Knowledge Management Systems Contents Introduction Knowledge Management Evolution

Knowledge Management Systems

Contents Introduction Knowledge Management Evolution of Knowledge Management Drivers of Knowledge Tacit and Explicit Knowledge KM in virtual organization Implementing knowledge management solutions Knowledge Management Systems on learning organizations Knowledge Management systems – issues, challenges and benefits

Introduction The nature of work has changed enormously with the shift from an industrial economy to a knowledge economy. The major drivers in changing this focus have been: Rapid advances in technology, The growing importance of international business & Increased recognition of individual needs and expectations. Knowledge Management is an important way of effectively deploying the resources and expertise in organizations.

Knowledge Management is the management of the organization towards the continuous renewal of the organizational knowledge base. Knowledge management is a technique of harnessing knowledge as an asset for organizational use to facilitate constant improvement. KM aims towards identifying the valuable resource of the collective expertise of the workforce - often called the intellectual capital. Intellectual Capital of an organization is the sum of everything everybody in a company knows.

Cont… Implementing KM enables an organization: To learn from its corporate memory Share knowledge Identify competencies in order to become a forward thinking and learning organization.

Evolution of Knowledge Management Knowledge in a typical business environment still lacks a definition. Peter Drucker, Paul Strassmann and Peter Senge are the notable individuals who stressed upon knowledge management. Drucker and Strassmann focused on the growing importance of information and explicit knowledge as organizational resources. Senge focused on learning organization as a cultural dimension of managing knowledge. Classical economic theory ignored knowledge as an asset.

Cont… Two factors emerged in recognizing the organizational knowledge. The concern over how to deal with exponential increases in the amount of available knowledge. Increasingly complex products and processes. 1980’s saw the development of systems for managing knowledge that relied on work done in artificial intelligence and expert systems, giving us such concepts as: Knowledge Acquisition Knowledge engineering Knowledge Base-Systems Today knowledge Management which appears to present a highly sought - after alternative to unsuccessful TQM, business process re-engineering initiatives.

Knowledge Management in current perspective Knowledge Management is making a strong come back. Some of the factors those are driving the need for knowledge management are: The economic down turn Downsizing, outsourcing and joint venture The need to share, team up and learn that leveraging business to employees portals. KM is thus a business imperative - a survival technique at least.

Knowledge Management first initiatives - their outcomes. There was too much emphasis, without understanding the intricacies of the entire process. Companies spent too much money with little or no return on their investments. The inability to translate theory into practice. KM was not attached to business processes. The focus on the technology Most of the organizations thought that the human components hold little or no relevance in the entire process.

Knowledge Management Drivers The primary drivers behind the implementation of the KM solution is to improve profits and increase revenue streams. While the secondary drivers include employee retention and customer satisfaction. Other important drivers for KM implementation within an organization are: Downsizing Mobile work force Globalization Rapid Change

Knowledge Based Drivers Organizations are faced with issues, arising from the lack of a proper and organized knowledge distribution systems Due to which, their employees cannot find the requisite knowledge when required. KM initiatives support active and complete transfer of knowledge from successful projects to new ones In the process reduces the extend of wasteful expenditure of resources.

Technology Drivers Technology drivers for KM are motivated by new openings in organizations to contend through knowledge process differentiation and employing technology. Technology has revolutionized the way the individuals as well as organizations communicate, store and exchange data at a lower cost and higher speed.

Intra-Organizational Drivers The organizational structure has to undertake a dramatic change to implement the requirements of effective knowledge management. Organizational culture also needs to change radically to accommodate these requirements.

Human resources Drivers HR drivers of KM include: The need for improved knowledge transfer Sharing and creation in cross functional teams of knowledge workers Deal with complex and changing employee expectations. To respond to competitive challenges Expansion of the organization beyond the traditional and functional areas.

Process Drivers Process drivers focus attention to improve work processes through KM related initiatives. An organization which has to proactive and anticipate the forces that will shape the markets, their field of operation must use knowledge to control process.

Economic Drivers Knowledge reschedules traditional economics of an organization by generating additional returns and additional values hence it is increasingly employed. Basic economic theory suggest most assets with the exception of knowledge are subject to diminishing returns.

Financial Drivers As an asset , knowledge defies economic theory. Knowledge assets increase in value as more and more people use them. KM provides a worth wide opportunity to integrate knowledge in a way that enriches the quality of decision making throughout the organization.

Essentials of Knowledge Management Knowledge needs to be defined in relation to intelligence, experience and common sense. Knowledge is know-how, an gathering of facts, procedural rules or heuristics. These elements are defined as follows: A fact is a statement with some element of truth about a subject matter or a realm. A procedural rule is a rule that describes a series of associations relative to the main. A heuristic is a rule of thumb based on years of experience.

Cont… The beneficial aspect of knowledge is that it can give back for some investigative time. Another aspect of knowledge is specificity, it cannot be relocated from one problem realm to another. Values, beliefs and integrity are related to knowledge.

Intelligence refers to the ability to gain and apply knowledge. It is the ability to built or look upon knowledge. Knowledge exchange is directly responsible for much of the experts competence in applying knowledge and for the difficulty of making it explicit. Capacity to understand use language is another characteristic of intelligence. Intelligence people learn quickly and make effective use what they learn.

