You might be asking, “What is the
knowledge economy?” The knowledge economy as a term was popularized by Peter
Drucker in his 1966 book, “The Effective Executive.” The definition of the
knowledge economy is: an economic system that relies more heavily on
intellectual capabilities than physical inputs or natural resources. Instead of
traditional inputs, big data analytics and automation are fundamental to the
production process.
With the advent of the knowledge
economy, there
has been an increase in the production of intangible assets, especially
proprietary technology and patents. The IT/ICT industries are at the fore-front
of economic growth in areas like AI and robotics. In the knowledge economy,
exchange between research centers, universities, and think tanks
abets further innovation. It is also characterized by the development of
regions focused on certain industries – technology in Silicon Valley and automotive
engineering in Germany.
Research
has shown that investments in information technology result in growth in
productivity that exceeds that of other investments – but only when coupled
with organizational changes. Common organizational changes may include the
introduction of profit-sharing plans and increased employee participation in
decision-making.
The
knowledge economy is considered the primary cause of the expansion of STEM
jobs. Occupational paths such as computer science, engineering, chemistry, and
biology offer the greatest opportunities for career growth and executive
leadership positions. Skills like data analysis, working with financial models,
and the ability to innovate are in high demand in this economy.
In a
knowledge economy, there is also an increased demand for teamwork,
problem-solving, communication, and certain computer skills. These skills are
seen as complements to education, not substitutes.
Knowledge
economy workers are typically highly-educated. However, a high level of education
is not required. But do knowledge economy workers always need formal degrees in
the subject area they are pursuing? While formal education is linked to
increased rates of participation in the knowledge economy, highly literate
people, or people with technical training in a specific area, participate at
the highest rates.
Characteristics
Of the Knowledge Economy
Below are a few characteristics of the
knowledge economy:
- Institutional
structures that provide incentives for entrepreneurship and the use of
knowledge
- Availability
of skilled labor and a good education system
- Access
to information and communication infrastructures (ICT)
- A
vibrant innovation landscape that includes the academic world, the private
sector, and civil society
- An
increased demand for workers in STEM subjects
- The
development of “clusters” of industries in certain
geographic regions
- A
steep rise in the number of patents
- Knowledge
exchange between industries
- Innovation-driven
producers and uses (example: open-source software and customer feedback)
The four pillars of Knowledge Economy
The application of knowledge is one of
the key sources of growth in the global economy. But many developing countries
fail to tap the vast stock of global knowledge and apply it to their needs.
They need not deny themselves this vital tool for growth. By building on their
strengths and carefully planning appropriate investments in human capital, effective
institutions, relevant communications technologies, and innovative and
competitive enterprises, developing countries can capitalize on the knowledge
revolution. With the sustained use and creation of knowledge at the center of
the economic development process, an economy essentially becomes a Knowledge
Economy. It is an economy where knowledge is acquired, created, disseminated
and used effectively to enhance economic development. The successful transition
to the Knowledge Economy typically involves elements such as long-term
investments in education, expanding innovation capability, modernizing the
information infrastructure, and having an economic environment that is
conducive to market transactions. The Knowledge Economy framework asserts that
investments in the four knowledge economy pillars are necessary for sustained
creation, adoption, adaptation and use of knowledge in domestic economic
production, which will consequently result in higher value-added goods and
services. This would tend to increase the probability of economic success, and
hence economic development, in the current highly competitive and globalized
world economy. The four pillars of the Knowledge Economy framework are:
1.
An economic incentive and institutional
regime
The economic and institutional regime of
an economy stimulate creativity and incentives for the efficient creation,
dissemination, and use of existing knowledge, and provides good economic
policies and institutions that permit efficient mobilization and allocation of
resources. A “knowledge-conducive” economic regime should be open to
international trade and be free from various protectionist policies in order to
foster competition, which in turn will encourage entrepreneurship (Sachs and
Warner, 1995; and Bosworth and Collins,2003). Government expenditures and
budget deficits should be sustainable, and inflation should be stable and low.
Domestic prices should also be largely free from controls and the exchange rate
should be stable and reflect the true value of the currency. The financial
system should be one that is able to allocate resources to sound investment
opportunities and redeploy assets from failed enterprises to more promising
ones.
2.
