A long and winding road may be an apt description of the path Jeremy Lin took — from college point guard to being cut by two professional basketball teams to sleeping on his brother’s couch to being the supernova providing a ray of hope for basketball fans.
But this path less-traveled also provides a lesson for businesses everywhere, including all of us in the insurance industry.
As one sportswriter noted, Lin almost never got his chance because “so-called experts are always looking in the same places.”
That represents a very real problem in business decision-making called confirmation bias. We tend to believe past performance does guarantee future results, so we go with what works because it has always worked.
That may no longer be enough in this competitive environment, which in itself may be one reason for the rapidly expanding use of advanced analytics by insurers. Advanced analytics help allow us to overcome the biases inherent in human judgment, and the results can be outstanding. It can help a business interpret what is happening, prepare for what will happen and help shape the future it wants to happen.
Advanced analytics involve the use of modern data mining, pattern matching, data visualization and predictive modeling tools to produce analyses and algorithms that help businesses make more effective decisions. With this foresight, analytics can help determine which events may have the most impact on the enterprise as a whole.
Predictive analytics is now coming into its own both because of the findings of cognitive science and behavioral economics and also because of a recent and rapid proliferation of huge databases, cheap computing power, and advances in data acquisition, aggregation, visualization, applied statistics and machine learning techniques.
My colleague John Lucker and I recently authored a Deloitte report called "Forward Focus: Analytics – Turning Data into Dollars." We mention that companies that put advanced analytics into place have experienced or expect to experience some or all of the following:
- Gain deeper, more relevant business insights to inform decision making;
- Bring advanced analytics techniques, such as predictive analysis and regression modeling, within reach of a wider cross-section of the organization;
- Apply analytics to effectively address industry challenges;
- Strengthen data governance at each level of the organization;
- Effectively anticipate and respond to significant business challenges as they emerge;
- Reduce costs through more defined, data-driven decision making;
- Use automation to help reduce latency;
- Use analytic capabilities and outcomes to change management efforts;
- Create a culture that thrives on fact-based decisions;
- Achieve more consistent, objective and prospective business decisions; and
- Effectively respond to and manage risks.
In real life, advanced analytics can have a positive impact in just about any area of an insurer’s operations. As an example, one P&C carrier applied advanced analytics to its claims operations. A projected reduction in loss costs of 8 percent on an annual recurring basis was just one of the positive outcomes.
That’s called playing to win.
This column originally appeared at Insurance Networking News.
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