Roundtable Recap: Finding the Balance Between Driving Revenue & Managing Costs

In July, the School of Hotel Administration’s Center for Hospitality Research (CHR) hosted a virtual roundtable called Finding the Balance Between Driving Revenue & Managing Costs. A group of twenty-three academics and experts from various sectors of the hospitality industry attended the two-hour event. Through moderated discussion, they challenged the industry’s long standing practice of managing top line room revenues, proposed a shift to managing cash flow, and aimed to uncover opportunities for turning talk into action, with their ultimate goal being industry wide implementation of profit management and profit benchmarking.

The roundtable discussion addressed three key aspects of the issue: People, Process, and Technology. The main takeaways from each session are highlighted below.

Key takeaways

People

For many years, the hospitality industry drove profits by managing costs (particularly, variable operational costs) at the hotel level, with operations and finance managers focusing on the bottom line. It wasn’t until the 1990s, when revenue management came on the scene, that hoteliers started thinking about managing top line revenue. These two very different ways of thinking resulted in tension between the top line-focused revenue managers (RMs) and the bottom line-focused operations and finance managers.

Later, as the distribution landscape grew more complex, the industry soon realized that all demand is not created equal. While nearly all booking channels had costs, they varied greatly from channel to channel. To address this complexity, the revenue management discipline gradually incorporated distribution costs into its profit maximization strategy. At the same time, it became clear that the standard practice of measuring and maximizing room revenue alone was insufficient, and that it would be necessary to control and manage all revenue-generating departments because they all contribute differently to the bottom line. As a result, the role of RMs was redefined and expanded.

Now, RMs are being broken out of their silos and integrated into all strategic areas of the business (sales, marketing, operations, finance, etc.) because of their broad knowledge. Recognizing the value of revenue management, hotel companies are asking more of their RMs and challenging technology providers to be more innovative and do more, faster.

The importance of analytics within the revenue management discipline is also growing. Analytics, however, are not hoteliers’ strong suit, and analysts within the industry are not necessarily experienced in data modeling, data science, and predictive analytics, but they need to be (and many are) conversational in these areas to fit into the post-COVID revenue management model.

Taking all of the aforementioned challenges into account, the roundtable participants offered up solutions. To tackle the growing importance of analytics, one participant suggested automating or outsourcing data science expertise. For example, hotel companies could hire PhDs and data scientists to develop the models, and RMs could be the end users.

When it came to profit-oriented strategy, participants unanimously agreed that existing conflict between different industry players—owners, management companies, and brands, as well as among different roles within a hotel—could be detrimental to advancing profit management. Participants identified the following areas of conflict:

• Hotel management agreements (which are contracts between hotel owners and hotel operators controlling the management of a hotel property) have a performance clause that is based on the top line revenue and not on bottom line metrics. Participants concluded that in order to manage and maximize profit efficiently, these contracts need to be updated to align objectives around profit metrics.
• There’s a similar challenge with franchise agreements, where royalty fees are based on top line revenues. While it’s unlikely to change, hotel owners should be aware of this and consider it when making strategic decisions that affect their bottom line performance. This includes decisions to accept promotions, campaigns, or pricing recommendations initiated by the brand. Any recommendations should be run through a property-level profit analysis before a decision is made.
• Revenue managers are still incentivized based on RevPAR, which means their actions could be misaligned with ownership’s desire to maximize profit: for example, dropping rates in an effort to drive RevPAR through increased occupancy could ultimately hurt bottom line performance.
• Sales departments currently don’t assess profitability when quoting a group rate. They’re also incentivized on the top line revenue, so profit isn’t their focus.
• The same goes for marketing departments when planning (or running) campaigns and promotions.

