E-Handbook: Data science skills spawn success in AI, big data analytics Article 2 of 4

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Reskilling the analytics team: Math, science and creativity

Technical skills are a must for data scientists. But to make analytics teams successful, they also need to think creatively, work in harmony and be good communicators.

In a 2009 study of its employee data, Google discovered that the top seven characteristics of a successful manager at the company didn't involve technical expertise. For example, they included being a good coach and an effective communicator, having a clear vision and strategy, and empowering teams without micromanaging them. Technical skills were No. 8.

Google's list, which was updated this year to add collaboration and strong decision-making capabilities as two more key traits, applies specifically to its managers, not to technical workers. But the findings from the study, known as Project Oxygen, are also relevant to building an effective analytics team.

Obviously, STEM skills are incredibly important in analytics. But as Google's initial and subsequent studies have shown, they aren't the whole or even the most important part of the story. As an analytics leader, I'm very glad that someone has put numbers to all this, but I've always known that the best data scientists are also empathetic and creative storytellers.

What's churning in the job market?

The role of statisticians and data scientists is changing -- and becoming more and more important in today's dynamic business world.

According to the latest employment projections report by the U.S. Bureau of Labor Statistics, statisticians are in high demand. Among occupations that currently employ at least 25,000 people, statistician ranks fifth in projected growth rate; it's expected to grow by 33.8% from 2016 to 2026. For context, the average rate of growth that the statistics bureau forecasts for all occupations is 7.4%. And with application software developers as the only other exception, all of the other occupations in the top 10 are in the healthcare or senior care verticals, which is consistent with an aging U.S. population.

Fastest-growing U.S. occupations
Statistician is fifth among occupations with at least 25,000 workers projected to grow at the fastest rates.

Thanks to groundbreaking innovations in technology and computing power, the world is producing more data than ever before. Businesses are using actionable analytics to improve their day-to-day processes and drive diverse functions like sales, marketing, capital investment, HR and operations. Statisticians and data scientists are making that possible, using not only their mathematical and scientific skills, but also creativity and effective communication to extract and convey insights from the new data resources.

In 2017, IBM partnered with job market analytics software vendor Burning Glass Technologies and the Business-Higher Education Forum on a study that showed how the democratization of data is forcing change in the workforce. Without diving into the minutia, I gathered from the study that with more and more data now available to more and more people, the insights garnered from the data set you apart as an employee -- or as a company.

Developing and encouraging our analytics team

The need to find and communicate these insights influences how we hire and train our up-and-coming analytics employees at Dun & Bradstreet. Our focus is still primarily on mathematics, but we also consider other characteristics like critical- and innovative-thinking abilities as well as personality traits, so our statisticians and data scientists are effective in their roles.

As an analytics leader, I've always known that the best data scientists are also empathetic and creative storytellers.

Our employees have the advantage of working for a business-to-business company that has incredibly large and varied data sets -- containing more than 300 million business records -- and a wide variety of customers that are interested in our analytics services and applications. They get to work on a very diverse set of business challenges, share cutting-edge concepts with data scientists in other companies and develop creative solutions to unique problems.

Our associates are encouraged to pursue new analytical models and data analyses, and we have special five-day sprints where we augment and enhance some of the team's more creative suggestions. These sprints not only challenge the creativity of our data analysts, but also require them to work on their interpersonal and communication skills while developing these applications as a group.

Socializing the new, creative data analyst

It's very important to realize that some business users aren't yet completely comfortable with a well-rounded analytics team. For the most part, when bringing in an analyst, they're looking for confirmation of a hypothesis rather than a full analysis of the data at hand.

If that's the case in your organization, then be persistent. As your team continues to present valuable insights and creative solutions, your peers and business leaders across the company will start to seek guidance from data analysts as partners in problem-solving much more frequently and much earlier in their decision-making processes.

As companies and other institutions continue to amass data exponentially and rapid technological changes continue to affect the landscape of our businesses and lives, growing pains will inevitably follow. Exceptional employees who have creativity and empathy, in addition to mathematical skills, will help your company thrive through innovation. Hopefully, you have more than a few analysts who possess those capabilities. Identify and encourage them -- and give permission to the rest of your analytics team to think outside the box and rise to the occasion.

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