- Dashboards or Balanced Scorecards? Those trace back to 1987.
- Web-based travel reports? Gotta be 15 years old, at least.
- Comparative price benchmarking? 15 years old, minimum.
- Travel program benchmarking done online?7 years old.
- “One number score”, aka batting average? 5 years old.
My point? Corporate travel managers need a new generation of travel data tools. I’m not selling anything. But I can see the numbers on the wall, at least in terms of what’s needed. Here goes:
Core Value: is Descriptive, should be Prescriptive
Maybe we’re fenced in by the very term “data reporting” – it’s explicitly a rear-view mirror, isn’t it? Sure, some users need to know what happened, but the real value from travel data is to help decide what should happen.
Travel and procurement managers don’t add much value by reporting yesterday’s news. They need to come up with well-informed plans of action to improve things. Hard to do that without good data, and to a fair extent, we have the raw ingredients. What we don’t have are the explanatory and predictive analytics wrapped around the data. Think Bing (nee FareCast) or FlightCaster for category managers.
Data Sources: are Isolated, should be Integrated
The two main sources of corporate travel data are a company’s reservations and credit card payments. Those are very private data sets, and rightfully so. But you can do only so much with your own data.
Travel benchmarking services like Travel GPA and NBTA’s Managed Travel Index are a first step. But benchmarks look backward.
To produce more sophisticated analytical and predictive tools, we’ll need to tie into external data sources. Sources like airline flight schedules (published 10 months in advance), hotel building and occupancy forecasts, and supplier-specific should-cost models. There’s gold in those data integration hills, for sure.
Context: is Shallow, should be Deep
I hate stupid travel statistics. Data such as average ticket price, average airline discount and average room rate add zero value – unless they are placed into meaningful context.
To date, the two main sources of context are time and peers. By time, I mean historical trends, and by peers, I mean compared to a benchmark. But those are shallow contexts. We can do better.
Start by asking this question whenever you see a travel statistic, like average ticket price:
What should it be?
Getting a well-informed answer to that simple question takes you a long way toward getting real value from your travel data system. Answering that question implies a key ingredient – one missing from most every data reporting system out there.
Namely goals. Well-informed, fact-based targets. The backdrop that brings meaning to those stupid statistics. Not that determining good goals is an easy job – but that’s part of the higher value-add we need to expect from the next generation of travel data reporting tools.
Strike “reporting” – let’s think of them as travel data prescribing tools. Now who’s going to fill that prescription?
TIILTS stands for Travel Innovations I’d Like To See. This is the fourth in a series.
LinkedIn users are welcome to join the TIILTS group. You’ll find a faster flow there of innovation-related posts.
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