I’ll never forget the last hotel industry downturn. I was working for Steve Wynn in Las Vegas, a market that was hit especially hard.
In late 2007, despite early signs of an economic recession, everything in the travel industry was actually moving along quite swimmingly. The Wynn, along with most other hotels and casinos in Las Vegas, was enjoying rather healthy occupancy, ADR and revenue numbers.
A few months into 2008, however, we started observing some weird demand trends. Group business began slowly declining. Transient wasn’t dropping off as fast, but there were still concerns, especially as we were getting ready to open a second tower, called Encore.
The slowdown proceeded through most of 2008. Then, in February 2009, the last straw broke the camel’s back. When President Obama implied that trips for financial executives were unnecessary excess, specifically naming Las Vegas, Wynn (along with the rest of The Strip) took a nosedive.
CEOs who accepted financial bailout funds “can’t go take a trip to Las Vegas or go down to the Super Bowl on the taxpayer’s dime,” Obama said. The comments could not have come at a worse time. Corporate belt-tightening was already widespread, and Obama’s callout led more companies to cancel annual conventions over fear of negative public opinion.
Wells Fargo had already booked their 2009 annual convention with Wynn; the company was supposed to reward their team members with the whole Vegas shebang – clubs, restaurants, etc. Fearing a poor perception, they were forced to cancel. For me, that cancellation was the first true indicator that we were on shaky ground.
Here we were on the Las Vegas Strip having just doubled our capacity, and now we had no group business to build a base.
To this day, I look at the information we had on hand in 2009 and compare it to the information we have now. What decisions did we make then, and what would we do now? What did we learn?
Revenue Management Has Come a Long Way
Truthfully, while the demand dive took its toll at Wynn, it didn’t scare me. Instead, I saw it as an opportunity to bring to light some of the errors we were making as an industry. For me personally, it was an opportunity to shake up traditional revenue management.
I began pitching a unified Revenue Strategy operation where all the various departments that help operate a casino hotel would come together and work toward a common goal. By ensuring we all met at least once a week and worked with the same technologies and from the same data sets, we could make stronger decisions and, at the very least, steal share from our competitors.
To solve short-term challenges, we turned to leisure business and began discounting. Looking back, we did way too much business with opaque OTAs. The problem with that strategy was that, for a company like Wynn, slashing rates too low meant we were getting the wrong people in the door.
So we learned very quickly to not treat all customers and all offers the same. I pitched to management the idea of yielding each room type and each promotion individually. On higher-demand days we should reduce the discount, I said, and on lower-demand days we should increase it. These changes shouldn’t be made across the board, but instead each segment and in some cases even each customer should get its own rate.
Of course there was resistance from management. Operationally it was a nightmare, and I heard a lot of “We can’t do that” and “It’s too complicated.” But what my colleagues didn’t understand is that, even in a recession, you still have days in which people want to come to your property.
Even in 2009 there were days that the hotel was full. But instead of five full days in a row, now we were only getting two or three. So promotions that were based on length of stay in hopes of filling shoulder nights were not faring so well. Because many travelers wanted to visit but could not commit to five days, we were losing business.
What became known as an Open Pricing strategy allowed us to offer promotions that weren’t based on length of stay but instead yielded discounts daily based on supply and demand. This way, if customers wanted to stay three days instead of five, they received a bigger discount on the lower-demand days and a smaller discount on the high-demand days. If we neared capacity, the offer wasn’t closed, the discounts were just yielded down, ensuring no one who came looking for a room was turned away.
When the rubber meets the road, people are willing to try anything. At Wynn, we made the best of the situation by implementing a rudimentary, Excel-based Open Pricing model. We now had strong promotional business that didn’t kill the peak periods and didn’t kill the shoulder dates. It pretty much saved our ass.
What Could We Have Done Differently?
While it was clear almost immediately that Open Pricing was the solution, the fact that we were a little late was not lost on us. If we’d had a more comprehensive and readily available Open Pricing strategy prior to the downturn, things wouldn’t have become so bad in the first place.
And I still look back fairly often and wonder, if we had the future booking data in 2007 that we have now, how much difference it would’ve made.
We would’ve seen the indicators much further in advance. Web shopping data alone—data from the booking engine that shows how many people are looking versus how many people are booking—would’ve been extremely helpful.
I’m not going to say that hotel forecasts would’ve predicted the severe demand dips that we experienced. In such a volatile market, hotels will never be able to forecast that accurately, especially given the major change that occurred in the way travelers were booking rooms. But true forward-looking data, coupled with smart alerts from a real-time revenue management system, would’ve raised flags much earlier in the process. We would’ve had much more time to prepare.
In a stable market, predictive analytics models are very good at forecasting the future. In a volatile market, forecasts aren’t that reliable. So the difference maker is having triggers that recognize changes in demand early on and alert the user that action is required.
Fast-forward nearly 10 years, and the evolution of predictive analytics has opened our eyes. When you can see indicators earlier in the cycle, you can take action before your competitors. So it’s not about nailing the forecast 11 months out, it’s about continually optimizing your pricing strategy and sounding the alarm when necessary. The earlier you get indication of change, the more time you have to put a plan in place.
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