Part 1 | General revenue management and strategic pricing

Revenue or yield management in hotels is a practice that has evolved significantly in its relatively short history. Adopted by hotels in the late 1980s, after the airline industry demonstrated great success using inventory, capacity and pricing to ‘manage’ revenue, revenue management has become one of the most integral and identifiable aspects of hotel operating strategy. Yet perhaps understandably, today’s brand of hotel revenue management differs significantly from that of two decades ago. Changes in the general approach to revenue management, pricing strategy, channel management, inventory allocation and the use of information as pertains to revenue management have redefined the field.

Just as detailed historical analysis might have represented best pricing practice in the early 1990s, stock market-influenced algorithms reside on the cutting edge of today’s pricing thought. Similarly, the emphasis on occupancy or average daily rate that might have dominated revenue managers’ attitudes two decades ago has given way to the primacy of revenue per available room (RevPAR). Examples like this abound, and in the next couple of columns we’ll be sharing all of our revenue management expertise with our readers, in a series that examines the current best practices of revenue management.

Today’s article looks at pricing and overall revenue management approaches, while the next article will focus on channel management and inventory allocation, and the third and final article in the series will deal with the role information plays in revenue management today, and the best practices associated with harnessing that information to best effect.

Strategic Pricing

Pricing is an aspect of revenue management that features several intriguing and innovative developments in recent years. While pricing has always been a significant driver affecting both occupancy and RevPAR, in the current environment of unprecedented price transparency, rates have assumed an even greater role. Determining the optimal rate to present to a potential customer has therefore become one of the single most important aspects of revenue management. The fundamental fact that the right rate- one that attains the balance between simulating enough demand to maximize occupancy, while not leaving money on the table in the form of too-low ADR- is the key to a successful revenue management strategy makes pricing perhaps the most important aspect of revenue management.

The question then becomes, how can a hotel determine what an optimal rate should be at any given time? In times past, this would hinge on historical analysis and be computed by applying a discount to a predetermined rack rate. In this basic form, the aims of revenue management are barely met, and in today’s environment they cannot provide an adequate competitive advantage. Rather, the best revenue managers and revenue management systems rely on stock market principles to formulate complex algorithms that can generate with accuracy the optimal rate. Furthermore, these systems work in real time, making subtle adjustments at brief intervals of time to maintain the best rate. The two best practices at work here are automation and an advanced algorithmic approach to pricing.

Stock Market Pricing

The principle of optimum pricing is familiar to financial experts, particularly those that work with commodities. For hotels, it’s a less familiar concept, but there is no reason this should be so. High-performing hotels utilize a comprehensive revenue management system that sets prices based on both historical considerations and current market conditions, giving it twice the range of more traditional pricing strategies. These systems mirror similar systems in place at financial companies.

Most financial price-setting formulae utilize two decision makers to ensure the highest level off effectiveness, with one system correcting and accounting for the other. Sophisticated hotel revenue management programs do the same thing. A hallmark of these innovative revenue management systems is dual programs: a main program and a secondary program. The main program generates rates based on historical data, taking into account page positioning on online sales channels, competitors’ rates, inventory availability and other variables, and implements them across the sales channels. The second program monitors the first program in terms of effectiveness, and makes adjustments accordingly.

This process, a mathematical generator coupled with an efficacy-driven monitoring program, is the foundation of every neural network employed by large trading firms. Because the two programs work off of one another, the system as a whole becomes adaptive. It is this adaptive nature of such revenue management systems that enable them to consistently outperform traditional revenue management techniques, and that truly highlight the advantage of applying stock market principles to hotel revenue management.


The innovative nature of the above systems and all of their algorithmic and computational power would be wasted without a significant measure of automation. Automation is the best practice that often makes or breaks a pricing strategy or the pricing aspect of a revenue management system.

Determining which channel is selling inventory fastest is usually a minute-to-minute decision, and that determination is best left to an automated system. Moreover, an automated RMS of the appropriate sophistication makes those decisions with less information than a human revenue manager. An algorithm-based computer program can recognize, by combing through data faster and by extrapolating trends and tendencies with less raw input, which channel is performing best, and allocate inventory there at the appropriate price. This can- and should- happen automatically; those hotels that incorporate a high degree of automation into their revenue management systems can be said to be exhibiting an industry best practice.

