ITIL® Intermediate RCV Tutorial : Knowledge Management

Knowledge Management

Welcome to lesson 8 of the ITIL Intermediate RCV tutorial, which is a part of the ITIL Intermediate RCV Foundation Certification course. This learning unit deals with how the KM process contributes to RCV practices.

Let us look at the objectives of this lesson.


By the end of this ‘Knowledge Management’ lesson, you will be able to:

  • Understand the complete overview of the purpose, objectives, scope, and importance of KM as a process, and the benefits of deploying a service knowledge management system (SKMS).

  • Discuss the basic layers of the KM concept using the data-information-knowledge-wisdom (DIKW) structure, as well as what constitutes an effective KM strategy with practical techniques for enabling knowledge transfer.

  • Explain the KM policies, principles, concepts, activities, methods and in relation to RCV practices and the importance of the stakeholder groups.

  • Review the efficient use of KM critical success factors and key performance indicators.

In the next section, we will look at the purpose and objective of the knowledge management process.

Planning to get ITIL Intermediate RCV Certified? Check out our course here!

Purpose and Objectives of Knowledge Management

The purpose of the knowledge management process is to:

  • share perspectives, ideas, experience and information

  • to ensure that these are available in the right place and at the right time to enable informed decisions

  • to improve efficiency by reducing the need to rediscover knowledge.

The objectives of knowledge management are to:

  • Improve the quality of management decision making by ensuring that reliable and secure knowledge, information, and data is available throughout the service lifecycle

  • Enable the service provider to be more efficient and improve quality of service, increase satisfaction and reduce the cost of service by reducing the need to rediscover knowledge

  • Ensure that staff have a clear and common understanding of the value that their services provide to customers and the ways in which benefits are realized from the use of those services

  • Maintain a service knowledge management system (SKMS) that provides controlled access to knowledge, information, and data that is appropriate for each audience

  • Gather, analyze, store, share, use and maintain knowledge, information, and data throughout the service provider organization.

In the next section, we will look at the scope of the knowledge management process.

Scope of Knowledge Management

Knowledge Management is a whole lifecycle-wide process in that it is relevant to all lifecycle sectors and hence is referenced throughout ITIL from the perspective of each publication. It is dealt with to some degree within other ITIL publications, but this chapter sets out the basic concept, from a Service Transition focus.

Knowledge Management includes oversight of the management of knowledge, the information and data from which that knowledge derive Knowledge management excludes detailed attention to the capturing, maintenance and use of asset and configuration data.

Let us understand Knowledge management value to the business in the next section.

Knowledge Management Value to Business

Successful management of data, information, and knowledge will deliver:

  • Conformance with legal and other requirements, e.g., company policy, codes of professional conduct

  • Documented requirements for retention of each category of data, information, and knowledge

  • Defined forms of data, knowledge, and information in a fashion that is easily usable by the organization

  • Data, information, and knowledge that is current, complete and valid

  • Data, information, and knowledge to the people who need it when they need it

  • Disposal of data, information, and knowledge as required.

Knowledge management provides value to all stages of the service lifecycle by providing secure and controlled access to the knowledge, information, and data that is needed to manage and deliver services. Knowledge management is especially significant within service transition since relevant and appropriate knowledge is one of the key service elements being transitioned.

Examples where successful transition rests on appropriate knowledge management include:

  • User, service desk, support staff, and supplier understanding of the new or changed service, including knowledge of errors signed off before deployment, to facilitate the roles within that service

  • Awareness of the use of the service, and the discontinuation of previous versions

  • Establishment of the acceptable risk and confidence levels associated with the transition, e.g., measuring, understanding, and acting correctly on results of testing and other assurance results.

In the next section, let us see how Knowledge management value to the business with respect to Service Transition.

Knowledge Management Value to Business w.r.t Service Transition

Effective knowledge management is a powerful asset for people in all roles across all stages of the service lifecycle. It is an excellent method for individuals and teams to share data, information, and knowledge about all facets of an IT service. The creation of a single system for knowledge management is recommended.