Experience relates to what we have done and what has in the past happened in a specific area of work. Experience also leads to expertise. Expertise is also intuition and the ability to access one’s knowledge. Experience is closely related to knowledge. Knowledge develops over time through successful experience. Experience in using knowledge allows people to refine their reasoning processes in a knowledge management environment.

Common Sense Common sense refers to the unreflective opinions of ordinary humans, which comes naturally to a child as young as 3 or 4 years old. Common sense is not easily learned or acquired. Lack of common sense makes technology fragile. That is computers rarely go beyond the scope of their data ware house or knowledge base.

Data-Information-Knowledge Data Facts, images or sounds + interpretation+ meaning/relevance +purpose = Information Formatted, Filtered and summarized data + action + application = Knowledge Instincts, ideas, rules and procedures that guides actions and decisions. +intuition + experience = Wisdom

Cont…. Thus A collection of data is not information. A collection of information is not knowledge. A collection of knowledge is not wisdom. A collection of wisdom is not truth.

Types of Knowledge Shallow and Deep Knowledge Shallow knowledge or readily recalled surface knowledge indicates minimal understanding of the problem area. Deep knowledge is based on experiential information chunked as an entity and retrieved from long-term memory on recall. Knowledge as a know-how Know-how is not book knowledge, it is practical experience. Common Sense as Knowledge

Procedural to episodic knowledge Procedural knowledge Knowledge that is used over and over again. Declarative knowledge Knowledge that the expert is aware or conscious of. It is a shallow knowledge. Semantic Knowledge Chunked knowledge that resides in the expert’s long range memory Episodic Knowledge based on experiential information chunked as an entity and retrieved from long term memory recall.

Tacit and Explicit Knowledge Tacit knowledge Knowledge used to create explicit knowledge, the mind-set of individuals that includes intuitions, values, and beliefs that stem from experience. Explicit Knowledge based on experiential information chunked as an entity and retrieved from long term memory on recall.

Tacit Vs Explicit Knowledge TACIT KNOWLEDGE EXPLICIT KNOWLEDGE Knowledge of experiences (Body Skills) Knowledge of Rationality (Mind) Simultaneous Knowledge (Here and now) Sequential Knowledge (There and then) Analog Knowledge (practice) Digital Knowledge (Theory)

Expert Knowledge Expert knowledge is clustered or chunked in a long range memory. Chunking promotes expert performance but can also make it difficult for experts to be aware of their own knowledge in a way that allows them to describe it to others.

Social and Axiomatic knowledge Social knowledge comes into view at social situations and is inclined to control behaviors In a business environment the built-up of social knowledge results in corporate culture. Axiomatic Knowledge Is the basic knowledge that is believed to be intrinsic within organizational employees and is required for their participation in the organizational knowledge process.

Knowledge Management Systems KMS refers to a system for managing knowledge in organizations for supporting creation, capture, storage and dissemination of information. The idea of a KM system is to enable employees to have ready access to the organization's documented base of facts, sources of information, and solutions. KMS systems deal with information so they are a class of information system and may build on, or utilize other information sources.

Distinguishing features of KMS �Purpose: � KMS will have an explicit Knowledge Management objective of collaboration and sharing good practice. �Context: � One perspective on KMS would see knowledge is information that is meaningfully organized, accumulated and embedded in a context of creation and application. �Processes: � KMS are developed to support and enhance knowledgeintensive processes, tasks or projects.

Cont… Participants: � Users can play the roles of active, involved participants in knowledge networks and communities fostered by KMS. Instruments: � KMS support KM instruments like expertise locators, skill management systems, collaborative filtering and handling of interests used to connect people, the creation and fostering of communities or knowledge networks

Forms of KMS Document based i. e. any technology that permits creation/management/sharing of formatted documents such as web, distributed databases etc. Ontology/ Taxonomy based: these are similar to document technologies in the sense that a system of terminologies (i. e. ontology) are used to summarize the document Based on Artificial Intelligence technologies which use a customized representation scheme to represent the problem domain. Provide network maps of the organization showing the flow of communication between entities and individuals Increasingly social computing tools are being deployed to provide a more organic approach to creation of a KM system.

Challenges in KM Systems Development Changing Organizational Culture: Involves changing people's attitudes and behaviours. Knowledge Evaluation: Involves assessing the worth of information. Knowledge Processing: Involves the identification of techniques to acquire, store, process and distribute information. Sometimes it is necessary to document how certain decisions were reached. Knowledge Implementation: An organization should commit to change, learn, and innovate. It is important to extract meaning from information that may have an impact on specific missions. Lessons learned from feedback can be stored for future to help others facing the similar problem(s).

Benefits of KMS Sharing of valuable organizational information throughout organisational hierarchy. Can avoid re-inventing the wheel, reducing redundant work. May reduce training time for new employees Retention of Intellectual Property after the employee leaves if such knowledge can be codified.

Challenges for Implementing Knowledge Management Solutions Creating continuous learning opportunities for people. Providing opportunities for dialogue and inquiry. Encouraging collaboration and team learning in a sustained manner. Identifying and developing leaders who model and support learning at the individual, team and organizational levels.

Cont. . Establishing collaboration and team learning in a sustained manner. Providing individuals frequent occasions for discussing, debating and clarifying what constitutes knowledge in their areas or work. Helping people identifying the role, requirements and implications of knowledge for work performance. Focusing more on the flow circulation of knowledge than its stocking.