4. Surveys say there simply aren’t enough people with
the unusual blend of software skills and statistical
savvy to go around. Arguably even more important,
high-impact data scientists bring collaborative
temperaments and business acumen to data-driven
initiatives. Unfortunately, there’s no shortage of
individuals with just enough statistical and software
knowledge to be data-dangerous. For many
organizations, a mediocre data scientist may be worse
than none at all.
5. WHAT TO DO?
Stop hunting for that data science unicorn
and/or silver bullet.
Chances are slim that your organization would even
be able take full advantage of their talent. But the
opportunities for data-science-enabled efficiencies
and innovation are too important to defer or deny.
6. SMARTEST ALTERNATIVE
What organizations should start doing is
seed-fund and empower small cross-
functional data-oriented teams explicitly
charged with delivering tangible and
measurable data-driven benefits in relatively
short periods of time.
8. The emphasis is on building greater data capability than
better digital infrastructures. The goal is to make all of
the organization — not just the geeks and quants —
more conversant in how to align probability, statistics,
technology and business value creation. No black boxes
or centers of analytic excellence here; they want data
science to be a cultural value, not just a functional
expertise.
10. So are these teams ultimately a short-term fix rather
than a more sustainable solution to the data scientist
shortage? Yes. But in the same way that the rise of
mobile devices has changed how organizations
communicate and collaborate internally and externally,
the concurrent rise in Big Data and analytic
opportunities means that smart organizations would be
foolish to outsource this away from the very people
who need to be more data-driven.
11. Sometimes the data show
that “buying time” the right
way can be a terrific
investment.
14. People don’t need to become data scientists, but they do
need to understand and appreciate key principles and
practices of data science.
Capable team > Elusive Data Scientist.
