Knowledge Management: Meaning, Nature, Importance, Applications, Challenges

Everything you need to know about knowledge management. Knowledge Management (KM) is the process of generating, accumulating, sharing and using knowledge for improving organisational performance.

It is creation of new skills, capabilities, competencies and sharing the use of this knowledge by organisational members. In other words, it is a process of creating an interactive learning environment where people transfer and share what they know, internalize it and apply it to create new knowledge.

The term knowledge management is very comprehensive and encompasses different components from identification of knowledge to making available the right knowledge at right time to the right users.

However, KM as a discipline is of recent origin, with new concepts emerging constantly. Often, it is portrayed simplistically, discussions typically revolve around blanket principles that are intended to work across the organisation.

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Knowledge management may be defined as the system that identifies the knowledge requirements and their sources, generates the required information, processes, analyses and suitably presents the information, stores and makes available the knowledge to the right people at right time in the right format.

Learn about:-

1. What is Knowledge Management 2. Meaning of Knowledge Management 3. History 4. Nature 5. Levers 6. Importance

7. Dimensions 8. Applications 9. Significance 10. Pitfalls and Problems 11. Trends and Challenges.

Knowledge Management: Introduction, Meaning , Nature, Applications, Levers, Importance, Dimensions and Challenges

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Contents:-

What is Knowledge Management
Meaning of Knowledge Management
History of Knowledge Management
Nature of Knowledge Management
Levers of Knowledge Management
Importance of Knowledge Management
Dimensions of Knowledge Management
Applications of Knowledge Management
Significance of Knowledge Management
Pitfalls and Problems of Knowledge Management
Trends and Challenges of Knowledge Management

Knowledge Management – What is Knowledge Management

Knowledge Management (KM) is the process of generating, accumulating, sharing and using knowledge for improving organisational performance. It is creation of new skills, capabilities, competencies and sharing the use of this knowledge by organisational members. In other words, it is a process of creating an interactive learning environment where people transfer and share what they know, internalize it and apply it to create new knowledge.

Some experts including Peter Drucker say that “KM is a bad term because knowledge cannot be managed. You should create conditions for the generation and application of knowledge, which means learning.”

KM involves knowledge-focused activities, which are given below:

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1. Generating new knowledge.

2. Accessing valuable knowledge from outside sources.

3. Using accessible knowledge in decision making.

4. Embedding knowledge in processes, products or services.

5. Representing knowledge in documents, data-bases and software.

6. Facilitating knowledge growth through culture and incentives.

7. Transferring existing organisation into other parts of the organisation, and

8. See the impact of KM.

Knowledge Management – Meaning

The term knowledge management is very comprehensive and encompasses different components from identification of knowledge to making available the right knowledge at right time to the right users. However, KM as a discipline is of recent origin, with new concepts emerging constantly. Often, it is portrayed simplistically, discussions typically revolve around blanket principles that are intended to work across the organisation.

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Knowledge management is the name of a concept in which an enterprise consciously and comprehensively gathers, organises, shares, and analyses its knowledge in terms of resources, documents, and people skills. In early 1998, it was believed that few enterprises actually had a comprehensive knowledge management practice (by any name) in operation. Advances in technology and the way we access and share information has changed that, many enterprises now have some kind of knowledge management framework in place.

As Wikipedia observes, Knowledge Management programmes are typically tied to organisational objectives such as improved performance, competitive advantage, innovation, developmental processes, lessons learnt transfer (for example – between projects) and the general development of collaborative practices. KM is frequently linked and related to what has come to be known as the learning organisation, lifelong learning and continuous improvement.

KM may be distinguished from Organisational Learning by a greater focus on the management of knowledge as an asset and the development and cultivation of the channels through which knowledge, information and signal flow.

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KM comprises a range of practices used by organisations to identify, create, represent and distribute knowledge. It has been an established discipline since 1995 with a body of university courses and both professional and academic journals dedicated to it.

There is a broad range of thought on KM with no unanimous definition. The approaches vary by author and school.

KM may be viewed from each of the following perspectives:

i. Techno-centric – A focus on technology, ideally those that enhance knowledge sharing/ growth.

