Could analytics be killing innovation?

DisruptiveView

As featured in DisruptiveViews

Business is becoming ever more dependent on analytics in making key business decisions. Big data holds a wealth of information that, if extracted and processed effectively, gives management a tool to plan future paths based on historic information.

There is no question that this is of great value, but does it diminish the role of good management in making decisions based on gut feel and market moods not always reflected in stored data?

It is, after all, much easier to justify a company’s direction by quoting “real” information. That, of course, ignores the fact that analytics can yield almost any desired result if massaged accordingly, and that its value as a tool must be tempered with management skills gleaned from academia, work experience and external thought leadership.

So: is the abundance of data and the ease of processing it killing off innovation?

No, according to analytics vendor Sopheon, which promotes itself with statements like: “As the amount of data inside organizations grows and more data becomes available from external sources, big data and analytics will become a key basis for your innovation and competitive success. “But it doesn’t explain how.

Jean-Paul Isson – writing on Analytics and Innovations for the American Management Association – stated that “data intelligence from multiple sources, intelligence integration, or data convergence is the lifeblood of innovation in analytics. Cutting-edge companies are leveraging ways to understand, explain, and predict customer behavior by combining site analytics with social media analytics, mobile analytics, predictive models powered by text analytics, customer buying behavior, information captured via CRM systems, information gathered via conversations with the service team, email exchanges, customers’ site reviews, site behavior, and social media behavior.”

Again, great rhetoric but no details on how analytics actually helps innovation. I’m still finding it hard to see the relationship. Could we be repeating the recent era of MBA fever when everyone rushed to get a degree in business management and a whole generation of managers became qualified on the same set of use cases and business success stories that have little to do with the requirements of digital business today?

Is management today becoming too reliant on data, and old data at that, to determine the future needs of customers (i.e. innovate)?

These are not environments that appeal to innovative staff, many of whom walk away to try their luck bringing their ideas to fruition on their own. Many are helped by crowdfunding, others are investing in themselves. But very few, it seems, are funded by the companies that had them under their wings and failed to see their potential.

Could analytics be used to uncover these assets? Probably not, but good management could, because the human element would come into play. And it’s that human element that we could lose as we become more dependent on data to make decisions.

Perhaps the secret lies in predictive analytics, which Wikipedia describes as encompassing “a variety of statistical techniques from modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future, or otherwise unknown, events.”

Now we’re talking! But is innovation just about the future, coming up with new things that we will need or want? Or is it also about improving things we already have? Either way, analytics may play a role, but humans still come up with the most innovative ideas and this should be nurtured just as much as big data.

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