To become more data-driven is the stated goal of many gaming operators around the world, but the table game space continues to play catch-up with slots. Things aren’t nearly as bad as they used to be though.
“I can remember dealing craps and we had a group coming in from Venezuela and the pit manager kept me on the stick for an hour because he thought I would deal more 7’s than anyone else,” said Mike May, vice president of table operations at Pechanga Resort & Casino, who delivered the opening keynote at this magazine’s Cutting Edge Table Games Conference last November. “Every morning, he would throw salt on the crews’ shoulders before they got on the table. Imagine you’re new to gambling and you work for folks who don’t talk about skill sets, math and probability, but they’re managing from the standpoint of gamblers themselves.”
That was the culture a few decades ago in in Atlantic City where May started out. “For me, it was a very strange environment; if you were a table supervisor you got yelled at if your games were losing. Compared with the slots department, we were the red-headed stepchild from an analytics standpoint.”
Things changed for May when someone gave him Jim Kilby’s book Casino Operations Management. “There were other people as well who looked at the business differently, but Jim put it down on paper and taught classes at UNLV that explained how we made money at table games,” he said. “This extraordinary focus on pricing and utilization and understanding that there is a sweet spot in table games. I grew up in an environment where if the tables weren’t full, you weren’t doing your job. Jim pointed out that your tables shouldn’t be full; the percentage occupied should fit the demand of the region you’re operating in. Through his work, we were able to create some basic analytics on pricing and utilization. We also worked with companies like Bally’s and IGT to create some rudimentary data.”
Today, May is one of the foremost data evangelists in the table game business. Here are some things he has discovered along the way:
Create your own data scientists: “Some operators have brought in MBAs from the outside, I felt we had really smart operators, let’s send them to get an MBA,” said May. “Then I thought, why an MBA? What do we really need in table operations?” Today, Pechanga send people out for data science training, teaching them SQL and Access.
“The IT folks are the ones who have all this knowledge and information and we come in and want to know how many people are coming down from Los Angeles on Saturdays. How cool would it be to have an operator who knows what queries to formulate and can draw the data directly? It’s a lot cheaper for you to spend money internally than to invest in technology and all these other things that are out there. Some people come through your operation and go through dealer, floor and pit; find out if they have a passion for it. Some of them do, and it’s a lot cheaper to send them to a few classes that help them understand all these kinds of metrics as opposed to sending them to USC for their MBA, which would probably cost the property about $80,000.”
Ramp up data collection: “When I got to Pechanga, there were probably about 100 reports a year coming out of the property from the table games department; right now we generate about 8,000,” said May. “Every day we have reports going out to our pit managers and shift managers. This stuff is all stored, and this gets back to data scientists, because, whether it’s in SDS, CMS or a Word document, your data scientists can look at this information and help you as you move forward.”
Actual theoretical on rated play:“If you really want to treat that top-end customer the way they should be treated, you need to hard code your top 100 blackjack players and find out exactly what the house advantage is on those individual customers,” said May. “A lot of people say then you won’t be able to comp as much. What you’ll find is a lot of those players are above the house advantage that they set the games at. You have customers that are at .41 percent house advantage, you’re getting 1.0 percent. Your other customers are at 2.0 house advantage and you’re only giving them 1.0 percent. The difference between a player who plays head-to-head with the dealer at a 2.0 percent house advantage is extraordinary from a comping standpoint. Slots have this ridiculous advantage on us, where they know everything that their customers do and comp accordingly. We don’t have that yet, but this tool is there.”