Big Data

Personality clashes stalling your data science team? Try the Myers-Briggs Type Indicator

What personality types are your data scientists? If you don't know, you aren't getting the highest performance and productivity out of the team. Learn how personality assessment tools can help.
 

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In my 20 years of working with data scientists and other information management professionals, I've observed that most have a particular personality type. Your chances of having the same personality type is very low. In fact, if you're leading your data science team based on the way you'd like to be lead, you only have a seven percent chance of getting it right.

In order to get the highest performance and productivity from your data science team, it's important to understand each person's personality type.

Myers-Briggs Type Indicator personality assessment tool

There are many personality assessment tools available, though I would start with the Myers-Briggs Type Indicator (MBTI) because it seems to be the most popular. If you're unfamiliar with MBTI, I suggest cultivating a base understanding of what it is and what it can do for you. One of my all-time favorite books on the subject as it applies to leaders is Introduction to Type and Leadership by my colleague Sharon Lebovitz Richmond. It's concise and loaded with great information.

I'm going to give general advice on getting the most from your data science team. I'm not a certified MBTI practitioner, and I don't play one on TV, but I would be remiss as a management consultant if I didn't have a working knowledge of how to apply MBTI in leadership situations, and the same applies to you.

It's very important that you consult with an MBTI expert before making any serious decisions with your team, as it's the only way to get accurate MBTI assessments. Plus, there are a lot of very wrong ways to use MBTI that can get you into serious trouble. That said, to get the most from your data science team, you must adjust for the personalities in your group.

The typical data scientist personality

Not all data scientists have the same personality, but I've noticed some patterns that probably won't surprise you. Your team should comprise of more than just the whiz-kids (leadership, management, business experts, etc.), but for the sake of this discussion, I'm focusing on them.

I find that most data scientists are INTJs (Introversion, Intuition, Thinking, Judging), or what Sharon calls Visionary Strategists. Only a small fraction of leaders are INTJs. So, if you're trying to motivate and inspire your data scientists based on your personality--and you're not an INTJ--you're not making the best moves. Most of us need to flex to the INTJ to best communicate and inspire superior performance (including yours truly--I'm an INFJ, which is Introversion, Intuition, Feeling, Judging).

Leading with personality

It should come as no surprise that most data scientists are introverted. This means their source of energy is with their internal thoughts and experiences. Your phone charges when it's docked--your data scientist re-energizes by being alone. Data scientists can be very social and outgoing, but it's a drain. You should provide an environment where they can be alone, such as a private office. Forcing them into an open-office configuration or a full-time pair-programming arrangement is not a good idea.

Data scientists also activate information through intuition. The inputs to their decision-making process are inferential and aggregated, unlike their counterparts who use purely sensory data. This area of their personality reflects onto their competence in predictive analytics--reflecting on the past to extrapolate the present into the future. This can be a challenge when you're trying to run an adaptable organization. Help them focus and project on the things within the organization that are more stable. For instance, your markets may shift, though the signals that indicate a market shift may not. You can have them focus on the signals, while you handle the implications of your market's new direction.

Data scientists make decisions through a logical, rational, thinking process. They do care what other people think, yet everything must pass the logic test before it makes sense. They will rarely make an illogical decision just because someone else will be affected, so your charisma and magnetic personality will only carry you so far. Make sure you have a rational explanation for all the decisions you make.

A data scientist controls his or her destiny by analyzing the available data and judging the best course of action. This is in contrast to the perceiving personality types who have a tendency to collect information and adapt to their environment. Most data scientists come up with hypotheses and often have strong opinions around their conclusions. They will argue with you--sometimes violently. This is not a bad thing, but you must be exceptional at managing conflict. If they're not challenging your direction, something's wrong, and it's important that you get at the root of why they're not voicing their opinion.

Summary

You cannot lead your team effectively until you understand the individual personalities that make up your team. MBTI is a great tool to help you in this area, but you must heed two cautions before using it: You should never use MBTI to anticipate behavior, and you should always consult an MBTI expert.

I've shared what I've observed to be a common personality type for a data scientist, but you won't know for sure until you have each team member properly assessed. Start by locating an MBTI expert, and do a proper set of assessments on you and your team. It will make life a lot easier for everyone involved.

If you've assessed the personality types of your data science team members, how did you alter leadership approach after you had that information? If you haven't assessed their personality types, is it because you haven't had the resources or interest in doing so? Share your experiences and feedback in the discussion.

 

About

John Weathington is President and CEO of Excellent Management Systems, Inc., a management consultancy that helps executives turn chaotic information into profitable wisdom.

1 comments
dbmarketing
dbmarketing

So we should use pseudoscience to persuade our scientists to work together? I'm not trying to be a jerk, but seriously, the M-B? Here is some educational reading on it, and if you have access to JSTOR I'd strongly recommend looking at some peer reviewed studies that back these up:


http://www.psychologytoday.com/blog/office-diaries/201007/the-problem-personality-tests

http://www.afr.com/p/national/work_space/the_problem_with_personality_tests_gL9bJFukbVFuYV3v7gbYgO

http://abcnews.go.com/Business/personality-tests-workplace-bogus/story?id=17349051


And finally, one last note, but everything old is new once again:


http://www.hreonline.com/HRE/view/story.jhtml?id=39419841


The above link makes some very good points regarding personality testing and how it fell out of vogue in the 1960s when, as with the SAT/ACT and college performance, it was shown that there was no significant link between job performance and personality trait.


So can we all agree to move away from the testing band wagon? Especially when you're trying to do it to data scientists who should know better and will probably end up mocking you behind your back?

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