The BIG Rethink meets big data: how it’s transforming our industry
Here’s a fact to stop you in your tracks: there are currently at least 97 zettabytes1 of data in the digital universe.
That’s 97,000,000,000,000,000,000,000 bytes.
Or 97 trillion gigabytes.
Or roughly 13,000 times the scientifically estimated number of grains of sand on planet Earth.
Yes, really.
And that eye-watering number is growing. With the figure estimated to reach 181 zettabytes by 20252, the big question for data is: how do we find meaning in the mass input and turn it to our advantage?
When we think of big data these days, we inevitably tend to think about the technical innovations that have been developed to make sense of it: AI, machine learning, predictive analysis, and quantum computing.
Let’s face it – no matter how good your Excel skills are, a spreadsheet’s not going to cut it anymore.
So that’s the big picture – but what does this mean for the travel management sector? How can we effectively use all of this data to introduce control, mitigate risk, and enhance the experience for all corporate stakeholders, from finance and travel managers to the travellers themselves?
Let’s get started.
Redefining reconciliation and taking back control
Travelling for business can be a complicated affair.
From tickets, taxis and time spent in hotels to delays, stopovers and lunches on the go, each trip has a multitude of transactions that all feed into the overall cost.
Traditionally, reconciling all of this has been a serious pain point for those tasked with keeping track of it all.
Sounding familiar?
Well, the key to unlocking this problem lies in the data it generates. Having the tools to collect that data in the first place, in the right format, is where the latest technology shines.
The alignment of data with the systems that ingest it is the secret here – that’s when insightful decisions can be made. The ability to get truly granular with all those data points delivers the ultimate benefit pair: control and flexibility.
Control can have a negative rep – think “big brother” – but when combined with flexibility, it actually affords more freedom and choice to employees. Smart data analysis and monitoring empowers end users, reassuring them (and their employer) that they’re keeping within company policy and acceptable use – and that they have the power to make meaningful decisions at the ground-level about how they pay for things. Combined with automated reconciliation, this streamlines the entire process for everyone involved.
So how do you make sure the right data, in the right format, is collected in the first place?
Let’s join the ongoing quest for standardisation.
Setting new standards
We can paint an optimistic picture of all data coming from a single source that’s perfectly formatted, but the reality is usually very different.
Multiple payment architectures, suppliers, endpoints and even local cultures can all make for a mess of poorly aligned data.
But AirPlus and the travel management platform Roomex can offer the answer. By working together, we can create integration frameworks that map multiple data points from business travel activity and standardise the output so that our customers can track things like an employee ID or a project code across multiple transactions and systems.
More and more big players are signing up to this model, but the continuing challenge is that smaller players and ancillary data points require very specific mapping to integrate into the main data set.
At the product end of the process, innovations such as being able to issue a unique card specifically for a single trip – whether the latest virtual cards or physical ones – can standardise the format and provide the opportunity to customise which data points are collected in the first place.
We’re still at the start of a long journey towards standardisation, but we’re already seeing the real-world benefits it produces – and wherever there are clear opportunities to save money, the markets will ultimately follow.
But even if it’s perfectly standardised, how exactly do we work with all of this data once we have it? And how do we extract meaning from it all?
Uncovering the tools of the trade
Let’s take a moment and look at the question: what is big data, anyway?
It’s a term that’s been kicking around since the 90s, but as is often the case with these things, it’s easy to assume people know what you’re talking about when the definition may not actually be universally understood.
The general consensus is that big data is a set of information – whether from a single source or multiple sources – that is so large that traditional manual or even semi-automated analysis tools are simply of no use anymore.
Fancy managing four billion rows in a spreadsheet? No, we don’t either. The other aspect of big data is that with such a huge scale comes the potential to find the clusters and patterns hidden within – if only you had the right tools to discover them. As with any job, having the right tools is just as important as the material you’re using them on.
- AI AND CHATGPT
You probably saw it coming, but this is the point where AI enters the conversation.
According to Abdalslam, 41% of corporate travel managers3 expect travel brands to use AI to provide them with significant travel suggestions.
Using AI to analyse huge data sets is far from new, but the recent rise of OpenAI’s ChatGPT has inserted the technology firmly into the cultural zeitgeist.
You can be told that AI can do all these amazing things and be mildly interested, but when you ask ChatGPT to write you a poem about the benefits of digital payment systems and it knocks out an entertaining, rhyming, six-stanza piece in less than 15 seconds (seriously, try it), it all suddenly becomes very real.
