By Kevin Meyer
I've been observing the growing love affair with "big data" with increasing skepticism, and perhaps even worry. Long-time readers know I've always been this way; in fact, one of my first posts – seven years ago – was on the mis-use or over-use of data and algorithms: The False God of the Almighty Algorithm. Later posts demonstrated how a simple white board can sometimes analyze and plan a situation – such as a factory floor – better than software. Years later I believe that more than ever.
Recently Dr. Art Langer of Columbia University has written a couple of articles that align with my concerns over an obsession with big data. In CIOs Shouldn't Let Big Data Rule Their Decision-Making he discusses how data can sometimes lead to the wrong conclusions.
Once you rely on big data, it tends to become omnipotent in the decision-making process.
We must remember that our markets are constantly changing and the
variables that dominate decision-making are extremely complex—and there
are many great decisions that are made by people that go on intuition
and “gut-feel.” And there are many CEOs that consistently state that
many of their decisions have little to do with logic.
CIOs beware—don’t forget the power of the human factors.
Data is a tool, like many others. Dr. Langer's most recent article, It's Not Just the Data, Stupid, expounds on this a bit more.
We are being overwhelmed with the use of digital data to make decisions.
You can’t read much these days without immediately seeing buzzwords
like “Big Data,” “Business Analytics,” or “Business Intelligence.”
Discussing process issues is passé; how to deal with data is the “in”
thing for business discussions, especially at board meetings.
More and more, I’m seeing other ways in which we’ve become increasingly reliant on data testing.
And once again we are losing sight of the context and perspective. Dr. Langer quotes Ron Sentz, VP of EMSI:
“The biggest limit to big data is our ability to interpret it. People
need to understand why they are using data. What is the end goal?” Sentz
said. “Data is also like an assembly of facts, which aren’t necessary
the same thing as truth. If facts are poorly interpreted, it could lead
to the wrong conclusions.”
That last sentence needs to be repeated: Data is also like an assembly of facts, which aren't necessarily the same thing as truth.
We see that in so many areas. Politics, climate change, marketing, and even when trying to schedule a complex factory floor. We get so sucked into data that we assume it is fact. We get so sucked into facts that we assume it is truth.
Mark also references two quotes that I've both enjoyed and been troubled by:
"In God we trust, all others bring data." – Dr. W. Edwards Deming
"Data is of course important in manufacturing, but I place the greatest emphasis on facts." – Taiichi Ohno
The problems I see with people and organizations caught in big data, or just plain old data, are two-fold:
The desire if not requirement that data must be used with every decision creates paralysis. In the lean world we are taught to seek perfection, but sometimes we forget that the one thing more important than perfection is simply progress. I've been part of situations where the data is never quite good enough, the analysis of data never quite complete, the conclusions from analyses never quite solid. So nothing happens.
Equally dangerous is an overconfidence on data, and subsequent analyses and conclusions. Data becomes facts becomes truth. In the two articles I referenced by Dr. Langer there are several examples where this is not the case.
Because truth requires perspective, context, reference, and understanding. Knowing when outliers are relevant or irrelevant, when the dataset is complete or incomplete, and how to make the correct, or necessary, conclusions when data is incomplete or inappropriate. Experience and intuition create relevance. The ability to create relevance is a core component of leadership.
Facts are not just data. Truth is not just facts. Don't forget the human factors.