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ii. Organisational – How does the organisation need to be designed to facilitate knowledge processes? Which organisations work best with what processes?

iii. Ecological – Seeing the interaction of people, identity, knowledge and environmental factors as a complex adaptive system.

Knowledge Management – History

Although the phrase “knowledge management” entered popular usage in the late 1980s (e.g., conferences in KM began appearing, books on KM were published, and the term began to be seen in business-oriented journals), Knowledge Management has been around for many decades. Librarians, philosophers, teachers, and writers have long been making use of many of the same techniques. However, it could also be argued that knowledge management has been around far longer than the actual term has been in use.

Denning (2000) relates how from “time immemorial, the elder, the traditional healer and the midwife in the village have been the living repositories of distilled experience in the life of the community”. Some form of narrative repository has been in existence for a long time, and people have found a variety of ways of sharing knowledge in order to build on earlier experience, eliminate costly redundancies, and avoid making at least the same mistakes again.

For example, knowledge sharing often took the form of town meetings, workshops, seminars, and mentoring sessions. The primary “technology” used to transfer knowledge consisted of the people themselves. Indeed, much of our cultural legacy stems from the migration of different peoples across continents.

H. G. Wells (1938), though never using the actual term knowledge management, described his vision of the “World Brain,” which would allow the intellectual organization of the sum total of our collective knowledge. The World Brain would represent “a universal organization and clarification of knowledge and ideas”.

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Wells anticipated the World Wide Web, albeit in a utopic idealized manner, when he spoke of “this wide gap between …at present unassembled and unexploited best thought and knowledge in the world….We live in a world of unused and misapplied knowledge and skill”.

The World Brain encapsulates many of the desirable features of the intellectual capital approach to Knowledge Management – selected, well-organized, and widely vetted content that is maintained, kept up to date, and, above all, put to use to generate value to users, the users’ community, and their organization.

What Wells envisaged for the entire world can easily be applied within an organization in the form of an intranet. What is new and is termed knowledge management is that we are now able to simulate rich, interactive, face-to-face knowledge encounters virtually through the use of new communication technologies.

Information technologies such as an intranet and the Internet enable us to knit together the intellectual assets of an organization and organize and manage this content through the lenses of common interest, common language, and conscious cooperation.

We are able to extend the depth and breadth or reach of knowledge capture, sharing, and dissemination activities, as we had not been able to do before, and we find ourselves one step closer to Wells’ (1939) “perpetual digest… and a system of publication and distribution” “to an intellectual unification … of human memory”.

In the early 1960s, Drucker was the first to coin the term knowledge worker. Senge (1990) focused on the “learning organization” as one that can learn from past experiences stored in corporate memory systems. Barton-Leonard (1995) documented the case of Chapparal Steel as a knowledge management success story. Nonaka and Takeuchi (1995) studied how knowledge is produced, used, and diffused within organizations and how such knowledge contributed to the diffusion of innovation.

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A number of people, perceiving the value of measuring intellectual assets, recognized the growing importance of organizational knowledge as a competitive asset. A cross-industry benchmarking study was led by APQC’s president Carla O’Dell and completed in 1996.

It focused on the following KM needs:

1. Knowledge management as a business strategy.

2. Transfer of knowledge and best practices.

3. Customer-focused knowledge.

4. Personal responsibility for knowledge.

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5. Intellectual asset management.

6. Innovation and knowledge creation.

Milestones in the development of modem technology offer another perspective on the history of KM – industrialization beginning in 1800, transportation technologies in 1850, communications in 1900, computerization in the 1950s, virtualization in the early 1980s, and the early efforts at personalization and profiling technologies in 2000.

With the advent of the information or computer age, KM has come to mean the systematic, deliberate leveraging of knowledge assets. Technologies enable valuable knowledge to be “remembered” via organizational learning and corporate memory, and they also enable valuable knowledge to be “published”— that is, to be widely disseminated to all stakeholders.

The evolution of knowledge management has occurred in parallel with a shift from a retail model based on a catalog (here one should recall Ford’s famous quote that you can have a car in any color you like—as long as it is black) to an auction model (as exemplified by eBay) to a personalization model where real-time matching of user needs and services occurs in a win-win exchange model.

