Our blog post ‘Why your airline KPIs have to be adaptable to specific situations’, was an ‘appetizer’ on why airlines should migrate to dynamic and flexible dashboards and KPIs — not only in crisis time. Today, I want to go into detail with some specific ideas and visualization design examples of how airlines could adapt their KPIs in the specific crisis scenarios.
Leaving aside for a few moments the #COVID19 crisis, I would like to focus on other possible crisis scenarios that I’ve considered interesting and will explain through the use of real-life examples. For this, I’ve decided to bring into the table three of the most recent and strong happenings in the aviation industry.
In the three different cases, airlines have suddenly found themselves in what are considered ‘tough situations’ that required immediate attention and response. However, to be able to improve the decision-making process for these specific situations these airlines needed to adapt their operational awareness overview.
First, I want to begin with one of the most crucial topics, airspace and border restrictions. For this case I decided to use one of the most important diplomatic crises, that took place in the middle east region.
The Gulf Crisis, Airspace and Airport Access Restrictions
After the political crisis initiated in mid-2017, the countries of Saudi Arabia, United Arab Emirates, Bahrain, Yemen, and Egypt cut the diplomatic relations with Qatar, blocking frontiers and forbidding the country’s airlines, such as Qatar Airways, from flying through their airspace and from-to their airports and vice versa. This required for Qatar Airways to be forced to immediately cancel around 18 regional flights and reroute its remaining flights to other destinations due to the airspace restrictions. (Source: BBC News Qatar crisis: What you need to know, July 19, 2017).
For such a situation, it’s necessary that an airline counts with a detailed station overview, where it could easily identify the restricted areas. Additionally, it will enable the count of airports and/or stations restricted per country, at a single glance.
This would not only facilitate the rerouting process, from-to other destinations, but also contribute to build the entire scenario overview with the support of additional relevant KPIs such as: cancellation rate, impacted flights and AOGs (Aircraft-on-Ground). With this information in hand, airlines can proceed to initiate the immediate required rerouting process, the fueling estimates, restructure network planning, pricing strategy, fleet and crew planning, passenger rebooking, among others.
How you could approach KPIs when there are air traffic or airport restrictions?
In the image above, you can see the station overview map where you can easily identify the restricted stations by the use of a light gray color to differentiate the affected countries or regions and dark gray for all none-affected regions.
At the same time, each country has its stations highlighted using bubbles linked with detailed pop-up signs indicating the impact rate, share of flights, flights impacted over total, cancellation rate and delay rate. The size of the bubbles indicates the share of affected flights compared to all scheduled flights on that day and on that specific airport.
The coloring of the bubble shows the impact rate based on the Index Calculation by Factor where the lowest value (1) corresponds to a low severity and the higher the value the more critical the factor is (5). In this hypothetical case we have selected the following criteria:
|Delay >3hrs||Departure with delay of more than 3 hrs||4||High|
|Delay >2hrs||Departure with delay of mor than 2 Hrs||3||Medium|
|Delay >1 Hr||Departure with delay of mor than 1 Hr||2||Medium|
|Delay <1 Hr||Departure with delay of less than 1 Hr||1||Low|
|Flight without incidents||Regular operating flight leg||0||Low|
Now, the calculation of the impact rate was performed in the following manner:
Impact Rate = ((#of Flight Legs with CXX * 5) + (#of Flight Legs with Delay > 3 Hrs * 4) + (#of Flight Legs with Delay > 2 Hrs * 3) + (#of Flight Legs with Delay > 1 Hrs * 2) + (#of Flight Legs with Delay < 1 Hrs * 1) + (#of Flight Legs without incident * 0)) / Total # of Flight Legs
Don’t forget, the selected criteria and punctuality thresholds are only examples. Each airline can adapt these to their specific situation and requirements. Looking into detail into the other KPIs we also have:
The donut widget on the right-side upper corner contains the flights impacted rate showing an overview of the entire affected operation including not only the flights canceled but the ones who have also been delayed due to rerouting requirements. The proportions between canceled and delayed can be differentiated with the colors orange (delays) and red (cancellations).
Aircraft on Ground
The middle donut widget indicates the amount of aircraft that are currently grounded (AOGs) due to the impact of flight canceled. How should this fleet be re-assigned to the still operating routes?
The donut widget on the right-side lower corner contains the amount of restricted destinations in order to determine the impact range of the entire operation. How many destinations from the entire operation are restricted or blocked? Can this be compensated with additional flights in the remaining operative destinations?
Airline Crisis Dashboard: When your fleet can be the cause of the situation.
