David Snowden on KM & Social Media

Knowledge Management: Social Media in the “Third S-Curve”


by Madanmohan Rao      Oct 29, ‘09

Knowledge Management consultant and author


Email: madan @techsparks.com



As usual, David Snowden (founder, Cognitive Edge) delivered an informative and witty keynote address on KM, this time at the fourth annual KM India summit (www.KMindia.in) in Chennai. I have heard him several times, at KM Asia in Singapore and KM World in Santa Clara, and each time he adds something new to his superb blend of complexity theory, organisational innovation and narratives. David’s first trip to India was decades ago as an aspiring Jesuit priest (!!!), and his conference debut in India with a KM hat is certainly a new avatar.


Drawing on Charles Handy’s work (author of “The Empty Raincoat”), David began by sketching three successive business paradigms over the past hundred years, each marked by new disruptive technologies in the backdrop of an economic recession. Each paradigm follows an “S curve” of adoption and then fading relevance.





Success factors


Scientific Management (Taylor, Drucker)


Mass production

Control of function

Systems Thinking (Kaplan, Senge, Nonaka)


Mass customisation

Control of information

Social Computing, Pervasive Technology Environments


Mass collaboration

Ability to situate in a network; distributed cognition

Table 1: Successive Business Paradigms (source: adapted from David’s PPT @ KM India 2009)


KM needed today’s social computing tools ten years ago to fulfil its true promise then, Snowden observed, demonstrating an array of tools, all available for free. The era of social computing allows people to compete as networks rather than organisations.


“The technology for the original vision of KM is now largely available for free or at a low cost,” Snowden said.


Snowden identified 7 principles for KM in a world of ubiquitous social computing tools:

1. Knowledge can only be volunteered not conscripted. Social computing works because everyone is a volunteer. Knowledge sharing takes place as a natural social activity in such environments.

2. We only know what we know when we need to know it. Human thinking is centred on pattern-based intelligence and not information processors. The practice of sleeping on a decision is a good example of letting subconscious memories and past experiences working on the decision and letting patterns emerge.

3. In the context of real need, few people will refuse to share their knowledge.

4. Tolerated failure imprints learning better than success. The way people learn from practice how to publish information on Wikipedia and Twitter are good examples here. Apprentices learn from masters via their own mistakes as well.

5. The way we know is not the way we say we know.

6. We always know more than we can say and say more than we can write. Narrative is a very important form of KM.

7. Everything is fragmented; humans seek messy coherence. There will therefore be limits to the semantic Web. Context is everything, even in the case of explicit content.


The rise of Twitter is a good example of knowledge sharing via fragmented micro-narrative, which lends itself to real-time capture and deployment. Implications of this for KM are that managers should rely less on “readymade recipes” but more on “cooking principles;” they should focus on knowledge flows rather than just knowledge stocks, and on social networks and not just CoPs; and user behaviours of gifting are more important than employee financial rewards on social networks.


A terrific Q&A session followed. I asked David what the “fourth S-curve” may be after the “third S-curve.” He said the answer could be in further distributed cognition and decision making. Examples could include the Grameen Bank’s model of lending networks possibly extending to learning networks.


In the long run, social computing tools have helped humans go back to their tribal forms of association and knowledge-sharing around campfires. The challenges for us in this day and age are that our educational system trains us in too much specialisation, when what we need is more thinking as generalists and an understanding of a broad range of disciplines including computer science, philosophy, communication and anthropology. These cannot be fulfilled by MBAs, whom David condemned as a product of the 1980s doomed to die out (always trust David to come up with rousing controversial statements!!).


In terms of competitive advantage, India can be in a good position in the knowledge era thanks to its wide cultural diversity, and also since Hinduism has never lost touch with non-causal systems and can offer frameworks for dealing with chaos.





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