Casino hotels began implementing automated, or Web-based, Revenue Management solutions before multi-family housing (MFH) operators did. In some ways, the RM tools for both sectors are similar; in other ways, they’re different. It’s important to compare and contrast their functions for casino hotels and MFH to see how MFH can profit from the gaming industry’s experience.

There are many more transactions with casinos than with multi-family housing, so casino RM has a lot more data to analyze in making traffic forecasts and optimal pricing decisions. Guests book the hotel rooms for a few nights, perhaps, so there’s constant turnover, but tenants stay in apartments a lot longer and their rental decision carries much more financial impact.

That difference also puts more pricing pressure on the lease rent optimization solution used in MFH. If your forecast data influences a decision that under-charges for a new lease, the rental company may waste the best-value potential of that unit for years. But the after-effects of a bad pricing decision on a casino gambler’s three-night hotel stay end when he leaves.

Casino hotels value guests; MFH operators value rental units

Both casino hotels and MFH housing communities serve many types of customers and make room inventory available to them after collecting and interpreting data from the RM system. However, the MFH administrators set prices after analyzing the rental unit’s value, whereas casino hotels distinguish between higher- and lower-value customers through bid pricing recommendations made by the revenue management process. In other words, a high-roller who’s going to drop a bundle on blackjack will get a much better room rate than a conventioneer who might only get a therapeutic massage after hours instead.

Depending upon how much he bets, the high-roller might get his room comped, but for casino hotel operators like Boyd Gaming, comping isn’t the reflexive decision it used to be for property managers before RM technology. By updating to automation, Boyd actually reduced its comp rate by 35% while increasing cash revenue 4%. Their top gaming customers get comps or the best rates, and non-gaming, or retail customers are charged rates to make their value equivalent to the gamers. But Boyd also rewards its loyal non-gamers. Its optimization process factors in other ways that non-players add value, such as spa use and dining, and when Boyd implemented its new RM system, it phased in its new rates policies slowly for longtime non-gaming guests.

Controlling for seasonal variations and economic shifts

Seasonal variations in business affect the forecast assumptions and optimizations of the MFH and hotel/casino RM systems. There are surface similarities in how seasonal traffic varies for each venue. Casinos tend to have more summer than winter business in colder climes; the opposite is true in hot-weather areas. But since this pattern is a lot more pronounced in multi-family buildings, they have much more at stake in having a Web-based system control for traffic fluctuations at certain times of year.

Revenue management in MFH looks closely at an apartment building’s expiration profile to see when people are moving out throughout the year. Nobody wants to move to Buffalo in January. So, it’s going to be costly if large numbers of renters give up their apartments in mid-to-late fall. A technology solution has to factor this expiration profile into its recommendations so that the complex won’t get stuck with a lot of vacancies in winter.

Both MFH and casino hotel revenue management solutions can quickly adjust their forecasts to reflect shifting economic conditions. Yet they respond differently to those forecasts. With MFH, there’s much greater demand and pricing volatility because rental housing will draw a lot of newcomers when the economy tumbles. Housing isn’t a discretionary expense for them. Not so for hotel casinos, which are discretionary, luxury outlays for people. Gaming stays relatively insulated from economic turmoil.

This raises a point about the designs of each system. They’re similar, too, but the mathematical models, and therefore, the forecasting logic, are different. In that economic downturn, for example, automated RM will track the shadow market, where condo demand softens and many more homes are rented because the owners can’t afford them and have to lease them out. That impacts the overall rental market. Lease rent optimization systems see the MFH landscape in terms of hot and cold markets and adjust accordingly: when markets are hot, they call for higher rents and faster rent hikes; when the markets are cold, they recommend keeping rents high at first and then lowering them gradually to spread out revenue reductions.

Because rental units change hands much more slowly than casino hotels change guests, the automated revenue management model for MFH also takes the longer view. It forecasts demand based on history as well as how bookings are gaining or losing steam.

Employee compensation also tied to setting room/unit rates

The two RM systems also handle employee compensation differently, although both make it a priority to optimize for incentive packages that are fair, equitable and consistent with industry best practices. MFH and casino hotel operators have to measure actual and potential business, but they don’t do that the same way.

Casino hotels tally how many people stay with them, and how many either cancel reservations or try to, but can’t get bookings.

MFH has traditionally relied on the closing ratio, which creates an incentive to game the system. Apartment complexes have guest cards that every visiting potential renter fills out. If one out of 10 visiting prospects rent a unit, that 10% ratio is pretty good. If 20 prospects come by, but none of them move in, it reflects badly on the employees. That tempts staffers to leave many of those guest cards blank to artificially pump up the closing ratio—and management loses a lot of demand information that it needs.

Today wise MFH managers base incentives on things like staff compliance with pricing decisions and customer satisfaction ratings. Those measures are more pertinent to the overall success of the organization. When Post introduced a pilot RM program in 2006, it paid employees their full bonuses during the testing period.