Moving forward the second crisis scenario emerges from the two recent tragic accidents. The first one relates to Lion Air’s Flight 610, on the 29th of October 2018, covering the route Jakarta to Pangkal Pinang and the second one from Ethiopian Airlines’ Flight 302 on the 10th of March 2019, covering the route from Addis Ababa to Nairobi. The only thing in common with these two accidents was, that they both were operated by the same aircraft type, the new Boeing 737 Max 8.
The results of the different investigations indicated that a system that was implemented to help the plane avoid stalls had a malfunction. At the same time, crew members were not properly informed nor trained to override the software in case failure, which contributed to the accidents. (Source: New York Times Boeing 737 Max: What’s Happened After the 2 Deadly Crashes, October 28, 2019).
The second accident triggered an immediate reaction from governments around the world who ordered the entire fleet type to be grounded until the situation was clarified. This means the aircraft grounding was set for an indefinite period of time. For airlines depending on this fleet for a high percentage of their operation or airlines who have placed orders and expect to initiate operations with the Boeing 737 Max 8 it is important to figure what is the current situation.
- How many flights were scheduled with this aircraft type?
- How much of the entire fleet is grounded?
- How many flights are impacted and need to be assigned a new aircraft?
At the same time, airlines need to visualize the effects and evolution of the situation during the duration of the crisis, with the use of historical data. How many impacted flights per day (cancellations, delays)? Due to the change of aircraft are there capacity constraints? How many impacted passengers?
Having a grounded fleet? You should focus on these KPIs
The following example can provide an idea of how airlines can adapt their operational awareness in this type of situation.
Here comes one of my favorite parts of visualization. Mixing real-time data with historical data in a single workspace, using the same KPIs as before. But before moving on, I want to explain why I consider this real-time vs. historical mixture one of my favorites.
With real-time data, you are aware of the current situation, but usually doesn’t allow you to have an overview of how the situation was in the past and how it has been evolving during the time. By having this mixture in your dashboards, you can evaluate if the implemented measures are having a positive, negative or even a neutral effect, and proceed to make further decisions.
On the left side of the dashboard, airlines can use the KPIs to determine the impacted flights (delayed and canceled), AOGs and restricted destination of the current day, with the use of donut widgets.
This KPIs can get into more detail with the use of bar charts covering a defined period of time (days, weeks, months- it’s totally up to you). This will help you have an overview of the situation’s evolution during time. Has it improved? Has it become more challenging?
To check into detail the fleet impact you can also divide the information and KPIs based on the different aircraft type your airline has. How many impacted flights canceled or delayed, that were scheduled to be operated with a specific aircraft type? How many are non-operative?
And moving on to the last but not least of the crisis scenario examples…
Airline Crisis Dashboard: Strikes interfering in your operation
The last crisis scenario that I had in mind is also a very common one on affecting our industry. We constantly see airport or airline strikes affecting the regular operation and therefore the management has to react and do it fast.
A very famous example is the French Air Traffic Strike on May 2019, where air traffic controllers opposed to the new working conditions implemented by the government.
Even though these situations tend to be for short periods of time, or at least defined, the airlines need to act in pro of protecting their passengers.
In this case, airlines have to identify for example which airports are closed? How about also considering the number of alternative airports? This in case the situation is focused in one station.
In case, of an airline strike, it is necessary to visualize the cancellation rate, the passengers impacted, the AOGs, and also the historical evolution of the strike. For example? How many passengers are affected per day? Below I want to share with you an example of how a strike can have an impact of your passengers. Let’s never forget KPIs should also focus on the human factor.
Are your passengers being affected by the crisis?
If the crisis takes place in different stations you can see how many passengers are affected per station, but not just that. It is also possible to consider going into detail to understand the affected passengers per class. This could be done by the use of a donut map as seen above and the pop-up signs with the detailed information per affected station. What could this facilitate? Compensation overview? How many passengers should be rebooked?
Some other KPIs that could be considered in this case are:
How many passengers have canceled flights and how many have delayed flights?
Passenger by Booking Class
With this KPI you can easily visualize the proportion of passengers affected per class and the total amount of affected passengers of the day.
How many passengers have been rebooked in other flights, from the total amount passengers of the day?
What I wanted to transmit are the different opportunities you have to adapt your dashboards and information. The KPIs consider to be relevant for these specific crises’ scenarios are entirely flexible. This can vary according to each airline’s business model. Let us know your thoughts and ideas about what other KPIs can be relevant during this or any other scenario that comes to your head. Which other events do you have in mind where airlines need to apply fast decision-making in order to reduce the impact on their passengers? Share your thoughts with us.