Educated and skilled workers
The global knowledge economy is placing
new demands on labour, who need more skills and knowledge to be able to
function in their lifelong. These demands require a new model of education and
training. Lifelong learning improves people’s ability to function as members of
their communities, education and training increase social cohesion, reduce
crime, and improve income distribution. A lifelong learning encompasses formal
learning (schools, training institutions, universities), non-formal learning
(on-the-job and household training), and informal learning (skills learned from
family members or people in the community). It allows people to access learning
opportunities as they need them rather than because they have reached a certain
age.
3.
An effective innovation system
An innovation system of firms, research
centers, universities, consultants, and other organizations that influence the
way by which a country acquires, creates, disseminates and uses knowledge is
the one which provides an environment that nurtures research and development
(R&D), which results in new goods, new processes, new knowledge, and hence
is a major source of technical progress.
4.
A modern and adequate information
infrastructure
The impact of ICTs on the economic growth
can be observed by looking at the multifactor productivity factor (MPF)
measurement. The productivity growth by ICTs is usually through two main
channels: First, greater investment in ICT, which boosts labour productivity
growth by raising the stock of capital available to each worker, and secondly,
rapid productivity growth occurring in the production of ICT goods.
Intellectual capital
Most leaders these days are aware of the importance of human
capital. It’s the intangible value their employees contribute to their
organization.
But the most successful businesses are those that know how to leverage
their intellectual capital.
Intellectual capital is the total value of all of an organization’s
intangible assets. It includes human capital but goes beyond it. It takes a
holistic view of all the aspects of a business that give it a competitive
advantage.
This includes original data, customer satisfaction, employee
experience, and internal processes and structures.
Companies that measure their intellectual capital can use it to:
- Create more value
- Improve products and services
- Drive sales and growth
- Increase efficiency
- And, deepen customer and partner relationships
That last point is key. Managing intellectual capital well can actually
create more intellectual capital. That makes you tough to compete against.
So, let’s take a deep dive into what intellectual capital is, examples
of intellectual capital, and how to increase your intellectual capital.
Intellectual assets include:
- Knowledge
and skills of individual team members
- Research
and innovation capabilities
- Organizational structure
- Information systems
- Training
- Any other intellectual
property created by the company
Intellectual capital also includes strong relationships with customers
and strategic partnerships with other businesses.
It can also cover product development, any innovation or discovery made
by the company, and any patents or copyrights that it owns.
Original research and investigations also contribute to a company's
intellectual capital. So do any data generated by the research.
The impact of intellectual capital should not be underestimated.
Understanding it can help you improve your human resources management.
It can inform your decision-making processes and help you
create strategies that improve your business. Building intellectual capital
can improve business performance by contributing to the knowledge economy.
Organizations can improve their intellectual capital by:
- Creating new products
- Carrying out research
- Acquiring patents
- Hiring better employees
- Encouraging intellectual
curiosity
- Improving training
programs
What are the 3 major categories of intellectual capital?
Intellectual capital is broadly divided into three main categories:
- Human capital
- Relational capital
- Structural capital
Let’s take a closer look at each one.
Human capital
Human capital refers to the value of the human resources within an
organization. It includes all the skills, know-how, core competencies, and
experience of each employee. This value isn’t reflected in the company’s
balance sheet.
Organizations with strong human capital management usually
have high employee satisfaction and retention. They also tend to score
high on employee experience.
Employee turnover causes the company to lose skills and knowledge. This
decreases both its human and intellectual capital. Employee retention is
therefore crucial for strengthening intellectual capital.
Performance reviews can help boost human capital, as they help
identify skills gaps. They can then address those gaps through:
- Professional
development
- Reskilling
- Upskilling
Relational capital
Relational capital refers to the value of the relationships the
organization has with:
- Customers
- Suppliers
- Employees
- Investors
- Other actors in the sector,
including its competitors
Customer capital falls under relational capital. It refers to the
customer relationships and levels of satisfaction among existing customers.
Relational capital also refers to the company’s reputation among
potential customers. It includes branding, brand awareness, and brand perception.
But relational capital doesn’t only refer to customers. It also includes
the company's reputation among investors, stakeholders, suppliers, and
competitors.
Structural capital
Structural capital refers to the organizational structures and
systems for the management of:
- Employees
- Assets
- Finances
- Products and services
- Customers
- Suppliers
Structural capital is the behind-the-scenes stuff that is the secret of
a truly successful business.