In 1969, the launch of ARPANET allowed scientists and researchers to communicate more easily with one another in addition to being able to exchange their large data sets. They came up with a network protocol or language that would allow disparate computers and operating systems to network together across communication lines.

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Next, a messaging system was added to this data file transfer network. In 1991, the nodes were transferred to the Internet and World Wide Web. At the end of 1969, only four computers and about a dozen workers were connected!!

Simultaneously, many key developments were occurring in information technologies devoted to knowledge-based systems – expert systems that sought to capture “experts on a diskette,” intelligent tutoring systems aimed at capturing “teachers on a diskette,” and artificial intelligence approaches that gave rise to knowledge engineering in which someone was tasked with acquiring knowledge from subject matter experts, conceptually modelling this content, and then translating it into machine-executable code.

McGraw and Harrison-Briggs describe knowledge engineering as “involving information gathering, domain familiarization, analysis and design efforts. In addition, accumulated knowledge must be translated into code, tested and refined”. A knowledge engineer is “the individual responsible for structuring and/or constructing an expert system”.

The design and development of such knowledge-based systems have much to offer knowledge management, which also aims at the capture, validation, and subsequent technology-mediated dissemination of valuable knowledge from experts.

Knowledge Management – Nature

Knowledge management draws upon a vast number of diverse fields such as:

1. Organizational science

2. Cognitive science.

3. Linguistics and computational linguistics.

4. Information technologies such as knowledge-based systems, document and information management, electronic performance support systems, and database technologies.

5. Information and library science.

6. Technical writing and journalism.

7. Anthropology and sociology.

8. Education and training.

9. Storytelling and communication studies.

10. Collaborative technologies such as Computer Supported Collaborative Work and groupware, as well as intranets, extranets, portals, and other web technologies.

This list is by no means exhaustive, but it serves to show the extremely varied roots that gave life to KM and continues to be its basis today.

The multidisciplinary nature of KM represents a double-edged sword. On the one hand, it is an advantage because almost anyone can find a familiar foundation on which to base their understanding and even practice of KM. Someone with a background in journalism, for example, can quickly adapt his or her skill set to the capture of knowledge from experts and reformulate them as organizational stories to be stored in corporate memory.

Someone coming from a more technical database background can easily extrapolate his or her skill set to design and implement knowledge repositories that will serve as the corporate memory for that organization. However, the diversity of KM also presents some challenges with respect to boundaries. Skeptics argue that KM is not and cannot be said to be a separate discipline with a unique body of knowledge.

This attitude is typically represented by phrases such as “KM is just IM (Information Management)” or “KM is nonsensical it is just good business practices.” It becomes very important to be able to list and describe what set of attributes are necessary and are in themselves sufficient to constitute knowledge management both as a discipline and as a field of practice that can be distinguished from others.

One of the major attributes of KM relates to the fact that it deals with knowledge as well as information. Knowledge is a more subjective way of knowing and is typically based on experiential or individual values, perceptions, and experience.

Popular examples to distinguish data from information and from knowledge include the following:

1. Data – Content that is directly observable or verifiable; a fact—for example, listings of the times and locations of all movies being shown today— I download the listings.

2. Information – Content that represents analyzed data—for example, “I can’t leave before 5 so I will go to the 7:00 P.M. show at the cinema near my office.”

3. Knowledge – At that time of day, it will be impossible to find parking. I remember the last time I took the car I was so frustrated and stressed because I thought I would miss the opening credits. I’ll therefore take the commuter train. But first I’ll check with Al. I usually love all the movies he hates so I want to make sure it’s worth seeing!

Another distinguishing characteristic of KM as opposed to other information management fields is the ability of KM to address knowledge in all of its forms, notably, tacit knowledge and explicit knowledge.

Knowledge Management – 7 Knowledge Levers: Customer Knowledge, Knowledge of People, Knowledge of Products and Services and a Few Others

Organizations commonly use seven knowledge levers to exploit knowledge. Of these, the main ones are knowledge of people, products, and processes.

