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Playing With the Big Boys

Data Analytics for Small Operators: Low-Cost Techniques to Mimic Economies of Scale

Playing With the Big Boys

As gaming saturates regional markets, casinos that once existed in their own monopoly now find it increasingly difficult to improve financial performance through organic revenue growth. Companies eager to show year-over-year improvement have largely focused on increasing their margins, and industry consolidation provides the necessary economies of scale.

While large brands like Las Vegas Sands and MGM Resorts continue to dominate in size, others have worked to absorb the remaining regional commercial competition—as seen with Eldorado Resorts’ acquisitions of Isle of Capri Casinos and Tropicana Entertainment, Penn National Gaming’s acquisition of Pinnacle Entertainment, and even Golden Nugget’s recent bid to acquire Caesars Entertainment.

Synergies driven by this level of M&A activity include operational excellence through the development and sharing of best practices, labor savings through the centralization of leadership roles, and purchasing power on everything from slot machines to shampoo.

An exemplary benefit of consolidation is found in data management and analysis, which can be expensive and time-consuming. Enterprise data warehouses are costly, and the IT and analytics professionals required to manage and leverage them command high salaries. Return on these types of investments is highest when their costs can be spread across several properties in a portfolio sharing the resources.

But as large gaming brands expand and regional brands consolidate, one segment remains relatively untouched: Native American casinos. The economics in tribal gaming are different. Because of jurisdictional restrictions, these casinos operate as individually owned entities and, even among those that operate multiple casinos, the vast majority cannot benefit from the scale that many commercial operators have built.

In this article, we explore three critical ways tribes and single-operator properties can mimic the economies of scale that many of their competitors enjoy around data and analytics operations while remaining budget-conscious and growing ROI. Our methods include improving existing reports, developing centralized data storage incrementally, and fostering a culture of collaboration between analysts and operators.


Method 1: Make the Most of the Data You Already Have

Nearly every casino or department within a casino already uses reports in some capacity, whether it be a daily operating report, a profit-and-loss statement, or a structured post analysis for marketing events and campaigns. There is a common tendency to get set in how we view and consume these reports—looking for a specific number or two and glossing over the rest; or worse still, becoming too busy to read the report altogether.

By doing so, we risk losing sight of more nuanced trends or opportunities. What’s changing? What’s stable? It’s important that reports are designed to help us efficiently answer these questions, extract the information we need to make good decisions, and spot trends. Regular conversations between report authors and end users are a low-cost way to ensure we receive meaningful, timely information to inform our decision-making. The questions below can help drive this evaluation process:


Do I need this report?

The first step in evaluation should be considering whether we need the report at all. Ask yourself what motivates you to read it. Is the information valuable and useful? Do you actually use it to make decisions, or is reading the report merely a force of habit? Reporting should evolve as our businesses evolve; even reports that provide excellent value should someday sunset, yielding to new reporting that is more effective. Allowing less useful reports to retire not only reduces inbox clutter but also frees up the report author’s limited time to provide value in other ways.


What information in this report is valuable to me?

Once we’ve established that a report itself provides value, we must ensure its design efficiently delivers the information we want. Reports need to be easily and quickly consumable—if we’re constantly searching for a specific number in a report or performing ad-hoc calculations with the data provided, it may be time for a refresh.

We have always found the most success in updating design and presentation when operators and analysts review the report together. End users should discuss the information that interests them in the report, share questions that come to mind as they consume it, and provide any of the ad-hoc manipulations they’re performing. The more the analyst knows about how the operator is using the report to make decisions, the more tailored and easier-to-use the report can be made. Likewise, the analyst who built the report may have had a use case in mind that he or she can share with the operator.


What information would make this report more valuable to me?

Hand-in-hand with what we already find valuable in a report is what’s missing that would make the report even more useful. It is critically important to identify and communicate information gaps in report content to its authors. Sometimes a report only shows a snapshot when a trend would be useful. Sometimes a report shows a trend but insufficient details in a snapshot. Other common information gaps are caused by the time period of the report or lack of data accessibility.