Specific application to service transition domain can be illustrated by considering the following examples:

  • Blurring of the concept of intellectual property and information when engaged in sourcing and partnering, therefore new approaches to controlling ‘knowledge’ must be addressed and managed during service transition

  • Knowledge transfer often being a crucial factor in facilitating the effective transition of new or changed services and essential to operational readiness

  • Training of users, support staff, suppliers and other stakeholders in new or changed services\

  • Recording of errors, faults, workarounds, etc. detected and documented during the service transition stage of the service lifecycle

  • Capturing of implementation and testing information

  • Re-using previously developed and quality assured testing, training, and documentation

  • Compliance with legislative requirements, e.g.,Sarbanes-Oxley, and conformance to standards such as ISO 9000 and ISO/IEC 20000

  • Assisting decisions on whether to accept or proceed with items and services by, delivering all available relevant information (and omitting unnecessary and confusing information) to key decision makers.

Let us now look into the policies of Knowledge management.

Knowledge Management Policies

Knowledge management policies are required to guide all staff in the behaviors needed to make knowledge management effective. Policy statements will be very dependent on the culture of the organization but typically might include the following:

  • Knowledge and information needed to support the services will be stored in a way that allows them to be accessed by all staff when and where they are needed.

  • All policies, plans, and processes must be reviewed at least once per year.

  • All knowledge and information should be created, reviewed, approved, maintained, controlled and disposed of following a formal documented process.

In the next section, we will learn about DIKW structure of this process.

The Data to Information to Knowledge to Wisdom (DIKW) Structure

Knowledge management is typically displayed within the Data-to-Information-to-Knowledge-to- Wisdom (DIKW) structure. The use of these terms is set out below:


Data is a set of discrete facts. Most organizations capture significant amounts of data in highly structured databases such as service management and service asset and configuration management tools/systems and databases.

The key knowledge management activities around data are the ability to:

  • Capture accurate data

  • analyze, synthesize, and then transform the data into information Identify relevant data and concentrate resources on its capture

  • Maintain integrity of the data

  • Archive and purge data to ensure optimal balance between availability of data and use of resources.

An example of data is the date and time at which an incident was logged.


Information comes from providing context to data. Information is typically stored in semi-structured content such as documents, email, and multimedia. The key knowledge management activity around information is managing the content in a way that makes it easy to capture, query, find, re-use, and learn from experiences so that mistakes are not repeated, and work is not duplicated.

An example of information is the average time to close priority 2 incidents. This information is created by combining data from the start time, end time and priority of many incidents.


Knowledge is composed of the tacit experiences, ideas, insights, values, and judgments of individuals. People gain knowledge both from their own and from their peers’ expertise, as well as from the analysis of information (and data). Through the synthesis of these elements, new knowledge is created. Knowledge is dynamic and context-based. Knowledge puts information into an ‘ease of use’ form, which can facilitate decision-making.

In service transition, this knowledge is not solely based on the transition in progress but is gathered from the experience of previous transitions, awareness of recent and anticipated changes and other areas, which experienced staff will have been unconsciously collecting for some time.

An example of knowledge is that the average time to close priority 2 incidents has increased by about 10% since a new version of the service was released.


Wisdom makes use of knowledge to create value through correct and well-informed decisions. Wisdom involves having the application and contextual awareness to provide strong common-sense judgment. An example of wisdom is recognizing that the increase in time to close priority 2 incidents is due to poor-quality documentation for the new version of the service.

Let’s look at an illustration in the next section.

The Flow from Data to Wisdom

The picture shown below depicts the flow of knowledge management structure from data to wisdom and at the same time creating a link between context and understanding in every step.

In the next section let us learn about the SKMS.

The Service Knowledge Management System (SKMS)

So, what is SKMS?

Specifically, within IT service management, knowledge management will be focused on the service knowledge management system (SKMS), which is concerned, as its name implies, with knowledge. Underpinning this knowledge will be a considerable quantity of data, which will also be held in the SKMS. One very important part of the SKMS is the configuration management system (CMS).

The CMS describes the attributes and relationships of configuration items, many of which are themselves knowledge, information or data assets stored in the SKMS. The relationship between the CMS and the SKMS is shown in the figure below.

This figure is a very simplified illustration of the relationship of the three levels, with configuration data being recorded within the CMDB, and feeding through the CMS into the SKMS. The SKMS supports delivery of the services and informed decision-making.

Let us look at few examples of items that should be stored in SKMS in the next section.

