Travel managers rely on accurate, timely and complete travel data to achieve their business goals of controlling travel spend, negotiating with suppliers, and managing programme leakage. In fact, without accurate travel data, it is very difficult for travel managers to make informed decisions when driving supplier negotiations.
However, a study* by the GBTA revealed that businesses struggled to reconcile data from multiple data sources, with staff spending an astonishing 442,000 hours per year manually reconciling and cleaning travel data. With only 37% of travel managers believing their data is completely accurate, this presents a major industry challenge.
Other findings from the study reveal that:
o Staff spend $22.7m per year manually reconciling and cleaning travel data
o 73% say that they have challenges reconciling differences in reports due to data formatting
o 82% of travel managers agree that they have to manage multiple data sources
o 64% do not trust that they have complete data to calculate the total cost of a trip
We know that travel managers typically rely on at least three data sources to forecast spend and make bookings: the travel management company, the corporate credit card and the expenses management system. However, as the majority of this data is held by external providers, the total cost of individual trips cannot be accurately calculated with data management systems using standard ‘deterministic’ rules because they often fail to mirror real-life travel behaviour.
For example, an employee books a trip from London to Paris for one week. He/she returns from the trip and claims for food and travel-related expenses before or after the trip officially started (this could be a cab ride to the airport, breakfast before the flight, etc.). A data management systems that works on a deterministic set of rules and principles may exclude these items from the total cost of trip because it’s not always possible to identify all the relevant costs, thereby reporting an inaccurate total cost of trip.
A travel manager, on the other hand, will know that these costs relate to the trip and attribute them accordingly. But what happens when there are thousands of travellers and thousands of trips?
The answer lies in data consolidation and machine learning automation. By combining data and machine technology, Travel managers can access a central repository of consolidated and de-duplicated travel data to quickly and accurately calculate total cost of individual trip. Armed with this information, they are in a much more powerful position to negotiate favourable terms with suppliers.
This post was written by Keesup Choe, CEO at Pi. Pi will be exhibiting at the Business Travel Show on 24-25 February 2016 - buyers can register for free entry to meet 250 suppliers, choose from 60 conference sessions and network with 7,500 professionals at www.businesstravelshow.com.