Carlson Wagonlit Travel this week launched "a next-generation data insight, reporting and visualisation tool that works like a personalised search engine that knows everything about the client's travel programme".
There is no doubt about the benefit that CWT AnswerIQ will potentially bring to the TMC's clients. As Eric Tyree, chief data scientist, described: "You type your request in the search box, AnswerIQ goes through all your data, and gives you the answers — visualised for ease of understanding."
Clients will have access to three years' data which can be visualised in different ways.
There is a potentially massive benefit in what CWT is doing. There is also a potential shortfall.
Clients are already able to access their booked data but the clear suggestion is that the CWT tool will be able to use that data to identify either the problem — or solution — for which the client is searching. The description suggests more than a passing resemblance to Egencia's Analytics Studio which was launched this summer at GBTA.
Making use of AI and machine learning to analyse data and suggest improvements or solutions is valuable but as Egencia pointed out in its launch, these tools not only allow managers to make use of data to see how behaviour can affect cost but they can do this visually.
The visualisation enables any findings to be easily communicable to the other stakeholders that travel managers must inevitably convince when they seek to make changes.
A travel department no longer exists in isolation. Managers are increasingly working with other corporate stakeholders from areas such as IT, finance, HR and risk. These people may all have an interest in the travel policy or programme but that is a far cry from their understanding all the nuances of business travel or having the time to try to understand the implications of any changes in travel policy or sourcing practices.
Stakeholders are professionally interested but any analysis of corporate travel or recommended changes to travel policy needs to be communicated to them clearly and effectively. A data insight, reporting and visualisation tool can do this.
That is powerful. But is it enough?
These tools rely on historical data. Although CWT maintains that its data store is updated throughout the day, what it is collecting, measuring and analysing is achieved data so all policy decisions based on this are in fact based on past behaviour.
The trend is to use multiple sources including, for example, general economic market trends and social media to build up a picture of probable future behaviour.
This so-called predictive data is invaluable in identifying probable future demand and behaviour and therefore adjusting travel policy and buying decisions based on what is likely to happen rather than what has happened.
When the AI/visualisation tools can generate predictive data, they will be very powerful indeed.