steadily increasing. And I’m not even talking about big data, machine learning and stuff like this. But I’m talking about a reliable, comprehensive and broad data source to fuel analytics measures.
Many airlines —especially small and mid-sized airlines— we have been talking to through recent years have not been operating a dedicated data warehouse. Conversely, data often is stored in databases of different systems. However, such a setup massively hinders the process of data analytics.
As mentioned above, one crucial step to provide real-time information and KPIs is in connecting data sources, collecting data, and storing it.
Accordingly, while gathering all required data, a combined and reliable source can be provided for data analytics. Without any additional hardware, interface, or anything else.
The only step to take is to provide access to this data. Typically, this is achieved by using standard tools, for example, Tableau or PowerBI.
The benefits are obvious:
- Besides standard analytics tools, no need for additional infrastructure.
- You can access a holistic data platform
- Integrated data can are useful for both analytics and in the context of your real-time dashboard.
Although we actively promote real-time KPIs and dashboards, weekly and monthly reports still have a right to exist and provide additional value. From our experience with airlines, many of them still rely on manual or semi-automated creation of weekly and monthly performance reports.
Also, from discussions with airlines, we know that the creation process can be painful due to collecting data from different sources. But that’s not all. Afterward, raw data is often calculated and prepared in Excel. As a final step, Powerpoint is commonly used to create a report.
Summarized, a time-consuming, inefficient, and error-prone process.
Since one vital function of real-time dashboards is in calculating KPIs, it seems reasonable to extend the usage from real-time to historical reports. Especially bearing in mind that all required data is already available.
With our product, the A:Wall, we provide a smart add-on that calculates historical KPIs (weekly, monthly, etc.). Subsequently, KPIs are offered in an easy-to-read report format on a defined regular base.
Single-source-of-truth or API to drive business
The final use case we want to introduce is a more complex one. But also one that holds an enormous potential. Again, the core idea behind is that the data warehouse contains data from a variety of operational systems. Moreover, this use case addresses a particular challenge many airlines face.
Setting up new systems or extending existing ones often leads to the process of building required interfaces. Usually, building those interfaces is one of the main efforts and cost drivers. This is mainly driven by the fact that data is scattered across various systems in different formats and quality.
Of course, middleware solutions are one way to tackle this challenge. Nonetheless, an alternative we consider as even efficient is in providing structured access to the entire data contained in the warehouse.
We achieved this by setting up a standardized API that allows access to data in real-time. Thereby, systems that require specific data can efficiently utilize the existing API and request required data in standardized, documented, and structured way.
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