New Data Dimensions

What will that improved data and AI layers begin to bring to travel programs?

Hopley: There are so many ways you can look at data and analyze it, but people aren’t doing it because they’re in their little silos. And even if you are benchmarking with a TMC, maybe you are looking at five “like” companies or maybe 10. But why not look at a much bigger data universe and see what’s really going on in the market—especially if you can apply AI layers to it? AI will take all the data and information we’ve got, and it will be able to tell you—probably accurately, but we’ll have to make sure the models are right—which carriers you should be doing business with and what rates, or how your contracts should be different. It’s not going to be comparing one company’s negotiated rate against another. Rather, it will understand the market and the individual program and be able to deliver insights. That’s where we’re going with it. And not just for airline contracts, but that’s an example, and I find it absolutely fascinating. 

You will need the data from corporations to do that.

Hopley: Yes, but why not contribute the data if 1) it’s completely de-identified and 2) the corporate stands to be compensated for it each time another company pings against it?

Is there a point at which all this just becomes available in a booking tool in real time? Or, for that matter, it’s able to project a future rate to inform bookings at the point of sale?

Hopley: I think decision-making in corporate travel has been relatively myopic based on too little information at the time of purchase. So currently it may be better to have a rule in place and a negotiated rate to control spend to a known level, rather than making the best decision with the information you have in the moment.

So what happens to the concept of negotiated rates if there’s real-time data visibility? Are you saying there won’t be a need for them?

Hopley: I think that’s the right question, but I think it’s going to evolve because we don’t have validated proof that it will work. We assume it will work, so we move into this process, and we assume it will be better, but it’s too early to say. However, I’m going to go down that path [of trying to provide decision-making data at the point of sale] because I think it will, and I think it will make life a lot easier.

 Is it all about rate, or how would you facilitate other decision-making factors?

Hopley: Take a hotel, for example. Does it have a restaurant? Does it have a swimming pool? Does it have a club floor or a meeting space? There are all types of decision-making factors when you are booking a hotel room. Does it have the amenities you need for the trip, and what is the price? Travel managers may want to think that a hotel is booked because it’s company policy and, therefore, it’s the sensible thing to do. It might be that it’s not the sensible thing to do. What if an adjacent hotel has better amenities, a meeting room and costs less? In an AI system, they could collect all the individual pieces of data quickly and assemble them in a way in which someone, instead of making a decision based on policy or—sometimes—on points, they can make the decision based on the value to them. Then, looking at that data, again aided by AI, the buyer could learn what specifically their travelers value and, potentially, drive better and more effective deals if they do continue to negotiate.

Thank you so much for spending the time to speak with me, Susan.

Hopley: It’s been a pleasure. Bye from the U.K. It’s time for tea.