By Greg Peters
Nearly 60 years ago, a leading scientist in the fields of cognitive psychology and artificial intelligence, Herbert Simon, coined the term “satisficing” to describe the dilemma people face when making decisions. Even though our own rationality drives us to make the optimal choice, the process usually requires more time, information and effort than we have available. As a result, we make decisions that are good enough to satisfy and suffice, and leave it at that.
“Good enough is where you find average,” according to Mike Babcock, who is the only hockey coach to lead teams to victories in the Stanley Cup, World Championship and the Olympics. In his book, Leave No Doubt, Babcock talks about the fear of being average as his motivation to never settle for just good enough – a credo he used to inspire the Canadian Olympic team leading up to the 2010 Olympics, where they took the gold medal.
We applaud, and even expect this philosophy in sports, yet in business, we often settle for good enough. Managers have long satisficed, relying on experience and intuition to make decisions, because there are so many to be made and not enough time. With the rise of big data, and the widespread use of algorithms to gain insights from it, making an optimal choice is now possible.
Companies no longer have to settle for OK decisions. In fact, companies that fail to embrace big data to make decisions will be less competitive in their markets. That failure is less likely to result from technology challenges; rather, it’s more likely to be caused by managers’ resistance to trust math and science to guide their decisions.
Recent research, based on detailed survey data from 179 large, publicly-traded companies, from an economist at the Sloan School of Management at MIT, Erik Bryjolfsson, found the following: “Firms that adopt data-driven decision-making have output and productivity that is five to six percent higher than what would be expected given their other investments and information technology usage. Furthermore, the relationship between data-driven decision-making and performance also appears in other performance measures such as asset utilization, return on equity and market value.”
Decisions made using big data may significantly widen that performance gap. In the Hype Cycle for Cloud Computing 2012, Gartner predicts, “Big data will deliver transformational benefits to enterprises within two to five years, and by 2015 will enable enterprises adopting this technology to outperform competitors by 20 percent in every available financial metric.”
Given these benefits, why do firms continue to make subjective decisions, particularly while the first-mover advantage still exists?
It is not the technology, cost, or analytical skill gaps that prevent organizations from embracing big data. It is primarily because key executives still believe that experience and judgment are enough to make a good decision.
As a result, too many companies fail to empower and provide front-line employees with the information to make optimal sales and marketing decisions. They have limited time, experience, and information as compared to the untapped insight embedded in corporate databases, and generally crave direction and guidance – not just access to data and reports. The end result is thousands of sub-optimal decisions made each quarter, often leading to just average financial performance.
This is not a “man versus machine” story, but rather “man plus machine,” where the combined result is a better outcome. Managers should provide input into algorithms then deliver guidance directly to employees, rather than a dictated best guess. Information needs to be pushed to where it can do the most good — to employees in the field. Arming them with this level of guidance will result in decisions that are optimized, consistent, and aligned with company strategy.
In the same way we now struggle to imagine how business worked before computers and the Internet were pervasive, years from now we will look back at subjective decision-making in disbelief. Smart companies recognize this and are moving fast to exploit this new approach for competitive advantage.
Greg Peters, is President and CEO of Austin-Based Zilliant, providing data-driven guidance to help B2B companies make their numbers. Prior to Zilliant, Greg served as president and CEO of Vignette, a leading content management company and one of the most successful IPOs of 1999.
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