Service Transition

4. Service Transition Processes

^4.1PLAN/SUPPORT

^4.2CHANGE

4.7 Knowledge Management

The ability to deliver a quality service or process rests to a significant extent on the ability of those involved to respond to circumstances - and that in turn rests heavily on their understanding of the situation, the options and the consequences and benefits, i.e. their knowledge of the situation they are, or may find themselves, in.

That knowledge within the Service Transition domain might include:

Identity of stakeholders
Acceptable risk levels and performance expectations
Available resource and timescales.

The quality and relevance of the knowledge rests in turn on the accessibility, quality and continued relevance of the underpinning data and information available to service staff.

4.7.1 Purpose, Goal and Objective

The purpose of Knowledge Management is to ensure that the right information is delivered to the appropriate place or competent person at the right time to enable informed decision.

The goal of Knowledge Management is to enable organizations to improve the quality of management decision making by ensuring that reliable and secure information and data is available throughout the service lifecycle. The objectives of Knowledge Management include:

Enabling the service provider to be more efficient and improve quality of service, increase satisfaction and reduce the cost of service
Ensuring 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
Ensuring that, at a given time and location, service provider staff have adequate information on:
Who is currently using their services
The current states of consumption
Service delivery constraints
Difficulties faced by the customer in fully realizing the benefits expected from the service.

4.7.2 Scope

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.

4.7.2.1 Inclusions

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

4.7.2.2 Exclusions

Detailed attention to the capturing, maintenance and use of asset and configuration data is set out in Section 4.2.

4.7.3 Value To Business

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 their 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.

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 through 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 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 phase
Capturing of implementation and testing information
Re-using previously developed and quality assured testing, training and documentation
Compliance with legislative requirements, e.g. SOX, 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.

4.7.4 Policies, Principles and Basic Concepts

4.7.4.1 The Data-to-Information-to-Knowledge-to-Wisdom 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.

Figure 4.37 The flow from data to wisdom
Figure 4.37 The flow from data to wisdom

Data is a set of discrete facts about events. Most organizations capture significant amounts of data in highly structured databases such as Service Management and Configuration Management tools/systems and databases. The key Knowledge Management activities around data are the ability to:

Capture accurate data
Analyse, synthesize, and then transform the data into information
Identify relevant data and concentrate resources on its capture.

Information comes from providing context to data. Information is typically stored in semi-structured content such as documents, e-mail, 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.

Knowledge is composed of the tacit experiences, ideas, insights, values and judgements 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 experience of previous transitions, awareness of recent and anticipated changes and other areas that experienced staff will have been unconsciously collecting for some time.

Wisdom gives the ultimate discernment of the material and having the application and contextual awareness to provide a strong common sense judgement. This is shown in Figure 4.37.

4.7.4.2 The Service Knowledge Management System (SKMS)

Specifically within IT Service Management, Knowledge Management will be focused within the Service Knowledge Management System (SKMS) concerned, as its name implies, with knowledge. Underpinning this knowledge will be a considerable quantity of data, which will be held in a central logical repository or Configuration Management System (CMS) and Configuration Management Database (CMDB). However, clearly the SKMS is a broader concept that covers a much wider base of knowledge, for example: The experience of staff

Records of peripheral matters, e.g. weather, user numbers and behaviour, organization's performance figures
Suppliers' and partners' requirements, abilities and expectations
Typical and anticipated user skill levels.

Figure 4.38 is a very simplified illustration of the relationship of the three levels, with data being gathered within the CMDB, and feeding through the CMS into the SKMS and supporting the informed decision making process.

Figure 4.38 Relationship of the CMDB, the CMS and the SKMS
Figure 4.38 Relationship of the CMDB, the CMS and the SKMS

4.7.5 Process Activities, Methods and Techniques

4.7.5.1 Knowledge Management Strategy

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. But even in this case developments should always be established with a view to as wide as practicable a span of Knowledge Management - covering direct IT staff, users, third party support and others likely to contribute or make beneficial use of the knowledge.

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

The governance model
Organizational changes underway and planned and consequential changes in roles and responsibilities
Establishing roles and responsibilities and ongoing funding
Policies, processes, procedures and methods for Knowledge Management
Technology and other resource requirements
Performance measures.

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
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.

4.7.5.2 Knowledge Transfer

During the service lifecycle an organization needs to focus on retrieving, sharing and utilizing their knowledge through problem solving, dynamic learning, strategic planning and decision making. To achieve this, knowledge needs to be transferred 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 for any Service Transition into support. They will be reliant on information sourced from release management such as known errors going into production but which are not show stoppers for the release schedule, or known error scripts from any of the technical support teams. Links with HR, facilities and other supporting services need to be established, maintained and utilized.