General Approaches to Revenue Management

As changes in approach to revenue management have flourished in the past few years, those approaches that work best have distinguished themselves as a special sort of best practices. The best approaches to revenue management in general are those that use RevPAR as the dominant metric, and those that emphasize the usage of revenue management systems to enhance revenue managers’ efficacy, rather than making revenue managers take control of the never-ending calculations and pricing updates. In hotels displaying RM best practices, revenue managers think proactively, not reactively and focus more on optimizing processes and working with other sales/marketing teams to develop and implement long-term pricing strategies.


At the dawn of revenue management, occupancy was the metric of the moment. The mantra of ‘heads in beds’ was on the lips of every general manager and hotel owner, with the rationale being that higher occupancy inevitably led to more revenue. That approach has changed significantly, and continues to evolve.

New metrics of the moment crop up every day, with various analysts and experts touting ADR and even exotic constructions like GOPPAR (gross operating profit per available room) as the best yardstick for determining revenue management efficacy. The best measure, though, remains RevPAR; a hotel that uses RevPAR as the guiding goal for a revenue management strategy is a hotel that is exhibiting the best approach to revenue management.

RevPAR remains the only revenue management metric that a hotel can literally “take to the bank”- and as such keeping RevPAR at the forefront of any revenue management strategy is a best practice in the industry.

Revenue Management Systems

There is a latent distrust of revenue management systems among some hotels (and some revenue managers), driven by the fear or assumption that a comprehensive RMS - one that handles aspects of pricing, channel management, inventory management and distribution- cannot perform as well as a trained and talented revenue management team. The best hotels, however, have embraced RMS as technological enhancements to existing revenue management teams, an advancement that frees key personnel to work on productive, revenue-generating tasks rather than the minutia of revenue management maintenance.

Fully-function RMS that interact with property management systems and perform all of the tasks outlined above have become indispensible to high-performing hotels both of the large-chain variety and among forward-thinking independent properties. The use of such systems has become a best practice in the industry.

Each of these best practices- using stock market principles and systems as the basis of a pricing strategy, executing that pricing strategy with automation, approaching revenue management through a RevPAR lens, and placing an emphasis on comprehensive RMS systems- is in use at many of the best performing hotels in the US and around the world. Moreover, each of these practices can be implemented for any hotels that wish to establish a competitive advantage in their markets. Both pricing and general approach to revenue management are inescapable aspects of the field, and of overall hotel operations, and so emulating these best practices should become an imperative for any hotel seeking positive growth.

Be sure to return for Jean Francois Mourier’s next best practices article which will examine channel management and inventory allocation, two incredibly relevant components of revenue management in the internet age.

Part 2 : Rate discipline, the leveraging of real-time information, and price prediction

Two weeks ago in this space, we discussed two prominent operational areas of hotel management, strategic pricing and the general conception and underlying attitudes of successful revenue management. When considering revenue management, though, more than these two aspects come to mind. In fact, the most visible aspect of revenue management in today’s operating environment is the use of the most up-to-date information available, one of the topics of today’s article. Another is rate discipline, which is subject to wide interpretation and can sometimes be at odds with other revenue management aims, like occupancy maximization. The third aspect of revenue management covered in this article is the important process of predicting future prices, and generating rates that align with those predictions.

These areas of revenue management are related to the first set of best practices outlined in our previous article: strategic pricing, which relies on both real-time information and accurate price predictions; and overall revenue management approach, which informs (or is influenced by) the concept of rate discipline. And like the revenue management strategies examined in the previous article, the best practices in the areas of information use, rate discipline and prediction have evolved over time. As little as ten years ago, the best, most recent information available about competitors’ rates came out in quarterly Smith Travel Research reports, or we discovered through call-around rates, GDS and rack brochure rates. Now, that data is constantly available and readily accessible – and I don’t mean in call-arounds. Likewise, price and rate prediction could only be achieved by consulting historical tables; rate discipline and its effects on brand identity and future room sales was barely considered two decades ago. Today however, the best revenue management systems employ sophisticated algorithms to generate optimal prices.

Rate Discipline

Rate discipline often comes up in reference to discounting or across-the-board rate cuts. The theory holds that deep discounts implemented to boost occupancy or stimulate demand (a common practice during the recession) deteriorate the hotel’s brand image. As mentioned, sometimes this practice can run contrary to other important aims, and sacrificing occupancy to maintain strict rate discipline can be as financially irresponsible as knee-jerk discounting. The best practice, then, is to dynamically adjust rates based on demand, without going too far in either direction.

