Travel 22nd December 2020 - 5 min read

Don’t analyze and fix, predict and prevent

By Jason Kramer

I’m Jason, your Data Insider – a former travel management consultant turned data geek. In my new gig at leading data intelligence firm PredictX, I have seen what an effective data strategy can do for all-round travel programme improvement. I want to share this knowledge to those wanting to start or improve their current data strategy. Each month I will be sharing a different tip. This month’s tip is: Don’t analyse and fix: predict and prevent.

In my last blog, we spoke about avoiding the data dump and some remedies to avoid it. The data dump is when your monthly reports and dashboards arrive from your TMC or their consultancy and your anxiety rises because you question its accuracy and you’re struggling to find what you “need to know.” This approach is neither valuable nor efficient, but it is common.

In my newest blog, we take what we learned about using multiple sources of data (TMC, card, expense, HR), applying a data verification process and then communicating the data story. By taking these valuable steps, you can easily have data that is timely, accurate, and that can lead to more progressive action in your programme.

Our next step is leveraging your data and making it fit for the future. We want to move away from the common “analyse and fix” model of travel management and instead apply the more forward thinking model of “predict and prevent.” If you look at it in the context of your suppliers, those suppliers can predict traveller behaviour and future travel demand by applying machine learning and thus extract the optimal price at any given time of booking. Suppliers are able to “predict and prevent” and you can too. Why not apply that same concept to your travel data?

Buyers can apply the same mechanisms suppliers use. They can do it by incorporating TMC, card and expense data into a broader data strategy that includes existing technology to optimize it.

Instead of using data to “analyze and fix” patterns in past travel, you can leverage your data to “predict and prevent” unfavourable outcomes in future travel. This will allow you to see, ahead of time, what impact the changes you make to the programme now has on programme performance in the future. Armed with this intelligence, you are best positioned to make smarter decisions for your programme.

Prediction in 2020 and beyond

Considering the pandemic has wreaked havoc on using historical travel-related data in 2020, buyers should start looking beyond past behaviour and analyse future behaviour instead. As we negotiate a return to travel, programme activity will need to be monitored more closely and more predictively in order to ensure employee safety, have more control over bookings made and negotiate rates in, what promises to be, an increasingly volatile and rapidly changing market.

So how do we use data to “predict and prevent”?

We can use data to gain valuable insight into the future when it comes to two things: traveller behaviour and total spend.

Predict future traveller demand and behaviour

“The best predictor of future behaviour is past behaviour”, are famous words said by many including psychologists Albert Ellis, Walter Michel, and B.F. Skinner, as well as writers like Mark Twain.

If we look at traveller booking habits, we can easily analyse the data on their booking patterns and use predictive analytics to determine future demand, market share performance, and, if required, correct behavioral challenges.These are a few examples. Once companies are armed with this knowledge they can better plan their air, lodging and ground programmes to provide maximum value and improved deals.

Predict future travel spend

One of the best use cases of data is the ability to forecast results before they happen. Let’s take your budget as an example. If you’ve budgeted 100M in travel related spend in 2021, a frequent question you will receive is how are you performing according to budget. Using predictive analytics, you are able to apply current spend trends as well as past spend patterns to forecast budget vs performance each month. If you analyse this per department, you can use data to communicate intelligently how any department is performing to their own travel budgets, rather than only looking at the company as a whole.

If your data strategy allows you to easily access this visibility, decision-making will be easier to do and stakeholders may be more willing to buy-in to your strategies.

With an unpredictable 2021 and an increased profile for the travel team within their companies,communicating data that shows visibility into the future is now vital. Gaining visibility into the future will impact decisions made today steering committees will be able to create improved company policies and strategies around the return to travel in the future.

Even though predictive analytics and machine learning is thought to be a future reality, its capabilities are already here today. Travel suppliers are using more intelligent analytics to augment their strategies. Buyers can start doing the same. Using this technology, all players in your travel ecosystem can work together to better serve travellers.

Address safety issues ahead of time

Naturally proactive traveller safety is paramount. When it comes to ensuring traveller safety and flagging any risky bookings, pre-trip data feeds are essential. Using pre-trip data, you can see any potential issues ahead of time and take action. The biggest challenge is: how do we easily spot these data points? Nobody is going to spend hours looking at the data.

Today we have machines to do this for us. Instead of just receiving a data feed, machine learning models can analyse these data feeds proactively and flag potential risky bookings or fraudulent transactions ahead of time. The PredictX Digital Assistant can do this for you.:proactively scanning data overnight and delivering a “task list” by flagging potential violations and safety issues for you first thing in the morning.

Another helpful tool is The PredictX Inspector for Expense data, using machine learning to catch even the most complicated fraudulent transactions. You will no longer have to fight fires and manage issues, but instead will have time to work more proactively – ensuring a smoother transition back to safe travel and more time to focus on strategy.

PredictX uses machine learning technology to create data analyses that not only “analyses and fixes” past trips but uses predictive analytics and forecasting to help travel buyers “predict and prevent”. Issues can now be dealt with earlier on and the travel programme is optimised for the future. If you want to hear more about how we use pre-trip data, forecasting and predictive analytics in our platform, book a quick consultation.

Jason Kramer
By Jason Kramer
5 min read

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