Making decisions about what to improve and how to measure the rate of improvement requires a systematic use of data. But whether we're dealing with raw data, data bases, or spreadsheets, it's important to use the right data. Doing so is not always as simple as it sounds.

Many organizations today are already awash in data, as well as anticipating tsunamis of numbers, thanks to the Industrial Internet of Things (IIoT) and, as some forecast, the Internet of Everything. As Professor Patrick Wolfe, Executive Director of the University College of London’s Big Data Institute has noted, “The rate at which we’re generating data is rapidly outpacing our ability to analyze it.”

Data’s dark side emerges when unfiltered information is used as a threat, a smoke screen, or to obscure the facts. So, it’s easy to see why some view data as a not-too-pleasant four-letter word. In some cases, it certainly can be.

Data alone can easily elicit anxiety, boredom, fear, sensory overload, and, in some cases, even excitement. Today’s business leaders must find ways to make data more user friendly to be successful in reliability and maintenance, in operations, and, ultimately, in delivering benefit to their organizations, customers, and stakeholders.

When organizations really begin using their data and making it actionable for the benefit of the business, employees, and customers, the bright side of data emerges. That's because data is the foundation for eliminating problems and improving organizational performance.

But let's back up. What is data anyway? Moreover, in plant environments, what is "the right data?" When we delve into it, we find digital data, bits and bytes, numbers and decimal fractions, text, alphanumerics, and mathematical symbols. Whatever data looks like, it is actually representing certain conditions or objects. And it is limitless.

Output from a machine sensor is also called data. It can be very useful, redundant, irrelevant, or totally useless. But it’s still data. Real-time data is online. Archived data is offline.

Keep in mind that amassing data for data’s sake can be a futile effort. It’s what we do with our data that’s most important: turning it into actions through smart, informed decisions. After all, data is the fuel that drives the reliability-improvement engine. Then it tells us how well our improvements have worked.

So, let’s find ways to make "the right data" actionable for the good of the business, employees, customers, community, and owners. In my next article for The RAM Review, I'll highlight one organization’s recent data-discovery journey and discuss seven critical success factors in making data actionable. Stay tuned.

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