This includes its:
- Policies and processes
- Vision
- Mission
- Value statement
- Company culture
- HR management
- Financial management
- Tools
- Ways of working
- Best practices
What are examples of intellectual capital?
Since intellectual capital is intangible, you might be wondering what
actually classifies as intellectual capital. So, let’s take a look at a few
examples for each component of intellectual capital.
Human capital examples
Examples of human capital include the most in-demand
skills in a given industry. They include technical skills, soft skills,
and personal attributes.
Examples of technical skills include:
- Software development
- Project management
- Marketing
- Coding
- Sales
- UX design
- Artificial intelligence and
machine learning
- Social media management
- Healthcare
- Video and audio editing
- Software development
Examples of soft skills include:
- Communication
- Listening
- Leadership
- Empathy
- Problem-solving skills
- Creativity
- Persuasion
- Time management
- Collaboration
- Adaptability
Personal attributes include:
- Mental fitness
- Physical health
- Experience
- Resilience
- Loyalty
- Punctuality
Relational capital examples
Relational capital refers to the network of employees, leaders, and
external stakeholders that enables an organization to carry out its work. This
includes external partners and anyone who makes the company’s work possible.
For example, the relational capital of a legal firm may comprise:
- Attorneys
- Clients
- Employees
- Leadership team
- Board members
- Referral partners
- Intermediaries
- Suppliers
Whereas the relational capital of a PR agency may comprise:
- Creative team
- Sales team
- Clients
- Leadership team
- Media partners
- Journalists
- Sector experts
- Audio-visual production
companies
- Suppliers
Relational capital also includes brand awareness. This means that
all branding, marketing, and advertising form part of a company’s relational
capital.
Structural capital examples
Structural capital is unique to each organization and will depend on the
sector it’s in. For example, the structural capital of a construction company
may include:
- Buildings such as office
buildings and warehouses
- Safety regulations
- Employee code of conduct
- Pay structure
- Employee training and
manuals
- Database of customers
- Database of suppliers
- Processes for receiving and
fulfilling orders
- Client contract templates
- Tools and machinery
- Trade secrets or proprietary
methods
- Automations
Knowledge
According
to Webster's Dictionary, knowledge is "the fact or condition of knowing
something with familiarity gained through experience or association". In
practice, though, there are many possible, equally plausible definitions of
knowledge. A frequently used definition of knowledge is "the ideas or
understandings which an entity possesses that are used to take effective action
to achieve the entity's goal(s). This knowledge is specific to the entity which
created it."
An
understanding of knowledge requires some grasp of its relationship to
information. In everyday language, it has long been the practice to distinguish
between information — data arranged in meaningful patterns — and knowledge —
which has historically been regarded as something that is believed, that is
true (for pragmatic knowledge, that works) and that is reliable.
In recent times, theoretical objections to the concept of truth (e.g., by
post-modernists) or to that of reliability (e.g., by positivists) have led to
some blurring of the distinction. The interchangeable use of information and
knowledge can be confusing if it is not made clear that knowledge is being used
in a new and unusual sense, and can seem unscrupulous insofar as the intent is
to attach the prestige of (true) knowledge to mere information. It also tends
to obscure the fact that while it can be extremely easy and quick to transfer
information from one place to another, knowledge is sticky: it is often very
difficult and slow to transfer knowledge from person to another. (C.f. the
World Bank's 1998 World Development Report on Knowledge for Development which
begins with the false assertion that knowledge travels at the speed of light.)
In
assessing attempts to define knowledge it can be helpful to remember that the
human mind has often been seen as capable of two kinds of knowledge — the
rational and the intuitive.
What
is the Data, Information, Knowledge, Wisdom (DIKW) Pyramid?
The DIKW Pyramid represents
the relationships between data, information, knowledge and wisdom. Each
building block is a step towards a higher level - first comes data, then is
information, next is knowledge and finally comes wisdom. Each step answers
different questions about the initial data and adds value to it. The more we
enrich our data with meaning and context, the more knowledge and insights we
get out of it so we can take better, informed and data-based decisions.
Knowledge Pyramid, Wisdom Hierarchy and
Information Hierarchy are some of the names referring to the popular
representation of the relationships between data, information, knowledge and
wisdom in the Data, Information, Knowledge, Wisdom (DIKW) Pyramid.
