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The Case for Data Discovery

Thoughts on the limitations of old reporting tools.
Apr | 1 | 2014

Apr | 1 | 2014


As someone who does a decent amount of networking, I’m often asked “What do you do?” or “What’s your book about?” With regard to each, I’ve become pretty adept at giving soundbites. If people want to know more, they’ll ask. If not, they won’t. The pour soul who doesn’t have a quick response to questions like those isn’t doing himself any favors.

So, what’s The Visual Organization about in a nutshell?

In five words, visualizing data promotes data discovery.

Short enough for you? Good. If I’ve done my job, then I’ve piqued your interest and you are asking yourself questions like:

  • Why does data discovery matter?
  • Do existing reporting tools like dashboards and KPIs lend themselves to data discovery?

On Dashboards and Data Discovery, and Likelihoods

With regard to the first question, the case is fairly straightforward. Data discovery mattered less in previous decades because there was, quite simply, less data and less to discover. Yes, companies could survey their customers about their experiences after the fact, not that many of us like answering cold calls or filling out forms. Grocery stores could send coupons in the mail based on prior purchases. That seems so quaint today.

Today, at least in most industrialized countries, the majority of us walk around with a Web-enabled smartphone. This is doubly true for the most attractive demographic: young people. It’s not hard to reach a customer in real time and make contextual offers. This wasn’t remotely possible even ten years ago.

It’s precisely because of the data deluge that discovery matters so much.

And it’s precisely because of this data deluge that discovery matters so much.

A decade ago, Walmart famously discovered that customers during hurricanes were more prone to buy strawberry Pop Tarts and beer. Some of the traditional applications and methods that have worked well for years will continue to bear fruit. Dashboards summarize structured enterprise information, allowing employees to see what’s taking place. They enable some degree of curiosity.

Many Eyes, Tableau, d3.js, and the other contemporary data visualization tools that I discuss in The Visual Organization up the ante. No, they don’t guarantee any customer or employee revelations but, when used correctly, they increase the chances that employees discover new things about their customers. Case in point: Netflix using the color of movie and TV show jackets as part of its matching algorithm.

Simon Says

Look, I get it. Employees (especially senior managers) don’t have all day to play with data. What’s more, in many cases, organizations have yet to deploy the tools to encourage the very exploration that would benefit them most. Still, organizations that fail to embrace data discovery and exploration are limiting themselves.


What say you?

I wrote this post as part of the IBM for Midsize Business program

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