However, the seven levers are as follows:

1. Customer knowledge to know their tacit needs and serve them better

2. Knowledge of people to understand their expectations

3. Knowledge of products and services to strengthen the marketing strategy

4. Knowledge of processes to make products right in the first time

5. Organizational memory database, reading material in sharing mode

6. Knowledge of relationships to deal with suppliers, employees, and stakeholders such as customers, shareholders, and regulatory bodies, and obviously the community

7. Knowledge assets that refer to intellectual capital of the workforce.

These points are elaborated here:

1. Customer Knowledge:

International standards on ‘quality management system—fundamentals and vocabulary’ (ISO 9000:2000) states that the first principle on ‘quality management is customer focus’. Since customer focus enables an organization to move towards growth and increase the revenue, it becomes an important responsibility of the organization to understand and keep the market requirements and their expectations in mind.

The main strategy for many companies today is to be able to identify and meet the implied and unstated needs of the customers to gain competitive advantages.

2. Knowledge of People:

Imparting knowledge to people is considered as a pay back. In simpler terms, it is believed that training is costly but non-training is costlier. One must share knowledge at individual levels as well as at organizational levels. A knowledgeable workforce forms the backbone of an organization. Organize innovation workshops, train the people on expert and learning networks, make people adaptable to change, encourage them to work in teams to derive the benefits of synergy, and so on.

3. Knowledge of Products and Services:

Organizations are seen to produce and market goods to their customers, along with a user booklet/guide. Morey (2001) advises to surround products with knowledge, such as the user guide/booklet or operation manual incorporating tables on ‘troubleshooting’, ‘do and do not’, ‘take care of your own item’, etc. These are examples of knowledge intensive services. One benefit with this is that most of the customers are able to maintain their consumer durable items.

For example, BPL provides its customers with a user manual that provides details on installation (guide to install), maintenance, precautions to be observed, handling the remote, connecting other equipment, and most importantly, preliminary troubleshooting for its TV. The points on troubleshooting are of great help to customers.

4. Knowledge of Processes:

Process is a set of interrelated activities, irrespective of the nature of goods or services. Any process has its inputs (tangible and intangible) to get the desired output. Hence, it becomes very important for an organization to embed the knowledge into business processes and managerial decisions in all functional areas, for example planning, purchase, material control, production and maintenance, quality control, storage, preservation, and delivery for the best results.

5. Organizational Memory:

Examples of organizational memory include course materials in sharing mode, computer databases on intranet, etc. The Camellia School of Business Management (CSBM) offers a variety of course programmes and has reputed faculty members with enriched industrial experience from multiple disciplines. The faculty members develop course notes and allow them to be shared by other interested members of faculty.

This practice, within the purview of organizational memory, helps anyone in the institute to gather knowledge. This knowledge lever further extends with the display of mission, vision, policy, objectives, targets/goals, and strategies of the organization.

An employee’s database includes several parts, for example static information (such as date of birth, designation at entry), dynamic information (such as age, present designation), performance details, achievement records, behavioural aspects (non-conforming with the rules, norms), and human dimensions (personality traits, motivation, lifestyle inventories, occupational values, etc.). An individual at any particular time can look into the complete details of any employee. It can also be used to look for other employees.

6. Knowledge of Relationships:

Knowledge flows between an organization and its suppliers (vendors), employees (internal customers), and stakeholders such as customers, shareholders, regulatory bodies, community, etc. All the parties benefit from the flow of knowledge. An organization needs to communicate with its suppliers about its requirements and places purchase orders for raw materials.

An organization receives purchase orders for finished goods from its customers.

In today’s time and age, organizations must create online facilities so that the suppliers can know about the load on the organization arising out of the demands from customers. The supplier will then be ready to deliver the items as per the bill of materials. This will reduce the time taken by the organization to prepare and place orders.

7. Knowledge Assets:

Intellectual capital is an intangible asset of an organization. The intellectual capital of an organization includes human assets (knowledge, skill, experience, pragmatism, maturity, etc.), its capital (system, procedure, process, work instructions, databases), intellectual asset or property (patents, copyrights, logo, emblem, trademarks, research findings), and customer assets (quality and depth of relationship).

