I recently attended a presentation by Dr. Franck Schuurmans, a guest lecturer at the Wharton Business School and a consultant for Decision Strategies International. He captivated the audience with explanations as to why decision makers make irrational business decisions.
A simple exercise he used with the audience to demonstrate one of his points was providing a list of ten questions such as identifying in what year was Mozart born? The assignment was to select the extremes such that within the range you believed you had a 90% confidence the correct answer fell in between. Mozart was born in 1756, so for example you could have narrowly selected 1730 and 1770 or 1600 and 1900. The range was your choice. Surprisingly the vast majority chose correctly for five or less of the ten questions. Why so bad? Most chose too narrow bounds. The lesson is that people have an innate desire to be correct despite no penalty for being wrong.
Dr. Schuurmans did a nice job not lecturing deeply into the nuances of cognitive psychology and the theories of bounded rationality that brought the Nobel Prize in Economics in 1978 to Dr. Herbert Simon for his research. Dr. Schuurmans explained …
I recently attended a presentation by Dr. Franck Schuurmans, a guest lecturer at the Wharton Business School and a consultant for Decision Strategies International. He captivated the audience with explanations as to why decision makers make irrational business decisions.
A simple exercise he used with the audience to demonstrate one of his points was providing a list of ten questions such as identifying in what year was Mozart born? The assignment was to select the extremes such that within the range you believed you had a 90% confidence the correct answer fell in between. Mozart was born in 1756, so for example you could have narrowly selected 1730 and 1770 or 1600 and 1900. The range was your choice. Surprisingly the vast majority chose correctly for five or less of the ten questions. Why so bad? Most chose too narrow bounds. The lesson is that people have an innate desire to be correct despite no penalty for being wrong.
Dr. Schuurmans did a nice job not lecturing deeply into the nuances of cognitive psychology and the theories of bounded rationality that brought the Nobel Prize in Economics in 1978 to Dr. Herbert Simon for his research. Dr. Schuurmans explained irrational decision making in layman’s terms.
A takeaway I got was that humans have limited rationality between our ears – our brains were designed to hunt prey. Typically what people do is defer to mental shortcuts from learning by discovery. The academic term is heuristics. So for example, one decides to take an umbrella if the sky has dark clouds but not if it is sunny. Is one 100% sure? Probably good enough for the umbrella decision. But do you know or just think you know? This example gives a glimpse of limits of decision making. Mental shortcuts, gut feel, intuition and so on typically work except when problems get complex.
When problems get complex, then a new set of issues arise. Systematic thinking is required. What often trips people is they do not start by framing a problem before they begin collecting information that will lead to their conclusions. There is often a bias or preconception. One seeks data that will validate one’s bias. The adverse effect as Dr. Schuurmans described it is “We prepare ourselves for X and Y happens.” By framing a problem, one widens the options to formulate hypothesis.
How is this relevant for applying business analytics, the emerging field of interest to improve organizational performance? A common misconception by information technology specialists is equating business intelligence (BI) technologies such as query and reporting techniques with advanced analytics like data mining and forecasting. Experienced analysts don’t use BI to search for the proverbial diamond in a coal mine. Instead, they apply business analytics – including BI but also data management and advanced analytics – to uncover relationships, correlations and patterns in the various data. Business analytics requires easy and flexible access to the data, the ability to manipulate it, and software that can analyze past data but also predict future outcomes. By applying business analytics, organizations arrive at better and faster business decisions. But IT tends to exhibit gatekeeper behavior proclaiming, “We own the data and if you want a report, we’ll write it for you.”
Without initial problem framing and a confirmatory approach, mistakes are inevitable. Sadly, as Dr. Schuurmans observed, many often do not learn from their mistakes but repeat them with more gusto.
In his book, Predictably Irrational, author Dan Ariely observes “We are all far less rational in our decision making than standard economic theory assumes. Our irrational behaviors are neither random nor senseless – they are systematic and predictable. So wouldn’t economics make a lot more sense if it were based on how people actually behave? That simple idea is the basis of behavioral economics.”
I expand on Ariely’s quote by asking wouldn’t getting the ROI out of our treasure trove of mostly unused raw and transactional data make a lot more sense if we properly applied business analytics?
