Our task was to understand how predictive analytics can affect airline business.

It was necessary to understand what factors this would affect. To solve this problem, I

used Mind Mapping. Our framework included directions that they were mutually

exclusive and collectively exhaustive.

The aerospace industry is very complicated.  If you add up all the profits of all

airlines in the world in the last year, it is still lower than that of Apple or Google have

separately. And we have to remember that this industry still has perishable stocks,

ruthless prices, and perfect competition when customers visit online portals where they

see airlines collide.  As a rule, you will see that the order of aircraft exceeds the

expected demand. New airplanes have extended delivery times, which leads to high

cyclicality. Hence, we need to model economics for a notional route bottom-up and

analyze all drivers.

At the top level, our framework consists of two areas: revenue and expenses

(Figure 1).  Here we show that predictive analytics during digital transformation can

increase revenue as well as reduce costs.

Further, revenue can be divided into passenger flow and price per passenger

(spends per passenger).  Predictive analytics can affect passenger loyalty, and ultimately

Figure 1. Framework of document analysis

Source: Author’s compilation

increase the number of flights that they perform, and also encourage spending more on

one flight.

Costs can be divided into variable and fixed costs.  Using predictive analytics,

there is possible to reduce fuel costs, direct labor, as well as other expenses per

passenger. There is also the possibility of reducing the cost of servicing aircraft, as well

as other expenses that fall on the management of the airline.

After the analysis, I can consider the main results that we obtained. Using Mind

Mapping, I got three insights:

• predictive analytics help to increase the number of passengers;

• predictive analytics would help to increase the average passenger spends;

• predictive analytics help to improve costs of the airlines.

Direction                     Airline  Revenue  Costs

Emirates Airlines

Last-minute sells over miles  redemption using predictive  analytics would help to increase the  number of passengers  Smart maintenance using  predictive analytics would  reduce costs

Investing in more expensive  passengers motivates them to use  airline services more

Qatar Airways

Individual offers via predictive  analytics for the passengers affect  revenue  Cooperation with hotels using  predictive analytics to increase  loyalty, hence increase the number  of passengers

Predictive analytics to reduce  fuel consumption

Airlines using predictive analytics  can encourage passengers to spend  money on other things

Singapore Airlines

Tracking, measuring, and  benchmarking costs with the  use of data analysis would  improve costs

Flexible miles for flights would  encourage more people to buy  tickets

Advanced techniques in the pricing  of airline tickets would choose the  best price, thereby to increase  revenue

Table 1. The role of predictive analytics in airline digital transformation, grouped by the

direction of influence

Source: Author’s compilation

Having obtained the results (Table 1), we can say that at the top level, predictive

analytics can improve both the revenue and expenses of the company.

Revenue can be improved by increasing passenger flow and price per passenger

(spends per passenger).

Costs can be improved by reducing variable and fixed costs. Using predictive

analytics, there is possible to reduce fuel costs, as well as other expenses per passenger.

There is also the possibility of reducing the cost of servicing aircraft, as well as other

expenses that fall on the management of the airline.

In general, the analysis results can be called successful, because using Mind

Mapping I was able to get all the information I needed.