The intellectual capital or intangible assets of the organization need to be identified and measured. This is important because unless one measures, it becomes difficult to monitor and improve. As an HR expert, one has to add value to the intangible assets. To bring about the value addition, one must develop an able and energetic team to initiate a dynamic role to manage the patents and other intellectual capital.

Knowledge Management – Importance

Knowledge is the most dynamic force driving the development of any society. The world, in fact, is experiencing an information/knowledge revolution.

The importance of knowledge to today’s world is highlighted by such usages as knowledge society, knowledge worker, learning organisation, knowledge explosion, etc.

Knowledge is a core competence that can provide competitive edge to individuals, organisations and nations. Knowledge generation, managing knowledge and imparting and disseminating knowledge are, therefore, of critical importance.

Knowledge is the key resource in intelligent decision-making, forecasting, design, planning, diagnosis, analysis, evaluation, and intuitive judgment. It is formed in and shared between individual and collective minds. It does not grow out of database but evolves with experience, successes, failures and learning over time.

Knowledge allows for making predictions, casual associations, or predictive decisions about what to do – unlike information, which simply gives us the facts.

In short, knowledge allows the creation of capability which determines the ability to do things.

Knowledge Management – Dimensions: Given by Michael Polayni’s, Nonaka and Takeuchi

A common framework for categorising the dimensions of knowledge discriminates between embedded knowledge as knowledge which has been incorporated into an artifact of some type (for example, an information system may have knowledge embedded into its design), and embodied knowledge as representing knowledge as a learned capability of the body’s nervous, chemical, and sensory systems. These two dimensions, while frequently used, are not universally accepted.

It is also common to distinguish between the creation of “new knowledge” (i.e., innovation) versus the transfer of “established knowledge” within a group, organisation, or community. Collaborative environments such as communities of practice or the use of social computing tools can be used for both creation and transfer.

Michael Polayni’s distinction between tacit and explicit knowledge, reformulated by Nonaka, is useful to understand some important aspects of the process of knowledge generation and management.

Tacit knowledge is personal, context-specific and is stored in the heads of people. It is knowledge that is difficult to formalise, record, or articulate; it is stored in the heads of people. Tacit knowledge consists of various components, such as intuition, experience, ground truth, judgment, values, assumptions, beliefs and intelligence. Tacit knowledge is subjective and experimental and is difficult to formalise, record, or articulate.

Belief, perspective, mental models, ideas and ideals are examples of tacit knowledge.

Explicit knowledge is objective, rational knowledge that can be expressed, modified and transmitted in a systematic and formal language, documents, databases, webs, e-mails, charts, etc.

Nonaka and Takeuchi argued that a successful knowledge management (KM) programme needs, on the one hand, to convert internalised tacit knowledge into explicit codified knowledge in order to share it, but, on the other hand, it also must permit individuals and groups to internalise and make personally meaningful codified knowledge they have retrieved from the KM system.

Knowledge Management – Process: Identification of Knowledge Needs, Identification of Data Sources, Acquisition/Generation of Knowledge and a Few Others

The knowledge management system of an organisation typically has the following processes:

Process # 1. Identification of Knowledge Needs:

The important first step in knowledge management is the identification of the knowledge requirements of the organisation. The knowledge requirements may vary from organisation to organisation, depending on factors like the nature and scope of its business, competitive and other business environments, future plans, etc.

Process # 2. Identification of Data Sources:

Once the data needs are identified, the next step is identification of sources of data for generating the required knowledge. Data/knowledge may be readily available somewhere. If they are not readily available, primary data will have to be gathered and the sources of such primary data have to be identified.

Process # 3. Acquisition/Generation of Knowledge:

The next stage is acquisition/generation of knowledge. It may include acquisition of books and other publications or other available materials, sourcing from internet, etc. Collection of primary data or generation of entirely new knowledge may be done in-house or may be outsourced. Outsourcing even R&D is common today.