There are core similarities between MFH and casino hotel RM solutions—first and foremost, that they’re not just software systems, but rather a way of operating that helps organizations achieve their main purpose. For casino/hotels, that’s drawing the highest-value customers possible; for MFH, filling units at rents that ensure profitability.

Both tools are about forecasting demand—though they sift through different sets of factors that can affect a forecast—and then using the same kind of optimization engine to recommend room or rental unit rates. In each case, the forecast function predicts how demand will show up and how it matches up with the available room inventory.

Central pricing control—taking the emotion out of pricing decisions

Casino/hotel and apartment RM operations share the ability to maintain a central repository of pricing data controlled by a senior-level revenue optimization manager. MFH operators like Post Properties and Mid-America Apartment Communities strongly endorse that arrangement, and many other organizations have recently begun to realize the need to institutionalize this position within the management structure. Previously, people performed this task on a de facto level in some companies, but without formalized responsibility.

The beauty of this arrangement is that it takes the pricing decision away from the community managers on the ground. Those people have too many building site tasks to be bothered with pricing. They also don’t have the global view of what’s happening on a regional basis with other properties managed by their company. The most telling point is that community managers interact everyday with tenants, even becoming friends with some of them. It’s going to be a lot harder for these customer-facing managers to pull the trigger on a rent hike, or a non-renewal of a lease at the current rent, if the decision is theirs to make. Better to explain that they can’t change the rate the central office computer spat out.

The markets for tenants and guests aren’t the only markets that are critical to pricing. So is the labor market, and how it’s compensated. Knowing the prevailing salary, bonus, incentive and benefits levels in comparable properties is how MFH and casino gaming businesses can set their market compensation profiles. RM systems do this very well.

It follows that automated revenue management is the best way to protect the business integrity of the pricing decision because it removes gut-level emotion from it. That creates discipline in the pricing process and gives it credibility throughout the organization.

When MFH operators have put pricing in the hands of individuals, instead of an RM system, they’ve been vulnerable to shifts in the pricing criteria when those individuals leave. Turnover is constant at the community manager level, so there has to be a system in place that ensures smooth continuity in business operations and pricing calculations. Top optimization officials are highly intelligent industry veterans who usually come from the operations side of the business. (That’s the case with companies like Post, Archstone Smith—the originator of lease rent optimization—Simpson Property Group and Equity Residential.) But it doesn’t take a rocket scientist to figure out and implement an RM system. Apartment management companies generally can find those people in their ranks instead of importing someone from outside. That also contributes to dependability and consistency.

By establishing an unbiased, uniform pricing system, online optimization shields MFH organizations from the nightmarish prospect of housing discrimination lawsuits. If the rent is the same for all incoming or existing tenants, the possibility of discriminatory intent doesn’t exist. That preserves what MFH operators need most of all—a deserved reputation for fairness and integrity.

Tangible revenue benefits for both sectors

Because it’s highly sensitive to the wealth of customer transactions in casino hotels, automated RM can make a huge difference in revenues for those properties – in the neighborhood of 10-15%. (IP Resort Casino Spa, in Biloxi, Mississippi, had an eye-popping 300% jump in its average daily rate after going to an automated solution—just 20-months after being pummeled by Hurricane Katrina.) Because casino hotels get to know their base clientele very well, they can gather a lot of data for their customer profiles. That’s invaluable for creating marketing opportunities.

The biggest value of an RM solution lies in forecasting future demand by customer segments. That complements the nature of the casino gaming business. Nobody has to visit a casino, and people who do can chose among competing casino hotel venues. That’s why these hotels can, and must stimulate customer demand – to be their best customers’ preferred choice. (Demand management is a big challenge for mega-operators like Trump Entertainment Resorts, which controls almost 3,000 hotel rooms—or one quarter of the total—in Atlantic City. They put an RM system into all three of their Atlantic City properties.) Pumping up demand to outpace supply puts the casino hotel in position to get the best possible revenues out of their bookings. That’s what revenue optimization is all about.

MFH operators can reap tangible revenue benefits of up to 5%, with the industry average being about 3 ½%. It’s not as much as the casino hotels are getting, since pricing opportunities arrive over the longer term, instead of every day. But the automated RM design can quickly factor in data from rapidly changing conditions—like the abrupt closing of a local manufacturer that was a big jobs generator—and long-range trends to recommend the right price point for a rent. That’s a big planning benefit for MFH communities.

Lease rent optimization also is very attuned to what competitors are paying staff and charging for rents. Operators no longer have to set prices according to arbitrary lease restrictions anymore, either, such as six-month, 12-month and month-to-month. They can accommodate tenants for customized leases. Simpson does this by providing its community managers with a daily list of RM system options covering two to 12 months. This is a lease-closing strategy that cuts down the number of units lying vacant.