Like other hierarchy models, the
Knowledge Pyramid has rigidly set building blocks – data comes first,
information is next, then knowledge follows and finally wisdom is on the top.
Each step up the pyramid answers
questions about the initial data and adds value to it. The more questions we
answer, the higher we move up the pyramid. In other words, the more we enrich
our data with meaning and context, the more knowledge and insights we get out
of it. At the top of the pyramid, we have turned the knowledge and insights
into a learning experience that guides our actions.
How to
Scale Data Up the Knowledge Pyramid
So, let’s have a look at the individual
components of the Knowledge Pyramid and how we move from one to the next.
Data
Data is a collection of facts in a raw or unorganized
form such as numbers or characters.
However, without context, data can mean little. For
example, 12012012 is just a sequence of numbers without
apparent importance. But if we view it in the context of ‘this is a date’, we
can easily recognize 12th of January, 2012.
By adding context and value to the numbers, they now have more meaning.
In this way, we have transformed the raw sequence of
numbers into
Information
Information is the next building block of the DIKW
Pyramid. This is data that has been “cleaned” of errors and further processed
in a way that makes it easier to measure, visualize and analyze for a specific
purpose.
Depending on this purpose, data processing can
involve different operations such as combining different sets of data
(aggregation), ensuring that the collected data is relevant and accurate
(validation), etc. For example, we can organize our data in a way that exposes
relationships between various seemingly disparate and disconnected data points.
More specifically, we can analyze the Dow Jones index performance by creating a
graph of data points for a particular period of time, based on the data at each
day’s closing.
By asking relevant questions about ‘who’, ‘what’,
‘when’, ‘where’, etc., we can derive valuable information from the data and
make it more useful for us.
But when we get to the question of ‘how’, this is
what makes the leap from information to
Knowledge
“How” is the information, derived from the collected
data, relevant to our goals? “How” are the pieces of this information connected
to other pieces to add more meaning and value? And, maybe most importantly,
“how” can we apply the information to achieve our goal?
When we don’t just view information as a description
of collected facts, but also understand how to apply it to achieve our goals,
we turn it into knowledge. This knowledge is often the edge that enterprises
have over their competitors. As we uncover relationships that are not
explicitly stated as information, we get deeper insights that take us higher up
the DIKW pyramid.
But only when we use the knowledge and insights
gained from the information to take proactive decisions, we can say that we
have reached the final – ‘wisdom’ – step of the Knowledge Pyramid.
Wisdom
Wisdom is the top of the DIKW hierarchy and to get
there, we must answer questions such as ‘why do something’ and ‘what is best’.
In other words, wisdom is knowledge applied in action.
We can also say that, if data and information are
like a look back to the past, knowledge and wisdom are associated with what we
do now and what we want to achieve in the future.
Types of Knowledge
When creating a knowledge
management strategy, the different types of knowledge must be taken into
account in order for the end result (of creating a knowledge base) to be
as useful as possible in both the short and long terms. So how can you best
understand things like explicit vs tacit knowledge?
What are the 7
types of knowledge?
- Explicit
knowledge
- Implicit
knowledge
- Tacit knowledge
- Procedural
knowledge
- Declarative
knowledge
- A Posteriori
knowledge
- A Priori
knowledge
The 7 types of
knowledge
1. Explicit
knowledge
Explicit knowledge
is knowledge covering topics that are easy to systematically document (in
writing), and share out at scale: what we think of as structured information.
When explicit knowledge is well-managed, it can help a company make better
decisions, save time, and maintain an increase in performance.
These types of
explicit knowledge are all things that have traditionally been what has been
captured in a knowledge base or as part of a knowledge management strategy.
It’s formalized documentation that can be used to do a job, make a decision, or
inform an audience.
Explicit
knowledge examples
Companies can share
explicit knowledge by maintaining well-documented information in the
company knowledge base. Examples of explicit knowledge include things like FAQs, instructions,
raw data and related reports, diagrams, one-sheets, and strategy slide decks.
2. Implicit
knowledge
Implicit knowledge
is, essentially, learned skills or know-how. It is gained by taking explicit
knowledge and applying it to a specific situation. If explicit knowledge is a
book on the mechanics of flight and a layout diagram of an airplane cockpit,
implicit knowledge is what happens when you apply that information in order to
fly the plane.