Participants proposed the following steps to align stakeholders:

5. Update hotel management agreements by designating profit-oriented metrics as the basis for performance management and compensation.
6. Align objectives on the property level or the cluster level across departments to target profit maximization.
7. Automate or outsource data science expertise and concentrate on the bottom line performance and total revenue generation rather than top line room revenue, with more actionable insights generated by those models.
8. Ensure that, at the property level or at the cluster level, RMs understand data, have strategic skills to help align other departments toward profit maximization goals, and are able to skillfully make decisions based on a model’s outputs.
9. Ensure that people in these roles are engaged, properly compensated, and have a growth mindset.

Process

Turning to business process, participants identified several purposes it should serve:

• Ensure stakeholders across departments have access to the technology described in the previous section.
• Address aspects of profit maximization through human-technology collaboration and make it ubiquitous.
• Define the process for managing exceptions and overriding system decisions.
• Define how to measure results from these actions and overrides.

Additionally, new revenue management models need to be forward-looking and include new data sources (in addition to the historic internal booking data) to measure demand accurately and adapt to fluctuations in demand and segment shifts efficiently. Within these new models, participants envisioned artificial intelligence, machine learning, and talented people working together to make smarter decisions.

Participants also agreed that recent disruptions caused by the pandemic and other factors have pushed hotel companies to reevaluate their processes to determine whether they actually generate ROI (from the profit standpoint) or are just a matter of habit.

The group proposed a “zero based budgeting approach” that would require a review of business processes every few months to identify those that still add value and shed old habits—including those that developed as a reaction to the crisis and those that no longer contribute to the bottom line.

Technology

Challenges

As discussed in the previous section, there are clear challenges with the existing processes that prevent the industry from adopting true profit management efficiently. And historically, where the process is broken—we turn to technology to help us solve the problem.

However, our current reality is that hoteliers are offered a very minimal amount of technical functionality that would make profit maximization a user-friendly task. We need better tools that would allow the industry as a whole to track or forecast total revenue, manage and optimize expenses, or easily benchmark performance against each other in a standardized manner, for different regions, sizes or types of hotel properties.

Current systems (as well as integrations and data flows between those systems) concentrate on the top line room revenue, a limitation that contributes to departmental silos where each uses different metrics to assess performance, leading to contradictory initiatives. We lack tools to help different stakeholders and departments understand what actions they need to take individually to collectively reach profit maximization.

How do we solve it?

Data gathering and data analysis are the core aspects of this problem, which can be addressed through technology. Roundtable participants identified the following avenues for moving forward:

• We need more clarity and uniformity across organizations about who owns the data, what the format is, and how we interpret it. There is a clear need for a data standardization initiative by hospitality organizations to address the frequency at which certain expenses are recorded, as well as consistency and completeness of this reporting.
• The general understanding about the existing data sources is the following:

1. There is an agreement that in order to make progress toward proper profit management and benchmarking, hotels need to have their profit & loss (P&L) statements uploaded to the cloud, which would enable data collection of all revenue streams and cost categories. Then those statements need to be analyzed.
2. In addition, the revenue categories reflected in the P&L may need to be broken down for some full-service properties into more granular items. For example, an F&B category may include restaurants, catering and other revenue generating streams. Separating these items, however, will provide better individualized insights for each of these departments. To report on ancillary revenues, P&L is not enough. We can turn to the General Ledger (GL) and analyze separate line items from that source.
3. Data about distribution costs are currently not recorded anywhere but can be measured by analyzing corresponding rate codes in property management systems/central reservation systems (PMS/CRS) with some additional manual user input.

• Raising awareness among hotel owners and operators about the necessity of profit-oriented data sharing is crucial. That communication needs to be framed around positive outcomes and how hoteliers will benefit from this initiative, which can start from a small sample of hotels. Once those owners start seeing the benefits, it will create a snowball effect.
• We also need to continue conversations about privacy and security of data in the cloud to address lack of trust and owners’ unwillingness to share profit-level data. It is necessary to clearly communicate that data gathering is secure and confidential.

There are a few companies in the industry (e.g. data providers) that have made some progress toward profit-oriented data gathering. However, there is more progress to be made to enable automated daily updates on a large scale across the industry.

