Never in human history have we had access to as much data as we do today. In recent years, the tools and strategies we use to process and understand insights derived from this data have become one of the hottest commodities – and with good reason.
NB: This is an article from Flyr for Hospitality (formerly Pace Revenue), one of our Expert Partners
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Organizations are able to harness the power of data to gain a deeper understanding of their operations, customer behaviors, and market trends, unlocking competitive advantages.
Data-driven decision-making is the new normal. And while the hospitality industry has always used data in its revenue management strategies, AI can allow hotels to elevate that practice. AI-driven revenue management systems are steadily making inroads in the hotel industry because of their many benefits over traditional systems.
Let’s explore the advantages of AI-driven revenue management systems (RMS) over legacy systems and manual efforts. However, we do not believe that it’s an “all or nothing” line of reasoning. AI will augment revenue managers for better job performance without replacing the people it’s meant to serve.
Let’s take a look at how revenue managers and AI can work together for even better results (and bottom lines).
A Vast and Profitable Data Trove
One of the hallmarks of AI-driven revenue management systems is their ability to analyze vast amounts of data quickly and accurately. And while legacy systems and revenue managers do analyze data, there’s just no way for them to match AI’s speed and accuracy – especially when it comes to pricing strategies, speed is critical.
People typically analyze historical data and make predictions based on past trends. An AI-driven RMS analyzes current data, such as transactions, shopping, room occupancy rates, seasonal trends, and local events, to adjust hotel pricing and inventory in real-time. By combining historical data with real-time data, hotels are able to limit biases and make predictions on their current and future business – not the past.
Another advantage of AI-driven revenue management systems is their ability to learn and adapt over time. They train themselves. As the system analyzes more data and makes more decisions, it becomes better at predicting demand and optimizing pricing and inventory. AI-driven systems that are able to constantly learn translate to a steady increase in revenue over time as the RMS performs its own fine-tuning.
Real-time data will provide more gains in almost every scenario. However, that doesn’t mean revenue managers’ knowledge, expertise, and experience isn’t essential.
Multi-sourced insights power personalized offers
AI-driven revenue management systems plug into your existing systems and can analyze a wide range of data sources to inform analytics and decisions and produce personalized pricing and offers. Using machine-learning algorithms, the advanced RMS can analyze customer behavior, preferences, booking history, and data from outside the organization, such as competitor rates, weather patterns, and events. And it will stick to that data, meaning it will remain free of bias and won’t be prone to under or overestimations, unlike their human counterparts.
Advantages of an AI-driven RMS
The most significant advantages of an AI-driven decision-making RMS are the following:
- Enhanced Data-Driven Insights
- AI’s ability to quickly and accurately analyze massive datasets from within and outside the organization allows hotels to make more agile and informed pricing and inventory decisions.
- Speed & Efficiency
- An AI-driven RMS enhances the ability for data analysis by orders of magnitude. It can also perform repetitive tasks more efficiently, freeing up people for more strategic tasks.
- Bias Reduction
- An AI-driven RMS minimizes bias in decision-making, providing more objective pricing decisions that remain grounded in data.
- Reduced Costs and Increased Revenue Growth
- Through automation, AI-driven RMSs enable significant cost reductions in revenue management while growing revenue and profitability.
However powerful an AI-driven revenue management system may be, human management is still required. An AI-driven RMS isn’t meant to supplant human revenue managers but to support and enhance decision-making. And while neural networks are meant to emulate the inner workings of the human brain, there remain some areas in which they fall short.
- Strategic Decision Support
- AI-driven revenue management systems output data-backed pricing and inventory decisions, but knowledge, experience, and intuition allow the revenue managers to interpret and validate that output and assist in fine-tuning the system by providing feedback and suggestions for improvement. These systems can also help make decisions in situations where the data may be incomplete or ambiguous.
- Creative Problem Solving
- While AI can assist in identifying problems and potential solutions, it cannot go beyond its data. In other words, it does not have the same capacity for creativity as humans, who drive innovative thinking.
- Emotional Intelligence
- The hospitality industry is all about people – and people are emotional beings. AI systems, RMS or otherwise, are not able to provide insights into guest behavior and preferences that are not present in the data. Only the people supporting their guests can work beyond the data, making decisions based on factors that are not quantifiable.
Will AI Replace Hotel Revenue Managers? The Answer Is a Resounding NO.
The Washington Post reminds us that labor benefited alongside productivity throughout the 19th and 20th centuries with technological advances. The optimal strategy is going to be synergy: AI working hand in hand with human knowledge and intuition is the way forward. It is best summed up in the statement, “AI won’t take your job; a person using AI will.”
By combining the strengths of AI-driven revenue management systems and the knowledge and experience of revenue professionals, hotels can take a more holistic approach to revenue management. AI will serve as a powerful ally, enhancing the performance of revenue managers by automating mundane tasks and providing decision intelligence for better forecasting and smarter pricing. By offloading repetitive tasks to AI, revenue managers can focus on higher-value activities that require human expertise and critical thinking.
Hotels that can strike the right balance between these two elements will be better equipped to make informed decisions that maximize profitability while providing a better guest experience. Using AI can open up countless opportunities for hoteliers and revenue managers. So, let’s embark on this journey of AI evolution, creating a future where we work side by side with AI to achieve extraordinary results.
Steve Jobs, co-founder of Apple may have said it best when asked if he still believed in the limitless potential of technology, He answered yes. “But it’s not a faith in technology. It’s faith in people.”
