The October 2011 issue of the Harvard Business Review included an interesting article, “Learning to Live with Complexity.” Its authors, Gokce Sargut and Rita Gunther McGrath, describe the difference between something being merely complicated and genuinely complex.
Let’s think in terms of systems. Complicated systems have many moving parts, like a wristwatch with gears, but they operate in patterned ways. In contrast, complex systems have patterned ways, but the interactions, or variables are continually changing. In the former, one can usually predict outcomes; the math may be easy, with linear relationships. In the latter, certain factors cause changes in the constant interactions with numerous variables and nonlinear relationships. For example, an air traffic controller must adjust for delays caused by weather and aircraft maintenance.
To make better decisions, the modeling and analytics need to be adaptive and flexible. They need to have self-learning capabilities to get increasingly smarter. They need powerful high-performance analytics that can process big data.
Being Proactive, not Reactive
With today’s uncertain recovery from global recession, the stakes have never been higher for managers to make better decisions with analyzable information. Companies that successfully use their information will out-think, outsmart and out-execute their competitors. Superior enterprises are building their strategies around information-driven insights that generate results from the power of analytics of all flavors, such as segmentation, regression analysis and predictive analytics. They are proactive, not reactive.
Executives are human and can make mistakes, but when companies fail, these are not simply minor misjudgments. In many cases, their errors are enormous miscalculations that can be explained by problems in leadership. Regardless of how decentralized some businesses might claim to be in their decision-making, corporations can be rapidly brought to the brink of failure by executives whose personal qualities create risks rather than mitigate them. These flaws can be honorable, as with the sad decline of Kodak due to weak strategy, or less than honorable, as was the case with rogue CEOs such as Dennis Kozlowski of Tyco, Ken Lay of Enron, John Rigas of Adelphia and Steve Hilbert of Conseco.
Mental Shortcuts Work Until Problems get Complex
Franck Schuurmans, a guest lecturer at the Wharton Business School at the University of Pennsylvania, has captivated audiences with his explanation of why people make irrational business decisions. A simple exercise he uses in his lectures is to provide a list of 10 questions, such as “In what year was Mozart born?” You’re given a list of possible ranges, and you’re supposed to select a range of that you feel 90 percent confident that the correct answer falls within. For example, Mozart was born in 1756, so you could narrowly select 1730 to 1770 or you could more broadly select 1600 to 1900. The range is your choice. Surprisingly, the vast majority only choose correctly for less than five of the 10 questions. Why did his subjects choose so poorly? Because most choose too narrowly. The lesson is that people have an innate desire to be correct, despite no penalty for being wrong.
Schuurmans’ research goes deeply into the nuances of cognitive psychology and the theories of bounded rationality, which earned Herbert Simon the Nobel Prize in economics in 1978. A key observation is that humans have limited rationality between our ears; our brains were designed to hunt prey.
Typically, people defer to mental shortcuts from learning by discovery. The academic term is heuristics. For example, a man decides to take an umbrella if the sky has dark clouds, but not if it is sunny. The clouds are probably enough of a clue for this minor decision, but is he 100 percent sure it will rain?
Do you know with precise accuracy or just think you know with latent doubt? This is an example of the limits of decision-making. Schuurmans observed that mental shortcuts, gut feel, intuition and so on typically work – until problems get complex.
When problems do get complex, then a new set of issues arises. Systematic thinking is required. What often trips people up is that they start collecting information to lead to the conclusion before they begin framing a problem. There is often a bias or preconception. One seeks data that will validate one’s bias. The adverse effect is that, as Schuurmans describes it, “We prepare ourselves for X and Y happens.” By framing a problem, one widens the options to formulate hypotheses.
BI and Drill-Down Queries are Insufficient
How is this relevant to business analytics, the emerging field of interest to improve organizational performance? A misconception of IT specialists is that they equate applying business intelligence technologies with drill-down query and reporting techniques, such as data mining.
In my November 2011 Information-Management.com article, I wrote that, in practice, experienced analysts don’t use BI as if they were searching for a diamond in a coal mine. They don’t flog the data until it confesses with the truth. Instead, they first speculate that two or more things are related or that some underlying behavior is driving a pattern seen in various data. They apply business analytics more for confirmation, rather than for random exploration. This requires analysts to have easy and flexible access to data, the ability to manipulate the data and the software to support their investigative process.
Delegate More Decisions to Employees
Without initial problem framing and a confirmatory approach, mistakes are inevitable. Sadly, as Schuurmans observed, many do not learn from their mistakes, repeating them with more gusto.
To sustain long-term success, companies need leaders with vision and inspiration to answer: “Where do we want to go?” Then, by communicating their strategy to managers and employees, they can empower their workforce with analytical tools to correctly answer: “How will we get there?” This goes to the heart of analytics.
Executives and managers at the top of an organization’s hierarchy need to become more comfortable with delegating decisions to their employees. Employees make hundreds, possibly thousands, of decisions every day, such as pricing, customer targeting, risk mitigation and freight distribution routing. Incrementally better small decisions add up, and may contribute to the financial bottom line more than the few big decisions made by executives. Today’s problems and opportunities are increasingly more complex, rather than being just complicated. Applying analytics will be essential to sustain a competitive edge.
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