Its true power is in understanding context. It does this by analysing a staggeringly vast data set, discovering connections and patterns, and then using its learned language model to articulate its findings back to us in plain English (or code, for that matter).
You can easily see how this process can be transposed to any set of data large enough to provide meaningful context to AI software. But what is the potential of broader benefits for travel management? How can big data and AI – and its siblings predictive analysis and modelling – help revolutionise the industry?
Predicting the future of travel management
Let’s take a glimpse into the future role AI and predictive analysis could play in the travel management industry.
ANTICIPATION AND MACHINE LEARNING
Miss Smith travels to Paris every three weeks for a board meeting.
She has her regular hotel and her regular days of travel. The travel booker at her company knows this, but also looks after 200 other regular travellers.
Then one week, the usual hotel is three times the price. Everything else is sold out and it’s too late to rearrange the tickets. Why? Because a major conference was on in London that week and no one realised.
Well, what if AI knew about it already?
In fact, what if it knew six months ago when the conference was announced and had already alerted the travel booker, who had plenty of time to shift the booking that week or get ahead of the rush for rooms? That’s just saved the company real money – and when repeated at scale, the savings could become enormous.
The idea of intelligent, optimised itineraries is compelling. And the benefits it could bring to all booking activities are huge.
Including those such as:
- Optimising travel itineraries, including things like most cost-effective travel routes, flights, rooms or even sustainable services
- Taking individual employee preferences and satisfaction criteria into account when booking
- Making bookings around - and preserving - an employee's current schedule
RISK MITIGATION
Companies around the globe are leveraging AI to ensure legal compliance and mitigate risk.
They’re leveraging AI-driven systems that can spot a trend of increased spending from a particular cost centre well before it would be flagged by travel managers or finance departments, who would have to manually trawl through the data to audit it.
It’s not about pointing fingers – it’s about using the available data to better inform all levels of business and help people to do their jobs more effectively, confident in the knowledge they have the most relevant and timely information at their fingertips.
And - especially when it comes to fraud risk - AI is being used to combat the problem on an unprecedented scale. In fact, according to TransUnion online fraud attempt rates for financial services rose 149% between Q4 2020 and Q1 2021 4.
This would be impossible for humans to manage solely on their own.
With that in mind, we can safely avoid the doomsday panic of “the machines will take our jobs!” and instead be optimistic about the power of augmentation. A human workforce, enhanced and facilitated in their roles by the ability of AI to process and contextualise vast amounts of data into manageable, actionable chunks.
As with any new, emerging or rapidly evolving technology however, it’s always wise to be cautious and build fallbacks and redundancy into any business-critical systems.
It’s all about ultimately improving the customer experience. Freeing a skilled and motivated workforce from having to do laborious and repetitive data-based tasks opens the door to innovation, creative thinking, and proactive customer support.
Add to that the reduction in human error and the precision of deep cost analysis and you have an incredible opportunity to transform the industry at every level.
Key takeaways
- Tools now exist to make sense of massive amounts of data from the travel management industry
- AI is already being used and the potential for it to transform the industry is huge, but it’s not infallible
- Big data and AI should offer us the ability to be more agile, and evolve quicker
- AI isn’t replacing a workforce anytime soon. It will actually free up skilled workers to concentrate on more important things that will add real value to businesses
- Standardisation of data is vital to the future of the travel management industry
- The next stage in AI is being able to anticipate behaviours and transactions in a way that will save money and be more time-efficient
Want to know more? Talk to us. And check back soon for the next episode in our podcast series.
Amazon Music: https://amzn.to/49OCQET
Apple Podcast: https://apple.co/3RbWNOT
Spotify: https://spoti.fi/46suOie
Sources
1 https://www.g2.com/articles/big-data-statistics, How Big Is Big? 85+ Big Data Statistics You Should Know in 2023, G2
2 https://www.g2.com/articles/big-data-statistics,How Big Is Big? 85+ Big Data Statistics You Should Know in 2023, G2
3 https://abdalslam.com/travel-management-statistics, Travel Management Statistics, Trends and Facts 2023, Abdalsam.
4 https://newsroom.transunion.com/fraudsters-shift-focus-at-mid-point-of-2021-from-financial-services--to-travel-and-leisure-and-other-industries/ , Fraudsters Shift Focus at Mid-Point of 2021 from Financial Services to Travel and Leisure and other Industries, TransUnion.