The good news is that we already have examples of hotel companies that have implemented profit-oriented data sharing and data analysis successfully. Every single line of their incoming data is remapped so that it’s consistent and standardized across their whole portfolio of properties.

Thanks to those successful examples, we already know that this is achievable. Now, we need to create a scaled solution using the right cloud-based technology.

And once scaled, this information can be used for benchmarking across the industry, to help hotels measure their level of competitiveness with other hotels in their market and spot potential performance issues. This type of benchmarking is extremely valuable, regardless of property size and type, as long as the data is standardized, normalized and consistent, and gathered regularly and automatically.

What we also need to consider is that scaling and automation is easier to achieve for chains, but the majority of hotels in the world are independent. We need a good technology solution that could address both segments.

The future

We have identified areas of opportunity for the industry to make progress toward profit-oriented measurement and benchmarking. Once this is achieved, the next step will be to develop solutions that incorporate machine learning algorithms that not only measure and analyze profit-level performance but also allow hotels to target profit maximization by optimizing the right metrics, rather than optimizing RevPAR.

Roundtable participants’ ultimate message to the industry: focus on possibilities, not barriers.

Thank you

Thank you to the co-chairs, Linda Canina and Kelly McGuire; session leaders, Mike Lukianoff, Dan Skodol, and Ira Vouk; subcommittee member, Vivek Bhogaraju; and the participants listed below for their contributions to the roundtable.

Participants

• Vivek Bhogaraju MMH ’06, GM, Revenue Performance Solutions, Lodging & Vacation Rental, Expedia Group
• Linda Canina, Dr. Michael Dang Director, Center for Hospitality Research & Georges C. and Marian St. Laurent Professor in Applied Business Management, School of Hotel Administration, Cornell University
• Alfonso Delgado MMH ’00, Managing Director, Solution Development Partners
• Ian-Michael Farkas, Vice President, Local Measure
• Robert Gilbert ’82, President and CEO, HSMAI
• Eliot Hamlisch, Executive Vice President, Loyalty & Revenue Optimization, Wyndham
• Adam Hayashi, Vice President, Revenue Management & Analytics, AccorHotels
• Alena Huberts, Director of Special Projects, Life House
• Ashwin Kamlani MMH ’03, Entrepreneur & Advisory Board Member, Pillsbury Institute for Hospitality Entrepreneurship
• Klaus Kohlmayr, Chief Evangelist & Development Officer, IDeaS Revenue Solutions
• Mike Lukianoff, Data Science Entrepreneur
• Sekhar Mallipeddi, Worldwide Technical Leader for Travel, Amazon Web Services (AWS)
• Robert Mandelbaum ’81, Director of Research Information Services, CBRE | CBRE Hotels Research
• Asís Martínez-Jerez, Associate Professor, School of Hotel Administration, Cornell University
• Sarah McCay Tams, Director of Content, Duetto
• Kelly McGuire MMH ’01 & Ph.D. ’07, Managing Principal Hospitality, ZS
• Andrada Paraschiv, Vice President of Hospitality, Beekeeper
• Gordon Potter, Professor Emeritus, School of Hotel Administration, Cornell University
• Dave Roberts ’87 & MS ’88, Lecturer, School of Hotel Administration, Cornell University
• Dan Skodol MMH ’04, Vice President of Data Science and Analytics, Cendyn
• Vincent Slaugh, Assistant Professor, School of Hotel Administration, Cornell University
• Maxine Taylor, SVP Asset Management, CHMWarnick
• Ira Vouk, Founder & Principal, Hospitality 2.0 Consulting

Click here to download the roundtable recap from the eCommons.

Learn more about the CHR

About the Author – Ira Vouk is a Hospitality Technology and Revenue Management consultant and coach, tech innovator with nearly 20 years of practical experience in the hospitality industry, contributing writer for various hospitality platforms and a frequent speaker on the topics of hospitality technology, revenue management and automation.