It is well understood that full visibility is the essential element between an unmanaged versus managed travel programme. When we have better access to data we have the tools to understand what drives programme activity and what we can do to change it. But how much data do we need besides the basic consolidation of TMC, Card and Expense data?
We live in a world where we have access to more data than ever before, yet it can sometimes be overwhelming and confusing to determine what data we need and what will drive value within a travel programme.
Currently, most travel programmes are preoccupied with in-house consolidation. That is, they examine agency, card and expense data to gain visibility into what is leaving the company bank account and where it is going. This covers the basics: what is officially booked, what extra is spent on the corporate card and what extra is spent via other payment options and expensed. Only by looking at this data can we achieve an accurate view of programme spend without leakage.
The new approach to programme visibility
In 2020, it is not enough to just look at the basics and look at what is spent but also look at the drivers behind the spend.
If certain programme elements are undesirable, what is motivating it and, more importantly, how can we change it?
Analysing what is spent is a one-dimensional way of looking at a travel programme. At PredictX, we advocate that organisations look at the three dimensions of travel data.
What are the three dimensions of travel data?
A three-dimensional data analysis looks at what travellers are spending, where they are spending it and why they are spending it.
The first dimension: what are we spending?
This simply refers to how much money is leaving the bank account. Seems simple, yet it requires a global view of spend from agencies, cards and expense systems. Often referred to as a “total trip cost” these three sources are our bread and butter when it comes to programme management. Reconciling this data with General Ledger (G/L) data from finance is also a handy way to assess if this figure is truly accurate. When your financials are right, you automatically hold credibility with internal stakeholders. This is the first step.
The second dimension: where is the spend occurring?
Now we have a trusted view on what is leaving the bank account, we need to know the details around these transactions. When is the trip? Where is the trip? How long is the trip for? Does it take place in a risky area? Is there a tax impact? This information becomes crucial when we assess risk, are looking at duty of care or are assessing traveller well-being. We cannot answer any of these questions if we are purely analysing data from a cost point of view.
Most TMCs and quality third-party data companies are easily able to provide this situational data feed from booking tools.
What adds an extra dimension to this data is an overlay from the HR data feed and corporate hierarchies. This tells you who is travelling. In light of the Covid-19 crisis, this became particularly important. Managers wanted to know if their team members are safe.
The who becomes important if we examine traveller well-being, for example. When we know how many trips a certain traveller is taking and for how long these trips are, we have an understanding of their level of traveller happiness and we can relate this to many other aspects of the business, including employee retention. Knowing this layer allows travel managers to make improved policy decisions based on the wider company mission and goals.
The third dimension: why is the spend happening?
When we look at a two-dimensional diagram, we can more or less understand what it is representing in reality. Yet, in travel data, companies using only two dimensions miss out on the following:
- How negotiated prices perform against the market
- How spend may be impacted by future supplier pricing strategies
- How travellers feel about programme suppliers
- Does greater travel spend correlate with improved company objectives? (productivity, sales close rates etc.)
- How traveller satisfaction correlates with traveller personas
- Whether or not your efforts to drive demand have the intended outcome
An easy example is matching booking data to shopping data to understand what the market is offering. This is instrumental in understanding why travellers are booking certain flights or rooms. Are they booking away from a preferred supplier due to unavailability? Is the rate more favourable via consumer sites? This data not only is telling you why certain suppliers are being booked or not being booked but can become an excellent bargaining chip in any supplier negotiation.
Another example is linking travel data to CRM data. What is the purpose of the trip? Is it driving growth for the company? Should more care be given to certain trips with a higher ROI attached? This data can also be used to understand whether travel is necessary or not. We can drive spend down in this way while boosting spend for trips that are linked to company growth. Imagine having these figures available for the c-suite!
In today’s data abundant environment there are infinite possibilities for what data we can analyse. As long as we know what questions to ask our data and how we can relate these questions to programme improvement we can take a giant first step in understanding our spend, our travellers and our supply chain.