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PHIL SIMON

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Big Data: Preventing Big Failures

Thoughts on avoiding the pitfalls of traditional IT projects.
Apr | 14 | 2015

 

Apr | 14 | 2015
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IT projects break bad all the time. At their worst, they even cause companies to go belly up and high-profile lawsuits.

Google “IT project failures” and you can spend weeks reading horror stories such as the ones referenced above. In fact, failure is the rule, not the exception. In 2012, the Standish Group reported that only 39 percent of software projects were considered “successful.”

Yawn.

Statistics like these are old hat. Those numbers may even be a tad understated, much akin to hacking data. Chief execs don’t like to admit that their pet projects failed.

There’s no magic formula, listicle, or five-point list.

Historically, most IT projects have involved back-office systems and what I call Small Data. Against this backdrop, it’s only fair to ask how organizations can avert similarly dismal results with the big stuff.

There’s no magic formula, listicle, or five-point list. Still, organizations would do well to keep the following advice in mind:

  • Think about which model works best for your organization. No, you don’t have to predict where you’ll be in five years, but Big Data doesn’t just happen willy-nilly. Some degree of thought about who does what, when, and how behooves everyone. General goals are important to discuss. A bunch of isolated “projects” is unlikely to yield the best outcomes.
  • Recognize that executive permission is not required. At the same time, though, everyone need not be on board. There will always be people who resist the import of data, unstructured or otherwise. Fortunately, we live in an era of cloud computing, open-source technologies, “platforms” like Kaggle. Collectively, these mean that certain pockets, departments, divisions, and groups in an organization can proceed without the imprimatur of everyone else.
  • Understand that culture is critical. Forget about how many petabytes of unstructured a newfangled application can process. Of course that matters, but ask yourself this: Why does Netflix understand its customers so well? There are many reasons, but the entire organization realizes the import of data. Everyone, from entry-level employees to the top brass. I know because I spoke there last year. Execs don’t just spew vacuous platitudes about Big Data. They actually walk the walk.
  • Treat partners as truly valuable partners, not whipping boys. Far too often, organizations treat their vendors as hired help, not the valuable, free-thinking resources that they can be. Over the years, I’ve had several clients tell me in a matter-of-fact manner, “We don’t pay you to think.” I’ve never understood why a client would hire an alleged expert and not at least listen to that person’s honest advice.

Simon Says

Big Data is only increasing in importance, a point that I emphasize in Too Big to Ignore. No, there’s no magic on/off switch. Understanding the pitfalls, however, will decrease the chances of past IT project failures.


This post comes from IBM for MSPs. The opinions expressed here are my own.

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