Where Big Data Can't Replace Human Insight

Dr. Irving Wladawsky-Berger, whose views I greatly respect, has long been a cheerleader for the power that technology brings to innovation. As the former SVP of IBM, who ultimately helped steer Big Blue into the Internet era, he ought to be. However, lately, he's been expressing some reservations about the role of big data analytics in decision making. In particular, relying on automation to make decisions for us.

For low-level operational decisions, the application of technology to sift through big data and run it through algorithms makes perfect sense. Renewing a policy with updates and price adjustments or flagging an instance of potential fraud, for example, are straightforward processes that can be handled by the machines. However, high-level strategic decisions – such as expanding the number of claims adjustors for a certain region, or opening new offices – may always require human guidance.

Then, there's all those decisions that fall in between – that are slightly more than operational, but not quite strategic to the business.  The question is, how much human intervention or oversight may still be required. This is particularly the case with more complex scenarios, and the challenge is a constant state of change. Corporate financial results, mergers and acquisitions are all unpredictable events that require human intervention and learning.

As Wladawsky-Berger puts it: “With operational decisions, we have to learn to distinguish between those situations when decisions can be embedded in automated processes, and those that require human intervention. With strategic decisions we have to learn the difference between complicated but predictable contexts, and complex and intrinsically unpredictable ones.” 

The key takeaway here is that there is a huge range of operational decisions where it makes sense to automate and digitize as much as possible. However, there certain decisions that can't be left to the machines. The difference is knowing where to draw the line.

Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.

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Analytics Data and information management
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