Collaborative Thinking

Project Status: Social Networking Within The Enterprise

A lot has gone on since my last update in September. My workload has been incredible over the past few months (September/October) and will continue that way until mid-November when I wrap up the data gathering and consolidation phase of this field research effort. On top of all the travel needed to conduct 1/3 of these interview sessions in a face-to-face manner, I attended a couple of vendor events (Oracle and Cisco) and presented at our Catalyst conference last week in Prague. So my life has been more than a little hectic. But - I wanted to share some info on the project's progression. As it stands now:

• The number of organizations participating stands at 22
• The number of interview sessions look like it will end up being 33
• The number of hours spent listening to people "tell their story" regarding social networks is about 50 hours
• About 1/3 of these interviews have been face-to-face sessions
• About 15 or these sessions have been with non-IT groups (line-of-business management, HR management, corporate communications, etc)
• The remaining sessions have been with representatives from IT organizations
• Each session seems to produce 10-15 pages of hand-written notes
• The hand-written notes are interpreted in a group session to produce "affinity statements"
• The number of affinity statements seems to run around 70 per session
• The consolidation phase will have over 2000 affinity statements to filter / sort / categorize / etc.

This project has been very demanding (consuming virtually all of my attention that past few months) but the insight has been incredibly unique and much different than any other research method I've applied over the years since I've been an analyst (1996). The interview sessions will close out the end of next week (11/7) and be followed by the consolidation session in mid-November where our team will "let the data speak to us". After that event, the process becomes more normal - an analysis review session for my proposed document(s) and a deliverable due end of January (actual publishing will depend on the overall production schedule).

Sometime in late November I should be back to a more normal blogging pattern....

Platform Architectures

Interesting read...

The Architecture of Platforms: A Unified View — HBS Working Knowledge

Abstract

The central role of "platform" products and services in mediating the activities of disaggregated "clusters" or "ecosystems" of firms has been widely recognized. But platforms and the systems in which they are embedded are very diverse. In particular, platforms may exist within firms as product lines, across firms as multi-product systems, and in the form of multi-sided markets. In this paper we argue that there is a fundamental unity in the architecture of platforms. Platform architectures are modularizations of complex systems in which certain components (the platform itself) remain stable, while others (the complements) are encouraged to vary in cross section or over time. Among the most stable elements in a platform architecture are the modular interfaces that mediate between the platform and its complements. These interfaces are even more stable than the interior core of the platform, thus control over the interfaces amounts to control over the platform and its evolution. We describe three ways of representing platform architectures: network graphs, design structure matrices and layer maps. We conclude by addressing a number of fundamental strategic questions suggested by a unified view of platforms.

The Architecture of Platforms: A Unified View — HBS Working Knowledge

KM Principles

A concise and very effective set of guidelines from David Snowden:

Knowledge can only be volunteered it cannot be conscripted. You can’t make someone share their knowledge, because you can never measure if they have. You can measure information transfer or process compliance, but you can’t determine if a senior partner has truly passed on all their experience or knowledge of a case.

We only know what we know when we need to know it. Human knowledge is deeply contextual and requires stimulus for recall. Unlike computers we do not have a list-all function. Small verbal or nonverbal clues can provide those ah-ha moments when a memory or series of memories are suddenly recalled, in context to enable us to act. When we sleep on things we are engaged in a complex organic form of knowledge recall and creation; in contrast a computer would need to be rebooted.

In the context of real need few people will withhold their knowledge. A genuine request for help is not often refused unless there is literally no time or a previous history of distrust. On the other hand ask people to codify all that they know in advance of a contextual enquiry and it will be refused (in practice its impossible anyway). Linking and connecting people is more important than storing their artifacts.

Everything is fragmented. We evolved to handle unstructured fragmented fine granularity information objects, not highly structured documents. People will spend hours on the internet, or in casual conversation without any incentive or pressure. However creating and using structured documents requires considerably more effort and time. Our brains evolved to handle fragmented patterns not information.

Tolerated failure imprints learning better than success. When my young son burnt his finger on a match he learnt more about the dangers of fire than any amount of parental instruction cold provide. All human cultures have developed forms that allow stories of failure to spread without attribution of blame. Avoidance of failure has greater evolutionary advantage than imitation of success. It follows that attempting to impose best practice systems is flying in the face of over a hundred thousand years of evolution that says it is a bad thing.

The way we know things is not the way we report we know things. There is an increasing body of research data which indicates that in the practice of knowledge people use heuristics, past pattern matching and extrapolation to make decisions, coupled with complex blending of ideas and experiences that takes place in nanoseconds. Asked to describe how they made a decision after the event they will tend to provide a more structured process oriented approach which does not match reality. This has major consequences for knowledge management practice.

We always know more than we can say, and we will always say more than we can write down. This is probably the most important. The process of taking things from our heads, to our mouths (speaking it) to our hands (writing it down) involves loss of content and context. It is always less than it could have been as it is increasingly codified.

Cognitive Edge