Today we’ll look at data reporting’s sexy cousin, analytics. Well, “sexy” may be a stretch, but my point is that data reporting is not very interesting, while good analytics can make you say “Wow – look at that!”
Travel category managers can be overwhelmed by all the data available to them. Data reporting tools are necessary, but they typically produce “dumb” data. By dumb, I meanstatistics, like average ticket prices, or total spend by supplier, that lack context. (See this video of a “pretty but dumb” travel data reporting tool). You need context to put the data in perspective.
Let’s take three examples; one from an airline sourcing project, one from a cost savings study, and one from a hotel category review:
Example 1: Airline Sourcing Project
Assume that the data reporting tool tells us:
|Airline||Total Spend||Number of
|Avg. Segment Price|
By itself, this is remarkably useless data. There’s no context – no insight as to why American’s average segment price is higher, despite having a larger total spend than Delta. There could be any number of good reasons. But what we want right now is to use our data and some analytical horsepower to create a compelling negotiating position to take into a discussion with American. Here’s what that discussion looks like:
“Good morning, American. As you know, we gave you $3.5 million in spend last year. Our analysis shows that we could have given you as much as $4.2 million, much of which would have come from Delta and United. We also found that we could have given you as little as $2.6 million by using those carriers more aggressively.
“We’re prepared to move the extra $700K to you if you’ll increase our discount from 7% to 12%. Otherwise, we’re prepared to shift $900K away from you and onto other airlines. We realize that in that case we’d get no discount from you, but the discounts from the other airlines will make us whole.”
What are the analytics behind this negotiating position? It’s a combination of:
- Modeling the flight schedules of the relevant airlines in each of the buyer’s city pairs
- Modeling the buyer’s ability to move its travelers from one airline to another
- Analyzing the current airline contracts
- Modeling each airline’s cost structure and profit margins on the buyer’s spend
Travel data reporting tools just don’t go this extra mile. You’ll need to use airline category consultants who have the sophisticated modeling tools and corresponding flight schedule databases. Which consultants are the best in the business? TRX Travel Analytics (my old firm), followed by American Express, Carlson Wagonlit and BCD Travel’s Advito group.
Example 2: Cost Savings Study
Let’s say your CFO wants to know how much your firm would save by changing the travel policy’s cabin allowance. The cabin allowance determines when a traveler is entitled to use Business or First Class; often it depends on the duration of the flight.
Here’s what a good (illustrative) analytical answer looks like:
This chart’s appeal is that it shows the savings potential for whatever limit you may want to use in the cabin policy. This example shows a savings of about $500K by limiting Business Class to flights of seven or more hours, and a savings of about $1 million by moving the limit to 11 hours.
This type of analysis makes it easy for a category manager to show senior management the “pain versus gain” tradeoff. Some companies will want the maximum savings; others will be more mindful of the traveler perspective. Either way, the analysis has done its job of informing the audience about the savings potential associated with this policy element.
Example 3: Hotel Category Review
As a category manager, you need to know which hotel chains offer your firm the most coverage. By coverage, I mean having hotel properties near where your travelers typically stay, and that these properties are acceptable in terms of their quality ratings. For many category managers with fragmented hotel spend, this is a tough question.
You’ll start with the data from your reporting tool, but it needs to be processed with more analytical insight. Why? Reporting tools show where your travelers stayed – not where they didn’t, but could have – stayed. For this analysis, we need to bring in the nearby hotels (and their quality ratings, bed capacities and chain affiliations), and process this data into hotel clusters.
Once that’s done, you can see the answer quite clearly. Here’s an illustrative Hotel Chain Capacity chart, tailored to the buyer’s hotel footprint in the U.S. It shows each chain’s share of beds in the buyer’s clusters (clusters are neighborhood-level markets).
Category managers constantly need facts and figures. Data reporting is necessary, but never sufficient – you need high-quality analytics to help make the best (if not always the sexiest) recommendations and decisions.
(I originally posted this article in SupplyExcellence)