Here’s an example we’ll continue to follow: a hotel reservations report may not incorporate patron information that could be helpful for hotel staff looking to provide extraordinary guest service. Report authors can diagnose why an information gap exists and develop solutions. Gaps caused by time periods can be resolved quite easily through supplemental reporting. Analysts can create a trend report to go along with a snapshot report.

Data accessibility gaps, like the interest in viewing a patron’s ADT or F&B preferences alongside hotel reservations, are generally caused by a need to view data from multiple departments or business units in the same report, and these may be harder to tackle. Even so, they spark valuable conversations about centralizing data, which we propose a strategy for addressing later in the article.

Do I receive this report at the right time?

As creatures of habit, we may be accustomed to receiving a report on a set schedule, be it daily, weekly or monthly. But is that schedule optimal? We should ask ourselves if a change in delivery timing would help us make better decisions, and communicate those needs to the report author.

If we need information daily or weekly for it to be effective, and we are only getting it every two to four weeks, there may be easy ways to solve this problem—perhaps the analyst is creating a 30-slide PowerPoint deck when a few key summary numbers are all we need. Or, we may need to consider an investment in reporting infrastructure that is more push-button if analysts are putting reports together manually that arrive too late to be effective.

Typically, the more frequently a report is delivered, the higher the burden on analyst and technical resources, so there may be limitations to what is immediately possible. But these conversations provide an important starting point for understanding reporting demands in the organization. What’s more, a focus on these questions will help direct energy to the most important information needed so that resources are appropriately allocated. It is best to keep analysts motivated and empowered by ensuring that the information and analysis they provide is being used to make more effective decisions.


Method 2: Centralize Your Data Incrementally (Without a Costly Warehouse)

Data within a casino resort tends to become siloed in the department that generates it: marketing controls marketing data, casino operations controls gaming floor data, and food and beverage data often stays buried in the point-of-sale. This hinders creation of more nuanced reports like the hotel reservations we described earlier.

Centralized data stored and maintained from a single location and accessible by many departments provides the technical infrastructure necessary to quickly and efficiently create these cross-departmental reports—reports that will become even more useful as our view of the customer evolves. Casinos have begun to rethink guest worth to include spend off the casino floor, and centralized data storage that combines guest activity data across gaming, hotel, retail and F&B departments is vital for these calculations.

Additionally, developing centralized data storage is crucial to expanding the data analytics capabilities of an organization, as many off-the-shelf analytics tools require a central data source to function.

Knowing how much information to bring into a central data source can be challenging. While well-designed enterprise data warehouses (EDWs) that capture every nugget of data created in the organization are an analyst’s dream-come-true, development and maintenance of these systems can require significant time, talent and capital investments. EDWs and the analytic capabilities they enable can be extremely valuable, but the return on investment may not make sense for small operations or organizations just beginning their shift to more data-driven decision-making. A better approach for these casinos may be to start small, with only the most pertinent information, and incrementally build their centralized data source as a more analytics-driven culture and its associated demand for data grows.

Avoid the temptation to map every piece of information into an all-encompassing data warehouse. In fact, rather than a “warehouse,” aim for a much smaller “storeroom” that houses only the most important data items in your organization. Start with feedback from the report reviews and aggregate the items that report users identify as most important for driving their decisions, or that they’d most like to see in new reports. Likewise, ensure that information that is relevant across multiple departments is among the first to enter the storeroom. These common items provide good starting points for building your central data storage.

Remember, the goal here is to eliminate data silos. Once a storeroom is established, teach analysts how to access it and build from it. Many low-cost tools can plug right into such an environment, and the value provided from sharing a single source of truth across the enterprise will provide the opportunity to experiment as well as the use case for future storeroom expansion.


