Turning Data Into KnowledgeMay 20, 2016January 2, 2018George Linzer

In today’s digital world, sifting through the mass of bits and bytes to find and organize relevant facts, analyses, and opinions into credible and actionable knowledge can be a challenge for the best of us. In an information age that has suddenly gone from the starry night sky of the ancient Greeks to the dense star fields revealed by the Hubble telescope, it has become humanly impossible to analyze all the data to extract meaning, to turn it into actionable knowledge that we use and make easily accessible to others. As leaders and communicators, that is a big part of our job because doing so can be the difference between success and failure, progress and stagnation, and, in some cases, life and death.

We now look to “big data” for what our brains cannot do. We use computer algorithms designed to comb through millions, even billions of data points to help us understand increasingly specific characteristics about increasingly smaller groups of people, and even about a single individual. Like those Greeks who identified the stars that outlined the mythic hunter Orion, leaders today need to be able to look at the mass of data and identify the data points that give shape to their vision and show them how to navigate the tricky business of developing value, community, and return on investment.

Big data promises to extend human knowledge in many areas, but like a lot of new technologies, our expectations about big data may exceed the current reality. According to Gartner’s annual Hype Cycle reports, excitement over new technologies and the ideas they generate tend to render us blind to this notion that expectations often exceed actual performance, which is usually a great victory for the marketers of the technology but a disappointment to its early adopters. When a technology does not live up to the hype, it falls into what Gartner calls the “trough of disillusionment”, which is where Gartner placed big data in the 2014 Hype Cycle for Emerging Technologies.

Gartner has been producing its hype cycle reports for more than 20 years, an important data point in itself. Today, the reports cover a number of areas, including Digital Marketing, another area notorious for over-hyped new developments like social media, which has been falling into the trough of disillusionment for the last two years. Still, despite a history of failed expectations (does anybody remember Pathfinder.com, Time-Warner’s first attempt at conquering the web that turned into a $50 million money-sucking black hole?), a lot of smart people still rush to embrace “the latest and greatest” despite this well-known cycle of hype, some who fully understand the risk/reward opportunity while others do not. Their failures and successes become the lessons for those who follow.

Data, be it big data or small, is only useful if we use it, and treat it with respect and a deep sense of what it can and can’t tell us. It is important that we ask the questions and use the tools specific to our circumstances to harness the available information so that we can most effectively advance our objectives. When we do these things and gain the desired knowledge, it’s like we’re able to point up to three stars in the crowded night sky and say with authority, “See, there’s Orion’s belt.”