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Why and how to measure the impact of knowledge management are questions that never go away

Mentioned by Jenny Ambrozek

Amongst other things, this page contains an excellent definition of (and explanation of) Knowldege Management

Great guidelines to implementing a enterprise wiki, including behaviours for adoption, roles, approach, etc

Last year, we undertook a massive overhaul of the technology and approach we use for knowledge management, moving from a centrally managed, linear, taxonomy- and repository-based system to one that leverages the best of Web 2.0, including social software, user participation, and key market-driven concepts like sponsored links. We see this as a shift from "knowledge management" to "knowledge sharing."

Excellent collection of articles and essays on the topic of knowledge and learning.

"EdCast is a Silicon Valley based company founded by serial entrepreneur and venture capitalist Karl Mehta. EdCast's Open Knowledge cloud platform, built on OpenEdx, allows anyone to create a platform to host their own online classes."

Use of data analytics on HR data to provide insights to improved employee retention.

"LexisNexis has surveyed 500 people working in information services in a range of roles across Europe.  In depth interviews were held with professionals in France, Germany and the Netherlands and a broader survey was sent out to information professionals across Europe.  Finally, the researchers interviewed senior academics to review the findings."

McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions. The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.

McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions. The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.

The theme for the forthcoming KIN Workshop (1st December 2015) is "Knowledge in Action". Hopefully a title that will resonate with anyone who practices knowledge management, since it reminds us that knowledge without some form of action is worthless