Process # 4. Processing, Analysing, Presenting and Codifying:

The data/information/knowledge acquired/generated need to be properly processed, analysed, interpreted and presented meaningfully and usefully. They should also be systematically classified for easy identification for accessing any time.

Process # 5. Storing:

There must be a proper system for storing the knowledge so that they are available at the right time to the right people.

Process # 6. Policy and System:

As indicated in the definition of knowledge management, knowledge management is a system. That is the organisation shall establish the appropriate system integrating the various components and suitable technologies and methods.

The organisation shall also have an appropriate policy regarding knowledge management, including a policy in respect of accessing information, sharing/disseminating knowledge, protecting its knowledge base, etc.

Knowledge Management – Applications: Globalization of Businesses, Leaner Organizations, Corporate Amnesia and Technological Advances

The major business drivers behind today’s increased interest in and application of KM lie in four key areas:

1. Globalization of business – Organizations today are more global— multisite, multilingual, and multicultural in nature.

2. Leaner organizations – We are doing more and we are doing it faster, but we also need to work smarter as knowledge workers, adopting an increased pace and workload.

3. “Corporate amnesia”- We are more mobile as a workforce, which creates problems of knowledge continuity for the organization and places continuous learning demands on the knowledge worker. We no longer expect to spend our entire work life with the same organization.

4. Technological advances – We are more connected. Advances in information technology not only have made connectivity ubiquitous but have radically changed expectations. We are expected to be “on” at all times, and the turnaround time in responding is now measured in minutes, not weeks.

Today’s work environment is more complex because we now need to attend daily to the increase in the number of subjective knowledge items. Filtering over 200 e-mails, faxes, and voicemail messages on a daily basis should be done according to good time management practices and filtering rules, but more often than not, workers tend to exhibit a “Pavlovian reflex” when they note the beeps announcing the arrival of new mail or the ringing of the phone that demands immediate attention.

Knowledge workers are increasingly being asked to “think on their feet,” with little time to digest and analyze incoming data and information, let alone retrieve, access, and apply relevant experiential knowledge. This is due both to the sheer volume of tasks to address and to the greatly diminished turnaround time. Today’s expectation is that every- one is “on” all the time—as evidenced by the various messages expressing annoyance when voicemails are not responded to promptly or e-mails are not acknowledged.

Knowledge management represents one response to the challenge of trying to manage this complex, information-overloaded work environment. As such, KM is perhaps best categorized as a science of complexity. One of the largest contributors to the complexity is that information overload represents only the tip of the iceberg—only that information that has been rendered explicit. KM also must deal with the yet to be articulated or tacit knowledge.

To further complicate matters, we may not even be aware of all the tacit knowledge that exists; we may not “know that we don’t know.” Maynard Keynes hit upon a truism when he stated that “these …directive people who are in authority over us, know scarcely anything about the business they have in hand.

Nobody knows very much, but the important thing to realize is that they do not even know what is to be known.” While Keynes was addressing politics and the economic consequence of peace, today’s organizational leaders have echoed his words countless times.

In fact, we are now, according to Snowden (2002), entering the third generation of knowledge management, one devoted to context, narrative, and content management. In the first generation, the emphasis was placed on containers of knowledge or information technologies in order to help us with the dilemma exemplified by the much quoted phrase “if only we knew what we know”.

The early adopters of Knowledge Management, large consulting companies that realized that their primary product was knowledge and that they needed to inventory their knowledge stock more effectively, exemplified this phase. A great many intranets and internal knowledge management systems were implemented during the first Knowledge Management generation.

This was the generation devoted to finding all the information that had up until then been buried in the organization with commonly produced by-products encapsulated as reusable best practices and lessons learned.

Reeling from information overload, the second generation swung to the opposite end of the spectrum to focus on people, which could be phrased as “if only we knew who knows about.” There was growing awareness of the importance of human and cultural dimensions of knowledge management as organizations pondered why the new digital libraries were entirely devoid of content (“information junkyards”) and why the usage rate was so low.

In fact, the information technology approach of the first Knowledge Management generation leaned heavily toward a top-down, organization-wide monolithic KM system. In the second generation, it became quite apparent that a bottom-up or grassroots adoption of Knowledge Management led to much greater success and that there were many grassroots movements—which later became dubbed communities of practice.

