A perfect storm of waning demand, increased supply, and heightened competition have hospitality executives doubling down on Revenue Management innovation to drive profit in 2019 and beyond.
In fact, the Annual Revenue Analytics Hotel Revenue Executive Survey– a recent survey of senior hotel executives across North America – revealed that the majority see centralized decision-making and automation as a top priority.
How are they making it a reality?
Hotel executives are beginning to use market-level analytics, centralized group price optimization, and machine learning to transform how they manage revenue. Here’s how and what they can do to take it up a notch.
Taking It Higher with Market-Level Forecasts
Top hoteliers are adding market-level forecasting to their toolset so they can identify need – and address it – on a whole new level.
With market-level forecasting, hoteliers can see need dates for cities, clusters, regions and even guest segments, where previously they could only see need for individual hotels. With this much-expanded view, different markets, regions, and brands can deploy promotions, packages, and offers that are tailored to each segment. The result? They can address gaps more effectively and drive more revenue.
What’s more, hotels can use these forecasts to identify the optimal channels to drive business across their portfolio of properties. Without market-level forecasting, Revenue Managers have no choice but to make channel decisions based on what is most profitable for an individual hotel, regardless of how it impacts profit across all properties.
But with market-level forecasting, managers can make calls that maximize profit across the portfolio, making it easy for hotels to further optimize their channel strategy and deliver higher margins and profits.
A Centralized Approach to Group Pricing
It’s true – group price optimization is its own challenge. For decades now, hoteliers have been practicing Revenue Management on the transient market but have been unable to leverage analytical tools and technologies to address it at group business.
So, many have been forced to rely on “eyeball analytics” much in the same way transient was done 20 years ago. There simply hasn’t been a better way.
That’s all changed thanks to artificial intelligence, machine learning, and centralization. And the benefits are clear – the ability to take market-level analytics and predictive engines to price and close at an optimal level to drive revenue.
But what about the buyer in this modern age where customer experience reigns supreme? In the past, buyers were reliant on a sole individual who may not be able to accurately price or immediately attend to a prospective group. In the near future, a regional, centralized team will be able to quickly respond to requests with the right price, providing the immediate response that buyers require. As a result, on-property teams will be able to shift their time and attention to service and delivery.
The Catch: Blending Artificial Intelligence with Human Intelligence
So, AI is a panacea, right? Not so fast. There still is, and always will be, a need for the human element. Humans to discuss and review price quotes. Humans to address exceptions. Humans to focus on relationship-building. Without humans, it will all be for naught.
Automation – Today’s Must-Have
With market-level forecasts and centralized group pricing optimization, hoteliers can move key decision-making above property. But the level of effort to manage them manually is high – too high – especially for those Revenue Managers who oversee massive numbers of properties.
That’s why machine learning has become a must-have in 2019. Machine learning can help to automate these new advanced analytics capabilities, virtually eliminating the human effort from pricing and inventory controls. With this automation in place, Revenue Managers can effectively manage myriad of properties at scale. Even better, they can focus time and attention on those projects that computers can’t knock out of the park – meaningful price exceptions and larger events that move the business forward.
However, the benefits of automation won’t materialize unless Revenue Managers – who are used to managing by system override – develop confidence in these advanced analytics processes. Only by receiving education on these new analytical capabilities, and being involved in the design process, can Revenue Managers develop the trust required to make this much-needed automation a reality.
Paul Murray is the Vice President of the Hospitality Practice for Revenue Analytics. In this role, Paul is responsible for driving hospitality client engagements for the firm.
Tess McGoldrick is a Director at Revenue Analytics. In this role, she leads cross-functional project teams to develop high-impact solutions, leveraging Artificial Intelligence (AI), to drive organic revenue growth for her clients.
For more information, please visit https://www.revenueanalytics.com/.