Examples of Items that Should be Stored in an SKMS

The SKMS will contain many different types of data, information, and knowledge.

Examples of items that should be stored in an SKMS include:

  • The service portfolio

  • The configuration management system (CMS)

  • The definitive media library (DML)

  • Service level agreements (SLAs), contracts, and operation level agreements (OLAs)

  • The information security policy

  • The supplier and contract management information system (SCMIS), including suppliers’ and partners’ requirements, abilities, and expectations

  • Budgets

  • Cost models

  • Business plans

  • CSI register

  • Service improvement plans

  • The capacity plan and capacity management information system (CMIS)

  • The availability plan and availability management information system (AMIS)

  • Service continuity invocation procedure

  • Service reports

  • A discussion forum where practitioners can ask questions, answer each other’s questions, and search for previous questions and answers

  • An indexed and searchable repository of project plans from previous projects

  • A known error database provided by a vendor which lists common issues in their product and how to resolve them

  • Skills register, and typical and anticipated user skill levels

  • Diagnostic scripts

  • A managed set of web-based training courses

  • Weather reports needed to support business and IT decision-making (for example, an organization may need to know whether rain is likely at the time of an outdoor event)

  • Customer/ or user personal information, for example: to support a blind user who needs to have specific support from the service desk.

Many of these knowledge and information assets are configuration items. Changes to CIs must be under the control of the change management process, and details of their attributes and relationships will be documented in the CMS.

In the next section, we will look at an example of data and information in SKMS.

Examples of Data and Information in the SKMS

The picture shown below is the depiction of data and information in SKMS, and we have discussed on these elaborately in the last two sections.

Data and Information in SKMS

Next, let’s discuss how the KM strategy can be effective?

Effective Knowledge Management Strategy

To make the Knowledge management strategy effective an overall strategy for knowledge management is required.

Where there is an organizational approach to knowledge management, initiatives within service transition, IT service management, or other groupings should be designed to fit within the overall organizational approach.

In the absence of an organizational knowledge management approach, appropriate steps to establish knowledge management within service transition or within IT service management will be required. Even in this case, it is important to manage knowledge with as wide a scope as practicable – covering direct IT staff, users, third party support and others likely to contribute to, or make beneficial use of, the knowledge.

The strategy – either in place in the wider organization or being developed – will address:

  • The governance model, including the requirements of software asset management, Sarbanes-Oxley, ISO/IEC 20000, ISO/IEC 38500 and COBIT if these are applicable

  • Organizational changes underway and planned and consequential changes in roles and responsibilities

  • Establishment of roles and responsibilities and on-going funding

  • Policies, processes, procedures, and methods for knowledge management Technology and other resource requirements

  • Performance measures.

Moving on, let’s look at the steps involved in knowledge identification, capture, and transfer.

Steps In Knowledge Identification, Capture, and Maintenance

Specifically, the strategy will identify and plan for the capture of relevant knowledge and the consequential information and data that will support it.

The steps to delivering this include:

  • Assisting an organization to identify knowledge that will be useful

  • Creating a knowledge taxonomy and categorizing knowledge

  • Designing a systematic process for organizing, distilling, storing, and presenting information in a way that improves people’s comprehension in a relevant area

  • Accumulating knowledge through processes and workflow

  • Generating new knowledge

  • Accessing valuable knowledge from outside sources

  • Capturing external knowledge and adapting it – data, information, and knowledge from diverse sources such as databases, websites, employees, suppliers, and partners

  • Reviewing stored knowledge to ensure that it is still relevant and correct

  • Updating, purging, and archiving knowledge.

We have looked at the steps for knowledge identification, capture, and maintenance. But do you remember techniques for knowledge transfer?

Techniques for Enabling Knowledge Transfer

During the service lifecycle, an organization needs to focus on retrieving, sharing, and utilizing its knowledge through problem-solving, dynamic learning, strategic planning, and decision making. To achieve this, knowledge needs to be transferred to other people and to other parts of the organization at specific points in the lifecycle.

Many of the service management processes will link into this, for example allowing the service desk to have optimum knowledge and understanding at the point of any service transition into support. They will be reliant on information sourced from release and deployment management such as known errors going into live use but which are not show stoppers for the release schedule, or diagnostic scripts from any of the technical support teams.

