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Marc My Words: The Coming Knowledge Tsunami

by Marc Rosenberg

October 10, 2017

Column

by Marc Rosenberg

October 10, 2017

“Establishing processes and priorities for curating and managing knowledge within and outside your organization will help you become more efficient and your knowledge products—including, but not limited to, courseware—to become more effective and valued. There are technologies and tools to help you as well, but first, you need a strategy and a lot of buy- in.”

Get ready! If you think you are overwhelmed with information right now, you ain’t seen nothing yet. I was shocked, yet also unsurprised, when I read IBM’s prediction that by 2020, knowledge will likely be doubling every 11 to 12 hours.

The knowledge explosion

How precise is this prediction? Hard to tell. But the trend is incontrovertible. Knowledge is increasing at an ever-accelerating rate. One graphic tells the story. In 1982, Buckminster Fuller introduced his “knowledge-doubling curve.” To this, IBM added its post-1982 predictions (Figure 1).


Figure 1:
Buckminster Fuller's Knowledge Doubling Curve, with post-1982 addition by IBM

If knowledge were increasing at the same rate over time, handling it all would still be challenging, but the exponential growth of knowledge makes it all much, much harder. What’s causing this knowledge explosion? Here are four top reasons:

  • The Internet of Things. Estimates run as high as 50 billion interconnected devices by 2020. Soon, the amount of information generated by connected devices will likely match, if not outstrip, the amount of information generated by people.

  • Big data. Security and privacy issues notwithstanding, our increasing sophistication and ability to gather and analyze so much information is already providing new knowledge and insights that are increasingly helpful for decision-making. Without modern data analytics, and the advanced computing technology that powers it, a treasure trove of valuable information would go undiscovered.

  • Advancement of science and invention. Scientific discoveries and new inventions proceed at a blistering pace. According to the US Patent Office, over the last 50 years, the number of annual patents increased from about 50,000 to more than 325,000. Some new scientific discoveries and modern inventions replace older ideas, but, more often, these new discoveries and inventions are additive. Charles Duell, commissioner of the US Patent Office in 1899, famously remarked, “Everything that can be invented has been invented.” Boy, was he wrong!

  • The collaborative, knowledge-sharing society. The growing interconnectedness of individuals, teams, and organizations creates great opportunities for knowledge to be discovered, distributed widely, and enhanced by groups of people who, in the past, might have worked independently and perhaps been left in the dark. Indeed, much of today’s new knowledge is developed and disseminated by collaborating teams rather than individuals.

The half-life of knowledge

The accelerating growth of knowledge is not all we have to contend with. Compounding the challenge is how long that knowledge remains accurate and useful. Alvin Toffler, futurist and author of the famous book Future Shock (1970), suggested that “the illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” We all know that much of what we learned in school, on our first job, or even on our last job is of far less value now than when we first learned it, and that we must always be vigilant to recognize what knowledge is still valuable and what needs updating.

So, an even bigger issue is how long it takes for knowledge to become outdated, incorrect, or irrelevant. One measure of this is the half-life of knowledge, the amount of time it takes for knowledge to lose half its value. For many content domains, especially in science, technology, R&D, marketing, and even finance, the half-life of knowledge is shrinking. Information that 10 years ago was useful for 12 months might only be valuable for 6 months today.

The clash of knowledge doubling and knowledge half-life

The message is clear: When knowledge is doubling exponentially, yet the useful lifespan of that knowledge is decreasing significantly, the result is a knowledge tsunami—a seemingly unstoppable wave of new information pushing you forward, combined with an extremely forceful undertow of information that used to be valuable but is now just knowledge clutter, pulling you back.

What does this mean for us?

In the learning and performance business, we are all about knowledge—finding it, packaging it, distributing it, etc. We have a huge stake in keeping up with the knowledge onslaught without drowning. Here are 10 initial suggestions:

  • Get real. You can’t deny what’s coming; you must accept the critical nature of the coming knowledge tsunami and the impact it will have (or is already having) on your organization. Identifying the challenge, with all its inherent obstacles, and agreeing to address it, is key.

  • Work with SMEs. Help them organize and filter content so that only the most accurate and valuable content gets used. Develop a plan to continuously curate your content to assure that it is still valid.

  • Set up a unified content library. Create processes and repositories for content that are consistent and easy to use across the organization. This includes training and eLearning content, i.e., courses. Establish rules for how the library should function.

  • Hire a corporate librarian (aka, “content librarian,” “knowledge architect,” “digital content specialist,” you get the idea). Get someone on staff who knows how to organize, track, and manage your content in ways that improve its access, value, and usefulness. These skills are more specialized than you think.

  • Seek continuous content feedback from users. Provide ways for users to rate the value of the content they use and suggest areas for improvement. Use these data when evaluating, updating, or replacing content.

  • Establish a content publishing strategy. Determine how content will be published, not just in courses, but in any format, especially online. This will likely involve knowledge, as well as document and content-management technologies.

  • Establish a content expiration strategy. Get agreement on how and when content should be removed for revision or archiving. Again, technology can be very helpful here.

  • Coordinate across organizations and content types. Seek to collaborate on knowledge development and management when multiple groups use the content. Develop ways to track and evaluate similar content delivered in different media (for example, similar content published in a document, a video, and a course).

  • Protect your intellectual property first. Getting your arms around all the content your organization uses can be daunting, so it’s important to prioritize. In most cases you will find that your intellectual property—your trade secrets and copyrighted information—should be your initial focus. Generic, public-domain content can come later.

  • Set up a pipeline. Develop a “forward-looking” process for identifying and vetting content so that you are not inundated with new and often questionable information from multiple and perhaps unidentified (or unverified) sources.

You can find information on moving forward with these suggestions. Just search on “knowledge management,” “content management,” and “content curation” (you can also try putting “digital” in front of these terms), and then filter by your function (training, HR, IT, sales, customer care, etc.).

Establishing processes and priorities for curating and managing knowledge within and outside your organization will help you become more efficient and your knowledge productsincluding, but not limited to, coursewareto become more effective and valued. There are technologies and tools to help you as well, but first, you need a strategy and a lot of buy-in. Doing this now can avert the coming knowledge tsunami. You’ll still have big waves of content to deal with, but you can surf them to shore rather than be carried out to sea.


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An exceptional non-puff article. Getting our arms around the magnitude of the knowledge problem seems to be everyone's challenge. Based on what I am reading, however, IBM thinks that DATA is knowledge, when data only represents about 15% of knowledge. Theory, the most important part of knowledge, represents about 85%. Theory connects the dots (data). The theory behind the Wheel, for example, is the kind of knowledge that needs to be transferred. Real knowledge, not data, endures over decades, centuries and millennia. IBM may have the insight and numbers to support their argument of the knowledge tsunami, but they are still lagging in their understanding of what knowledge is. This article validates everything we are doing. Thank you - Dennis L. Thomas, IQStrategix
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