SaskGaming's Slot Floor Optimization

According to the Canadian Gaming Association, legalized gaming has more than doubled in size since 1995, from $6.4 billion in gaming winnings to about $15.1 billion in 2010. Slot operations make up the bulk of that money: up to 85 percent of casino revenue, according to some sources.

To have the power to reasonably forecast future results and do those 'what if ' scenarios at our convenience lets us make decisions about the timing and nature of machine replacements so as to achieve the most desirable business outcomes.
davidkoch

Elliott Daradich
Director of Slots, SaskGaming

The challenge
SaskGaming enjoyed positive revenue growth since opening Casino Regina in 1996 and Casino Moose Jaw in 2002. However, like others in the industry, its initial period of double-digit growth eventually plateaued as it became more established. Customer demand for slot machine play in particular seemed to be saturated.

In the fall of 2011, this was the issue facing Elliott Daradich, SaskGaming's Director of Slots for nearly 17 years. On board since the casino's inception, Daradich saw the business develop into an increasingly dynamic environment. With so many changes at once, he wondered: How could he plan the right mix of gaming choices, denominations and machine placements to optimize customer interest?

The solution
SaskGaming paired with SAS to assess and refine its data needs and improve its long-term planning process. Project heads from each organization adopted a multi-phased team approach that began in summer 2012 with a detailed test, or proof of concept.

The first step in the process was assessing and cleaning the available data. This would enable a detailed categorization of relevant information to gain insights into slot performance to date.

The data needed to be reviewed and revised for consistency to allow the history of similar games to be tracked. This was a key challenge, because the results of analysis can only be as good as the information that gets analyzed.

Next, the team used this information to provide a best-case forecast into how each game would perform in the next year. It became possible to determine leading predictors of guest preference, which would optimize profitability while supporting the integrity of fair and random play.

"Our databases lacked details about the attributes of individual games and machines," explains Daradich. "Now that we've seen what can be learned from this kind of information, we plan to redevelop and augment our data capture with an eye toward future analysis capabilities."

Using categorization and each game vendor's market research, it became possible to isolate a surrogate to help it analyze options for new game purchases. Moving forward, SaskGaming will be able to predict the potential impact of changes on slot performance based on "what if" scenarios. This provides much greater forecasting power than the traditional approach to decision making, which was limited to reports based on one variable, looking exclusively at historical data.

Finally, advanced optimization determined the best approach to future business, considering factors such as physical space and budget. This information will help SaskGaming optimize its slot purchase options, including analyzing which machines to replace and when to replace them, without hampering player experience through downtime.


The result

"In the end, the solutions offered by the test case promise a new perspective," says Daradich. "Better yet, we were there to take part and see it happen. Every Friday as we met as a team, we considered the results and next steps together. It gave me the opportunity to become comfortable with, and have confidence in, the outcome." "To me, what's different about this approach is no one is trying to isolate the one magic variable that matters above all else to customers and wil make the business thrive for years to come," adds David Koch, Analytics Specialist with SaskGaming. "Rather, we're simply identifying those games which customers find appealing even if we don't know why. This solution has helped us to immediately improve our understanding of customer preferences. As our databases become richer with new game and machine attributes, we'll also have stronger predictors of long-term gaming trends' performance, allowing us to make better decisions in the future."Power in SaskGaming's hands.

Competition in the entertainment market can be fierce. SaskGaming recognizes that with more competition for discretionary entertainment spending by customers, it needs to offer guests an entertainment experience that exceeds their expectations. The ability to make empirically sound decisions about which slots will best appeal to customers is more important than ever. The analytics solution enables users to move seamlessly through the entire process, from data collection to forecasting, prescriptive optimization and reporting.

"To have the power to reasonably forecast future results and do those 'what if ' scenarios at our convenience lets us make decisions about the timing and nature of machine replacements so as to achieve the most desirable business outcomes," said Daradich.

An example for all
Using analytics, SaskGaming now has a new perspective on its games data, allowing the casino to use analytics to offer the right games in the right locations to attract loyal and valuable customers.

The company is now considering the potential for slot floor analytics to improve its analysis capacity in other areas of its operations.

Adapted from Analytics and the modern casino: A game changer, originally published in Canadian Gaming Business, Spring 2013.

Challenge

SaskGaming required a solution to measure and analyze slot machine play so it could make better decisions about which games to purchase.

Solution

SAS Analytics, SAS Forecasting and SAS OR

Benefits

SaskGaming immediately recognized an upswing in potential revenue. They look forward to using the same approach for other areas of the casino.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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