Links with HR, facilities and other supporting services need to be established, maintained and utilized. There must be an effective and efficient mechanism to allow people to search and retrieve relevant knowledge. The challenge is often the practical problem of getting knowledge from one person or one part of the organization to another.

It is more than just sending an email! Knowledge transfer is more complex; more accurately it is the activity through which one person or unit (e.g., a group, department, or division) is able to learn from the experience, ideas or perspective of another. Its form must be applicable for those using it, and achieve a positive rating for ‘ease of use.’

The transfer of knowledge can be observed through changes in the knowledge or performance of recipients, at an individual or unit level. An analysis of the knowledge gap (if any) within the organization should be undertaken. The gap will need to be researched and established by direct investigation of staff’s understanding of the knowledge requirements for them to deliver their responsibilities compared with their actual observed knowledge.

This can be a difficult task to deliver objectively and, rather than risk resentment or suspicion. It is often worth seeking skilled and experienced support to build this. The output from the knowledge gap exercise will form the basis for a communications improvement plan, which will enable planning and measurement of success in the communication of knowledge.

Traditionally, knowledge transfer has been based on formal classroom training and documentation. In many cases, the initial training is provided to a representative from a workgroup who is then required to cascade the knowledge to working colleagues. Other techniques are often appropriate and form useful tools in the service transition armory.

Techniques worth considering include the following:

Learning styles

Different people learn in different ways, and the best method of transferring and maintaining knowledge within the service management and user community will need to be established.

Knowledge visualization

This aims to improve the transfer of knowledge by using a computer- and non-computer-based visuals such as diagrams, images, photographs, and storyboards. It focuses on the transfer of knowledge between people and aims to transfer insights, experiences, attitudes, values, expectations, perspectives, opinions, and predictions by using various complementary visualizations.

Dynamic forms of visualization such as educational animation have the potential to enhance understanding of systems that change over time.

Driving behavior

Knowledge transfer aims to ensure that staff is able to decide on the correct actions to deliver their tasks in any foreseeable circumstance. For predictable and consistent tasks, the procedure can be incorporated within software tools that the staff use for those tasks. These procedures then drive behavior in an accepted way.

Seminars, webinars, and documentation

Formally launching a new or changed service can create an ‘event’ that enhances the transfer of knowledge. Technology-based events such as webinars offer the ability to provide a high-profile knowledge delivery mechanism with the ability to retain it online and deliver it subsequently to other locations and new staff.

Internet and intranet portals can convey equivalent messages in an ongoing fashion and allow discussion forums to question and develop knowledge.

Journals and newsletters

Regular communication channels, once established, are useful in allowing knowledge to be transferred in smaller units – incrementally rather than ‘big bang’ can be easier to absorb and retain. They also allow for progressive training and adaptation to circumstance and time periods. Crucially, these techniques can be made entertaining and targeted at specific groups.

Discussion forums and social media

There are many different tools that can provide informal channels to allow consumers of knowledge also to create, update, and share knowledge based on their own experiences and perspectives.

Managing Data, Information, and Knowledge

Knowledge rests on the management of the information and data that supports it. To be efficient, this process requires an understanding of some key process inputs, such as how the data, information, and knowledge will be used.

This includes an understanding of:

  • What knowledge is necessary, based on which decisions must be made and how services should be supported

  • Which conditions need to be monitored (changing external and internal circumstances, ranging from end-user demand, legal requirements through to weather forecasts)

  • What data is available (what could be captured), as well as rejecting possible data capture as infeasible; this input may trigger justification for expenditure or changes in working practices designed to facilitate the capture of relevant data that would otherwise not be available

  • The cost of capturing and maintaining data, and the value that data is likely to bring, bearing in mind the negative impact of data overload on effective knowledge transfer

  • Applicable policies, legislation, standards and other requirements Intellectual property rights and copyright issues.

In the next section, let us learn about establishing data, information, and knowledge requirements.

Managing Data, Information, and Knowledge - Establishing Data, Information, and Knowledge Requirements

The following activities should be planned and implemented in accordance with applicable organizational policies and procedures with respect to the data and information management process. These planning and design activities are carried out during the service strategy and service design stages of the service lifecycle.