Method 3: Bring Analysts and Operators Together

A data-driven culture must encourage interaction between operations and analytics staff, which you’ll remember we advocated for earlier in this article. A challenge we commonly face is the conflicting feelings of analysts who believe their work is being ignored and operators who think analysts have insufficient context—perhaps understanding the “numbers” but not the “business”—to help them make decisions. It is imperative that the business eliminate this narrative so that the operators and analysts can work together and build the mutual trust and respect required in the joint pursuit of operational excellence. The methods we share above may bring an organization closer to the actionable answers it seeks, but this is only possible through true collaboration and partnership.

Creating the environment described above can be labor-intensive, but from a dollars-and-cents perspective, no direct monetary investment is needed to begin reshaping organizational culture. In fact, here is an example of where smaller operators can use size to their advantage. Since analysts and operators are all located on property, everyone has easy access to one another. Avail yourself of this unique opportunity to ensure that analysts and operators work together to share ideas and build the trust required for their relationship to thrive.

One simple and cheap way to get started is to facilitate analysts rotating through operational positions in the departments they serve, even if only for a shift. One of this article’s authors was horrified to learn how many ways data could be (and was being) entered incorrectly or ambiguously when she shadowed a player’s club desk for the first time. But the experience was invaluable, and shaped her sense of how data could be trusted. She has since worked with marketing teams on SOPs and with IT and analytics teams to develop better automated rules for merging guest accounts. Here are some additional ways you can foster this critical relationship, depending on where your role falls on the analytics-operations spectrum:


• Analysts

Seek opportunities to learn operating procedures, and always be sympathetic to the very real challenges faced by people who interact with guests. Build meaningful and deep relationships with business leaders to develop analytics champions who can vouch for your work and speak from experience to the business value added by data-informed decisions. To accomplish this, reach out to business leaders to understand what issues they face. Take time to understand the business perspective and context of a problem that may benefit from data analysis, and aim to provide relevant, actionable recommendations with your findings.


• Operators

Get to know the “numbers” people in your organization, which in most casinos are the planning and analysis resources. Communicate regularly with these individuals, take them to lunch, talk to them about what they’re working on, chat about the things you’d love to improve, and ask how they’d think about those challenges. Ask how they assist other departments—this may spark an idea about how their expertise can benefit your team.

Expose analysts to the day-to-day issues you and your team face so that they see the many variables. Involve them in the conversation when something seems off; reaching out shows a willingness to incorporate data-driven thinking into your operations and paves the way for future collaborations. Conversely, try to understand the type of data the analyst sees, and work with your team where possible to improve its quality. Analysts generally want three things: to work on interesting problems, to know that their work is being used, and to have that work recognized for its value. If you can provide this, they’ll dedicate enormous amounts of time and energy to your projects.


• Property Leaders

When you’re setting goals for the year, prioritize this type of relationship building. You have immense power to change the way your team thinks about the business and business goals. Putting your support behind these initiatives by budgeting lunches or directing analysts to spend a portion of their time shadowing can move the needle quickly and at minimal cost. Diversity of thought and experience makes everyone smarter and more effective.


• Identify and Change

As the industry consolidates to leverage economies of scale and develop efficiencies, tribes and other small operators are forced to balance the cost-benefit of similar improvements. It’s important that they identify low-cost opportunities to drive a large portion of this value. Some cultural changes, as well as some low-cost technology changes, can provide a lot of this budget-conscious value. We encourage these operations to take the following approaches:

  • Review and critique existing reports for opportunities to streamline, supplement, reorganize, improve delivery, and potentially sunset.
  • Remove data silos and develop high-value cross-departmental reporting and analysis through the creation of a centralized data storeroom. Do this thoughtfully and incrementally, rather than by undertaking a costly, all-at-once data warehousing project.

• Foster a culture that encourages two-way communication, development, empathy and a sense of teamwork between analysts and operators.

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