From time to time one of our clients asks me to sit in on a vendor presentation for some Revenue Management or Business Intelligence software. At the end of these demos the salesperson usually summarizes the value of the system by saying some derivative of “it allows you to make more confident decisions.” That is exactly the opposite of what the sales pitch should be. You see, in the hotel business there is no confidence problem. Managers across all departments are usually way too eager to make decisions with little or no information, relying mostly on their experience and gut instincts. I mean, that is what they get paid to do, right? That kind of bravado does not exist where there is no confidence.
What these sales people should be trying to do is demonstrate how their systems can provide “assumptions busting” insights that deflate the dangerous level of overconfidence that exists in hospitality decision making. This overconfidence is specially dangerous in Hotel Revenue Management where managers go about deciding on rates and rate changes by mixing a potent cocktail of superficial information and one-dimensional analysis with long-held assumptions and speculation of how demand reacts to pricing tactics. In fact, for the overwhelming majority of hotels in the world (of every rating) there is little or no research or calculations that typically go into making rate decisions other than a top-level Pace Report and Comp Shop. That’s because most hotel managers don’t think, or rather don’t know, that they need more information. In other words, there is a certain level of ignorance that fuels the overconfidence. This misinformed overconfidence has become an epidemic in the hotel industry, affecting the potential profit of hotel companies large and small.
Now, how can you begin the process of tackling the scourge of overconfidence at your hotel company? Like any self-improvement program you first have to acknowledge that you have a problem. For this we turn to the “Ignorance” Project at the University of Arizona(Q-Cubed). Q-Cubed developed a six dimension framework for understanding the different types of ignorance as applied to the medical profession. By understanding how ignorance actually fuels overconfidence you will be able to identify what is missing in your Revenue Management decision making process. Here are the four dimensions of the “Ignorance Map” that most relate to RM and how to tackle each one.
Known Unknowns – All the things you know you don’t know
Many hotel managers are OK with not knowing because they have concluded that either knowing will not affect their decisions or they can make an assumption that is close enough to the actual information. This dimension of ignorance is often displayed by GMs who insist that they do not need an RM. Expecting good results from decisions made knowing that there are gaps in your knowledge is akin to thinking that your car won’t need an oil change just because you don’t know how a car engine works. Begin by taking a serious inventory of the information you don’t have and the information that you need.
Unknown Unknowns – All the things you don’t know that you don’t know
There is no question that believing that you are more correct than you actually are is the biggest problem in Hotel Revenue Management today. This is the classical overconfidence dimension of ignorance. This is what keeps Revenue Managers from exploring the more analytical aspects of their profession because they don’t realize how deep RM analysis can actually go. Most have never been exposed to the scientific side of RM. They can’t even imagine that there is a way to stop guessing and start calculating your way to great rate decisions. These RMs take their own thought process and mental models as gospel. Staying on top of the latest research and literature and always asking “why” goes a long way in awakening you to the depth and complexity of the RM function.
Errors – All the things you think you know but don’t
The result of overconfidence is always the error, either confirmed or not. Unfortunately, many errors in RM are never revisited because once a day has passed few hotel companies go back and take an academic look at the results of their decisions. Unconfirmed assumptions, long-standing biases, and a lack of curiosity to dig deeper often lead to costly mistakes. Overestimating the accuracy of our knowledge is a basic human trait but it can be a disastrous bias in business. Challenge anyone, even yourself, when they use phrases like “I think”, “I believe”, “I hope”, “in my experience”, etc. I find that these type of evidence-less statements are usually wrong or at least outdated.
Denials – All the things too painful to know, so you don’t
Many times I have showed an RM the mathematical explanation as to why a rate change will not have the desired effect and they go ahead and make the rate change anyway. I then realize that it is hard for them to think that they don’t have as much control of demand as they think they do. This is when ignorance is actual bliss. This is also the reason why many managers tend to use only information that serves their agenda, ignoring the information that does not. While it may be uncomfortable, always try to find information that disproves your assumptions. That way you are sure that you have formulated a reasonable point-of-view.
It is no secret that the hotel industry is years behind other industries in its use of data and analytics. Yet the problem has little to do with having a lack of data or systems as much as it has to do with the failure of hotel managers to realize that they are making critical decisions with insufficient information. This type of ignorance is at its worst when it manifests itself as arrogance – which I have witnessed all too often among senior hotel executives. If and how hotel companies decide to mount a serious effort to destroy this epidemic of overconfidence will determine the importance that Hotel Revenue Management will have to the industry in the future.
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Robert Hernandez, Statistical Analysis and Data Mining for Revenue Growth Robert is an expert in the field of mathematical Hotel Optimization and Analytics. He has spent the last 17 years building data-driven forecasting and optimization models for companies in over 20 different industries, from tech to tourism. Robert possesses a very unique skill set including cross-disciplinary experience, advanced mathematical and analytics skills, data transformation, industry-specific knowledge and business-process improvement expertise. Robert began his career at the Walt Disney Company in Revenue Planning. Read More+