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How to make knowledge management more rigorous

Although the knowledge management field is maturing, a great deal of hand waving and hype surrounds it. False promises and over-expectations are being created; many vendors are calling their products “knowledge management” tools even though they might simply be database, information management or document management tools; a dearth of rigorous methodologies for doing knowledge management exists.

In Liebowitz et al’s work, conducted in the Laboratory for Knowledge Management at the University of Maryland-Baltimore County (UMBC), several interesting ideas emerged in analyzing the knowledge management methodologies that have developed to date.

First, most of the knowledge management methodologies are not comprehensive in terms of covering end-to-end concepts. Many of the methodologies focus only on the knowledge cycle process vs. covering other critical elements of knowledge management like integrating KM into the strategic goals of the organization.

Second, most of the knowledge management methodologies do not include double-loop learning (i.e., learning how to learn/learning and unlearning). That iterative feedback within and between knowledge management phases needs to be interwoven into a knowledge management methodology to have a learning organization.

Third, most of the organizations that either had or were developing a knowledge management system believed it was designed to achieve both process results and organizational outcomes.

Fourth, the knowledge management methodology should not concentrate simply on the technology infrastructure, but should focus more on the organizational and cultural aspects. The working mantra in the KM field is that people and culture are probably 80% to 90% of knowledge management, with technology being the other 10% to 20%. Thus, proper attention to the organizational and cultural issues is critical for the success of a knowledge management initiative. Last, knowledge management is a continual process of incremental improvement, not a one-time shot in the arm.

To develop a more rigorous approach to knowledge management, Liebowitz et al. developed a SMART (Strategize-Model-Act-Revise-Transfer) methodology for knowledge management. This turned into the SMARTVision knowledge management methodology for RWD Technologies (rwd.com), an international IT consulting firm. SMARTVision has the following components and phases:

RWD’s basic tenets to be interwoven in each phase:

  • Project management;

  • Technical reviews;

  • Change management;

  • Process training;

  • Quality assurance;


  • Perform strategic planning;

  • Determine key knowledge requirements (i.e., core competencies);

  • Set knowledge management priorities;

  • Perform business needs analysis;

  • Identify business problem(s);

  • Establish metrics for success;

  • Conduct cultural assessment and establish a motivate-and-reward structure to encourage knowledge sharing;

Outputs from the strategize phase:

  • Business needs analysis document;

  • Cultural assessment and incentives document;


  • Perform conceptual modeling;

  • Conduct a knowledge audit;

  • Identify types and sources of knowledge (i.e., knowledge assets);

  • Determine competencies and weaknesses;

  • Perform knowledge mapping to identify the organization and flow of knowledge;

  • Perform gap analysis;

  • Provide recommendations;

  • Do knowledge planning;

  • Plan knowledge management strategy;

  • Build a supportive, knowledge sharing culture;

  • Create and define knowledge management initiatives;

  • Develop a cost-benefit analysis;

  • Perform physical modeling;

  • Develop the physical architecture;

  • Develop the framework for access, input/update, storage and eventual distribution & use;

  • Develop a high level meta-data design;

  • Construct a visual prototype;

Outputs from the model phase:

  • Knowledge audit document;

  • Visual prototype (i.e., the knowledge map showing the taxonomy and flow of knowledge);

  • Knowledge management program plan;

  • Requirements specifications document;


  • Capture and secure knowledge;

  • Collect and verify knowledge;

  • Valuate the knowledge;

  • Represent knowledge;

  • Formalize how the knowledge is represented;

Classify the knowledge

  • Encode the knowledge;

  • Organize and store knowledge in the knowledge management system;

  • Combine knowledge;

  • Retrieve and integrate knowledge from the entire organization;

  • Create knowledge;

  • Have open discussion with customers and interested parties both internal and external to the organization;

  • Perform exploration and discovery;

  • Conduct experimentation (i.e., trial and error);

  • Share knowledge;

  • Distribute knowledge;

  • Make knowledge easily accessible;

  • Learn knowledge and loop back to Step 6;

Outputs from the act phase:

  • Knowledge acquisition document;

  • Design document;

  • Visual and technical knowledge management system prototypes;


  • Pilot operational use of the knowledge management system;

  • Conduct knowledge review;

  • Perform quality control;

  • Review knowledge for validity and accuracy;

  • Update knowledge;

  • Perform relevance review;

  • Prune knowledge and retain what is relevant, timely, and accurate and proven useful;

  • Perform knowledge management system review;

  • Test and evaluate achieved results;

  • Revalidate/test against metrics;

Outputs from the revise phase:

  • Evaluation methodology and results document;

  • Knowledge management system pilot;

  • User’s guide for the knowledge management system;


  • Publish knowledge ;

  • Coordinate knowledge management activities and functions;

  • Create integrated knowledge transfer programs;

  • Notify where knowledge is located and lessons learned;

  • Perform serious anecdote management (i.e., publicize testimonials of the benefits of the KMS);

  • Use knowledge to create value for the enterprise;

  • Sell (e.g., package knowledgebases for sale);

  • Apply (e.g., knowledge management consulting services, apply methodology);

  • Use (e.g., improve customer satisfaction, employee support and training);

  • Monitor knowledge management activities via metrics;

  • Conduct post-audit;

  • Expand knowledge management initiatives;

  • Continue to learn and loop back through the phases;

Outputs from the transfer phase:

  • Maintenance document for the knowledge management system;

  • Full production knowledge management system;

  • Post-audit document;

  • Lessons learned document;

Besides developing comprehensive knowledge management methodologies like SMARTVision, another way of making knowledge management more rigorous is to learn and borrow techniques from other disciplines that could readily apply to knowledge management. The database management/information retrieval, artificial intelligence, knowledge and software engineering, human resources management, and organizational behavior fields have addressed many concerns that the knowledge management community faces. For example, the knowledge engineering field uses various knowledge acquisition and representation methods to capture and formalize knowledge respectively. The knowledge management community should borrow those techniques and others, such as conceptual mapping for use in knowledge mapping, to solidify and enhance current knowledge management practices.

The organizational behavior and human resources fields have addressed cultural and motivation issues in organizations whose techniques could be borrowed and applied to knowledge management. By borrowing techniques from established reference disciplines, knowledge management practices can be more rigorous and substantive than current state-of-the-art knowledge management techniques.

Without digging deeper into knowledge management and making it more comprehensive, the fear is that knowledge management will be a fad rather than an important discipline. Business process re-engineering has been viewed by many as being a failure, and if the rigor isn’t put into knowledge management, the knowledge management field may suffer the same fate.

Dr. Jay Liebowitz is the Robert W. Deutsch Distinguished Professor of Information Systems at University of Maryland-Baltimore County (UMBC), e-mail liebowit@umbc.edu.

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