Managing big data, Part 2: Human questions and considerations

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In my previous post, I listed some of the technical questions and considerations that big data introduces. Truth be told, though, making sense out of big data requires much more than deploying new technologies, adding new services, tweaking database partitioning and ETL jobs, and upping compute power.482187289

No, finding the signal in the noise that is big data is as much of a human issue. As I learned early on in my career, technical chops by themselves only get you so far. The smartest person in the room may know the right answer, but can s/he effectively communicate it?

In this post, I'll address some of the human considerations broached by big data.

Better communication skills

In 2010, I attended a conference in Manhattan on "social business." One of the speakers included a statistician from a Fortune 50 company whose topic fascinated me: User behavior on the web.

Lamentably, the über-smart statistician didn't know his audience. From the get-go, he confused attendees with inscrutable charts and plenty of talk about p values and other statistical esoterica. I looked around the room to find everyone looking down at their devices, not up at him.

That's never a good sign.

Never before has it been more important to be aware of your audience, a point that I make in Message Not Received: Why Business Communication Is Broken and How to Fix It.

A new mind-set

Look at the companies that are "doing" big data better than anyone. They include Amazon, Netflix, Facebook and Google. At these organizations, you are unlikely to hear the following tired refrain, "That's the job of the IT department." (Insert Office Space reference here.)

For more on the Netflix data credo, click here.

Increased employee numeracy

As I wrote on this site a while back, everyday employees will need to become more numerate. Make no mistake: traditional database administrators (dBAs) are still vital in many organizations, but they surely can't do it all. They will have to learn new applications and programming languages to effectively deal with petabytes of unstructured data. New employees, partners and vendors will invariably play key parts.

Other key attributes

I'd be remiss if I didn't briefly mention a few other essential qualities for success with big data:

  • Willingness to learn and experiment with new tools. Sometimes applications outlive their usefulness. A tool that gets the job done in 2015 might not work as well as one introduced in 2020. Always be on the lookout for better ways to do things. Set it and forget it at your own peril.
  • The willingness to take a stand. You are never going to possess "all" of the data to make a decision. Understand that perfect information remains a myth.
  • Comfort with being uncomfortable. With more data than ever, senior execs increasingly run the risk of being proven wrong. This isn't 1880 or even 1980. We are living in an era of increasingly rapid change.

Simon Says: People still matter. Big time.

Without commensurate "soft and fuzzy" skills, even organizations with the most data and technology will fail to maximize their opportunities.

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About Author

Phil Simon

Author, Speaker, and Professor

Phil Simon is a keynote speaker and recognized technology expert. He is the award-winning author of eight management books, most recently Analytics: The Agile Way. His ninth will be Slack For Dummies (April, 2020, Wiley) He consults organizations on matters related to strategy, data, analytics, and technology. His contributions have appeared in The Harvard Business Review, CNN, Wired, The New York Times, and many other sites. He teaches information systems and analytics at Arizona State University's W. P. Carey School of Business (Department of Information Systems). He also runs 5marbles, an Agile software-development shop.

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