What Makes A Great Analytics Professional?

THE BIG IDEAS

  • Analytics professionals have different titles but a similar goal: use data to make better business decisions.

  • There are misconceptions about what makes a great analytics professional. The most common misconception is emphasizing a person’s technical skills as opposed to “softer” skills.

  • Big data may lead to new tools and tactics, but it doesn’t change the basic strategies used by analytics professionals.

  • Critical yet underrated traits of great analytics professionals include commitment, creativity, business savvy, presentation skills, and intuition.

  • Analytics education and certification are growing. These are important but don’t replace the need for critical interpersonal skills.

OVERVIEW

With the tidal wave of big data upon us, organizations need the right analytical talent to use this data to make important business decisions. But many hiring managers are in the dark as to the traits of a great analytics professional, and many misconceptions exist. In many instances, organizations focus too narrowly on a person’s technical skills. While strong technical skills are necessary, these skills alone are not sufficient. To be a great analytics professional, individuals need critical “soft skills” which include commitment, creativity, business savvy, presentation skills, and intuition.

CONTEXT

IIA faculty member, Bill Franks, discussed critical traits of analytics professionals and discussed how big data will (or won’t) change the analytics profession.

INSIGHTS ON GREAT ANALYTICS PROFESSIONALS

Analytics professionals have different titles but the same goal.

Organizations assign different titles to analytics professionals. They may be called “analyst” or “statistician” or “data modeler” or “data miner” or “advanced analytics consultant.” A new title that has emerged in the past few years is “data scientist.”

Organizations and analytics professionals shouldn’t get hung up on the title, as all of these titles convey that a person is an analytics professional. In each role the goal is the same: take data, manipulate it, analyze it, and gain insights to make a business decision.

There are misconceptions about what makes a great analytics professional.

Many people believe that being a great analytics professional is largely about technical skills, like programming in various languages, being a math whiz, and having statistics expertise. Specific industry expertise is also seen as essential.

But just believing that analytics success comes from technical skills is a misconception and misses the mark. Having solid technical skills is important, but technical skills alone are not adequate to be a great analytics professional.

“Having great technical skills is necessary [to be a great analytics professional], but it is not sufficient.” – Bill Franks

There are several important and underrated traits of great analytics professionals.

Bill Franks identified five critical non-technical traits of great analytics professionals. He also described how managers can look for these traits when assessing candidates.

  1. Commitment. In any profession, managers want people who are deeply committed to their work and go the extra mile. People either have this or they don’t, and managers don’t want to waste their time on people who lack commitment. What to look for when assessing candidates? Ask candidates to describe previous work experiences, describe work they’ve done, and explain how they have dealt with challenges and problems. Look for their attitude and a willingness to go the extra mile and do whatever it takes to get something done.

  2. Creativity. Most people don’t see analytics professionals as being terribly creative (and in Bill Franks’ experience, only 10–15% of people with technical skills are, in fact, creative). But the truth is that analytics pros need to be extremely creative in how they approach and solve problems. Every analytic endeavor is different and every data source seems to have issues. Therefore, creativity in adapting and solving problems is essential. Also, creative analytics professionals aren’t focused on perfection; their goal is constant improvement. 

    “Great analytics professionals are not just data scientists; they are also data artists.” – Bill Franks 

What to look for when assessing candidates? Look for candidates who think differently and who used different processes and approaches to solve problems. Also, ask candidates to describe solving challenging problems. The best candidates are those who tell a good story about their experience, as opposed to simply going through a list of steps.

  1. Business Savvy. Great analytics professionals have both strong business and technical skills. They understand what is important and have a sense for the proper level of granularity. For example, the overall direction of a trend is often more important than the precise result. Also, great analytics pros have cultural awareness. What to look for when assessing candidates? You want to hear about why a person made a certain decision. Was a decision based just on technical factors, or were cultural and business factors understood and considered?

  2. Presentation Skills. Being able to make a great presentation to non-technical audiences is critical. Great presenters minimize the details and focus on what matters most. They tell compelling stories, have great delivery, and are quick to the point. They don’t just deal with facts; they tap into emotions. What to look for when assessing candidates? Assess candidates’ presentation skills by having them give a short presentation. The topic can be simple, such as “tell me about yourself.”

  3. Intuition. This is the hardest trait to define and quantify. It is about whether people have a knack for being right the first time. It is about whether a person can understand a situation, frame a problem, and combine art and science to make the right decision. What to look for when assessing candidates? This is hard to assess. One area to ask about is a person’s background in art, music, or other creative areas, as analytics people with good intuition often have skills in these areas.

Education and certification have value, but they largely emphasize technical skills.

As analytics grows in importance, various analytics certifications and educational programs are springing up. Many of these programs are very good, and certifications serve as a useful starting point for those aiming to become analytics professionals. However, these programs tend to focus on technical skills. Just because someone has a certification or has participated in an analytics educational program does not mean they have all of the skills to become a great analyst.

Big data and the rise of unstructured data don’t change the skills needed by analytics professionals.

A fair question is whether the rise of “big data” and the increase in unstructured data will change everything for analytics professionals. The tools and tactics of analytics professionals may change, but the role and strategies of analytics professionals will remain the same: drive value from data through effective analysis.