Often, data and information are collected with no clear understanding of how it will be used, and this can be costly. Efficiency and effectiveness are delivered by establishing the requirements for information. Sensible considerations, within the constraints determined as described above, might include:

  • Establishing the designated data, information, and knowledge items, their content, and form, together with the reason, e.g., technical, project, organizational, service management process, agreement, operations, and information. Data is costly to collect and often even more expensive to maintain, and so should be collected only when needed

  • Encouraging the use of common and uniform content and format requirements to facilitate better and faster understanding of the content and help with consistent management of the data, information, and knowledge resources

  • Establishing the requirements for data protection, privacy, security, ownership, agreement restrictions, rights of access, intellectual property and patents with the relevant stakeholder

  • Defining who needs access to what data, information, and knowledge as well as when they access it, including the relative importance of it at different times. For example, access to payroll information might be considered more important on the day before payroll is run than at other times of the month

  • Considering any changes to the knowledge management process through change management.

Next is to define the information architecture of managing information, data and knowledge.

Managing Data, Information, and Knowledge - Defining the Information Architecture

In order to make effective use of data, in terms of delivering the required knowledge, a relevant architecture matched to the organizational situation, and the knowledge requirements are essential.

This, in turn, rests on:

  • Creating and regularly updating a service management information model that enables the creation, use, and sharing of information that is flexible, timely and cost-effective

  • Defining systems that optimize the use of the information while maintaining data and information integrity

  • Adopting data classification schemes that are in use across the organization, and if necessary negotiating changes to enable them to deliver, within the service management area.

Where such organization-wide (or supply chain or industry sector) schemes do not exist, data classification schemes derived for use within service management should be designed with the intention of their being applicable across the organization to facilitate support for future organization-wide knowledge management.

An Architecture for Service Knowledge Management

An example of knowledge, information, and data architecture is shown in the figure.

Architecture of Service Knowledge Management

The four layers include examples of possible content at each layer. In practice, it is likely that there will be multiple tools in use, each of which presents these four layers for a more limited purpose. For example, there may be a tool that provides all four layers for the CMS, or for support of incident and problem management.

The four layers in the figure include the following example content:

The data layer includes all of the tools needed to discover, collect, protect, share, audit and archive the data, as well as all of the data items themselves.

Data items include all of the CMDBs and DMLs as well as many other data assets needed to manage the services.

The information integration layer includes tools that enable data from multiple sources to be integrated, as well as the integrated information itself.

Tools at this layer include:

  • Schema mapping

This facilitates the integration of databases by defining which fields have similar data and how this can be transformed. For example, one database may have a field called ‘CPU Type’ which contains up to 10 characters.

Another database might store the same information in a 20-character field called ‘CPUTYPE.' Schema mapping would allow these to be consolidated in the integrated database. Metadata management This manages ‘information about information,' data dictionaries, field names, access rights, etc.

  • Reconciliation

This deals with inconsistencies within and between multiple data sources – selecting preferred data when there are multiple sources, correcting data based on rules, etc.

  • Extract

This deals with getting data out of multiple sources in order to re-use it.

  • Transform

This converts data from one format to another, often based on metadata from the schema mapping. For example, names might be stored as ASCII character set but need converting to a multinational character set for use within an integrated database.

  • Mining

This extracts patterns from data in order to transform it into information – for example identifying common types of incidents from data in the free text fields in incident records.

The knowledge processing layer is where the information is converted into useful knowledge.

Tools in use at this layer may include:

  • Query and analysis tools

For example to enable identification of configuration items that may require a particular security patch.

  • Reporting tools

To assemble information into useful reports.

  • Performance management

To analyze performance and capacity data and information.

  • Modeling tools

To perform ‘what if’ analysis of data and information, identifying consequences and alternative options.

  • Monitoring and alerting tools

To identify exceptions and issues relating to the data and information.

The presentation layer provides tools to enable searching, browsing, retrieving, updating, publishing, subscribing and collaboration. At this layer, there are different views of the lower three layers, which are suitable for different audiences. This may include a wide range of dashboards, scorecards, report formats, web pages, alerts, etc.

Each view should be protected to ensure that only authorized people can see or modify the underlying knowledge, information, and data. In practice there are likely to be multiple tools, each providing this presentation for a different purpose.

The example views shown in Figure include:

  • IT governance view - Including, for example, service portfolio reports, continual improvement information, risk and issue registers.

