The Big Data History Lesson

imagesI just got done listening to a keynote from McKinsey’s Matt Ariker on big data at the SOCAP Spring Symposium.  As I was listening I was struggling to find something more interesting to write than just reporting the highlights of his talk.  Then, about two thirds of the way through the hour long session, I got it.  Rather than ruining my own punch line.  Let’s see if you can figure it out.  See if you come to the same conclusion.

Matt started out challenging the audience with some good questions to ponder.  Like big data, what is it?  Why now? Why should you care?  One answer?  According to Tech Crunch, big data will drive $232 billion in spending by 2017.  So, yeah.  We should care.  Good so far.

Matt went on to share some other stats and also some of the key questions that his clients are asking on the subject.  Then, his presentation outlined what he believes, or is observing as some of the critical pains that organizations are currently experiencing with respect to big data.  In summary, they were as follows:

  • Lack of clarity on the vision and roadmap for big data.  Everyone wants all the data they can get there hands on without having the business questions identified first.
  •  Enterprise culture and mindset are not aligned.  There is not 100% buy-in and commitment from the C-Suite
  • Ineffective use of data and tools.  Data project scope creep is deadly.  Too many think “if I can get more data, why not?”  There ends up being too much time and resources spent on acquisition and aggregation at the expense of analysis and solving business problems
  • Ineffective integration of big data projects into business processes.  Internal stakeholders are not engaged in development nor accountable for delivery
  • Too much focus on technology and not business processes
  • Misalignment of required enterprise skills to execute on these projects. The focus is largely on technical skills, or in repurposing other skills and resources.

Did you figure it out?  This is history repeating itself.  Haven’t we seen this before?  Many, many times?  ERP.  CRM.  Virtually any big, enterprise technology initiative over the past 20 years has faced these same set of challenges.  You could take this post and do a find and replace.  Insert “ERP” or “CRM” in place of “Big Data”, date it 1995 or 2001 and the issues would be still relevant.

So, like back in 2000, there are companies that are doing it right.  So, perhaps the best place to start, the first mile of your roadmap, should be to find those examples and do what they are doing. Imitation is the sincerest form of flattery…and it just might save your career if you’re the one writing the big data checks in your organization.

 

Comments

  1. Tammy Cossairt says:

    Excellent observation (and highlights). Thanks for sharing. I think this also applies to Social Media Support. We didn’t know what we needed to report on or what support was going to be needed until we all had a chance to experience it and look at it from different perspectives (Marketing, PR, Brands, Consumer Affairs, R&D, Quality, C-suite, etc.. I think the most critical point to Big Data is that different stakeholders are going to have different needs, so it’s important to look around the entire organization to understand what you’re trying to capture and analyze.
    Unfortunately, that makes it all the more complex so we have to identify where we get the most return on the investments made.

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