anyone who would listen that the courses
that we teach to MBAs are not “real” analytics courses, since these classes do not require any computer programming (outside
of the Excel environment, which is viewed
pejoratively by techies) and do not delve
deeply into the algorithmic details behind
techniques such as optimization, regression
or cluster analysis.
This is just ridiculous.
First of all, in this kind of rhetorical response, one is required by custom to provide a definition, and mine comes from
Davenport and Harris’ book, “Competing
on Analytics”: Analytics, they state, is “the
extensive use of data, statistical and quantitative analysis, explanatory and predictive
models, and fact-based management to
drive decisions and actions.” Based on this
definition, it is clear that the skills needed
for successful analytics professionals are
both broad and deep. George Roumeliotis,
an analytics leader at Intuit, believes that
a good data scientist needs to be a skilled
business consultant who also has a broad
array of technical skills for data management, analysis and modeling [1].
What this means is that preparations
for a career in analytics should be built on
a three-legged stool of computing skills (including the ability to gather, merge, clean
and manage data), analytic capabilities
(with a special emphasis on basic probability and statistics, data mining, dimensionality
A NA L Y T I C S
reduction methods and fundamentals of optimization) and business effectiveness skills
(such as leadership, problem framing, teamwork, project management, communication
skills and negotiation). Any academic program that purports to be focused on preparing students for a career in analytics must
strive to address each of these three competencies in some meaningful way, though
there are an infinite number of ways to combine each of these somewhat orthogonal
vectors.
While I was thinking about all this, I
came across a blog entry on Forbes.com
entitled “Business Analytics Beyond BI:
Rise of the MBAs” [2]. The author, John
Furrier, is a tech industry veteran and
the founder of the website SiliconAngle.
com, which pays an awful lot of attention to analytics and Big Data [3]. Though
this relatively short article covered a lot
of ground, a handful of interconnected
“money quotes” caught my eye:
1. “Every department within a company
today is itching to apply data-driven
systems to their workloads.” What
he’s saying here – and what my
business school colleagues are
slowly starting to understand – is
we’re moving toward a time when
most professionals will have to be
conversant in working with data and
interpreting models. We will need to
start expecting more of our MBAs in
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