By Thornton May
Futurist, Senior Advisor with GP, Executive Director & Dean - IT Leadership Academy

“They couldn’t hit an elephant at this dist…,” were the last words of Union Army General John B. Sedgwick at the Battle of Spotsylvania in 1864.  He died as a direct consequence of not knowing [failure to understand what technology can do to you or for you]. The outgoing CEO at Intel Paul Otellini, was recently asked by PBS interviewer Charlie Rose: “What is going to be obsolete next?” Otellini responded without hesitation: “Ignorance.”

I agree with Mr. Otellini that high performance organizations are most definitely on a trajectory of abolishing ignorance. However, the migration out of cognitive darkness is not universal or evenly distributed. What is universal is that all enterprises – in all vertical markets will face the consequences of what they don’t know.

Movie Meltdown
Tom Davenport the Big Data poster-boy for both The Wall Street Journal and The Harvard Business Review has repeatedly intimated that analytics will remove uncertainty and risk from the movie business enabling studios to accurately predict the tastes and behaviors of audiences. A.O. Scott, the truth talking entertainment wunderkind at the New York Times recently labeled 2013:

the “Year of the Flop”… After Earth, White House Down, R.I.P.D., Pacific Rim, The Wolverine, Turbo, Elysium, and of course The Lone Ranger – these are among the releases that were, if not outright disasters, then at least far from the hits they were expected to be.

I agree with professor Davenport that analytics should make making a movie someone wants to go see easier. I can only conjecture why the current movie moguls got it so wrong in 2013. I can with some degree of certainty prophesize that a new crop of tinsel town executives will be making the next round of decisions.

Marketing Re-boot
In the past über-analytics have been known to mock linear thinking practitioners of the forecasting arts. There is the obviously apocryphal tale of market researchers deciding whether to put a train station in a town currently without one. The research team sends data collectors to the town to see if there is any demand for a station.  Upon arriving in the town, the researchers see no one waiting for a train and conclude there is no demand.

The world has changed its mind about knowing. Not only is one expected to know. One is now expected and apparently legally obligated to communicate what they know in such a manner that others can take appropriate action. Seven Italian seismologists and scientists went on trial and were subsequently convicted on manslaughter charges, accused of not adequately warning residents of a central Italian region before an earthquake that killed 309 people in April of 2009. Not knowing and not sharing efficaciously what one knows has consequences.

The tea leaves seem to indicate that in the not so distant future, EVERY senior executive will be expected to be aggressively entrepreneurial with regards to creating value with data. [See my Gustin Partners Blog [26 April 2013 http://www.gustinpartners.com/insights/post/leaderships-new-mandate-create-value-with-data].

Data Stories
During the past four months I have been going door-to-door collecting “data stories.” Working with four universities:

Florida State College at Jacksonville [http://goo.gl/D6jaq]
The Ohio State University [http://goo.gl/mQPmi]
University of Kentucky 
Olin College of Engineering [http://goo.gl/dOh2l1]

I have been asking a series of "data" questions:

[1] What stories are you/your organization being told about creating value with data?
[2] What stories are you/your organization telling about creating value with data?

Two primary story types emerged. There are “new data” stories and “bad data” stories.

One of the most intriguing new data stories emerged from Vince Kellen, Ph.D., the Senior Vice Provost for Academic Planning, Analytics & Technologies at the University of Kentucky. Dr. Kellen, who also serves as the University CIO aggregates traditional measures of academic achievement, mashes these up with digital indicators, performs high speed predictive analytics and creates a daily K-Score for every student. The K-Score is an algorithmically derived prediction of the probability that that particular student will succeed in their stated educational objective [i.e., chosen degree]. The K-Score is delivered to the student’s mobile device. It’s used to give students an understanding of how well they are doing over time.

Perhaps not so surprisingly some of the best sources of “bad data” stories is the U.S. federal government. Who can forget when in June 1930, based on the dog’s-breakfast of reports available to him, President Herbert Hoover declared, “The Depression is over,” when in reality conditions were quickly worsening.

Even today the government’s sic “best” statistical data on the health of small business is culled from quarterly reports and released eight months after the fact.*

The classic “bad data” story is also government related – the 1948 Chicago Tribune headline “Dewey Defeats Truman.” Pre-election polls predicted a 5-15 point Dewey victory. The issue was – the poll was conducted by phone. In 1948 phone use/ownership was not equally distributed throughout the population. Republicans were much more likely to own phones.

Do you have any contemporary bad data stories you would like to share?

* Steve Lohr, “More Data Can Mean Less Guessing About the Economy,” The New York Times [7 September 2013].