top of page
News

Enhancing Hotel Profitability: Leveraging AI and BI for Commercial Decision Support

By: Timothy Wiersma - President, Revenue Generation


Hoteliers who harness the potential of BI and AI to shape effective strategies will be the ones who succeed in the years ahead. With margins increasingly tightening, simply following market pricing and trends risks falling into the trap of trying to recover profitability in the wrong areas.


Recently I was engaged with an independent hotel located in a major urban market in eastern Canada. This hotel is relatively new and boasts spacious rooms and suites with a small meeting space platform and minor food and beverage. Service levels are excellent, and their reputation is growing as they ramp up their presence in the city.

When we first came on board to assist with the overall revenue optimization strategy, we noticed that the data they were using was often incomplete, the RM system was not fully optimized, and they were basing their strategy on a partial picture from one or two vendors that gave biased data to support the idea of using more of their channels. More often than not, they base their decisions on feelings rather than utilizing analytics to guide their decisions. Or they are making broad decisions based on partial data perspectives. The various departments inside the hotel were very siloed in their approach and did not fully understand the goal of the enterprise. This was in part because they didn’t have the tools or resources available to gain the situational awareness needed to prescribe the variables of demand and implement decisions based on the goal of capturing the more profitable side of the demand picture. This was also a situation where the goals inside the organization were not aligned and sometimes in conflict with each other.


As a result, this hotel was not profitable and not meeting pro forma expectations. Furthermore, management was finding themselves explaining why they were seeing negative profit margins in a market that was growing at a steady pace.


Establishing a robust business intelligence foundation to enable a deeper exploration of the profitable aspects of demand.

When we engage with a new customer, we begin by ensuring that we have a solid business intelligence (BI) platform, which then becomes the foundation for understanding situational awareness and considers not only top-line measures but also profitability components. This requires obtaining data from several sources such as including PMS, RMS, sales and catering, external sources such as STR, rate intelligence, and external demand measures. We then study key expense components from distribution channels, marketing efforts, and P&L KPIs that have direct impacts on profitability. Once built and implemented, we can accomplish the following:


·        Focused KPIs at your fingertips.

·        Reduce complexity.

·        Improve data access.

·        Increase data quality.

·        Offer dynamic, intuitive, interactive visuals.

·        Provide instant insights that drive value.

·        Engage users at all levels of your organization.


Furthermore, by leveraging BI, revenue managers and operations will be able to optimize pricing, enhance guest experiences, increase operational efficiency, and ultimately drive higher revenues and profitability.


Drive decision-making by science, not emotion.

Data science plays a critical role in revenue and profit optimization decisions by leveraging advanced analytics, machine learning, and holistic data to optimize pricing, inventory management, and distribution strategies.


It’s important to ensure that your executive teams are not basing their decisions on emotions. When you hear phrases such as “I feel if we did this….” or “let's cut rates because ….” it would be good to pause and ask the following questions:


·        What is the basis for this decision?

·        What supporting data suggests a move in this direction?

·        How will these decisions contribute to overall profitability?

·        What is the desired outcome?


When applying data science approaches, you can better understand demand on any given day or specific time period. Predictive analytics will be the basis for this forecast, which takes out guessing and allows revenue teams to be proactive in building the base of business. Furthermore, data science will let you know the types of demand over any given time period, allowing you to target the most profitable demand.


Depending only on Automated RMS systems can limit your profitability potential.

Automated hotel RMS systems can provide good short-term demand forecasts but tend to get lost in the longer-term trends. Also, RMSs only consider topline aspects and oftentimes do not understand the types of demand or the costs of acquisition components such as distribution, marketing, and commissions.


I have yet to find an RMS that takes a holistic profitability perspective when applying decision-making. This is where a robust business analytics platform becomes the basis for setting up your RMS to align with the overall objectives.


Additionally, most RMS systems do not consider contributions outside of room revenue. This leaves the revenue teams to decide how best to manage items such as event space and outlets. If left out, these areas may be under-utilized or may not be fully optimized for profitability.


Recently, we started focusing on commercial decision support for event space. This allows hotel teams to better understand demand measures such as the likelihood of a particular space to book hurdles and minimum spend requirements, and informs sales and marketing teams on promotional strategies as well as realistic targets that align with the overall enterprise strategy.


Stop looking at STR indices as your primary indicator of success.

Too often, I find hoteliers looking at STR indexes to gauge success and build future strategies. This limits your ability to drive profitability. Not all RevPAR gain equals advances in profitability.


I teach a revenue essentials class about every 8 weeks, and one of my favorite exercises is to show two different scenarios of room profit. One is built on the philosophy of emphasizing growing revenues through gains in occupancy, which often comes at the expense of rate. The other assumes a strategy of building rate through emphasis on retail pricing and shifts in the mix of business, sometimes at the expense of occupancy. Even with an occupancy loss, often a strategy of optimizing mix and rate wins the day from a profitability standpoint. This second approach may result in a slightly lower RevPAR index growth.


Strategies that optimize business mix and pricing, even at the expense of occupancy, often lead to greater profitability.


STR indices are only part of the KPI tool kit, and each hotel should determine which combination of indices is the most profitable given their circumstances.


The Bottom Line:

As we near the normalization point in overall occupancy in 2025, we cannot rely on any major occupancy gains moving forward, but the rate remains strong in most markets. This translates into overall gains in Rev PAR in 2025. How we build our strategy moving forward will determine if we are successful in flowing as much of that gain to the bottom line.


Optimizing hotel profitability in 2025 and beyond requires leveraging AI and business intelligence for effective commercial decision support. A robust business intelligence platform that incorporates data from various sources forms the foundation for understanding situational awareness and profitability components. This approach enables focused KPIs, improved data quality, and instant insights. Data science plays a critical role in revenue optimization by utilizing advanced analytics and machine learning to guide pricing and inventory strategies. While automated RMS systems are useful for short-term forecasts, they often lack a holistic profitability perspective. Hoteliers are cautioned against relying solely on STR indices as success indicators, as strategies that prioritize business mix and pricing optimization can lead to greater profitability, even at the expense of occupancy. The key is to base decisions on data-driven insights rather than emotion, considering all aspects of revenue generation and cost management to maximize overall profitability.


By the way….

That hotel I talked about earlier is now on a good path and has a positive future as a result of a shift in mindset, and education to take a holistic view of their situation, goals are becoming more aligned, and profitability is on the rise.

 


48 views0 comments

Comments


bottom of page