According to the Global Travel Staffing Barometer, due to the pandemic, travel companies around the world have laid off or furloughed over half a million people, and the number of LinkedIn users in the hospitality space applying the #opentowork hashtag to their profiles grows day after day. Most hotels are struggling to run operations with skeleton crews only, yet they do not have any real alternative. In some countries, in fact, the financial help coming from governments is close to zero, so the only option for these hotels is to get rid of "superfluous" staff and try to run their businesses with a fraction of their employees. This forced most properties to heavily concentrate and focus on productivity, trying to get the best out of dire circumstances. How will this situation affect hotels? Can a global reset actually be a good thing, after all, forcing the industry to get more done with fewer resources? Or will this trend damage the guest experience in the long run?

Jason G. Bryant
Jason G. Bryant
Vice President, Nor1 GTM - Oracle Hospitality

The use of intelligent technology is the most realistic lever to pull that enables hoteliers to do more with fewer resources. While simple technical automation of manual tasks in the hospitality industry is a worthwhile objective, I believe we will see the most significant gains by automating decision-making, specifically decisions of pricing, inventory management, and merchandising.

What resources are available could then be focused on serving guests and, more narrowly, on strategic objectives and analyzing how to drive the business. Hoteliers do not have the resources to invest in the mountains of daily manual tasks that existed prior to the pandemic, including balancing the house, setting offer prices, and determining what offers are compelling for which guest. This is likely not to change even as the industry recovers. The pandemic has forced us as an industry to take a step back and reevaluate how we run our businesses, including improving productivity and streamlining efficiencies.

As a result, those organizations that can leverage real-time, cloud-based Applied Artificial Intelligence that includes a domain-specific combination of machine learning, optimization algorithms, and layered with a conditions engine, will be able to realize a much higher level of precision in their revenue optimization with a far lower human cost. 

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