How Efficient Is Your Organization?

There’s an old saying that goes, “If it ain’t broke, don’t fix it.” This is good advice for most things like cars,  teams, or even family recipes. It’s also a good rule of thumb for avoiding unnecessary risk, for we all know that whenever we change the way something works, our approach to that something, or what we want the end result of that something to be, there is an unknown element of risk intrinsic in those changes. This leads many organizations, and many decision makers within those organizations, to adopt a passive approach when it comes to examining and re-examining just how well the processes within their enterprise systems are faring with the constantly evolving IT landscape.

And while this may be the case in your organization, if your IT department doesn’t know how effective and efficient it is at capturing, storing, and retrieving its data, it doesn’t matter how well the company is doing now. It won’t be 3-5 years from now. And that old adage? In hindsight it’ll seem like oversight, which will have long since become an omen.

Conversely, there’s another saying that goes, “You miss 100% of the shots you don’t take. ” Meaning without risk, there can never be opportunity. Lack of effort can turn into costly oversight in untold amounts of expense due to redundant and ineffective systems on the back end, and lost opportunities on the front end. And while no one want to get stuck with the bill, everyone wants to be recognized for their contributions.

In today’s digital environment, with buzzwords like, “Big Data“,”Cloud”, and “The Internet of Things (IOT)”, the more data you can capture, the better. The faster you can catch, process, analyze, and act on that data will be what separates companies who swim from those that sink. And while speed is important, so is being efficient. If you, or your IT department, can’t assess (with a high degree of accuracy)  the data your organization is processing and how efficient it is at doing so, as well as the quality of that data, identify bottlenecks and redundant data duplication, and then intelligently act on what you have, then it’s time to get proactive. “Good enough” is only good enough for so long until it isn’t. And by that point, it may be too late.

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