Horse-versus-Locomotive Competition

As a coffee drinker, I always wonder why I pay the same price for a take away black coffee at 10am as the sales rep nursing a coffee at a table for four during rush hour, drinking his Joe with two creams, three sugars and an extra heat protector sleeve. 

As Ian Ayres tells us in “Super Crunchers”, we are in a historic moment of horse-versus-locomotive competition, where intuitive and experiential expertise is losing out time and time again to number crunching. In the old days, many decisions were based on some mixture of experience and intuition. Today the name of the game is data. Data driven decision making is changing the way companies do business. In field after field, “intuitivists” and traditional experts’ are battling Super Crunchers. In medicine to movie rental recommendations, Super Crunchers are not just changing the way decisions are made, they’re changing the decisions themselves. 

Data-based decision making is on the rise all around us. In travel, rental car companies are refusing service to people with poor credit scores because data mining indicates a correlation with the higher likelihood of having an accident. 

Airlines are leaning to giving upgrades and other favorable treatment to customers that make them the most money, not those who travel the most.  Airlines have super crunched the numbers for years to maximize the profit on each seat creating a situation where we are all convinced every other passenger is paying a difference price.

70% of airlines are customers of Teradata, a firm that warehouses and analyzes large datasets. Continental knows not only what customers are profitable, but which customers are at risk. 

This leads me to a question about travel agency fees. When each trip is unique and every booking process is as different as the traveler or company involved, why do most TMCs charge the same transaction to every customer for each trip type? With the advent of super data mining, instead of having more profitable customers subsidizing the less profitable, would it not be better to target fees to the company, traveler, type of trip, services sold, agent experience, pain thresholds or even time of year or time of day booked? 

Super crunching has created a new science of extractions. Data mining increase firms’ ability to charge individualized prices that predict our individualized pain points. 

Is it possible for TMCs to data crunch the numbers and charge fees based upon a myriad of factors? Is it even possible? Tell me what you think.