  • Quality management view - With policies, processes, procedures, forms, templates, and checklists.

  • Services view - With service catalog, utilities, warranties, packages and service reports.

  • Asset and configuration view - Providing access to service assets, the CMS, status reports, CMDB data and other related information.

  • Service desk and support view - This may include the service catalog, users, and stakeholders, configuration items, incidents, problems, changes, releases, configurations, performance, etc.

  • Self-service view - Service and product catalogs, contacts, FAQs, procurement, incident management, access management, and request fulfilment.

This diagram must have given you a clear understanding of the KM architecture. In the next section, let us look at the procedures.

Looking to learn more about ITIL Intermediate RCV? Click to know more!

Managing Data, Information, and Knowledge - Establishing Data, Information, and Knowledge Management Procedures

When the requirements and architecture have been set up, data and information management to support knowledge management can be established. The key steps involve setting up mechanisms to:

  • Identify the service lifecycle data and information to be collected

  • Define the procedure required to maintain the data and information, and make it available to those requiring it

  • Define the activities and transformations that will be used to convert data into information and then to knowledge

  • Store and retrieve

  • Establish authority and responsibility for all required items

  • Define and publicize rights, obligations, and commitments regarding the retention of, transmission of and access to knowledge, information, and data items (based on applicable requirements and protecting security, integrity, and consistency)

  • Establish adequate backup and recovery of data and information; this should address reinstating the ability to make constructive use of information, not just the re-establishment of a database

  • Identify the requirements to review, in the light of changing technology, organizational requirements, evolving policy and legislation

  • If necessary, to adopt to changes in Information system infrastructure in the light of evolving hardware and software technology Security, service continuity, storage and capacity

  • Deal with collection and retention requirements Review stored knowledge, information, and data to ensure that it is still relevant and correct

  • Update, purge, and archive knowledge, information, and data in accordance with documented policies.

When the procedures are designed, put into effect and accepted the organization could:

  • Implement mechanisms to capture, store and retrieve the identified data from the relevant sources

  • Manage the data, information, and knowledge storage and movement, especially in line with appropriate legislation

  • Archive designated information, in accordance with the data, information, and knowledge management plan, including safely disposing of unwanted, invalid or unverifiable information according to the organization policy.

Now let us move to the next section on evaluation and improvement of managing data, information, and knowledge.

Managing Data, Information, and Knowledge - Evaluation and Improvement

As with all processes, the capture and usage of data and information to support knowledge management and decision-making requires attention to ongoing improvement, and the CSI register and service improvement plans will take as relevant input:

  • Measurement of the use made usage of the data and information management–data transactions

  • Evaluation of the usefulness of the data and information – identified by the relevance of reports produced

  • Identification of any data or information or registered users that no longer seem relevant to the organization’s knowledge requirements.

Like any other process, let us discuss the triggers, inputs, and outputs of knowledge management.

Knowledge Management Process Triggers

Knowledge management has many triggers, relating to every requirement for storing, maintaining or using knowledge, information or data within the organization.

For example:

  • Business relationship management storing the minutes of a customer meeting

  • Updates to the service catalog or service portfolio

  • Modification of a service design package

  • Creation of a new or updated capacity plan

  • Receipt of an updated user manual from a supplier

  • Creation of a customer report

  • Updates to the CSI register

In the next section, we will discuss the inputs and outputs of knowledge management.

Knowledge Management Process Inputs and Outputs

Let us discuss the inputs and outputs related to Knowledge Management.


Inputs to knowledge management include all knowledge, information, and data used by the service provider, as well as relevant business data.


The key output of knowledge management is the knowledge required to make decisions and to manage the IT services maintained within an SKMS. Crucial to knowledge management is the need to ensure that the benefits of knowledge management are understood and enthusiastically embraced within the whole organization.

Specifically, effective knowledge management depends on the committed support and delivery by most, if not all, of those working in and around IT service management. Errors within the service detected during the transition will be recorded and analyzed and the knowledge about their existence, consequences and workarounds will be made available to staff working in the service operation functions in an easy-to-use format.

In the next section, let us look at the inputs and outputs from Service operation staff.

