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The enterprise of the future: Yesterday, today, and tomorrow

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With this issue, KMWorld magazine marks the beginning of its 30th year. Launched in January 1992 as Imaging World magazine, a journal dedicated to the document imaging/management and workflow systems industry, the name was changed to KMWorld five years later as a reflection of the growing importance of knowledge management as a discipline.

Back in 1992, information-age organizations were already struggling with the exploding volume, velocity, and variety brought about by the arrival of what was called the information superhighway. And, they needed to get ready to compete in the global knowledge economy. This meant transforming their knowledge-hoarding organizations into knowledge-sharing enterprises.

Let’s take a look at some of the more impactful changes that have taken place since, the envisioned changes that didn’t happen and why, and the challenges we’ll likely be facing in the years and decades ahead.

Looking back

When we think about how far we’ve advanced over the past 3 decades, it’s rather impressive. But the advances have been mostly incremental, riding atop a wave fueled by Moore’s law, with semiconductor performance doubling and prices halving roughly every 2 years. Software applications have greatly benefited from this. On a conceptual level, technologies such as AI, machine learning, and natural language processing have changed little over time. The exponential performance gains in their application have come courtesy of massive increases in processing speed, memory capacity, and bandwidth.

As for KM, you’d think that after roughly 30 years, it would be a given. Far from it. In the past 3 decades, KM has appeared, disappeared, and reappeared multiple times on Gartner’s Hype Cycle. Shortly after the start of the new millennium, KM reached the vaunted Plateau of Productivity, while its current incarnation as a key part of CX (customer experience) is nearing the bottom of the Trough of Disillusionment.

Another barrier is our current obsession with data. With access to zettabytes of structured and unstructured data, algorithmically crunched and analyzed with virtually unlimited cloud-based processing power, many have come to believe that we now have greater certainty than ever about what we’re doing, and that we can significantly reduce risk. Even the U.S. Federal Reserve Bank publicly declares its monetary decisions are “data-driven.” But far too many data-driven decisions are narrowly based, even cherry-picked, to fit a preplanned agenda.

Remember when people used to say, “We’re drowning in information and starved for knowledge”? That’s still very much the case, but for different reasons. Today, much of the knowledge we need is readily available. The problem is having the courage and fortitude to properly act on it.

One barrier to action is that through all the ups and downs, cultural resistance to knowledge sharing stubbornly refuses to give in. What will it take to dislodge and overcome the resistance? Well, there’s nothing like a crisis to force people to change. And the year 2020 brought the perfect storm.

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