What to look for when hiring data analysts
 
What to look for when hiring data analysts
12 SEPTEMBER 2018 8:05 AM

Diversity in backgrounds and skills, a curious mindset and strong communications skills are all must-haves for today’s successful hotel data analysts, according to speakers on a recent panel.

NASHVILLE, Tennessee—At every level of the hotel industry, from property to corporate, analyzing data is becoming increasingly critical to success, which places even more importance on recruiting and retaining analytical talent, sources said.

Speakers on the “Analyzing the analytics profession” panel at the Hotel Data Conference in August talked about best practices for finding and keeping the best analytical talent, and why it’s such a key focus in this age of Big Data.

Why diversity is important
Panel speakers repeatedly stressed the importance of a diverse analytics team to bring varied viewpoints and perspectives.

“Really, the No. 1 theme with our team is diversity of background,” said Kathryn Kilburg, senior manager of competitive analysis at Marriott International. “It’s what brings true insights into our analysis. We have economists, mathematicians, hotel people, Wall Street folks—we even have a rocket scientist. We have all of these amazing minds and lenses coming together to make an analysis team robust.”

Nikhil Bhalla, VP of finance at RLJ Lodging Trust, agreed that a team with diverse backgrounds is “extremely important.”

“We have found you need a good blend of people with good analytics backgrounds, but you also need data translators—people who can take all of that data and find the insights. If you have one without the other, it doesn’t work,” he said.

Hotel-specific experience isn’t necessarily important, speakers said.

“We just hired a business intelligence team, and only one person is from the industry,” said Kathleen Cullen, SVP of revenue and distribution at Two Roads Hospitality. “It’s a fascinating process—people don’t have to be from the industry. It opens up some really good conversations.”

Balaji Krishnamurthy, VP of global strategy, corporate development and SynXis Analytics Cloud at Sabre, agree it’s important to have many skillsets represented on your team.

“You’re sifting through sand to pick up insights,” he said. “Having knowledge of a lot of things is important, like linear regression, to deep learning and machine learning.”

Kilburg said for her team, “having exposure to any sort of code is crucial,” since that helps people understand and evaluate the many types of data sets that cross desks.

Look for curious people
Having the ability to step back and see the bigger picture, dig deep and ask a variety of questions helps teams arrive at better solutions, speakers said.

“Instead of chasing Big Data, we look at big questions—what are the big, compelling questions an organization has?” Krishnamurthy said. “We start with big questions and then chase the data, so the guy or gal asking the tough questions—that’s the most important thing that needs to happen.”

Cullen agreed curiosity is a key trait of great data analysts.

“A natural curiosity is really important,” she said. “People have to have a desire to get to the bottom of the data—find out what it means, where it’s coming from. They have to have an eye for detail, but at the same time, be creative. They have to understand the technical pieces of data but also the business side. That will help them pull out the data and provide it in an understandable way to the right audience.”

Communications skills matter
Colleen Birch, SVP of revenue optimization at The Cosmopolitan of Las Vegas, emphasized that analytics skills and communication skills must go hand in hand.

“I look for people that have strengths on the analytical side, but also communication skills,” she said. “They can mine the data but then also sanity-check the data, too. They can understand and make sure it’s valid, and put it into a story that you can take to an operations committee meeting and get buy-in.”

Communicating data analysis out to the property or larger organization is critical, panelists agreed, but there are challenges.

“It’s about making the data as available to as many people in the organization as you can,” Kilburg said. “Once the data is with the people … is when the true analysis can come together.”

Cullen agreed, but she cautioned “too much can be overwhelming.”

Analysis “needs to be focused data to help people make decisions and actions,” she said. “Otherwise people can get lost in the data and nothing gets done.”

How to keep good people
Once the right team is in place, it’s especially important to keep the group stimulated and happy in their jobs, panelists said.

“We need to make sure people don’t get stale and bored, so investing in technology is important,” Birch said. “Keeping people challenged and putting new things in front of them creates excitement and ownership.”

“Make sure they’re doing what they love to do—what they’re passionate about doing,” Cullen said. “Ensure they know their work is being used and that there’s value in what they’re producing.”

A great analytics team also requires some insulation, Kilburg said.

“We have a lot of subject-matter experts on our team, so we do our best to create a bit of a wall, so not everyone in the organization is asking our analysts 400 questions at once,” she said. “We have to protect them so they can continue to follow their own curiosity.”

1 Comment

  • Serge September 12, 2018 3:25 PM Reply

    Great article, very insightful

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