Implicit knowledge
is gained when you learn the best way to do something. You can then take that
experience and synthesize it with other learned information in order to solve
an entirely new problem.
This type of
knowledge has traditionally been excluded from formal knowledge bases, as it
can be difficult to document and capture in a scalable way. In order to add it
to a knowledge base, think of it this way: “What new thing did I learn, would
it be useful to others, and how can I explain it?” Here is an example of documented implicit knowledge:
Implicit
knowledge examples
While implicit
knowledge can be more difficult to document, some examples of implicit
knowledge could include an individual’s ability to prioritize tasks or juggle
projects to meet deadlines.
3. Tacit knowledge
Tacit knowledge is
intangible information that can be difficult to explain in a straightforward
way, such as things that are often “understood” without necessarily being said,
and are often personal or cultural. This type of knowledge is informal, learned
with experience over time, and usually applies to a specific situation.
When it can be
captured (if it’s not, for instance, a feeling), it should be added to a
knowledge base. Doing so makes it easy to share expertise gained over time with
others who may need it.
Tacit
knowledge examples
Tacit knowledge can
be difficult to transfer and usually isn’t able to be stored. An example of
tacit knowledge could be a salesperson’s ability to know the perfect time to
give their pitch during a meeting. A combination of experience, reading social
cues, and other personal factors must come together to form that unique bit of
knowledge.
Since this knowledge
is learned with experience over time, companies can help employees strengthen
their tacit knowledge by sharing techniques and tips on handling certain
situations. An example of this could be a list of phrases for sales leads to
look out for when dealing with customer complaints. The sales lead could better
understand how to ‘read’ or rectify a situation by being prepared with possible
conversation outcomes.
4. Declarative
knowledge
Declarative
knowledge which can be also understood as propositional knowledge, refers to
static information and facts that are specific to a given topic, which can be
easily accessed and retrieved. It’s a type of knowledge where the individual is
consciously aware of their understanding of the subject matter.
This type of
knowledge is typically stored in documentation or databases and focuses more on
the 'who', 'what', 'where', and 'when' behind information and less on the 'how'
or 'why'. When documented, it creates the foundation for understanding the
subject matter and can help companies improve how they share procedural and
explicit knowledge.
Declarative
knowledge examples
Some examples of
declarative knowledge include an individual's ability to know what the company
goals are for the year. The individual can also understand how performance will
be measured due to reading the company newsletter where the goals and metrics
are shared across teams.
5. Procedural
knowledge
Procedural knowledge
focuses on the ‘how’ behind which things operate, and is demonstrated
through one’s ability to do something. Where declarative knowledge focuses more
on the ‘who, what, where, or when’, procedural knowledge is less articulated
and shown through action or documented through manuals.
Procedural
knowledge examples
Stemming from the
root “procedure”, an example of procedural knowledge could include a standard operating procedure on how to do
specific tasks, or use certain equipment in an organization.
6. A Posteriori
knowledge
A posteriori
knowledge is a subjective type of knowledge that is gained from individual
experience. While this type of knowledge isn’t one to be documented on a
company’s knowledge base, it still plays a critical role in the success of
teams. This kind of knowledge gives individuals the ability to know their
strengths and weaknesses that stem from their experiences, and can help
companies diversify their teams skill set.
A
Posteriori knowledge examples
Due to a posteriori
knowledge being derived from individual experiences, some examples of a
posteriori knowledge could include an individual's ability to lead teams based
on their previous roles in management, or the ability to de-escalate or diffuse
tense situations.
7. A Priori
knowledge
A priori knowledge
is the opposite of posteriori knowledge, and is gained independent of
experience or evidence. This type of knowledge is often shared through logical
reasoning, or one's ability to think abstractly. Although a priori knowledge
isn’t necessarily documented, it’s often shown in the form of team’s ability to
understand and reason when faced with situations.
A Priori
knowledge examples
Examples of a priori
knowledge could include one’s ability to excel in mathematics, or logical
reasoning due to their natural ability to understand and interpret information
without needing further explanation.
Knowledge Management
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.
