Fast-growing companies can use data analytics to optimise business travel’s performance – and contribution.
Planning a journey? Which route you’ll take? Chances are you’ll do research before you make your decision. You’ll compare your last trip, how you got there, ask friends about their experiences, and plan for any hurdles like road work or large events. This is data analysis in action to get you to your destination.
It’s also a vital part of travel management.
Travel management companies make sure that businesses have the relevant numbers at their fingertips: Trips taken, average fare paid, and the most popular cities.
Managers can now get numbers on anything their company did in the past. Now, travel managers can use real-time numbers to support future decision-making. This offers ample opportunity for business travel planners to use predictive data and leverage external sources to make travel policy decisions.
It’s the thinking behind data-driven enterprises, and it’s become standard operating practice for many organisations, especially fast-growing businesses.
Accenture’s recent report on data-driven enterprises describes organisations that are “maximising the value of data and treating it as a differentiated asset. It means using data as the basis for critical decision-making through high-quality analytics.”
Departments used to operate in information silos. They would keep track of their numbers, their way, for their purposes, and merge only the top-line figures. Being data-driven “means cultivating a mindset throughout the fabric of the business to continually use analytics to make fact-based business decisions. The goal is to reach a stage where the use of data and analytics by executives and employees becomes a natural part of their day-to-day workflows.”
Today, travel managers can use tools that can combine company-specific data with what is likely to happen with the company’s market, whether that be the sector or the regions of the world in where it does business.
Tools that link to data visualisation help with data analysis and can be packaged to form recommendations in an easy-to-understand picture for senior management, other internal stakeholders, and traveller.
A data-driven enterprise will allow the business travel planner to get a lot of useful data from other departments.
For example, a lot of travel sourcing strategy is based on past behavior. If Hong Kong, Frankfurt, and Melbourne were a company’s top business travel destinations last year, the travel manager might anticipate the same when they project next year’s travel volume. But access to the marketing team’s data might reveal that they’re planning a campaign to focus on Southeast Asia while sales team data could show this will be in tandem with targeting prospects in Singapore and Kuala Lumpur. It might all add up to a sudden spike in demand for travel on these routes.
Other departments may also be getting a lot of useful information from travel data.
For example, human resources might be reviewing how many hours each week employees work. In the past they may have measured working time as days that weren’t taken off for sickness or annual leave. But is a travel day – one when you have to get to London’s Heathrow airport in time for a 7 a.m. flight to Frankfurt, have meetings from 9 a.m.-5 p.m., and then head back to the airport for a 7:30 p.m. flight home the same amount of working time as a day in the office? This is an instance where business travel data could be very useful for human resources input into any traveller well-being policy.
It’s a win-win situation: Travel can benefit from internal data and other departments can benefit from travel data.
A good business travel partnership can help fast-growing companies achieve much more than getting travellers from point A to B.
Learn how growing tech business Top Hat are using data to get the most out of their business travel in our case study.