Raw Data By Itself Is Useless To Your Company

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Raw Data By Itself Is Useless To Your Company

Raw data is of little value to a business until it is turned into information. Information isn’t a whole lot more valuable — until it used to enable knowledge. That’s when you have something to really work with, to differentiate from competitors, to operate smartly. A simple enough concept, but not one put into play by many companies. Here’s why.

From a business standpoint, think of data as raw material sitting in individual databases. Think of information as some form of understanding of what the raw material represents. And then think of knowledge as what’s actionable once the information is filtered, combined and woven together in a meaningful way. Emphasis on meaningful and actionable.

Data used to be difficult and time-consuming to collect, expensive to store and complicated to analyze. Now, the opposite is true. Data is abundant and easily collected, inexpensive to store and much easier to analyze. Great news, except that businesses are drowning in all the data. They’re drowning in the data because they never really learned how to swim.

The reality is that businesses don’t want a ton of data. They want the information that leads to the knowledge which can be used to make better decisions. But everything has to start with the data (the raw material), which better be clean and correct. If it’s not, the information you want turned into knowledge will not be an accurate reflection of the data. Bad data wastes time and effort, adds cost, gives false impressions, results in inaccurate forecasts, etc.

So how do we get to the point of at least being able to tread water and not drown in data? There are three components.

  • First, clean and better organize your most operationally important data. There is no getting around this if your critical data is a disorganized mess. It’s a necessary investment if you want turn piles of data from a liability into an asset.
  • Second, find new ways of working. Realizing the substantial value inherent in your data isn’t likely with inefficient processes. Adding data to old, broken processes and hoping this improves things won’t work. Frustration will be the end result, plus regret for investing in new technology that doesn’t return what you expected.
  • Third, find someone internally or externally who’s really adept at analyzing information and translating it into answers to business questions. Most data contains interesting stories, but companies generally lack good storytellers. Interpreting how your information is useful for the people making important decisions is often an overlooked role. Don’t assume people are sufficiently skilled to handle this step themselves; most are not.

Computers are not (yet) artificial brains. Even with all the horsepower they now contain, they still are very limited when it comes to taking data and turning it into knowledge that drives good decision-making. And because knowledge can’t currently be stored in anything but a human brain, only people can make reliable judgments or develop reliable knowledge from information.

Is investing in technology for collecting, storing and analyzing data a wise move? Yes, but only if the right mix of people and skill-sets are used to turn the raw data into something much more valuable.

By |January 23rd, 2018|Insights & Impact|

About the Author:

For nearly three decades, Joe McGrattan has been helping companies leverage data technologies to conduct business more effectively in our digital economy. Joe’s blog contributions focus on business-oriented advice to companies on how to take advantage of their data to run smarter, faster, leaner companies.