Defibrillating Knowledge Management

This is not the original title for this blog, the change is a bow towards the good folks on the ACT-KM listserv, some of whom are checking for a pulse on the teenaged wrist of Knowledge Management.

The social graph used to be analog, fleeting and personal – which extended to our metaphors: “Whom do you call?” “When you spin your office chair around, who are you looking to?” “Whom do you trust to not steer you wrong?” Unless phone calls were recorded and transcribed, the conversations were fleeting. Water cooler chatter died away as people returned to their desks. Each participant taking with them their own knowledge of the interaction; based on their past experience, their cognitive biases evidenced through learning filters, and the random noise that affects the metaphorical learning that helps us navigate our day. While the sociology of trust relationships has not changed, and human cognition is still very much an analog function; the digitization of our interactions has increased dramatically over the past decade. The implications are profound for organizations and should be reflected and exploited in any competent KM strategy.

When these interactions are instead in a discussion forum, a wiki, or as a result of blogged comments, or using an instant messenger tool, or email, etc., the exchange of information is – at least theoretically – available for trend analysis; for addition to the corpus of organizational understanding; or for use by people who were not party to the original conversation, perhaps separated by time and distance.

With this new digitization of organizational conversations, the opportunity for an organization to understand, leverage, and enhance the social graphs represented by its members interactions is very real. The organization considered mature at KM, therefore, is one that learns from the conversations among its members – scaling the water cooler experience and aware of trends across the knowledge exchanges that fill our day.

Amazon.com has a business model that focuses on the ‘interest graph,’ the potential connections among people who share interests but who are not connected otherwise. By analyzing buying habits and interests over time, Amazon developed a “recommendation engine” the suggest purchases it has observed trending among “people like you.”

This concept of an interest graph can be brought into the enterprise as well – extending to expertise across organizational members who are unaware of people working on projects and problems similar to themselves. The idea that an organizational knowledge system can provide a level of work recommendation follows naturally – connecting otherwise disconnected workers based on common interests and need.

We often speak of KM in terms of generations – although few agree on the precise phases that have been experienced since the mid-1990s. One construct looks back and considers the phases as 1) document-centric, 2) person-centric, and 3) network-centric.

We used to base interventions (1st generation) under the KM umbrella believing that ‘organizational knowledge’ was contained primarily in our work artifacts; documents, spreadsheets, project plans, etc. Efforts to improve an organization’s KM were thus focused on repositories, with entreaties to “share your knowledge.” The tools were crude at first, evolved to become web-based and now are extended to ubiquitous mobile platforms. Early on, however, it became clear that the “provide and pray” approach failed to address the sociological challenges – there is a long human journey for most organizations to advance to becoming a truly collaborative enterprise. Core aspects of the organization, from process to management incentives and beyond, must adjust to realize this transformative vision. Technology alone never addresses the individual behaviors that have to adapt such that the organizational change can occur.

This led to a 2nd generation of KM, which recognized that not only did technology not change behaviors, but that knowledge is actually biologically determined. The knowledge structures in the mind of the receiver will never match those held in the mind of the sender. Expertise is personal, exchanged only as a result of a volunteer effort by the person, and transferred over trusted social networks. This led to a move away from (but not an abandonment of) document-centric architectures. We remain habituated to linearly constructed formal documents, standard procedures and checklists that guide our work and transfer best principles from previous workers and generations. This is the intellectual capital for most organizations, and resonates with the learning styles that begin with primary and secondary education. (This too, is subject to flux, as revolutions in education will reverberate in the workplace – challenging this presumption for some countries – beginning around the year 2025.) Nevertheless, the focus for 2nd generation KM was to connect these experts to knowledge seekers, and facilitate the exchange of trusted information across space and time within an (often distributed) enterprise.

The 3rd generation of KM, building on the first two, began to recognize that these networks represent the core organizational value. The valuable intellectual capital – that which truly distinguishes a firm in the market – exists in conversations between members of the organization. The 2nd generation is true enough for individual knowledge – we learn from others who volunteer their experiences, knowledge is not ‘transferred’ or ‘shared,’ it is learned. However, for organizational knowledge, the focus is on these conversations. This leads to the need to balance document repositories (databases and electronic document systems); ecosystems where expertise can be located quickly and questions are answered with accuracy and timeliness (email); and (3rd generation) advancing the health of the social graphs within organizational subcultures (social network analysis, emerging social business tools).

This generational path – representing almost two decades of the KM discipline – has been influenced by research in cognitive science and neuroscience, advances in information technologies, and the broad consumerization of social tools – often referred to as social media. Globally, most people are not active on these consumer tools; however in certain countries and for certain cohorts, the expectation that one will ‘live out loud’ is beginning to transform the workplace.

“Working out loud” refers to the fact that workers are embracing the behaviors that drive them in their leisure time to Facebook, LinkedIn, Twitter, Foursquare, etc., within the workplace itself. This transformation of the workforce, combined with enterprise-class social tools, represents the operationalization for this 3rd generation of KM. While references to this 3rd generation date back a decade, it is only in the past few years that people have altered their social behaviors to embraced the digitization of their social networks. The realization of this 3rd generation means that the informal networks and the interactions there that have always been critical to decision-making can now be leveraged, analyzed, extended, and advanced for dramatic increases in organizational value.

—–

* I am in revolt against expensive royalty-free photos, and will just use pictures from my own collection until I calm down.

Original post