In the previous post, the first five types of KM strategies were discussed. This post covers the remaining five types.
Even if captured knowledge has been analyzed and codified, it will not be of value unless potential users are aware of its availability. Thus, its existence must be disseminated, both widely to inform all potential users and narrowly to inform targeted consumers.
A variety of communications vehicles should be used to distribute knowledge. Newsletters, web sites, and email messages can be used to spread awareness. Blogs, wikis, podcasts, and videos can be visited online or subscribed to. Content can be dispersed through syndication and collected through aggregation, including the ability to personalize web sites to display only relevant information.
Examples of knowledge dissemination strategies include providing customized notifications of new or changed content, weekly newsletters featuring new submissions to repositories, and a KM corner on the organization’s home intranet page listing the top 10 most-reused documents for the current month. Monthly podcasts featuring interviews with thought leaders, weekly conference calls featuring conversations about lessons learned, and videos sharing proven practices are also good ways of increasing awareness.
Demand is the other side of supply. It involves searching for people and content, retrieving information, asking questions, and submitting queries.
Demand-driven knowledge management takes advantage of networks, supply, analysis and codification. It is stimulated by dissemination and enabled by making it easy to find resources.
Examples of demand strategies are expertise locators, ask the expert processes, and search engines. User assistance and knowledge help desks can help connect supply and demand by answering questions, providing support, and searching for content. Specific tools and techniques which enable demand for knowledge include e-learning systems, threaded discussions, and Appreciative Inquiry.
Focusing more on just-in-time knowledge management and less on collection, content can be provided at the time of need through networks such as communities. By only supplying information which is actually required, unnecessary knowledge capture can be avoided and time and resources used more efficiently.
Peter Drucker is widely quoted as saying “The knowledge that we consider knowledge proves itself in action. What we now mean by knowledge is information in action, information focused on results.” The payoff for motivating, networking, supplying, analyzing, codifying, disseminating, and demanding knowledge is results through action.
Peter Senge is quoted as defining knowledge as “the ability to make effective decisions, and take effective action.”
Making better decisions is supported by networks and analysis. Implementing changes to replicate proven practices and improving processes based on previous experience are also enabled by analysis.
Incorporating knowledge into routine workflow and utilizing processes and procedures can be done as a result of codification. Disseminating what has been learned allows it to be applied to new situations. Responding to requests, answering questions, and using and reusing content are actions which result from demand.
Responding, deciding, and reusing are good examples of acting as part of a knowledge management initiative. Another form of action is the next strategy – invent.
A special kind of action is invention. Creating new products and services, coming up with new ideas to try out, and developing innovative methods and processes can help transform an organization, industry, or a nation.
Generating new sources of customer demand, stimulating personal and organizational growth, and rethinking the existing rules of the road can help an organization develop, thrive, and endure. Failure to do so may lead to stagnation, decay, or death.
Knowledge management can help trigger the imagination by providing a continually replenished source of ideas and experiences. People help bring out the best ideas in each other through their interaction as a part of networks. Publishing white papers stimulates creative thinking. Analyzing collected knowledge reveals patterns and opportunities for new developments.
Cognitive computing can simulate human thought processes and mimic the way the human brain works, addressing complex situations that are characterized by ambiguity and uncertainty. Artificial intelligence can perform operations analogous to learning and decision making in humans. Intelligent personal assistants can recognize voice commands and queries, respond with information, or take desired actions quickly, efficiently, and effectively.
Using these approaches can enhance the capabilities of humans by augmenting their powers of observation, analysis, decision making, processing, and responding to other people and to routine or challenging situations. Cognitive computing tools such as IBM Watson, artificial intelligence tools such as expert systems, and intelligent personal assistants such as those offered by Amazon, Apple, Google, and Microsoft can be used to extend the ability of humans to understand, decide, act, learn, and avoid problems.
The next post will provide examples of how to apply all ten types of KM strategies.
KM thought leader Melissie Rumizen was an accomplished and highly respected leader in the field of knowledge management and knowledge strategy.
Book from KM expert Stan Garfield with 100 infographics on knowledge management proven practices with links to supporting external content
KM thought leader Katrina Pugh has a successful record in artificial intelligence, agile development, and organizational transformation
KM thought leader Wendi Pohs provided systems design and software tools, helping large companies integrate semantic technologies into their systems.