As we enter the annual hotel request for proposals season, I'm struck by how little sourcing innovation we've seen in this important category. Yes, we have a standard RFP format, and several good RFP technology platforms, but sourcing hotels is still like a long walk in the hot sun: You'll eventually get there, but not without cracking a good sweat and wishing for a quicker and cooler way. The good news is today there is a better way, and the story involves some lazy thinking and a bottle of wine.
First, let's agree on some of the fundamental problems involved in sourcing hotels:
- Dirty dataAgency and card data must be merged, de-duplicated and scrubbed.
- Data overloadWhich hotel data can you safely ignore?
- Stale bid listsIt's easiest to just use last year's bid list with a bit of tweaking.
- Clumsy market bucketsUsing city names or zip codes to organize hotel markets has severe limitations.
- Small-market knowledgeIt's really hard to know which chains best fit a program's smaller markets. Is Marriott or Hilton the better fit in Tucson? What about Toronto and Tampa?
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Buyers know with confidence which chains need to be at the negotiating table based on each chain's capacity to serve a corporate program. (These capacity numbers are based on each program's footprint and stay patterns.)
Measurements show how much travelers are supporting or avoiding any single property, brand or chain, so buyers can easily track savings achieved by the preferred hotel program in any market and/or quickly spot preferred hotels that are not getting their fair share of room nights. As such, clustering allows buyers to quantify the negotiating leverage they have over any property, brand or chain, and which competitors are the best alternatives--in every market, no matter how small.
This strategy also enables buyers to quickly prepare relevant bid lists by automatically weeding out hundreds or thousands of hotels that have room nights but are not relevant to any cluster. Buyers can know with certainty each hotel's nearby competitors, regardless of zip code or city name, making rate negotiations faster and more credible.
Clustering provides senior management with quick, yet credible, estimates of savings for: trading down, improving compliance with the existing preferred hotel program and taking advantage of the best rate in any cluster for a given level of hotel quality--roughly equivalent to a spot-buy strategy.
Additionally, the data input for clustering is equivalent to traditional hotel sourcing projects. The clustering process takes traditional hotel data (agency bookings and card payments) and scrubs it as part of the pre-clustering logic--but faster and more thoroughly than any buyer can do today. This eliminates all data scrubbing work on the buyer's side!
Once buyers grasp that clusters are simply neighborhood-level markets, the rest is straightforward. I see no barriers to buyers adopting this innovation and predict clustering will soon be a hotel sourcing best practice.
Suppliers will have some challenges, as well as some significant benefits, from taking a cluster-based view of corporate hotel programs. It remains to be seen if hoteliers will appreciate this view of their world.
Scott Gillespie--founder and former CEO of Travel Analytics, a travel procurement consultancy he sold to TRX--is the author of a U.S. patent covering airline bid analysis and co-author of a patent application covering cluster-based hotel data analysis. He is writing a book on travel procurement.