Controls at the Bellagio Casino Resort

Purpose of Case
The Controls at the Bellagio Casino Resort case was designed with several purposes in mind.
First, it illustrates a control system that is dominated by action and personnel controls, rather than results controls. The analysis of this system leads to insights about some of the factors that limit the feasibility of results controls.
Second, the case can lead into a discussion of what is meant by the term “tight control.” The case presents an excellent example of the application of tight action controls in the table games areas of the casino.
Finally, the case can lead into a discussion of the meaning of what auditors refer to as “internal control,” which is a subset of the broader area …show more content…

the benefit of being able to design better customer comp programs); however, the managers felt very strong about perhaps the most significant “hidden cost” of RFID, best expressed by the following quote from the case:
“Having too much information—knowing to the penny who wins or loses how much—isn’t always the best for the customer. At some point, the customers might lose some entertainment value if we monitor every little thing that happens. And we’re not sure that we understand all the privacy implications of this just yet. What if the IRS comes to us and asks for this information? We are in the entertainment business, and so we shouldn’t do anything that diminishes customer enjoyment.”

Results can be measured for individual pits and, of course, the casino as a whole, and these measures could be used for control over pit bosses and casino managers. But even those results controls are not used because they are not considered good indicators of the desirability of actions taken. One key indicator is the hold percentage (win/drop), but as is discussed in the case, this is a flawed measure. Even if the handle could be measured instead of the drop, the hold ratio would not be a reliable indicator of the desirability of the actions of the person being controlled because of statistical variations. On any given day, week, or even month, poor results might be blamed on a “high