The Future of Revenue Management Is Not What It Used to Be
By Gabor Forgacs, Associate Professor, Hospitality & Tourism Management, Ryerson University
Not too long ago we thought the future of Revenue Management would be more data; faster processing capability; more revenue streams optimized; and more properties managed by one revenue professional. Now that the second decade of the 21st century is nearing its final year we can see that the "more" and "faster" will give way to something slightly different.
How We Got Here
The revenue profession in the hotel industry has grown up: there are revenue analysts, revenue managers, directors of revenue, even vice presidents and other executives - it is fair to say the revenue profession is emerging as a champion of progress and a key to profitable growth in businesses that understand how mission-critical it is to drive revenue.
We can look back on the last three decades before look forward. It was logical to project the future in the nineties: it was predicted that more power and more influence would come to revenue professionals. The new field of revenue maximization got gradually recognized after the early years. Revenue professionals who traditionally got started deep inside the rooms division, very close to the Front Desk and the Reservation Office would rise to equal stature and clout as department heads, then division heads within organizations. After the value added through forecasting accuracy and rate-control wizardry became evident, a prediction was made that additional revenue streams of function space, catering and food and beverage would became inevitable options for inclusion with other possible revenue centers from parking revenue to spa for total hotel revenue management. This evolution was seen as a natural progress.
On the technology front the continuous improvement resulted in more data being collected, analyzed and leveraged to drive sustainable income growth. Operations today are dealing with more structured and unstructured data than ever before. Every tap on a screen, every tap or swipe of a coded card at a reader and every action of a smart phone offers valuable data that can be harnessed by software suites for optimization in rates, availability controls, for benchmarking and better reporting for operational purposes.
On the human resources side of things, as the technology developments outpaced the talent base there was an inevitable projection for the future: cluster management, where feasible. The function of a revenue professional has proven to be less location-specific: one revenue manager was able to direct multiple operations with seamless real-time connectivity. There is no need plus no budget to hire five or six revenue professionals to look after each individual smaller or even mid-sized hotels: one cluster manager is capable of taking care of all of those properties. Not to mention the fact how hard it is to find suitable candidates who have operational experience coupled with revenue management training and certification to fill all those positions.
It also became evident for educators that revenue management just doesn't exist at introductory level. Revenue management can only be studied on a fairly advanced level, once some fundamentals in a variety of disciplines have been mastered: financials, marketing, data science and operations management are vital underpinnings for any future revenue professional who dreams of making a positive impact.
If your boss thinks that totally automated forecasting and rate-rules setting or digital ad strength measuring metrics are the main disruptors, you need to sit him/her down for a friendly chat over a coffee. If the boss thinks that social media scores, or alternative lodging platforms like Airbnb, VRBO, etc. are the main new disruptors I suggest a heart-to-heart conversation over beer. The points that need to be laid out in a non-threating but firmly articulated manner are that the real, serious new disruptive forces are: machine learning, artificial intelligence (AI), and distributed ledgers.
The force of evolution is driving the field of revenue into new directions. We are on the cusp of a period where human intelligence is getting bolstered to do way more than before by purpose-built software that has the capacity to learn. More and more of the tactical-level decision making is getting successfully automated leaving more time and resources dedicated to higher-level thinking like strategy formulation. One example to illustrate the above is an app that is built for helping those who are buying airfare. The smartphone app (Hopper) studies the pricing practices of all the airlines that apply dynamic pricing. Based on historic data (what price points were offered at what time for same itinerary) and identifying patterns, the app predicts the optimum time to book a given flight fairly accurately. The airlines now understand how their own pricing tactics can be machine-analysed and exploited to help their customers to arrive at optimum purchasing decision for maximum value per seat, based on the data. The logical conclusion for airlines could be to elevate their thinking and identify strategies that help them compete more successfully as machine learning seems to counter their dynamic pricing tactics successfully.
We have seen a lot of examples over the years for airline industry examples being adopted by lodging industry operators. The above example may also be transferable into dealing with accommodation instead of flights. The lack of price parity is already exploited by targeted search and price comparison software capability to help find lowest rate for same room night for customers. These apps and comparison-shopping meta-searches are not even considered disruptors any more.
It is an important aspect of human nature to distrust machines. It takes time to accept that the hotel's system forecast was more accurate than the Front Office Manager's. It takes a while to resist the temptation for a manager to override price fencing measures or distribution channel-mix decisions put in place by a best-of-breed software suite. The continuous double-checking and comparisons take resources and the strategic thinking does not come easy if we are bogged down dealing with operational issues constantly. However, once we get to the level of meaningful strategic deliberations the potential offered by freeing ourselves from fighting low-level tactical troubles becomes promising.
We may even reflect on the crucial questions like do we need to compete on room rates at all? Or should we consider other core competencies, product attributes or differentiators? Do we track and measure only price points (net rate) for room revenue impact per booking while disregarding total spend per stay? Are there alternative ways of segmenting our market that offer a better understanding of both manifested and latent demand? Do we dig deeper than targeting e.g. millennials? An age bracket like that contains high income earners just as well as low income earners; frequent travelers and staycationers; domestics and internationals; and solo travelers plus couples - they might all be millennials. Segmentation evolves beyond demographics as we speak. Strategizing should rely on solid data, information and reflection as a start.
One thing is safe to predict: that nothing is stationary and everything keeps evolving and shifting in our world. Change is the only constant and artificial intelligence is likely to disrupt the ways service providers connect with customers: as we'll transact differently, revenue generation will be impacted. Certain silos as Sales, Marketing and Revenue Management will all be effected and will likely move (maybe by merging?) towards new ways of harnessing the power of data and leveraging technology.
As voice is gradually taking over other types of inputs (e.g. for search) and digital assistants start taking over mundane task completion from wake-up calls, daily news reading and location finding to sourcing and purchasing consumer goods, it is an inevitable consequence that more and more travel products will also be sold through Google Assistants, Alexas, Siris and other similar platforms. The purchase decision may be reserved to humans for now, but the searching and curating can be seamlessly conducted by AI. One key question arises: are service providers ready to start marketing to digital assistants instead of human eyeballs when a vacation or an accommodation product is the subject? How much different will that be in the key product variables when instead of instructing a personal digital assistant to book a ride to the airport, the request will be to book a flight or a weekend getaway package to Vegas or a cruise to Alaska? This new phase in connecting with customers will come sooner than we think.
The need to cater to both evolving customer needs and for meeting income targets set by owners and investors will be stronger than ever for hotels. The technology is an exciting new tool but it won't turn lousy customer service into satisfactory or a dead hotel location into a coveted place to stay. Revenue professionals will use the understanding of the potential upside of meaningful consumer insights, faster and better analytics, constant connectivity and responsiveness without forgetting that the fundamentals of hospitality never change. The future of Revenue Management is exciting and it is unfolding not exactly as we thought it would even a decade ago. However, looking forward is important. Preparing ourselves for the future will help us deal with the changes much better.
The future of Revenue Management is likely to be more than total revenue management or lightning fast market report generation or individualized room rate adjustment on the fly. If the fine balance between human strategy formulation, decision making and the application of artificial intelligence is found, good things are likely to happen.