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
– 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 – 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 and its application
Knowledge
and information have been commonly proposed to constitute a key part of the
unique resources for every organization and this has necessitated the practice
of knowledge management in modern day businesses. Many companies are currently putting together
methods that convert tacit and implicit knowledge into explicit knowledge, in
forms that can be coded, stored and transmitted, that way the knowledge can be
used by others in similar scenarios. Organizations want to act intelligently
and knowledge management has presented a platform to achieve this by helping
them deliver creative products and services which in time past was not
achievable due to limited knowledge. Managers now recognize that this knowledge
needs to be diffused and shared within the organization, hence the need to
create an enabling environment to achieve knowledge sharing and diffusion.
Several famous companies currently utilize knowledge management systems form
which they retrieve information from previous transactions and customers as
often as needed. Ford Motors Company (FMC) has been a long-time practitioners
of knowledge management in their product development process. They started by
using web-based knowledge management system to regulate quality standard across
all its product lines and this helped them maintain quality and avoid warranty
costs. General Electric (GE) is another successful implementer of knowledge
management. GE operates a people-based knowledge management system (Corporate
Executive Council) which consists of council of management staff that meet for
two days on a regular basis to share information and experience. Through this knowledge sharing process,
information on the business success factors are made known to GE‟s management. Amazon has also successfully implemented a
web-based knowledge management system.
Whether
you’re a large enterprise or a government agency, these knowledge management
applications are core building blocks for taking advantage of your most
essential information:
1. Intranet Search engine
Being able
to find what you need inside a company isn’t always easy. Company intranets are an excellent starting point for
making information available, but not every search box
is equal. Accessing information often depends on users knowing where something
is located (or who to call to find it). One of the most important knowledge
management applications, therefore, is a strong, semantic search engine that can reach all of your
enterprise content, and retrieve the precise items
that you’re looking for—marketing reports, product data sheets,
customer information, patent records, etc. — with the same speed and effectiveness that you would expect
from a typical internet search.
2. Document classification based on customized taxonomy
Simply
storing the company knowledge is useless: Effective enterprise search, therefore, starts with
deploying classification and taxonomy development tools rooted in an
understanding of language. The
taxonomy must reflect your organization’s unique vocabulary—the acronyms,
products and project code names that your internal users know by heart—in order
to be truly useful; a full understanding of meaning can help distinguish
between different contextual uses of information. Both are essential for
delivering precise information for search and other applications. For example, an energy company has its own
language, which requires a specific and
customized taxonomy that is able to associate content to the classes and nodes
with great precision.
3. Entity extraction
Identifying entities contained in content—people, places, locations, organizations,
as well ascustomized organizational entities— can provide a useful view of
unknown data sets by immediately revealing the who, what and were contained in
your information. Entity extraction is
an essential knowledge management application that helps transform unstructured data to data that is
structured, and therefore machine readable and available
for standard processing that can be applied for a number of business activities.
4. Customer feedback analysis
The opinions expressed online by your customers and users contain
valuable insight about
your companies, brands, competitors, products and services. Being able to
analyze the signals and feedback left by consumers on social media, forums,
reviews or classic survey mechanisms requires truly understanding what is being
expressed and how. Semantic-powered
knowledge management applications can cut through the slang, jargon and use of
different languages to provide strategic value from customer feedback.
knowledge management software solutions?
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Strategies of Knowledge Management
There are
different strategies to capture knowledge and they include the “push” and the
“pull” strategies. First, it must be made clear that knowledge can be captured
before, during, and after the processes actualize. Hence, there need to be
incentives for employees to contribute to the knowledge base. The push strategy
focuses on making employees contribute to the Knowledge Management system in a
proactive manner wherein individuals strive to contribute to the Knowledge
Management system and the knowledge base without any prodding or persuasion.
This approach is also known as the codification approach to Knowledge
Management.
Another
strategy is the pull strategy wherein individuals who need knowledge make
explicit requests to those who possess knowledge. In this case, the experts are
called upon request and hence the knowledge seeker pulls the information rather
than the expert pushing the information. This approach is known as the
personalization approach to Knowledge Management.
Motivations
for Knowledge Management
There are
several motivations that drive organizations to implement Knowledge Management
systems. As discussed in the introductory article, the need to have a Knowledge
Management system has become mandatory for certifications as well as to have
sources of competitive advantage. The most compelling motivation for having a
Knowledge Management system is that organizations do not have to reinvent the
wheel and subsequent iterations of the same process can be done in a more
efficient and productive manner. Indeed, the reuse of knowledge leads to
synergies between the different processes and helps in solving intractable
problems.
