We aim to highlight the evolving role of revenue managers in an industry increasingly influenced by AI and consider how best to integrate technological advancements with human skills to drive success.
NB: This is an article from Demand Calendar
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We present two scenarios in which Sarah, a seasoned revenue manager, and InsightMax, a state-of-the-art AI system, engage in a friendly competition to forecast hotel demand for an upcoming major international conference. Each scenario offers a different outcome, highlighting the unique strengths and limitations of their distinct approaches to prediction.
Despite technological advancements, hotels have relied on point estimates for demand forecasting for over half a century. This traditional method involves predicting a single, specific occupancy rate or revenue figure based on historical data and professional judgment. Point estimates provide clear targets and simplify planning, but they often lack flexibility and may not account for uncertainties or sudden market changes.
In contrast, AI systems like InsightMax employ probabilistic forecasting, which assigns probabilities to a range of possible outcomes rather than focusing on a single figure. This approach acknowledges the inherent uncertainties in demand prediction, offering a nuanced understanding of potential scenarios. Probabilistic methods enhance risk management by preparing for various outcomes, but they can be challenging for hotels accustomed to point estimates. Interpreting and acting upon probability distributions requires a shift in mindset and may introduce complexity into decision-making processes.
By exploring Sarah’s and InsightMax’s experiences, we aim to shed light on these different forecasting methods. The story illustrates how each approach impacts strategy development, adaptability, and overall performance in the dynamic environment of hotel revenue management. Through their competition, we examine the benefits and challenges of transitioning from traditional point estimates to probabilistic forecasting. We provide insights that can help hotels navigate this shift and leverage both human expertise and AI capabilities for optimal results.
Meet the Protagonists
A. The Revenue Manager: Sarah
Meet Sarah, a seasoned revenue manager with over 15 years of experience in the hotel industry. She began her career in hospitality straight out of college, working her way up from front desk associate to her current role through dedication and a passion for understanding the intricacies of hotel operations. Sarah has witnessed the industry’s evolution firsthand, from traditional booking methods to the advent of online travel agencies and the growing influence of social media on customer choices.
One of her greatest assets is her deep understanding of market trends. Sarah monitors economic indicators, travel patterns, and local events that could impact hotel demand. She has developed an intuitive sense of customer behavior, recognizing subtle shifts in preferences and expectations. For instance, she notes the increasing desire among guests for personalized experiences and sustainable practices.
