Imagine if you have a crystal ball that tells you what’s in store for you in the future. People who opt to know often do so in order to be prepared for what’s to come. But those who believe the future is in their hands would use this knowledge to prepare. You’re not simply steeling yourself for what’s coming, you are actively taking the necessary measures to improve your outcome.
We encounter predictive modeling on a daily basis in our personal lives – whether it’s Amazon telling us what we need to buy or Spotify playing just the right music we want to hear on a rainy afternoon, or Facebook picking the stories you want to read right now on your newsfeed.
While the call to action in these instances is simply to buy or to read, in business travel, the power of being able to predict traveler preferences and forecast prices have a much greater impact on what you do with that (fore)knowledge.
A lot of data collecting, computing, and analyzing go into the more than 85 indicators and metrics we use to make our predictions. They include historic travel data sets, along with public data on commodity prices and macro-economic indicators, among many others. We take into account things we can anticipate with certainty (holidays) and those that are as fickle as, well, the weather, literally.
Using proprietary algorithms, these data points are used to identify patterns and correlations that, in turn, help us generate robust predictions for a company’s future travel spend, down to the number of trips and cost per trip.
Armed with this data, businesses can course-correct before the budget is spent and reallocate resources accordingly – whether in response to anticipated peaks in traveler demand or to encourage travelers to use alternative airlines or hotels. At the same time, negotiations with suppliers are done with the advantage of knowing how to adapt your targets and caps. The number of suppliers being managed can also be limited or expanded using a forecast modeled on your special set of variables in the future.
On a more nuanced level, the power of predictive thinking is in being able to drive stronger program compliance. How? By developing personalized itineraries for travelers based on what we know from previous behavior and interests. But we don’t stop there. We also throw into the mix what we anticipate will be future trends in the market that impact supply and demand. This creates a virtuous cycle of compliance that isn’t reliant only on historical facts but incorporates many forward-looking indicators. Using the same data sets, we can, also, conversely, anticipate a non-compliant traveler and accurately predict a trip’s chance for success based on its return on investment.
As we will demonstrate time and again, the power of predictive thinking is in how expansive it is in scope, yet incredibly targeted in its utility.
In our succeeding blogs, we will show you predictive analytics in action and share specific experiences – from challenges to outcome – that’s predicated on accurate predictions.