Knowledge Management Process Inputs and Outputs - From Service Operations Staff

Front-line incident management staff, on the service desk and second-line support, are the point of capture for much of the everyday IT service management data. If these staff members do not understand the importance of their roles, then knowledge management will not be effective. Traditionally, support analysts have been reluctant to record their actions fully, feeling that this can undermine their position within the organization – allowing issues to be resolved without them.

Changing this to an attitude of appreciating the benefits (to individuals and the organization) of widely re-usable knowledge is the key to successful knowledge management. Problem-management staff will be key users of collected knowledge and typically responsible for the normalization of data captured by means of developing and maintaining scripts supporting data capture within incident management.

Next, let us look at the inputs and outputs from Transition staff.

Knowledge Management Process Inputs and Outputs - From Service Transition Staff

Service transition staff captures data of relevance through all lifecycle stages and so need to be aware of the importance of collecting it accurately and completely.

Service transition staff captures data and information:

  • Relevant to adaptability and accessibility of the service as designed, to be fed back via CSI to service design

  • Make ‘course corrections’ and other adaptations to the design required during the transition. Awareness and understanding of these will make subsequent transitions easier.

Let us now proceed to discuss the Knowledge management interfaces with other lifecycle stages.

Knowledge Management Interfaces with Other Lifecycle stages

Knowledge management has interfaces to every other service management process at every stage of the lifecycle. The SKMS can only be truly effective if all processes and activities use it to store and manage their information and data so that the maximum value can be extracted.

Even processes that manage their data and information separately should still use knowledge management concepts and activities to manage these.

It is likely that knowledge management tool selection will have an impact on tool selection for all other service management processes, and this is an important consideration when first setting up knowledge management.

In the next section let us look at the important aspects that can be looked at for understanding knowledge management.

Important Aspects of Knowledge Management to Understand

Here are few important aspects that one can consider to understand the Knowledge management process. You can go through these pointers given below, and start relating to topics discussed so far on data, information, and knowledge.

  1. How does it relate to other data, information, and knowledge?

  2. Where and how is it stored?

  3. Who is responsible for collecting, updating and maintaining it?

  4. What legal, regulatory or governance considerations apply to it?

  5. How long is it needed for, and how will it be consolidated, archived or deleted when it is no longer needed?

  6. Who should be allowed to access it? Where from? When?

  7. Who should be allowed to change it?

  8. Does it need to be audited, if so how, who by and how often?

Now, let us proceed to understand the different Critical Success Factors (CSFs) and Key Performance Indicators (KPI) of the Knowledge Management process.

Critical Success Factors (CSFs) and Key Performance Indicators (KPIs)

The following list includes some sample CSFs for knowledge management. Each organization should identify appropriate CSFs based on its objectives for the process. Each sample CSF is followed by a small number if typical KPIs that support the CSF. These KPIs should not be adopted without careful consideration.

Each organization should develop KPIs that are appropriate for its level of maturity, its CSFs and its particular circumstances. Achievement against KPIs should be monitored and used to identify opportunities for improvement, which should be logged in the continual service improvement(CSI) register for evaluation and possible implementation.

The following table lists the CSFs and their corresponding KPIs: 



Availability of knowledge and information that helps to support management decision-making

  • Increased number of accesses to the SKMS by managers

  • Increased percentage of SKMS searches by managers that receive a rating of ‘good.'

Reduced time and effort required to support and maintain services

  • Increased number of times that material is reused in documentation such as procedures, test design, and service desk scripts

  • Increased number of accesses to the SKMS by service operation teams

  • Reduced transfer of issues to other people and more resolution at lower staff levels

  • Increased percentage of incidents solved by the use of known errors

  • Increased results in knowledge management satisfaction survey of service operation teams.

Successful implementation and early life operation of new and changed services with few knowledge-related errors

  • Reduced number of incidents and problems categorized as ‘knowledge-related’

  • Increased percentage of successful service transitions

Improved accessibility and management of standards and policies

  • Increased number of standards and policies stored in the SKMS

  • Increased number of times that standards and policies in the SKMS have been accessed

  • Increased percentage of standards and policies that have been reviewed by the agreed review date

Reduced dependency on personnel for knowledge

  • Increased number of times that the SKMS is accessed

  • Increased percentage of SKMS searches that receive a rating of ‘good’ by the user

  • Increased scores in regular customer satisfaction survey for knowledge management

Let us now proceed to look at measuring benefit from knowledge transfer challenges and risks of this process.

