Data Analytics Fuels Innovation With Better Ideas Faster

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“How do you know?” is one of my favorite questions and a key reason for being such a fan of data analytics.  You can never have all the answers and may not even know all the questions.  With so much information just a few keyboard clicks away, it’s no wonder that ‘analysis paralysis’ cripples meetings, discussions or business plans.

Even simple questions yield complex answers.  That’s a good reason to add Thornton May’s “The New Know: Innovation Powered By Analytics” to your summer reading.  His ability to see where IT is going – especially while other “experts” are still sifting tea leaves – is an enviable bit of long-range vision.  We are ALL information analysts now — evolving from data vegetarians to ‘knowledge carnivores’ responsible for making smarter decisions ever more quickly with better data to support those choices.

Making data easier to understand – thank you data visualization tools – and then sharing and reacting using input from others is what distinguishes collaborative work from just delivering a book report the way you did in grade school.

My mother gave me another question, the classic “When are you sure you’re sure?” because things, circumstances and reactions are subject to change.

Actions, reactions and constant recalculation based on a seemingly endless data flow are the new normal and the data is moving faster than ever before.  Naturally, analytics software helps wrangle data and separates useful insights from noise.  But May observes that any enterprise has to know what happened in the past, why and how to affect the future.  The days of trial-and-error are numbered.

Challenges for CIO-level executives require managing big-picture corporate and strategy decisions using analytics.  “I don’t know” is quickly becoming an unacceptable reply and “How do you know?” is a test we should all prepare to pass.  More or better information isn’t the only miracle ingredient here – timing, who delivers the details and how those facts are expressed all play supporting roles.

May makes a strong case for RAM (or “Relationship Asset Management”) that supports the value of analytics and its ability to build stronger, long-term, trusted relationships among “carbon-based information assets” (y’know, humans or ‘people’).