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Data Without Context Is Bogging Your Team Down Most business leaders struggle to convert raw data into actionable insights.

By Natalie Lambert Edited by Dan Bova

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Remember when data was measured in gigabytes? Those days are gone. Now, we're trying to wrap our brains around terms like zettabyte, yottabyte, and brontobyte.

In 2015 alone, businesses generated around 7.9 zettabytes of data globally. That number is expected to more than quadruple by 2020. Within most organizations, all that data is stored across multiple systems that are overly complex and time-consuming. Just 12 percent of it ever gets used.

Employees have reached their breaking point. More than 90 percent admit to discarding data without fully reading it, and more than half say too much information causes their quality of work to suffer. When you add up all the time they waste wading through data, it amounts to a full workday each week.

Why? Because data without context is meaningless -- and it's bogging down employees, who are under increasing pressure to make sense of it all.

Related: Big Data Combined With Machine Learning Helps Businesses Make Much Smarter Decisions

Instead of driving business value, data is leaching productivity from many organizations. Nearly 60 percent of business leaders struggle to convert data into actionable insights, and 91 percent of companies are incapable of doing it quickly enough to drive decision-making. Often what they're missing is context.

To understand the relationship between data, context and insights, it helps to think of your business data as a pyramid: raw data forms the base, formatted information provides more context, and at the top, sits the insights that can help influence business decisions.

Data alone is just noise.

At the bottom of the pyramid you have all of your raw data -- reams and reams of unprocessed, computer-friendly facts residing in databases and spreadsheets. It's a potential goldmine, sure, but every mine contains far more dross than ore.

In an era when it takes just two days to generate as much data as humankind amassed from the dawn of civilization to 2003, many enterprises are in danger of suffocating under the weight of their own data and lack the employees with the advanced data analysis skills to mine it.

"Data is becoming ever more central to business decision making, and is extending to people with little or no training in data use and interpretation," says business consultant Barry Devlin.

Data today arrives in various formats that is then stored across multiple complex systems or spread out across different departments. That's why three-in-four firms say they want to be data-driven, but fewer than 30 percent are actually successful at it.

Raw data has limited business value without context since it fails to give employees the background they need to understand what it is, when it happened, where it happened, what else was going on, and so on. Throwing raw data at your employees doesn't allow them to leverage it to its full potential -- data must be processed for analysis or it will remain largely useless.

Related: 5 Lucrative Careers That Require Data Analysis Skills

Information puts data in context.

At the middle of the pyramid lies information, or data with context. Information is a collection of data points that help employees understand something about what's being measured -- in other words, it answers "who, what, where, when" questions. Businesses get information by processing, aggregating and organizing their data into more human-friendly formats such as data visualizations, dashboards or reports.

"Contextualization is crucial in transforming senseless data into real information -- information that can be used as actionable insights that enable intelligent corporate decision-making," says Wired contributor Alissa Lorentz.

Arming decision makers with information for analysis instead of raw data requires much less effort on their part to make sense of what's going on. But it still needs to be analyzed to figure out what to do with the information.

Insights need to be actionable to drive change.

At the peak of the pyramid sit the insights that deliver real business value. They answer the "So what?" question.

"They are the highly treasured output of all the work that goes into collecting, preparing and analyzing your data. Maximizing the actionable insights you receive from your analytics investments is important to your data-driven success," says data strategist Brent Dykes.

The most valuable insights are those that make you rethink something or push you in a new direction rather than simply answering a question. To generate actionable insights, businesses need to analyze their information and draw useful conclusions that influence decisions and drive change.

Related: Without Good Analysis, Big Data Is Just a Big Trash Dump

And while analyzing information will yield many insights -- not all of them will be actionable. Organizations that are able to detect relevant, personalized information and deliver it to the right person will be able to leverage their data to make better and faster decisions.

"At the end of the day, our overworked minds want to be spoon-fed insights," Lorentz says. "We want key signals and tightly packaged summaries of relevant, intriguing information that will arm us with knowledge and augment our intelligence."

And ultimately, that is the goal -- to bring employees back from the brink with tools that make them more capable and more intelligent. The result will be employees that are more productive and make better decisions.

Natalie Lambert

CMO at Instart

Natalie Lambert is the CMO at Instart. Previously, she was chief marketing officer at Sapho and was at Citrix, where she held multiple product marketing leadership positions. Prior to Citrix, Lambert spent seven years at Forrester Research, where she was the leading expert on end-user computing. 

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