With business beginning to recover, a hotel’s management has to start determining strategies that can improve business revenue, in short and mid-term. However, it is imperative that they are on the same page as the revenue team.
Murphy Mathew, APAC Solutions Engineer, IDeaS explains how the actionable insights from the revenue team can play an instrumental role in aligning the marketing strategies and cost projections. Strategies can thus be put into effect to enhance cash flow, protect the base business and stay ahead of the market by tapping into the benchmarking share.
What weaknesses in traditional RevPAR models were exposed during the pandemic?
Traditional RevPAR models focus solely on room revenue. With the pandemic, room revenue was missing for an extended time across the country. Hotels have always had other revenue streams, most often called out as ‘ancillary revenue’. And with the lockdown easing, it became evident that the ancillary revenues were now leading or equal to room revenues across many hotels. Traditional RevPAR models don’t capture this major contribution to the hotel’s top or bottom line.
Do RevPAR and RGI continue to be relevant and reliable models, or should hoteliers focus more on TRevPAR?
Yes, they are relevant, but for the rooms division. A smart revenue management strategist would want to take total revenue into account.
The general manager also wants a view of the overall profitability of a property. So you could say TRevPAR is more the focus now. However, this still misses other important elements from a profitability standpoint, such as servicing and channel costs. This is why I would argue that profit per available room (ProPAR) is the one we would see hoteliers use more and more.
Ensuring that systems are aware of servicing and channel costs and being folded into automated decision-making is what drives profitable outcomes for the property along with greater efficiency in avoiding these tasks being attempted manually. What we wanted to do was build a model with pieces like that—pieces of a jigsaw 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.
How can hoteliers’ budget for an increase in TRevPAR and measure their hotel’s revenue performance based off that benchmark?
In many hotels, revenue at the coffee shop, for instance, is not even identified as a non-resident or in-house guest. So, one needs to start as previously done with rooms forecasting, moving onwards to in-house and non-resident guest forecasting, and further onwards to the spend potential of every guest at the hotel across different revenue streams.
The other side of the coin is the cost incurred internally and externally for each of these sources. Last in the mix is the profit margin. Once you have these lined up, budgeting and reforecasting when needed would be an easy next step, especially with the right automated technology in place.
How can hoteliers identify and monetise newer revenue streams from varied departments other than focusing on revenue from rooms?
This would vary from hotel to hotel. I have spoken to hoteliers who have focused on their operational streams to tap into their existing expertise and brand awareness in the market for this service. Right on top is F&B, followed by a mix of catering, curated private events, and laundry, to name a few.
A glance through many recent marketing strategies would highlight innovative campaigns modelled around experiences. While F&B has clearly outperformed expectations by many, one of most creative ones I came across was usage of a hotel pool for fish farming in Kerala. While it might not be sustainable, their willingness to experiment and explore is admirable.
Over the years, hoteliers collected tranches of data from various sources. Are these still relevant in contemporary times when customer preferences and booking patterns have changed?
History is a small piece of the optimisation cycle and still relevant for understanding pricing patterns, demand patterns, length of stay, and booking behaviour. History is also relevant to identify seasonality, and comparing it with recent trends provides a framework for the analytics.
The important part is the decision-making of finding the relevant data sets. This could be a combination of years, months, weeks or future data along with supporting data sets about competitor pricing, forward-looking demand, reputation and price relationship, among others.
What is the drawback of trying to gauge business performance based on prior historical data, budget expectations, or competitor performance?
A hotel not using an advanced revenue management system (RMS) and setting their own rates based on their unique business forecast can either base their pricing assumptions on ‘gut-feel’ or look to match a competitors’ own pricing activity. Both approaches are misguided, if not dangerous.
By following a competitor on price, an hotelier should be prepared to be dictated by strategies they are unaware of, which risks setting off a chain-reaction in price reductions between rival properties that cannibalises revenues for both properties. Pricing by this methodology would mean the budget and forecast for upcoming months are at a high risk, not just from an accuracy standpoint but also from optimization point of view. Similarly, evaluating business performance on these lines would not be a best step forward.
With the increased focus on technology in recent months, how can hoteliers leverage analytics, data, and consumer insights to gain a competitive advantage in their market?
The cash flow in the market has forced a cautious approach. However, I have also heard directly from hoteliers of the intent to drive further with technology. Automation, efficiency with constrained resources, and profitability are the constant phrases I hear from hoteliers across India.
There is more willingness now to use analytics to drive decisions. This is significantly different from the traditional method of using analytics to evaluate a marketing campaign that was run last month. The approach should instead be, “At what rate, and booking window, should I run this new promotion so it complements my existing business base rather than displacing my existing business base?” This is just one of the examples wherein we see more and more hotels leveraging analytics to gain advantage in a highly competitive environment.
Can predictive analysis systems for pricing and managing hotels actualise to deal with real-time changes quickly?
Current times are indeed very dynamic—all the more reason for hoteliers to be agile. The secret to success here will be not just reacting to trends, but also forecasting a trend based on available data and hence proactively being able to set controls in the market.
Powerful and proactive analytics provide the compass needed to navigate market changes and demand shifts. The predictive analytics of an advanced RMS factor in many data sources, and yes, historical data along with recent trends and future pick-up. The analytics should be able to factor in these changes seamlessly and critically at a granularity that matters.
For instance, domestic leisure business may be still in line with recent months, whereas corporate travel business could have just picked up over the last couple of weeks. Predictive analytics at the granularity of segment and product ensures that relevant data is considered for both leisure and corporate forecasting in this example.
Thus, advanced analytics evaluate future on-the-books and pace, price sensitivity, market data, unconstrained demand, and even prices by room type and/or market segment, ensuring you drive the most profitable business to your property to help you recover faster.
How can hoteliers use this information to forecast and project future revenues in uncertain times?
Having access to an analytical system which surfaces the change in trends at granularities empowers hotels to project the revenues and profits for the times ahead. “There’s no one human that can physically do what this product can do—there’s so much that goes into the algorithm.”
One of our RMS clients said this, which fits in here absolutely. My advice is to invest in technology and automation. Seek out an RMS solution that meets the analytical requirements of your business and enables greater profitability across your entire property.
