Next year’s travel savings? Maybe. Next year’s travel spend? Maybe. But he won’t pick your firm’s future travel policy compliance rate, or next year’s average airfare, or your traveler’s future satisfaction with your online booking tool.
My point is that while firms spend a lot of money on travel data reporting, the core value that those pretty dashboards deliver is not very high – not in the grand scheme of your firm’s business.
Here’s why: Data reports are the result of the 20th-century management dictum “Measure what matters”.
Within the boundaries of a travel program there are dozens of things that matter. And so we’ve figured out how to measure them. In order to report them. In order to manage them.
But all those dials and gauges and stop lights really do is simply give you signals. Signals that you have to interpret to keep your travel program between the white lines of your side of the road.
What those travel dashboards don’t do is tell you how to get to a better travel program.
They can’t, because they have two big flaws:
- Data reports are stuck in the past
- Travel data reports are stuck in the world of travel
Enter Predictive Analytics
The key is linking travel’s impact to business outcomes. Outcomes that matter on a much bigger scale, like sales, customer satisfaction, employee attrition, health/safety costs, etc.
This will fundamentally change the way you view and manage a travel program.
Instead of seeking to minimize travel costs, you’ll be trying to maximize sales, or perhaps minimize employee turnover – by putting a travel program in place that clearly contributes to those goals.
If sales are trending down, or employee turnover is trending up, what should you, the travel manager do to help fix these problems?
Obviously, you’ll need some new lights on your dashboard – lights driven by data from Sales and HR. More importantly, you’ll need to know how to impact those non-travel metrics.
That’s where predictive analytics comes in. You need to have a data-driven understanding of how things like cabin policy and hotel tiers impact bigger, non-travel metrics like employee productivity, health and safety, and attrition.
You need to predict with confidence that by changing a variable in the travel policy, it will cost $X and improve the non-travel metric by Y%.
You’ll do this in one of two ways. If your travel program is big enough, you’ll be able to mine your own data and build these models. If your program is too small to offer enough data, you’ll depend on benchmarks and case studies from the larger firms.
Management theories evolve. Dictums change. It’s time to move on from measuring what matters to predicting what matters.
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