Insurers increasingly rely on big data analytics in the design of new customer plans, risk rating and fraud detection. But there always will be a need for human oversight and intervention to guide the final implementation of this analysis. Big data will never replace critical thinking, though it can certainly augment it.
Here are some myths about big data that need to be dispelled:
Myth: Big data is something new.
Reality: Big data has always been around, even back in the day when the largest disks in the world only accommodated about one megabyte apiece. Big data is a relative term in this sense. Even when defined as variety, data has actually been floating around in different formats for decades. There was mainframe data in EBCDIC format, vs. PC data in ASCII. There was binary data vs. text-based human-readable data. There have always been documents and spreadsheets. What has changed, however, is a proliferation of low-cost, often open source, tools to get at all this data.
Myth: Everyone is adopting big data, and living and breathing analytics.
Reality: It has just barely started to catch on. Reading analyst reports and listening to analysts, one can be forgiven for thinking every company of any size is working with big data. While it may seem that way, most organizations are only starting to get their feet wet when it comes to big data and big data analysis. Gartner reports that a recent survey finds only about 13 percent of organizations actually have big data solutions in place. As Gartner adds: “The biggest challenges that organizations face are to determine how to obtain value from big data, and how to decide where to start. Many organizations get stuck at the pilot stage because they don't tie the technology to business processes or concrete use cases.”
Myth: More is better.
Reality: It depends. There’s a general assumption that if you’re dealing with huge data sets, you’re more likely to get an accurate reading on the thing you’re studying. However, there’s a greater likelihood of false correlations that happen by chance as well. Plus, as Gartner explains, there’s a risk of decision-makers assuming that large data sets will be free of flaws, or will at least minimize the flaws to the point where they’re of less consequence. In reality, Gartner says, “although each individual flaw has a much smaller impact on the whole dataset than it did when there was less data, there are more flaws than before because there is more data. Therefore, the overall impact of poor-quality data on the whole dataset remains the same.” Add to that the fact that big data tends to be made up of data from outside sources, which adds more unreliability.
Myth: Big data will transform the organization into a data-driven dynamo.
Reality: If only. As with any other technology platform, paradigm or approach, it takes creative, innovative, open-minded management to move an organization into the 21st century. Technology is only a tool. If you take a creaky, moribund corporate culture and add big data without doing anything else, you will get a creaky, moribund corporate culture that has big data in it.
Myth: Big data will displace human decision making.
Reality: Big data will help automate a lot of decision-making, especially the day-to-day routine tasks. There’s a mistaken belief that decisions can be made at the touch of a button. In the process, we risk losing the sharpness of our critical thinking. There will also be pieces of data that are missing, or situations that change that the data doesn’t reflect. Big data will do a good job of reinforcing human decision making, but algorithms are just as fallible as the humans that write them.
Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.
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