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Little Data

December 20, 2012 by David Kay

You can’t escape hearing about Big Data right now—it has replaced “cloud” as the current hot buzzword in tech.  The idea is pretty simple: it’s easy to gather huge volumes of data from Internet clickstreams, scientific instruments, roadway sensors, and all the other collectors of digital information in the world…but it’s not always easy to process it.  Big Data techniques are designed to rapidly sort through these piles of bits and bytes in order to gain meaningful, actionable business insights…such as the fact that you like your friends’ cat videos on Facebook.

So, the technical definition of Big Data is all about how to do correlation and trend-spotting in near real time on petabytes and exabytes of data.  But in the popular imagination, I think it has come to mean something a bit broader.  Big data evokes a sort of automated Big Brother—a bank of servers tirelessly poring through tweets, searches, mobile location data, and YouTube comments.  Except, unlike Big Brother, most of this surveillance is designed to figure out how to send you the perfect marketing pitch, all without human intervention.

It’s exciting technology, but it’s a little bit creepy.  In our business, I think we need a complementary approach.  We need to get really personal with our data.  Let’s re-discover Little Data.

Most service and support leaders’ questions are hard to answer just by crunching the numbers.

  • What one product change would help customers the most?
  • How much is knowledge shortening resolution times?
  • How effectively is self-service helping customers?
  • What’s the loyalty impact of a particular support initiative?
  • How well are we collaborating?
  • How many contacts are we deflecting, and are they the right ones?
  • What’s the ROI of knowledge?

These Little Data questions require judgment as well as correlation coefficients; nuance as well as regression analysis.  They require estimations, surveys, interviews, and other less-than-perfectly-precise and human-intensive inputs.

But, as measurement guru Dean Spitzer says, it’s better to measure the important things imprecisely, than irrelevant things with perfect accuracy.

I’m excited to have just wrapped up one of these projects, focused on voice of the customer.  We have lots of Excel sheets, and StatPlus got a workout.  But the interesting part was thinking about the right questions to ask.  To me, the most satisfying results were the stories that emerged from the numbers…and the discussions and innovation triggered by those stories.

Something we hear all the time is, “we have all this data, but we haven’t had a chance to really dig in to it.”  Maybe it’s time for a Little Data project.

ps – registration is now open for our next KCS Foundations Workshop.  Anyone up for February in California?

Filed Under: KM, Measures, self-service, Voice of the Customer

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