We live in an era in which it's not terribly difficult for companies to ape many of their competitors' products and services, especially digital ones. For relatively small amounts of money (compared to years past), an organization can more or less mimic another's raison d'être and even specific functionality. As for design, it can be copied – and often is. (Case in point: Facebook has "borrowed" Twitter features like hashtags, trending topics and verified accounts.)
Against that backdrop, the arrival of big data is concurrently positive and negative, as I write in The Visual Organization. These days, two things are increasingly separating organizations from their competition:
- The number/quality of their customers/users
- The data that the startup or app collects
Now, make no mistake: These aren't the only things that drive success of any one entity. I'm not that delusional. People, products, patents, regulatory environments, access to capital, leadership, reputation and a cauldron of other issues can make or break an organization. As Amazon, Apple, Facebook, Google, Netflix and Twitter have shown, though, data is increasingly a source of sustainable competitive advantage.
Let's say that you really understand the data that your company is generating (#2). What's more, you augment that data with third-party data and metadata. Put those two together (as Netflix does), and you may very well be able to increase your user/customer base (#1).
Starting up
That's all fine and dandy, but how do you start when faced with vast amounts of largely unstructured data? Tackling big data is much more involved than implementing ERP, CRM and BI applications. And those weren't easy.
At a minimum, understand that new dataviz tools may be required to help employees understand large swaths of largely unstructured and semistructured data. Only through new tools can employees identify key trends, make better business decisions and possibly predict what will happen next.
Simon says: it's a journey, not a sprint
New tools? Uh-oh. Maybe you're a bit frightened based on past IT projects. After all, organizations often drop the ball on these types of things. Many don't start new deployments until they have "all of the data." Plenty of them only visualize "good" data, when in fact a dataviz can often and easily manifest outliers and problematic issues.
Others rely exclusively on Microsoft Excel and other stalwarts. Excel is great, but it's hardly the only game in town. More important, it simply can't handle petabytes of unstructured data.
Recognize that big data is a journey, not a sprint. The days of "set it and forget" are over.
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What say you?
