We have spent a good deal of time at the Analytic Hospitality Executive advocating for the value of big data for hospitality. Just a few months ago, for example, I wrote a two part series on how Big Data was a “big opportunity” for hotels and casinos. Our goal at this blog is to help you understand opportunities to leverage data and analytics to move your business forward. Big data and big analytics, and the technology to take advantage of them in particular is a complex and fast moving topic. New opportunities constantly present themselves. It is difficult to sort through what will be sustainable and what is a passing fad. It can be confusing, risky and uncertain. It is difficult to justify investment today when the game may be changed completely by tomorrow.

It is just this challenge that I want to address in this blog. With all the highly publicized opportunities in big data and the ever evolving technology landscape, most hospitality and travel organizations are proceeding with caution when it comes to this area – and with good reason. These are expensive investments with many moving pieces.

There has to be a balance, however. Hospitality companies need a solid data and analytics program to support their overall business strategy, and to stay competitive. This strategy should be carefully constructed in light of the business requirements and organizational goals. However, none of these initiatives have to be perfect right out of the gate. There is too much potential in the data to wait for the perfect data warehouse or the most robust analytics package with the most innovative real-time collection and delivery. This isn’t rocket science or brain surgery. Something is better than nothing. Directional guidance can be highly valuable, even if it doesn’t point you to the optimal solution.

I was reminded of this years ago when I was doing a consulting engagement at a casino buffet restaurant. Casino marketing was running a two-for-one promotion that was creating long waits for tables. So much so that the customer satisfaction scores that the managers were bonused on were suffering. We were called in to build some capacity or revenue management strategies to reduce wait times and increase throughput. In our initial meetings we brainstormed the idea of running an optimal table mix analysis – an optimization algorithm that matches table sizes to the party size distribution, reducing the number of empty seats. We needed to collect and analyze party size distribution, run the optimization algorithm and then scenario test to make sure the mix would stand up against the variability in the distribution.   When we returned a few weeks later to review initial findings, the manager pulled me aside. He told me he liked the table mix idea, figured he had too many four tops on the floor, and went ahead and replaced them with a bunch of tables of two. He told me he was doing about 36 more covers per hour, and that he felt like satisfaction was increasing. The actual analysis revealed that he was off by a few tables here or there, but the point was that he was able to take advantage of the opportunity to increase throughput and reduce wait times before the “perfect” answer came, just by using data gained by his own observation of the operations.

Before you bite off big data, you are better off working with what you have, driving value and using that to set the path forward.

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