Measuring Benefit from Knowledge Transfer

Although it is hard to measure the value of knowledge, it is nonetheless important to determine its value to the organization in order to ensure that the case for expenditure and support of knowledge management is maintainable. The costs associated with knowledge management can then be measured and compared to that value.

The value of improved knowledge transfer during service transition through improved knowledge management can be measured via the increased effectiveness of staff using and supporting the new or changed service.

This (effectively the steepness of the learning curve) in turn can be measured through:

  • Incidents and lost time categorized as ‘lack of user knowledge’

  • Average diagnosis and repair time for faults fixed in-house

  • Incidents related to new or changed services fixed by reference to the knowledge base.

Although not every element of the above can be directly attributable to knowledge management, the trends in these measures will be influenced by the quality of knowledge management, as shown by the example in the picture below.

Clearly, the performance of the support groups post-transition will be a determining factor of the quality of the knowledge transfer, typically delivered via training; however, it is more proactive to check understanding before arriving at this point.

After each piece of training activity, there should be a feedback mechanism to check understanding and quality of delivery. This could be in the form of a post-course questionnaire, or even a test to confirm understanding.

Knowledge Management: Challenges

The challenges of Knowledge management are:

  • Implementing knowledge management can be a difficult task. Most organizations already have stores of knowledge, information, and data that meet many of their needs, and it can be challenging to justify the effort that would be needed to create a consistent architecture for managing these.

  • Each group or team within the service provider may own and manage information that they use and may see knowledge management as interfering in their work.

  • The challenge is to help all the stakeholders understand the added value that a more holistic approach to knowledge management can bring, and continue to demonstrate this value as an SKMS is built.

In the next section, we will discuss the knowledge management risks.

Knowledge Management: Risks

Risks to knowledge management include:

  • Focusing on the supporting tools, rather than on the creation of value

  • Insufficient understanding of what knowledge, information, and data are needed by the organization

  • Lack of investment in the tools and people needed to support the SKMS

  • Spending too much effort on knowledge capture with insufficient attention to knowledge transfer and re-use

  • Storing and sharing knowledge and information that are not up to date and relevant Lack of support and commitment from stakeholders.

Now, let’s look at the relationship between CSI and Knowledge management.

You should also consider taking an ITIL Intermediate RCV Course now!

Relationship between CSI and Knowledge Management

Within each service lifecycle stage, data should be captured to enable knowledge gain and an understanding of what is actually happening, thus enabling wisdom

All too often an organization will capture the appropriate data but fail to process the data into information, synthesize the information into knowledge, and then combine that knowledge with others to bring wisdom. Moving on, let us look at an illustration that talks about KM enabling IT to make better decisions.

Knowledge Management Leads to Better IT Decisions

The diagram shown below depicts that DIKW structure that we had discussed in previous sections of Knowledge management helps working towards CSI and leads to better IT decisions.

Knowledge Management leads to better IT Decisions

With this we have come to the end of module 8, let’s recap.


Here is the summary of Knowledge management concepts that we had covered so far:

  • The strategy for Knowledge Management will identify and plan for the capture of relevant knowledge and the consequential information and data that will support it

  • Knowledge Management is a whole lifecycle-wide process in that it is relevant to all lifecycle sectors

  • Knowledge Management includes oversight of the management of knowledge, the information and data from which that knowledge derives

  • Knowledge Management is an excellent method for individuals and teams to share data, information, and knowledge about all facets of an IT service

  • The Knowledge Management process has specific application to Service Transition Knowledge Management plays a key role in Continual Service Improvement

  • It's important to determine the value of KM to the organization to ensure the case for expenditure and support of KM is maintainable

  • There are certain activities that should be planned and implemented in accordance with applicable organization policies and procedures with respect to the data and information management process

  • In order to make effective use of data, a relevant architecture matched to the organizational situation, and the knowledge requirements is essential

This is the end of Module 8, let’s proceed to learn about Roles and Responsibilities of RCV in the next module.

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.

Request more information

For individuals
For business
Phone Number*
Your Message (Optional)
We are looking into your query.
Our consultants will get in touch with you soon.

A Simplilearn representative will get back to you in one business day.

First Name*
Last Name*
Work Email*
Phone Number*
Job Title*