4. They are unusual blend of
software skills and statistical
savvy to go around.
data scientists bring
collaborative temperaments
and business acumen
to data-driven
initiatives.
5. According to Michael Schrage,
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.
6. What do we do now?
“Give up. Stop hunting .”
“You Don’t Need A Data Science Unicorn,
You Need A Data Science Team”
7. You want to cultivate internal
capability, not just hire it.
8. What Organizations have
started 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.
12. collective team learns from
each other and sends a
message to the rest of the
organization that even baby
steps in analytics could yield
large strides in outcome.
Limited ambition can do a
better job attracting credibility
and support than BHAGs.
13. Relevant Insights for a manager
#1 INSiGHT
“Start Small, Go Big”
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.
14. Relevant Insights for a manager
#2 INSiGHT
“People Are People”
Data scientists either produce analytics for
machines or humans, but generally not both. The
two types of analysis require different skills.
