Fast implementation while ensuring accuracy are goals that often work at against each other. Yet, speed and precision are always paramount to success. In today’s hospitality industry and in the field of revenue management solutions, both are essential to staying competitive. In these times of disruption that have caused hotels, resorts, and casinos to move quickly to change the way they deliver their services, applying the right pricing to the right channel at the right time have never been more important to hospitality businesses seeking to thrive in a new era.
What are the best practices to ensuring that a solution helps hotel revenue managers to focus on maximizing revenue potential? How do experts use emerging technology to set pricing, forecasting, and generally ensure that an offering is competitive even as the parameters change sometimes several times during the course of a day?
Enhancing revenue managers efforts with machine learning
Despite the many misconceptions around machine learning and algorithms, automation is not a threat to the work of revenue managers. In fact, these elements are the key means to meeting the demands of speed and precision in markets that are moving at an unprecedented pace. Hotel revenue management solutions with a machine learning component have freed up revenue managers to create a more data-driven process to selling rooms at the right price, based on internal data and an analysis of external market data, too.
With machine learning-driven revenue management platforms, revenue managers apply their expertise and experience with the market in a new way. Automation plays an integral part in updating pricing whenever needed, while leaving space for management teams to gain greater clarity on strategy much faster than before. This also leaves more room for better communications with sales and marketing, resulting in a greater alignment and focus on strategy. While automation takes care of the multiple adjustments to optimize rates for guest rooms and function spaces, revenue managers are freer to join the wider conversation with other departments on where to focus resources and on which segments that will gain the greatest competitive traction.
Consistent optimization with automated revenue management solutions
When building competitive momentum, it helps to know who the organization is actually competing with. It also helps to know where competition for the attention of guests is actually happening to ensure that resources are focused in the right places. From there, making sure that rates are updated across channels and adjusted appropriately based on market segments and regions so that they are always competitive at any given time is more important than ever before. Automated processes manage the adjustments aligned to comparable competitor offerings in specific markets, helping hotels to gain clarity and precision – not to mention speed – on strategy.
Once again, this is not to say that the expertise of hotel revenue managers isn’t needed when it comes to more informed forecasting. Revenue management solutions that incorporate machine learning handle the mechanics of managing constantly changing variables, while RM management can run scenarios to see how adjustments will affect competitive outcomes. In this way, managers still retain control while also keeping up with necessary rate optimization. This makes for a means to present a more consistently competitive offering in a way that wasn’t possible before.
Ready for what the future holds
To secure competitive traction, concentrating on systems that help your organization to define key data and implement quick actions to act on it is essential. Intelligent solutions and processes like revenue management solutions driven by automation and machine learning algorithms is an important facet to creating long-term resilience in a currently disrupted and fast-paced hospitality industry.
What are some other essentials to readying your business for what the future holds? We’ve created an in-depth resource that outlines what is needed to thrive in the 2020s.
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