Knowledge Management - Take your performance to the next level

What is Knowledge Management?

Knowledge management (KM) is a strategy and process designed to consciously and comprehensively identify, capture, structure, value, leverage and share an organization's intellectual assets in terms of resources, documents, and people skills in order to enhance its performance and competitiveness. KM is an audit of "intellectual assets" that highlights unique sources, critical functions and potential bottlenecks which hinder knowledge flows to the point of use. It protects intellectual assets from decay, seeks opportunities to enhance decisions, services and products through adding intelligence, increasing value and providing flexibility.

The vital importance of knowledge in business has always been recognised but, up until now, only a few organisations are able to manage it because they understood the problems, the opportunities, the strategies and solutions. This picture is gradually changing as models, methods, tools and techniques for effective knowledge management are becoming available and as organisations realise the importance of knowledge and thinking to their capacity to adapt to the changing world.

KM efforts typically focus on organizational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, integration and continuous improvement of the organization. KM efforts overlap with organizational learning, and may be distinguished from that by a greater focus on the management of knowledge as a strategic asset and a focus on encouraging the sharing of knowledge.


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Challenges

Organizations face various challenges in implementing knowledge management practices. Some of the common challenges are listed below.

  • Data Accuracy: Valuable raw data generated by a particular group within an organization may need to be validated before being transformed into normalized or consistent content.

  • Data Interpretation: Information derived by one group may need to be mapped to a standard context in order to be meaningful to someone else in the organization.

  • Data Relevancy: The quality and value of knowledge depend on relevance. Knowledge that lacks relevance simply adds complexity, cost, and risk to an organization without any compensating benefits. If the data does not support or truly answer the question being asked by the user, it requires the appropriate meta-data (data about data) to be held in the knowledge management solution.

  • Ability to support/deny hypotheses: Does the information truly support decision-making? Does the knowledge management solution include a statistical or rule-based model for the workflow within which the question is being asked?

Benefits

Careful application of Knowledge Management, like other assets, can result in better performance and profitability.

  • Lower costs of operations

  • Making informed business decisions

  • Higher quality of products / services and better recommendations

  • Increased productivity

  • Proper retention of intellectual assets
What's Next?