The Value of a Liberal Education -- Part I

Fourth of July week, Jenny and I picked up our two ten-year-old grandsons and took them to the Lair of the Bear, sometimes called "Cal Camp" which for a Stanford grad is admittedly a stretch, but I went incognito with my four degreed, fourth generation Berkeley wife.

We attended an evening talk by the incoming Dean of Undergraduate Students, Dr. Bob Jacobsen, who conducted a quite interesting discussion with about one hundred folk.  I will elaborate in the next few posts about that evening, but here I want to post something that I found incredibly insightful from a BloombergBusinessWeek blog this week, where third paragraph from the end 'says it all'.

BloombergBusinessWeek

Companies & Industries

Management Blog

Big Data Gets the Algorithms Right but the People Wrong

By Mikkel B. Rasmussen and Christian Madsbjerg

July 16, 2013

It’s hard not to feel a sense of reverence at the scale of all the information we generate. We create so much data every day that 90 percent of the information in the world today has been created in the last two years alone, according to IBM (IBM). To handle all that data, McKinsey estimates that by 2018, U.S. businesses will need 1.5 million new data managers and analysts.

Is it any wonder that these awe-inspiring numbers have managers excited that all this information will reveal amazing insights? For businesses, the promise of such revealing data sounds like a dream come true—a direct line to their customers, gaining immediate access to their habits, desires, and needs. Clearly, mining data for consumer intelligence has paid off for shareholders in companies like Amazon (AMZN) and Netflix (NFLIX).Despite the enormous growth in the amount of data—and the success of a few companies—the reality is that deeper insights for most organizations remain elusive. Data analytics is only a tool. When we use it as a strategy, we make assumptions about people and their behavior that have no genuine connection to the real world. Simply put, Big Data in itself gets people wrong.

To begin with, Big Data delivers thin data. In the social sciences, we distinguish between two types of human behavior data. The first—thin data—is from digital traces: He wears a size 8, has blue eyes, and drinks pinot noir. The second—rich data—delivers an understanding of how people actually experience the world: He could smell the grass after the rain, he looked at her in that special way, the new running shoes made him look faster.

Big Data focuses solely on correlation, paying no attention to causality. What good is thin “information” when there is no insight into what your consumers actually think and feel? A recent Accenture (ACN) report revealed that only 20 percent of the companies it profiled had found a proven causal link between “what they measure and the outcomes they are intending to drive.”

Without critical thinking skills, Big Data will never reveal patterns that have strategic value. Businesses need to cultivate the interpretive skills of their management teams.

Where do we get such skills? Our greatest forms of interpretive thinking come from fields of study in the softer social sciences—what we refer to as the human sciences. History, literature, philosophy, anthropology, and other human sciences have spent the last 2,000 years trying to get people right. The critical thinking skills garnered in these fields of study result in the richest understanding of human behavior.

Only an understanding of behavior at the deepest level can explain seismic shifts in consumer behavior. And that can open up possibilities for innovation.

If you can uncover the why, you will have a valuable perspective that long outlasts this much-ballyhooed Big Data movement. You will be the one who got the people right.

Rasmussen and Madsbjerg are senior partners at Red Associates, a strategy and innovation consulting firm based in the human sciences.