Before the 1980s, flying was considered a luxury exclusively for the moneyed few. But with the passage of the Airline Deregulation Act in 1978 and thus, the lowering of the cost ceiling for flights, newer airlines were given the chance to compete with titan companies. Flying was opened up as an economically viable option for travelers of all walks of life, and the travel industry as a whole evolved to accommodate some staggering changes.
Forty years later, the tech boom has made its own visible impact on travel, and one revolutionary force that has shaped the airline industry is big data. The collection of vast amounts of data, plus the employment of data systems that are expansive and agile enough to handle all of it, has proven a winning formula for travel-related businesses.
How has big data become a boon to the travel industry? Read on to find out about real-time data input, data management strategies in platforms employed by big companies, and a business model that’s reached new heights in optimizing travel.
How It Works: An Example from the Airline Industry
Suffice it to say that data analysis is no longer a second-fiddle process for the travel industry, which once depended on traditional analytics methods over extended periods of time in order to make eventual time-and-cost saving changes to their business models. Later, breakthroughs in computing technology have helped companies like airlines engage with big data in processes such as predictive analysis.
This means the approach to customer data is predictive, rather than reactive; instead of dealing with problems as they arise, the data management strategy becomes about pre-emptively tackling any inefficiencies, optimizing plans in real-time, and passing data back and forth efficiently between databases for immediate use.
Take the example of real-time flight planning by airline companies. Big carriers now employ flight planning services that optimize flight routes. This is done by analyzing a large body of data that comprises elements like costs, fuel, and travel time, i.e. what flight combinations are available between locations, what services are available, and what the range of costs is given those options.
The data is then replicated to a central data repository, and optimized plans are conveyed back to the customer airlines for local access. The data systems must be flexible, scalable, resilient, and airtight all at the same time equipped with the capacity to replicate so much data and work across hundreds of target bases, in a swift and secure manner.
A Business Model that Soars
The payoffs of real-time analytics are evident: when customers’ real-time needs are efficiently addressed, they are willing to make purchases at maximum value, and travel companies are able to substantially increase their profit margins. Those in the airline industry, for one, have seen theirs grow by millions of dollars across the years. Managing big data translates to a greater level of understanding between those in the travel industry and the customers that they service, with regard to the evolving list of needs per location, demographic, and others.
Ultimately, it is about growing the business model to meet these arising needs getting ahold of big data and creating a capable network to handle it all, crafting many possible options, and wisely allocating the resources to make it all happen.
Something like flying via airplane need not be a luxury anymore not with a burgeoning pool of customers who are more willing than ever to take to the air, and excited for airline companies to guide them toward all the best possibilities. And it’s a win-win situation a business that is willing to harness big data within a smart, creative, and accommodating model is well-prepared to soar sky-high into greater profits and growth.