Meyer adds while it can also be used to identify any travellers who have simply checked into the wrong hotel, the most popular use is dealing with “weather disruptions causing massive inconveniences across the US”.

The library function offers insight into spend. For example, reports can quickly be generated showing annual year-on-year spend comparisons - either set up as live reports with a unique URL, or emailed as a PDF. They can also be scheduled to be sent out by travel managers.

Triggers can also be set up, for example, if certain conditions are breached or met. As well as watching out for employees wandering into high-risk areas, certain staff may be placed on watch to ensure they receive the red-carpet treatment wherever they travel. Another trigger could be set up to ensure certain “rogue travellers” do not check into blacklisted hotels.

Click and go

Getting down to the minutiae of travel arrangements like this chimes with the current trend of “little data”. “Big data is just a phrase - and travel data is big data. We’re making data sets smaller,” Meyer argues.

“Gamification is another over-hyped word. Clients can point-score with Insight, for example, to show if someone is a good traveller or bad traveller. Gamification is about informing and encouraging.”

Overall, Insight is meant for high-level staff, cost-centre owners or people who don’t have a lot of experience with travel data. “It’s click and go,” claims Meyer.

“You don’t need a team of analysts to send out the data,” he adds. “Insight helps travel information get down to new levels. One of our clients deals with 90 countries, and spend data can now be sent out to 4,000 cost-centre heads. Historically, they wouldn’t have been able to have this.”

Intelligent data

However, as the travel industry evolves, so too does quality of data. Bryan Boswell, HRG lead product architect, says data is now becoming fragmented as travellers start using sites such as Airbnb. “The world we live in is constantly changing,” Boswell says.

“The Insight Data Manager intelligently pieces data together. We have a type of artificial intelligence that makes assumptions, but we’re open about this. We will tell clients it’s an 80% match, for example.”

However, he argues this ability to take onboard data from third parties, make assumptions and show the degree of accuracy, is what separates Insight from other tools.

As a result, Meyer believes Insight is “half-way there” and it will eventually replace all of the HRG systems. “There’s another two or three years to go, as there’s a lot of legacy there. And there are other challenges with getting good, hierarchical data from corporations.”

He aims to consolidate credit card data into the system - which may arrive sooner than later as the use of virtual cards grows among the card providers.

“We’re driving behavioural change, but the big challenge is getting ‘perfect’ data. Clients are starting to expect data perfection.”