Communities of practice are good vehicles to study knowledge sharing or the movement of knowledge throughout the organization to spark not only reuse for greater efficiency but also knowledge creation for greater innovation.

The third stage of Knowledge Management brought about an awareness of the importance of shared context – how to describe and organize content so that intended end users are aware it exists and can easily access and apply this content. Shared context creates shared meaning. Content needs to be abstracted from context. This phase is characterized by the advent of metadata to describe the content in addition to the format of content, content management, and knowledge taxonomies.

After all, if knowledge is not put to use to benefit the individual, the community of practice, and/or the organization, then knowledge management has failed.

Bright ideas in the form of light bulbs in the pocket are not enough; they must be “plugged in,” and this can only be possible if people know what there is to be known, can find it when they need to, can understand it, and— perhaps most important— are convinced that this knowledge should be put to work. A slogan for this phase might be something like – “taxonomy before technology”.

Knowledge Management – Benefits

KM is an asset which can be used for creating value for customers, respond to change in the environment, achieve corporate excellence and enable people to solve problems. Organisational resources cannot be properly utilised with knowledge.

Effective management of knowledge offers following benefits:

1. Promotes creativity and innovation.

2. Reduces cost of production by achieving economies of scale.

3. Reduces loss of intellectual capital for the organisation.

4. Increases productivity.

5. Breaks communication barriers within the organisation.

6. Gaining a competitive edge in the market place by converting intellectual assets into value.

Several Indian Companies (e.g. L&T, HLL etc.) are successfully applying Knowledge Management techniques.

Knowledge Management – Pitfalls and Problems

1. Absence of adequate knowledge system which captures and stores ‘tacit’ knowledge residing in the minds of personnel (having technical/scientific or other expert knowledge.)

2. Absence of an effective learning organisational culture. Many companies have inadequate filing and data-base management systems. There is a need to setup common knowledge domains (e.g. power point presentation, library search results etc.)

3. Inadequate to-and-fro dissemination of knowledge between the knowledge centre and other key stakeholders including manufacturing logistics and marketing divisions, institutional customers etc.

Business firms struggle in knowledge management when they are not able to identify as to which department is going to benefit from the knowledge effect. They have no plans for how their people should work, share, develop and apply knowledge to achieve the goals.

The main requirements for successful management of knowledge are given below:

1. Knowledge culture – Since knowledge is generated absorbed and used by humans, cultural issues are most important in knowledge management (KM). Organisational culture, in which creative thinking is permitted and encouraged, must be related and nurtured.

2. Knowledge strategy – Every organisation should develop a knowledge strategy which is based on different aspects of creating, sharing and using knowledge. The knowledge strategy should identify the knowledge gap i.e. what an organisation must know for the achievement of organisational goals and what it knows at present.

3. Technology – Technology is an important element for any knowledge management system. It provides the foundation for solutions, which automates and centralizes the sharing of knowledge. Knowledge management technology can be broken down into various stages i.e. knowledge generation, codification, storage, transfer and application. Information and communication technology can be used in all stages of knowledge management life cycle.

4. Knowledge team – Knowledge generation is an ongoing process. It is necessary to create a key team for continuous generation and sharing of knowledge. Companies should create valued knowledge manager positions. It would serve as a repository of business solutions.

In short, knowledge culture, knowledge strategy, technology and team are keys to success in K.M.

Knowledge Management – Trends and Challenges

The five modes of knowledge generation mentioned above also represent some dimensions of the trends in KM. They also indicate, implicitly, the challenges to knowledge management.

1. Acquisition:

Acquisition means acquisition of organisations engaged in knowledge generation and management (this has become common in the business sector) and acquisition of knowledge from other organisations, individuals, etc. (like purchase of know-how from research institutions and other organisations, including patented knowledge).

The attractiveness of acquisition of other organisations is possession of the knowledge source and established system for knowledge generation and management. It frees the organisation from the need to establish such a system from scratch which, in many cases, is time-consuming and fraught with several difficulties.

