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and software to the cloud has paved the way for easier and increased data centralization through advancements in areas like Integration Platform as a Service ( iPaaS ) and central data warehouses , such as Snowflake .
Now , rapid adoption of generative AI models , such as Large Language Models ( LLMs ) and Generative Pre-trained Transformers ( GPTs ), and continued adoption of analytical AI models , are enhancing the business intelligence discipline by providing a next level of analysis . Instead of simply serving up descriptive analytics , next-generation tools will decipher and analyze the relevant information for you and either serve up a recommended action or automatically take the next steps .
What kind of actions could we see AI taking for us ?
Anomaly detection . Was your food cost or labor cost abnormally high this week ? Did your booking engine experience a spike in conversions ? AI systems can detect those anomalies , alert the hotelier , highlight the necessary information and then recommend a suggested course of action .
Turning data to prescriptive insights . OK , you ’ ve got a pretty dashboard — what specifically should you be looking at ? AI will analyze reports and dashboards and generate actual insights , pinpointing areas to adjust and improve strategy .
Conversational data . Can
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you ask your data questions ? AI assistants provide the opportunity to send messages with questions about the data in reports and automatically receive insights and next-step suggestions in text format .
The evolution of AI has driven a shift in the type of data we consume today , from descriptive analytics to predictive analytics to prescriptive analytics . Descriptive analysis primarily focuses on summarizing historical data to understand past trends and events . Predictive analysis takes this a step further by using AI models to make predictions based on patterns found in historical data . Finally , prescriptive analysis harnesses AI to not only predict future scenarios but also recommend the best actions to achieve desired outcomes .
Soon , AI will enable a last step — let ’ s call it delegative — where after one approval click , software is automatically taking the recommended action for you . Once AI knows enough about our business and what decisions we would typically make , anomalies in data will automatically trigger optimal actions . For example , when a system detects that occupancy is spiking , AI might automatically schedule an extra housekeeping shift .
With time and repetition , hoteliers will be able to trust that their system is taking the right actions . When AI turns recommendations into actions , hoteliers can increase productivity and reallocate
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their time back to providing exceptional hospitality .
WHO OWNS THE DATA ? Over the past few decades , as data about the hotel business became more widely available and accessible , a growing concern was data ownership . On one hand , both brands and management companies need access to property-level and guest data to implement new strategies and tools , such as AI and personalization , that will improve efficiencies and guest experiences .
On the other hand , management companies are justified in protecting some financial data , such as profitability . For management companies that operate multiple brands , sharing data among competing brands also requires sensitivity and security measurements .
Guests also have rights to their data , and hotel leaders as well as solutions providers must become increasingly cognizant of those rights and put the right protections in place to keep guest data secure .
With protections in place , however , data sharing should be less of an issue today , and many solutions providers are moving toward more open systems that allow hoteliers to centralize data in a unified data warehouse accessible by different stakeholders in real time . Working with a solutions provider who understands the unique dynamics of the hospitality industry , and where the roadblocks exist today , is critical to ensuring necessary
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data is shared while certain data is protected .
Tensions will always exist over ownership of data , but , in the end , without increased data sharing , the industry will continue to lag other industries in innovation .
AI AS A CATALYST AI will be the catalyst to finally understanding the depths of performance and financial data to help run more profitable businesses . To get here , though , we must start with bringing all the available data together into what is commonly referred to as a “ single source of truth .” From there , we can begin to surface the data into digestible formats , such as dashboards and reports . Only then can we begin generating actionable insights .
Helpdesk chatbots are a great start to making teams more efficient and helping hotels tackle their biggest challenge : labor . But the prospects of AI being applied to business metrics across an entire property or portfolio will have a lasting impact on the evolution of hospitality operations .
Niki Johnson
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July / August 2024 hotelsmag . com 41 |