If you know what a flea flicker play is, not only are you a
fan of American Football, but you’re probably old enough to appreciate a pickup
game with friends that’s played in the middle of the street, over a virtual
game that’s played on a computer. The flea flicker is an old trick play that’s
very risky, but extremely fun to watch, especially when it works. It was used
in some high-profile games in the 1980s, then it disappeared for a long time
until Kurt Warner and the
Arizona Cardinals brought it out against the Falcons in the 2009 NFC wild card
for a 50-yard touchdown and an early lead. Even though it’s tempting
to embrace the latest and greatest theories on leadership and management,
sometimes a leader needs to go old school to get the job done.


Managing a big data analytics team is no different. I can’t
overemphasize the importance of management when running a big data analytics
team. As the leader, you are responsible for creating a compelling vision and
helping the team through the anxiety of change. Of course, your data scientists
and other analytics are responsible for developing the sophisticated analyses
that will bring you a competitive advantage. But who is going to organize and
manage all the moving parts that will bring this strategy home?

You have a few options. You could hire a heavy-duty
consultant like me; however, depending on what you’re trying to accomplish,
that might be like bringing a Howitzer to a gun fight. You could appoint one of
your existing managers to run the team; however, they probably have a full
plate already, and it’s hard to know whether they have enough of an analytic
background to successfully communicate with the data scientists. There is a
third option. If you’re running a small company, or you’re leading a division
with a relatively small budget, you might want to dust off the playbook from a
few decades ago. If you’re looking for a relatively inexpensive way to manage
your big data analytic team, consider hiring an out-of-work Six Sigma
Black Belt

Black Looks Good on You

There are a lot of things I like about the Six Sigma Black
Belt play. First and foremost, an experienced Six Sigma Black Belt should have
both the analytic and management skills to run a team of data scientists. Six Sigma is a management
developed by Motorola in the mid-1980s that relies on
Statistical Process Control (SPC) techniques to improve process quality. The
Black Belt on a Six Sigma project is the one responsible for managing the team
(comprised mainly of Green Belts) and helping with the more sophisticated
analyses. In this regard, a Black Belt has both the analytic background and
management experience that’s required to successfully manage a big data
analytic team.

Additionally, Six Sigma Black Belts seem to be available at
a pretty reasonable rate these days. A quick search on Glassdoor puts the national
median salary for a Black Belt at around $85K. That’s not bad, considering
you’re getting a statistician and manager all wrapped up into one package. And
remember, this is no average number-cruncher. When I trained at Motorola to
become a Black Belt, I learned a lot more than just means and standard
deviations. Black Belts need to support the Green Belts when they get stuck;
this takes a pretty advanced set of statistical skills.

Finally, Black Belts have the right attitude and passion for
numbers. Nobody in their right mind would do this job if they didn’t love the
subject matter. Although it seems soft and fuzzy, passion is an important
ingredient for this role. This passion will radiate when they communicate with
the data scientists, and they will appreciate it. This dynamic will foster team
cohesion and ease the team through inevitable conflicts.

Bottom line

Although Six Sigma has lost its luster over the last few
decades, it’s something to think about when you need to manage a big data
analytics team. Black Belts – the project managers on a Six Sigma project – are
qualified, passionate, and relatively inexpensive. It may take some training to
get them up to speed on the latest analytic techniques, but they have the mind
for it, and it should come easy for them. Take some time today to look for a
good Black Belt to run your big data analytics team. The American Society for Quality (ASQ) is
a good starting place, and LinkedIn is a
good place to see if one is in your network. My guess is that there are a good
number of under-employed Black Belts waiting to plug into your team – just tell
them to leave their parachute pants and boom-box at home.