June 23-26, 2013
INFORMS Healthcare 2013
October 6–9, 2013
2013 INFORMS Annual Meeting
June 5-6, 2013
Customer Analytics Summit 2013
June 10-14, 2013
Predictive Analytics World
September 8-14, 2013
2013 ASE/IEEE International Conference on Big Data
“Data science begins with data. Nothing gets built without data. Data science continues with science. Accurate, persuasive and effective prediction requires patterns. The process of discovering that pattern is science. Any product worth building requires a reliable pattern to exist in the data.”
– Christopher Berry, co-founder and chief science officer of Authintic, in his article on recommendation engines in the current issue of Analytics.
Industry NewsSmart grid analytics ROI to exceed $121.8 billion globally by 2020
Utilities worldwide must maximize efficiency for constrained energy resources. Many are realizing the smart grid vision by using SAS Analytics and SAS Data Management to discover powerful insights buried in volumes of new data. SAS enables utilities to harness data for pinpoint control and monitoring, usage and demand forecasting, rapid diagnosis and repair, as well as predicting output from renewable sources such as solar and wind. For those capabilities, business analytics leader SAS is ranked No. 1 for smart grid analytics and data management/movement in the recently released utility industry report, “The Soft Grid 2013-2020: Big Data & Utility Analytics for the Smart Grid,” by GTM Research.Read More
Industry NewsFICO analytic cloud to enable real-time customer engagement
FICO will deliver its analytic-powered customer engagement services via the new FICO Analytic Cloud, for creating, customizing and deploying analytic-driven applications and services. Application developers, FICO clients and FICO partners will be able to take advantage of these services to rapidly create, execute and manage high-volume campaigns that engage customers in real-time with mass personalization across channels including brick-and-mortar, social and mobile.Read More
Special ArticlesStudy: Who can best manage ‘voice of the customer’?
Over the next three years, global organizations will make understanding and interacting with the customer their top priority. So says a new study from The Economist Intelligence Unit titled, “Voice of the customer: Whose job is it, anyway?” Yet only 56 percent of respondents to the survey, sponsored by SAS, believe their companies clearly understand the customer today.Read More
Smart people, stupid choices
By Gary Cokins
The final leg of horse racing’s prestigious Triple Crown race, the Belmont Stakes, was held this past Saturday. The favored horse, I’ll Have Another, was scratched due to a leg injury. For gamblers who would likely to have bet on I’ll Have Another for the Belmont, maybe this saved them some money. Why? I will get to that in a moment.
To set up my answering the “Why?” let’s first discuss decision-making. I am fascinated about how and why poor decisions are made. A writer on this topic that I follow is Michael J. Mauboussin, chief investment strategist at Legg Mason Capital Management. In an article he wrote in The Futurist (March-April, 2010) he said, “Smart people make poor decisions because the mental software that we humans inherited from our ancestors isn’t designed to cope with the complexity of modern day problems and systems. In short, smart people, like everyone else, face two major obstacles to making good decisions. The first obstacle is the brain, which evolved over millions of years to make decisions unlike what we face in modern life. The second obstacle is the growing complexity of the world in which we live.”
Others have also written about this. In the book “Thinking, Fast and Slow,” Dan Kahneman explains the two systems that drive the way we think. System 1 is fast, intuitive and emotional. System 2 is slower, more deliberative and more logical. System 1 is largely unconscious and it makes snap judgments based upon our memory of similar events and our emotions. System 2 is painfully slow and is the process by which we consciously check facts and think carefully and rationally.
Kahneman, the recipient of the Nobel Prize in Economic Sciences for his seminal work in psychology that challenged the rational model of judgment and decision-making, points out is that System 2 thinking (slow) is easily distracted and hard to engage and that System 1 thinking (fast) is wrong as often as it is right. System 1 thinking is easily swayed by our emotions. As an example, he describes an observation that people buy more cans of soup in a grocery store when there is a sign on the display that says, “Limit 12 per customer.” People miss the opportunity to analyze.
Why I’ll Have Another would probably have lost the Triple Crown
Mauboussin recently wrote a blog for the Harvard Business Review titled “The Business Lessons of the Belmont Stakes.” Here’s an edited version of his points:
“It’s easy to think about I’ll Have Another’s chances to win the Belmont using the System 1 (fast) thinking. He won the Triple Crown’s first two races in impressive fashion. And handicappers certainly like his chances (the betting odds suggest a 50 percent t0 60 percent probability that he’ll outrun the other 11 horses in the race). System 1 thinking sees mostly upside.
“System 2 thinking (slow) paints a more pessimistic picture. Consider that of the 30 horses in a position to win the Triple Crown in the last 130 years, only 11 have succeeded. That’s about a 40 percent rate. But it gets worse. Prior to 1950, eight of the nine horses that tried, triumphed. Since 1950, only three of 21 have managed the feat, and none have done so since 1978. A success rate of less that 15 percent is not encouraging.
“Perhaps I’ll Have Another is a really special horse, you may be thinking, a once-in-a-generation speedster. Well, we can quantify that with something called a Beyer Speed Figure, a measure of a horse’s performance adjusted for track conditions. All you really need to know for this purpose is that higher speed figures belong to faster horses.
“Here are the speed figures for the Kentucky Derby and Preakness combined for the last seven Triple Crown aspirants, all of which failed, along with I’ll Have Another: Silver Charm – 233, Smarty Jones – 225, Funny Cide – 223, War Emblem – 223, Real Quiet – 218, Charismatic – 215, I’ll Have Another – 210 and Big Brown – 209.
“I’ll Have Another looks pretty lead-hoofed. Big Brown, the only horse that appears worse, was eased coming down the homestretch in the Preakness, paring a few points off of his speed figure. And he went on to finish dead last in the Belmont in 2008.”
The case for analytics
OK. One example of a horse race revealing how a better decision would have been made via using analytics may not be sufficient. But can you recall any decisions made by your managers or executives that were based more on their intuition, gut feel or political positioning rather than on fact-based information and analysis? If not, you are lucky to work with such competent people. My “guess” is most of you can recall one or more decision blunders. Intelligent people but stupid choices.