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 . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: 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 .
### Output: 