Acquisition, however, may have problems/challenges. Proper valuation of the organisation is important. There could also be the risk of hidden costs. The organisational culture is also, sometimes, a problem. In short, while taking over an organisation, all its problems are also being taken over.

2. Dedicated Resources:

Dedicated resource means investing resources and establishing systems for generating knowledge internally, like investing in and building up R&D facilities. Many business enterprises, research institutes and educational institutions of higher learning have such dedicated resources. Besides the physical infrastructure, the resources include, very importantly, the human resources.

Besides or instead of its own exclusive dedicated resources, an organisation may also dedicate resources for consortium generation of knowledge. Such alliance between organisations for R&D, etc., both at national and international levels, is a growing trend.

Dedicated resources also include resource earmarking for specific, though not very elaborate, knowledge gathering. This includes field studies and explorations.

Quite a lot of important but widely scattered and unorganised/undocumented knowledge, like traditional knowledge in many areas, can also be gathered so.

3. Outsourcing:

Outsourcing knowledge is becoming increasingly popular. This includes giving on contract or on some other arrangement research or other knowledge generation to other organisations (also to individuals). The main reasons for this are the expertise of the external source and cost advantages.

Knowledge Processing Outsourcing (popularly known as KPO) typically involves a component of Business Processing Outsourcing (BPO), Research Process Outsourcing (RPO) and Analysis Process Outsourcing (APO). KPO business entities provide typical domain-based processes, advanced analytical skills and business expertise, rather than just process expertise.

4. Data Mining:

The data mining technique can play an important role in knowledge generation and knowledge management in many complex data knowledge environments.

Data mining is sorting through data to identify patterns and establish relationships.

Data mining parameters include:

i. Association – looking for patterns where one event is connected to another event.

ii. Sequence or path analysis – looking for patterns where one event leads to another later event.

iii. Classification – looking for new patterns (may result in a change in the way the data is organised but that’s ok).

iv. Clustering – finding and visually documenting groups of facts not previously known.

v. Forecasting – discovering patterns in data that can lead to reasonable predictions about the future (This area of data mining is known as predictive analytics).

Data mining techniques are used in many research areas, including mathematics, cybernetics, and genetics. Web mining, a type of data mining used in customer relationship management (CRM), takes advantage of the huge amount of information gathered by a website to look for patterns in user behaviour. A data miner is a programme that collects such information, often without the user’s knowledge, as spyware.

5. Networking:

Networking has become an important and common source of knowledge sharing and development. There are both formal and informal networking’s. The advent of the internet has given a big boost to networking.

6. KM Technologies:

The technological developments are fast changing the knowledge management scenario. The early KM technologies were expertise locators, like online organisational yellow pages, and document management systems. Combined with the early development of collaborative technologies (in particular Lotus Notes), KM technologies expanded in the mid-1990s. Subsequently, it followed developments in technology in use in Information Management. In particular, the use of semantic technologies for search and retrieval and the development of KM specific tools such as those for communities of practice.

More recently, social computing tools (such as blogs and wikis) have developed to provide a more unstructured, self-governing approach to the transfer, capture and creation of knowledge through the development of new forms of community, network or matrix. However, such tools for the most part are still based on text and code, and thus represent explicit knowledge transfer. These tools face challenges in distilling meaningful reusable knowledge and intelligible information and ensuring that their content is transmissible through diverse channels, platforms and forums.

Knowledge Mapping is commonly used to cover functions such as a knowledge audit (discovering what knowledge exists at the start of a knowledge management project), a network survey (mapping the relationships between communities involved in knowledge creation and sharing) and creating a map of the relationship of knowledge assets to core business process. Although frequently carried out at the start of a KM programme, it is not a necessary precondition or confined to start up.

Knowledge management involves data mining and some methods of operation to push information to users. Some vendors are offering products to help an enterprise inventory and access knowledge resources. IBM’s Lotus Discovery Server and K-Station, for example – are products advertised as providing the ability to organise and locate relevant content and expertise required to address specific business tasks and projects. They are said to be able to analyse the relationships between content, people, topics, and activity, and produce a knowledge map report.