Analytics Tools May Help Replace Scarce Resources
If you believe the news reports, anyone in your organization could be doing analytics. But is the time right yet for just anyone to try their hand at it? There are questions over whether the tools are mature enough, whether business users are using the right tools or coming to the right conclusions. And there is always a question over whether or not data is secure given that processes may include cloud-based analytics.
Ideally, we would have more data scientists in our organizations to counter these potential issues, but the number of data scientists that are currently available or even the number that are soon to be graduating, won’t be enough to fully meet the demand. Recently, we have seen headlines about insurers partnering with universities to fill this pipeline, much like we have seen with actuarial and IT talent. Until these relationships pay off, however, insurers need tools that will help non-technical business users to make sense of big data. They also need controls in place to make certain that data’s reliability and security are not compromised. An article from Washington Exec last week shows us how this issue crosses all industries.
“The market — industry — must provide the mythical data scientists, but this workforce does not exist at scale yet,” said Dr. Gary Schiffman, Georgetown professor and governmental data security analyst, “And the market must provide tools that allow non-math-y and non-coding domain experts to draw correct conclusions from ‘big data.”
I think it is right for us to expect that good BI will have increased penetration and that this is going to help to compensate (in some small degree) for the scarcity of the “math-y” resources we need. The logical next-step then is data protection, understanding how data is being used, and then formalizing the process by which business users can regularly, and routinely, gain analytic insights. Giving business users the right tools, the right training, and pre-certified data sources has the potential to transform many well-meaning analytic diamonds in the rough into some of your organization’s next generation gems.
In our consulting practice we see insurers grappling with this every day by adding the tools that are needed to analyze and visualize their data in meaningful ways. Normally this comes at the end of a process where the enterprise begins to understand who needs data, which data they need and how it will be used. We’ll discuss more in the coming weeks regarding how insurers can begin taking advantage of BI tools and transform their ability to capitalize on big data.