During HITEC Dallas 2021, IDeaS Revenue Solutions, provider of automated revenue management software and services, announced the launch of Profit Optimization for its G3 Revenue Management System (RMS). This enhancement to the G3 RMS revenue science engine enables it to capture the most valuable business while considering the total contribution for each guest, allowing hoteliers to evaluate total revenues, profit margins for each revenue stream, and the costs associated with acquiring and servicing guest stays in real time, while determining highly sought metrics such as profit per available room (ProPAR). LODGING sat down with three executives from IDeaS—Dr. Ravi Mehrotra, president, co-founder, and chief scientist; Stephen Hambleton, director of product management and product success; and Mike Chuma, vice president of marketing, enablement, and engagement—to discuss the launch of this product extension, how the hospitality industry is evolving to incorporate more automation, and more.
What are you seeing in the hotel tech space that is informing your approach?
Mike Chuma: What we are seeing today on both the operations and the tech side is a massive shift towards efficiency. Cash is king, and the efficiency of the dollar is important, but most important is the efficiency of the actual person who is working in a role—for us, that is the commercial strategist, the revenue manager, and the revenue teams. We’ve made massive investments throughout the pandemic to really focus on the efficiency of the revenue manager and the cluster as you start to see organizations create more with less. We’ve nationally launched a product extension around total profit optimization. That has been the focus of our technology: to be more of an enabler of efficiency in the back-office digital transformation of those roles. How we play in that space is and something our team has really been focused on is transitioning from traditional revenue management optimization around revenue per available room (RevPAR) and moving towards profit per available room (ProPAR). And that comes in many different forms and flavors. We are now launching that ability to do so. People have been going after and trying to do for the last three decades. We have done it, and we can do it for organizations as small as limited and select services where you bring in channel costs and bring in the cost to service all the way up to luxury resorts with all the other ancillary revenues.
Can you tell me more about the origins of Profit Optimization for G3 RMS?
Stephen Hambleton: It came from two main areas; one of them is a limited-service business. Even before the pandemic, a big part of what drives limited-service profitability is servicing costs, because as an extended-stay business, essentially, if you can sell seven one-night stays, that is seven times more expensive than one week in that room, and that’s because that model typically services the room once a week. Making sure that systems are aware of that and that it is folded into automated decision-making is what drives profitable outcomes for the property and also efficiency because that’s not something that people at hotels can or should take care of manually. What we wanted to do was build a model with pieces like that—pieces of a jigsaw that you can put together in any combination. You can have servicing costs alone, servicing costs, and channel costs with the unsorted revenues, with or without the profit margins, so that whatever the needs of that hotel are—and, more importantly, what data they have available—can be folded in to meet that complexity.
This expands heavily on the model that we’ve always had. Something that we’ve touted throughout our history is that this type of decision-making shouldn’t be done by giving a general manager a list of recommended rates that they have to spend hours poring through to determine which ones they agree with and which ones they don’t. That’s not where people’s time is most efficiently spent. Instead, you give them the exceptions to manage. We make decisions for the business that drive efficiency so that humans can spend their time on the strategy around that.
How do you plan to evolve and expand the platform in the future?
Stephen Hambleton: This extension is essentially a change to our optimization model. We swap out the optimization engine so its objective function and focus becomes profit instead of room revenue, so it’s trying to maximize profit instead of room rates, which has been the edict of the industry for such a long time. Revenue is important, but it’s just one piece. What we want to start to do is support that wider model. As the industry moves towards attributes, you have to think about the value of a guest to you regardless of what they want to buy, which may or may not include a room. That’s really why we’ve taken this approach to make an extensible model. At a lot of hotels today, when you wander around, they don’t ask you to charge to your room; they don’t ask you for your membership number; you’re not even rewarded often for non-room spend. If we’re going to encourage the collection of data to support this type of profit optimization, we’re going to have to think differently about some of those core areas of our business and having the right data. It’s also valuable for guests to share that data because they get something in return.
How are your innovations helping to address the challenges related to labor?
Stephen Hambleton: There are probably two very broad areas where we are helping specifically in that area. One of them is that there’s been a really massive uptick in automation in the last year. Our large clients have started to say, “Why are we doing so many things manually?” There are things that we can already leverage the system to do. New clients are coming to us for help with that, and they recognize that all this talk about revenue as just being pricing is starting to dissipate. That’s been our message for a long time. Helping to drive automated decisions and just having the general manager tweak the few prices that they need to tweak to really leveraging our automation at scale has seen a massive pickup. That coupled with what we’ve been doing in the area of profit optimization to reduce costs, increase ancillary spend, and the profit overall associated with the properties—those are the things we brought together in addition to a real investment in making sure that analytics continue to adapt very quickly to an increasingly uncertain situation.
How has the pandemic impacted the adoption of this technology?
Mike Chuma: It’s really accelerating some of the tick lists of what hoteliers have thought that they wanted to do, but have either been reticent to, have pushed it down on their checklist, or have not really understood how to truly get there; it’s forced their hand. If you think about how profit changes the perspective of how the hotel—your managers, their people, their systems, and the money cashflow in and out—it’s forcing the silos to be broken apart because you have to optimize in every role in the commercial organization: across sales, across distribution, across marketing. And it’s really making those people band together so they can look to where they can find the next best revenue stream that is not a traditional revenue stream that they used to focus on. And they’re using our toolsets to be able to break down those silos.
Stephen Hambleton: The other thing I think that’s been really exciting is people have not only said, “Let’s catch up with capabilities that were already there that we hadn’t embraced.” There are also people looking to the future much more and saying, “Where can we bring automated decisions that have never been applied in our industry before?” A good example of that are things like campaigns; marketing campaigns can disrupt revenue strategy and sales strategies. Sales may contract rates that disrupt revenue and pricing strategy. And all these areas are really ripe for having more automation and automated decisions brought to them because people run a campaign and say it was good because it generated “N” number of room nights and “Y” volume of revenue, but nobody takes a step back to say, “Did we just cannibalize guests who would have bought other rates?” We’re starting to see people say, “Let’s not come back from this in the same position we were—let’s make sure we’re building a foundation that helps us to be even better and leveraging these types of resources as effectively as we can.”
Ravi Mehrotra: If you look back at the hotel industry, it has been rather slow in terms of going after technology and adopting automation. This pandemic has really opened their eyes. They are suddenly realizing that those who can change rapidly will survive. They have to take a look at their market segmentation. Human behavior itself, as a result of the pandemic, is undergoing some changes and what people were demanding versus what they’re going to demand in the future is not necessarily going to be the same. You really can’t go back and continue with the ways of the past as you move forward. Because if you really want to achieve results in a world where the world is changing and the world has changed, you must change the way you do things to adapt to the coming world. That is what I consider to be the silver lining in this pandemic: The hospitality industry is waking up, getting up, and realizing we need to run faster, we need to move faster, we need to rely more on technology, and not be afraid.
