What would the “Moneyball” casino look like?
As a Ph.D. candidate studying big data at UNLV, Ray Cho has given some thought to this question. Cho, who has 20 years of experience in the hotel industry, works as an analyst manager at American Casino & Entertainment Properties.
With advancements in computing and machine learning, businesses across different industries are exploring how to better use data to increase performance, revenue and customer satisfaction. Oftentimes, the issues are less technical and more political. It’s one thing to crunch the numbers. It’s another to get management to act on them. This is especially true when data contradict operating procedures entrenched as industry standards.
“If a team of analysts was building a casino on its own, it would look a lot different,” Cho said.
The gaming industry has collected information on players for decades, Cho noted. But he said there is more potential to apply the data to make more specific and targeted decisions, from daily operations on casino floors to bigger-picture directions chosen by chief financial officers. It’s not necessarily about collecting more data, he said. It’s about how you use the data you have. “The key word is efficiency,” he said.
Machine learning is an important tool. It’s a kind of artificial intelligence enabling computers to learn without being specifically programmed. The idea is that when these programs are exposed to new data, they can change spontaneously.
Read the full article by Daniel Rothberg on CDC Gaming Reports
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