DC VELOCITY Group Editorial Director
Mitch Mac Donald spoke recently with Dr.
Bradley on the value of predictive analytics for
digital supply chains. The following is an edited
version of their conversation. To watch the full
interview, go to https://www.dcvelocity.com/
dcvtv/news/5850503877001/.
QYou did a presentation at MHI’s fall con- ference titled “Predictive Analytics for
Non-Analysts.” Tell us a little about that.
A For the non-analyst, the hard work of ana- lytics is really the strategic approach. So
I talked a bit about three key components of
that—data streams, questions, and strategy—
and why organizations need to focus on them.
When we look at the emergence of technology in the supply chain, we have more data coming at us than we know what to do with—and
it’s coming at us from a multitude of different
angles. Organizations need to have a cohesive
process for how they’re going to manage that
flow of data. We already know the issue with
silos. Now, you lay on top of that more data
sources from other silos. That is why there is
a need to focus on the data streams first: How
are you going to manage the capturing, the
processing, and the structuring of that data?
Then, the next thing is the questions.
Oftentimes, what I find when I work with
executives is that they ask one question, but
really, they want an answer to another question. The reason why questions are paramount
is that questions drive the mechanism to get to
the solution. In other words, analytics is not
about which algorithm I’m going to use or which solution I’m going to apply. It is about what question am I
trying to answer. The question drives the approach or
the technique.
Then, last is strategy. You’d be amazed that approximately 80 percent of the organizations we work with
don’t have an analytics strategy. So, we are shooting for
something, and yet we have no guided direction with
respect to that.
Q So, if you’re a non-analyst, you should focus not on the algorithms and the codes and the databases
and where things link and how things get shared, but
rather on the questions you have and how analytics can
deliver answers to make better business decisions?
A Absolutely, because people are enamored with pre- dictive analytics, but predictive analytics essentially
tells you what is likely to happen. We don’t know that
it will. It is just what we believe based on the historical
data we have. But the better question is, what steps am
I going to take in the event that it does happen or in the
event that it doesn’t happen? So, we are trying to get
from just predictive analytics to prescriptive analytics,
where we have a prescribed approach to a particular
incident or outcome.
QPredictive analytics is a very hot topic right now. Why is that?
A I think it is the nomenclature itself. When we hear the term “predictive,” we think of it as this perfect
picture. We think we know exactly what’s going to take
place, or that we’ll have what I like to describe as a
heads-up view in an automobile: You know the direction you’re going, you know how fast you’re going, and
you know when your next turn is. People think that is
predictive analytics, but it is not. Predictive analytics is
the rearview mirror. The best vision you have of what’s
in front of you is really what’s behind you. Everything
else is hazy. So, you’re going to use your historical data
to try to anticipate what is likely to take place.
QThe industry is full of very bright people who are passionate about what they do and who are not
resistant to change. They see this coming and recognize
it is important, but they don’t know where to begin.
What is step one for these folks?
AFor me, step one is strategy. The reason I say this is that the data streams and the questions are going
to be contingent upon your strategic approach and the
strategic imperative you place around analytics in the
organization. We say we want to be data-driven organizations, but that can mean 10 different things. So,
the question is, what does it mean and what should it
mean for my organization? Once we put a stake in the
ground, this is our analytics strategy.
That is not to be confused with a big-data strategy.
You already know you live in a world with voluminous data. You don’t need a strategy around that. That
should be embedded in your IT strategy, which should