The primary effect of rate discipline is felt on the hotel’s brand. Associations between price and quality are natural for consumers to make, and perceived quality is a central component to any hotel’s brand image. Therefore, a rate discount negatively affects a hotel’s brand. (This is a simplification, of course; many hotels define their brand by bargain prices, and a high rate does not guarantee positive brand development. A correlation does exist, though.)

This effect is real, and cannot be dismissed. Brands have immense value. According to a 2002 Interbrand study, brand value accounts for approximately 38% of the value of the companies that own them. If discounting is damaging to a hotel’s brand, and maintaining one static rate is equally detrimental to RevPAR and occupancy, then the solution lies in variable rate, modified in real-time to best match demand conditions. This eliminates the either-or quandary of whether or not to engage in across-the board discounting. Instead, the highest rate likely to generate a sale is presented to the right customer at the right time. This is achievable through the use of advanced revenue management systems, the best of which will also optimize page position on OTAs, manage multiple sales channels, and manage room inventory. To maximize occupancy and rate, however, automation is key. Rates must be modified subtly, in real-time, to avoid the pitfalls of wide-scale discounting.

In the end, just because a hotel offers a particular rate doesn’t necessarily mean a consumer will take that rate. Rate discipline through dynamic pricing provides a workable solution to this truism.

Using real-time information

The hotel industry, like everything else, has entered its information age. Compared to years ago, when information about everything from competitors’ rates to booking pace to demand levels was tightly held by a select few gatekeepers, all of the information necessary to set the perfect rate is available to hoteliers at all times. Unfortunately, most hotels fail to adequately access this information, or if they do, fail to leverage it effectively. The best practice in information usage is exemplified by the advanced revenue management systems in place at some hotels, which constantly consults demand levels and monitors competing hotels’ rates and make adjustments to the rate being offered based on this real-time information.

The reason this valuable information is now widely available is, of course, the advent of internet sales. Because every hotel posts rates online through various sales portals, those rates can be monitored. Because an increasingly high percentage of room sales are made through the online sales channel, demand levels can be assessed minute to minute. And because hotels have unfettered access to this information through the web, they can act on it in a quick and decisive manner. To do this effectively, however, hotels need the right tools; most often, these tools are found in a comprehensive, automated revenue management system that can, among other things, accurately predict movements in hotel room price.

Price Prediction

Since revenue management involves a certain measure of prediction, it stands to reason that revenue management systems will draw from other industries where prediction is at the core of their business. Some revenue management systems incorporate option pricing principles to help generate optimal room rates. Other systems may also use primarily financial instruments to make predictions, or leverage emerging techniques like crowdsourcing or artificial markets. At any rate, the backwards-looking techniques currently in place at many hotels is fast becoming obsolete.

Predicting the direction of future prices may be a bit foreign to hotels, which often take a supply-side approach to rate setting. But the best practice in price prediction borrows from basic concepts in commodity and option pricing, which focuses almost exclusively on predicting what price the market will bear for a particular good in the near future. The hotel room, as a (relatively) uniform product with high perishability is as much a commodity as a bushel of corn. But as financial markets have mechanisms to determine the optimal price of a particular issue (futures markets, etc.), hotels often arbitrarily assign a rack rate, and (if they do) modify the rate presented to potential customers from there. A comprehensive revenue management system for hotels can set prices based on both historical considerations and current market conditions, giving it twice the range of more traditional pricing strategies.

Each of these best practices of revenue management- rate discipline, information usage, and price prediction- are integral to a comprehensive revenue management strategy. Like strategic pricing and the proper approach to revenue management in general, a hotel cannot operate to its fullest potential without engaging in the best practices outlined here. And while they may not be a magic bullet of lodging success, they can go a long way toward optimizing rates, generating positive and sustainable RevPAR, and gauging where rates ought to be in the near future – a key component of ongoing financial success.

Jean Francois Mourier is CEO & Founder of RevPar Guru, a company that has developed an alternative type of revenue management and real-time pricing solution (combined with automated online distribution) to help hotels maximize occupancy and increase their profits. The company’s Yield Dynamic Price Engine, an integrated revenue management and pricing solution, adds unprecedented power and real-time adaptability to the pricing process, leaving managers more time to run their hotels. You may reach him through or by calling +1.786.478.3500.