Above and Beyond KM A discussion of knowledge management that goes above and beyond technology.

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This publication contains my personal views and not necessarily those of my clients. Since I am a lawyer, I do need to tell you that this publication is not intended as legal advice or as an advertisement for legal services.
  • John Seely Brown: The Entrepreneurial Learner#KMWorld

    John Seely Brown, Chief of Confusion, Co-Chair of Deloitte’s Center for the Edge.

    [These are my notes from the KMWorld 2012 Conference. Since I'm publishing them as soon as possible after the end of a session, they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I've made any editorial comments, I've shown those in brackets.]


    • Context. Infrastructure over the last three centuries has followed a predictable S-curve: long periods of stability (approximately 50 years) followed by a period of intense instability, and then more stability. Now, we are looking at an indefinite period of change in which we should experience exponential growth in computation. This is our BIG Shift.
    • What’s happening in our BIG Shift?. In the old world, we could expect our knowledge to last over a work life of 50-60 years. Now, our knowledge has a half-life of five years. With knowledge changing this quickly, we can’t focus on knowledge stocks anymore; we have to focus on knowledge flows. With respect to infrastructure, we no longer have those 50-year S-curves. Instead, we are experiences a rapid set of S-curves of approximately one year each.
    • The Skadden Example. Peter Lesser, CTO of Skadden, noticed that incoming associates were solving training problems by posting queries/status updates via Twitter. He realized that the firm could learn from this example, so he set up a reverse mentoring program to understand better how to harness this behavior.
    • Learning Exemplar: World of WarCraft. This online game has two kinds of learning spaces. The first is the in-game learning: a kind of “collective indwelling” with constant experimentation and tinkering. This is a great way to share tacit knowledge. This game is too completed to play without specific data and personalized dashboards. Therefore, individual players set up personal dashboards that track the data of most interest to that individual, with a view to improving personal performance. The players also participate in after action peer-brased reviews that results in exponential learning. (This has been documented.) “Out-of-game” learning is more about creating a knowledge ecology that helps players gain and create knowledge faster. This learning happens daily within “guilds” that analyze the performance of the prior day and then provide recommendations for the next day’s game. They use videos, wikis, blogs, databases and various forums. This is a great way to filter information and create feedback loops rapidly.
    • Creating a Pull Platform: SAP. SAP created a software developer network to capture the insights of users. This provided an accelerated means of improving the Netweaver product.They created a new “pull platform” in which participants connect, innovate and reflect. The more individuals participate (posing smart questions, providing useful answers), the better they are known and, in some cases, the more individuals receive new career opportunities. Because of the strenght of the this community, the average time it takes to receive an answer to a question is 17 minutes. That answer usually can be validated by the next day.
    • Social Bookmarking: Mitre Corporation. Rather than forcing explicit knowledge (e.g., creating profiles, filling out expertise, etc.), they decided to try to capture information on the fly. The method they used was Social Bookmarking: as individuals found useful materials online and bookmarked it with a brief explanation, their system was able to builds links between people interested in similar topics. The next step could be to build gamification tools into this system to increase participation.
    • Looking closely at how work REALLY gets done: Xerox. The $200 million problem was rethinking how Xerox’s technology representatives work. When they examined how the work really happened, they discovered that trouble-shooting wasn’t simply about pulling out the heavy technical manual and looking up the answer. Rather, a tech rep would call up another tech rep who would come over to help. Together they would “create a dance around the machine” in which they conducted specific tests, analyzed the results and told stories to each regarding the last time they saw results like this. In other words, they worked by creating stories as they recovered prior experience, added the new data and that combination became the new story. This pattern of working led to the “Eureka” system, which gathered these stories and then arranged for them to be reviewed and validated. As more of a person’s stories were validated, that person (and the reviewer who validated the story) enhance their reputation within the community of tech reps. This social credibility proved valuable.
    • Intimate with Scale: Google Hangouts. This tool allows you to create a discussion group of up to 10 participants who converse via a video call. However, they have provided “legitimate peripheral participation” by allowing an unlimited number of people in your circles to listen into the hangout without being one of the 10 initial participants. (It’s like overhearning a great conversation.)
    • Supporting Distributed Work. Here’s the big challenge: much of the real work happens in the emergent, so how do we really support distributed work? We should create immediate ad hoc social groups that can solve problems in process immediately. As these exception conditions emerge, are resolved and documented, you have a remarkable knowledge process resulting in a rich knowledge base.
    • Takeaways. (1) in a world of constantly changing contexts, best practices don’t travel very well. (2) As contexts change, we need to move past stories (which explain a specific event) to narratives (which create a framework for moving us to action, perhaps in a new direction). (3) there are important shifts occurring: knowing what has moved to knowing what and where; making things moves to making things and contexts (e.g., remix); (4) in sense-making, we move from playing to reframing; in media, we move from storytelling to transmedia (e.g., how a story jumps from one medium to another — this has huge implications for corporate branding). (5) Identity Shift is the biggest shift of all. We’re moving from a sense of “I am what I wear/own/control” to “I am what I create, share and others build on.” How do I put something into play so others build on it? When you figure this out, you understand agency and impact.
    • Creation Spaces. Look below the radar screen. Interesting things are happening in cities within new “maker spaces” and “hacker spaces.” They are building new things that could change our economy.


    Published on October 17, 2012 · Filed under: Conference; Tagged as: ,
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