Apart from
these imperatives, Knowledge Management helps organizations to manage the
organizational arteries better as increased exchanges of information between
different individuals’ results in greater connectivity and more network
effects.
In other
words, Knowledge Management systems help in managing innovation and
organizational learning. This is a direct and beneficial effect of Knowledge
Management and one, which is driving more and more companies to have working
and efficient Knowledge Management systems.
Knowledge
System Testing & Deployment
1.
Key Definitions
➢
Logical testing answers the question, “Are we
building the system right?”
➢
User acceptance testing checks the system’s behavior
in a realistic environment. Answers the question, “Have we built the right
system?”
➢
Deployment refers to the physical transfer of the
technology to the organization’s operating unit
2.
Issues to Consider in Testing
➢
Subjective nature of tacit knowledge.
➢
Absence of reliable specifications make
knowledge-based testing arbitrary
➢
Problem of establishing consistency and correctness
➢
Negligence in testing
➢
Lack of time for system testing
➢
Complexity of user interfaces
3.
Attributes in Logical Testing
➢
Circular
➢
Completeness
➢
Confidence
➢
Correctness
➢
Consistency/inconsistency
➢
Redundancy
➢
Reliability
➢
Subsumption errors
4.
Key Testing Errors
➢
Circular errors tend to be contradictory in meaning
or logic
➢
Redundancy errors offer different approaches to the
same problem; duplication of knowledge
➢
Unusable knowledge is knowledge that comes up if the
conditions succeed or fail
➢
Subsumption errors in rules, if one rule is true, one
knows the second rule is always true
➢
Inconsistent knowledge, where the same inputs yield
different results
5.
Steps in User Acceptance Testing
➢
Select a person or a team for testing
➢
Decide on user acceptance test criteria
➢
Develop a set of test cases unique to the system
➢
Maintain a log on various versions of the tests and
test results
➢
Field-test the system
6.
Select Criteria for User Acceptance
Testing
➢
Accuracy and correctness of outcome
➢
Adaptability to changing situations
➢
Adequacy of the solutions
➢
Appeal and usability of the system
➢
Ease of use
➢
Face validity or credibility
➢
Performance based on expectations
➢
Robustness
➢
Technical/operational test
7.
Managing the Testing Phase
➢
Decide when, what, how, and where to evaluate the
knowledge base
➢
Decide who should do the logical and user acceptance
testing
➢
Draft a set of evaluation criteria in advance
➢
Decide what should be recorded during the test
➢
Review training cases, whether they are provided by
the expert, the knowledge developer, or the user
➢
Test all rules for Type I and Type II errors
8.
Issues Related to Deployment
➢
Selection of the knowledge base problem
➢
Ease of understanding the KM System
➢
Knowledge transfer
➢
Integration alternatives
➢
The issue of maintenance
➢
Organizational factors
9.
Selection of the Knowledge Base Problem
➢
System success may be assured if:
✓
User has prior experience with computer applications
✓
User has been involved in the building of the KM
system
✓
Payoff from the KM system is high and measurable
✓
KM system can be implemented without much difficulty
✓
Champion has been supporting the system all along
Success Factors in KM System Deployment
Integration Alternatives
➢
Technical integration through the
company’s LAN or existing information system
infrastructure
➢
Knowledge-sharing integration when the KM
system is usable company-wide
➢
Decision-making flow integration when the
system matches the user’s style of
thinking
➢
Workflow reengineering when the KM system
triggers changes in the workplace
Organizational Factors
➢
Top management support
➢
Support of the work of the champion
➢
Ensure a clean and supportive
organizational climate
➢
De-emphasize role of politics
➢
Knowledge developer should remain neutral
within the political arena
➢
Return on investment
User Training and Deployment
➢
Preparing for KM system training via
advance demos and easy to follow training
➢
Combating resistance to change
➢
Watch for knowledge hoarders
➢
Watch for troublemakers and narrow-minded
“superstars”
➢
Look for resistance via projection,
avoidance, and aggression
Postimplementation Review
➢
Watch for quality of decision making
➢
Reassess attitude of end users
➢
Review cost of knowledge processing
➢
Revisit change in accuracy and timeliness
of decision making
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