The current flight booking system involves a total of seven steps spread across primary sets of details and additional customer details. These steps, some critical and some not, become redundant the more you book flight tickets and can be predicted over regular use of a portal.
Humans have a tendency to fall into behavioral patterns that can be predicted. This is where Machine Learning comes into the picture. Using advanced computing algorithms to predict the outcome of flight booking tendencies, the entire process can be made simpler.
With this, the entire process can be brought down to two simple steps, drastically reducing the booking times from 30 minutes on average to less than 2 minutes.
Booking flight tickets could be as simple as saying "Hey Google, book me a ticket to San Francisco on the 12th of this month" and that's it!
This challenge gave me the opportunity understand the intricate details behind booking flight tickets, a process I myself was intimidated by, up until then! To be able to understand the system and optimise it gave me an opprtunity to benefit not just the millions of passengers who fly everyday but also my family and I directly.
Given more time to work on this challenge, I would have interacted with more participants to help me refine the scope of the solution and conceptualise a dedicated solution. I would also have designed possible deliverables that would reflect how the sysem would work.