The challenge is often the practical problem of getting a knowledge package from one part of the organization to other parts of the organization. It is more than just sending an e-mail! Knowledge transfer is more complex; more accurately it is the activity through which one unit (e.g. a group, department or division) is affected by the experience of another. Its form must be applicable for those using it, and achieve a positive rating of '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 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 work group who is then required to cascade the knowledge to their working colleagues. Other techniques are often appropriate and form useful tools in the Service Transition armoury. 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. Learning styles vary with age, culture, attitude and personality. IT staff can be usefully reminded, especially where they are supporting users in a different working style, e.g. graphics design, performers, sales teams, that merely because a knowledge transfer mechanism works for them, it may not be appropriate for their current user base.

For many some element of 'hands-on' experience is a positive support for learning, and simulation exercises can be a useful consideration, or supervised experience and experimentation.

Knowledge Visualization
This aims to improve the transfer of knowledge by using 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 understandings of systems that change over time. For example this can be particularly useful during a hardware refresh when the location of a component may change on an item, although the functionality does not alter.

Driving Behaviour
Knowledge transfer aims to ensure that staff are able to decide on the correct actions to deliver their tasks in any foreseeable circumstances. For predictable and consistent tasks, the procedure can be incorporated within software tools that the staff use within those tasks. These procedures then drive behaviour in the accepted way. Change process models (see Figure 4.2) and service desk scripts are excellent examples. This includes the ability to recognize when the laid down practices are or might be inappropriate, e.g. in unexpected circumstances, when staff will either move away from the laid down rules when they do not deliver as required or else will escalate the situation.

Seminars, Webinars and Advertising
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 deliver 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 deliver equivalent messages in an ongoing fashion and allow discussion forums to question and develop knowledge.

Journals and Newsletters
Regular communicating 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 groupings.

Aimed at the audience

A stock control system was introduced with staff in the warehouses directly inputting and working with the new system. Initially all documentation was formal and written in semi-technical terms and the staff taught how to use the system via traditional training and coaching. Once the system had settled in a monthly newsletter was planned to keep staff aware of changes, improvements, hints, tips etc. The first versions were, again, formal and addressed the required information only. It quickly became clear that the required knowledge was not in place within the staff. Success followed when the updates evolved into a genuine newsletter - among competitions, holiday snaps, humorous and even satirical articles the required user knowledge was transferred much more successfully. The lesson was that by targeting communications accurately at a known and understood audience, and making the experience pleasant, the required knowledge transfers along with the rest. and as a bonus the staff contributed entertaining articles and hints and tips they had evolved.

4.7.5.3 Data and Information Management

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

What knowledge is necessary based on what decisions must be made
What 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.

Successful data and information management will deliver:

Conformance with legal and other requirements, e.g. company policy, codes of professional conduct
Defined forms of data and information in a fashion that is easily usable by the organization
Data and information that is current, complete and valid
Data and information disposed of as required
Data and information to the people who need it when they need it.

Establishing Data and Information Requirements
The following activities should be planned and implemented in accordance with applicable organization policies and procedures with respect to the data and information management process. This plan and design is the responsibility of Service Strategy and Service Design.

Often, data and information is 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 and information 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 and information 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 and information 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 in the day before payroll is run than at other times of the month
Considering any changes to the Knowledge Management process through Change Management.

Define 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 is 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 example of a knowledge, information and data architecture is shown in Figure 4.39.

Figure 4.39 Service knowledge management system

Establishing data and information 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 required 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
Store and retrieve
Establish authority and responsibility for all required items of information
Define and publicize rights, obligations and commitments regarding the retention of, transmission of and access to information and data items based on applicable requirements and protecting its 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 (and if necessary to adapt 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.

When the procedures are designed, promulgated and accepted the organization can:

Implement mechanisms to capture, store and retrieve the identified data from the relevant sources
Manage the data and information storage and movement, especially in line with appropriate legislation.

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

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 service improvement plan will take as relevant input:

Measurement of the use made of the data and information management-data transactions
Evaluation of the usefulness of the data and information - identified by relevance of reports produced
Identification of any data or information or registered users that no longer seem relevant to the organization's knowledge requirements.

4.7.5.4 Using the Service Knowledge Management System

Providing services to customers across time zones, work cycles, and geographies requires good knowledge sharing across all locations and time periods of Service Operations. A service provider must first establish a service knowledge management system that can be shared, updated and used by its operating entities, partners, and customers. Figure 4.39 shows an example of the architecture for such a system.

Case study

Current situation
An organization analyzed that at least 75% of the cost of delivering support comes from resolving customer issues. It was using point technologies such as a service desk workflow tool, search engines, scripting tools or simple knowledge bases. These systems generally focused parts of the resolution process and they were not very effective. This contributed to dissatisfied customers, resulted in an ineffective service desk and caused integration issues for IT.

Solution
A comprehensive SKMS was implemented to help to address these obstacles by combining intelligent search and Knowledge Management with Service Management and business process support, authoring workflows and comprehensive self-service facilities.

The SKMS was supported by the problem management and Change Management process.

The experience of end users who come to the website for help was dramatically improved. Instead of an empty search box followed by no results or far too many, the application leads the user through a structured set of steps. Based on the specifics of the incident or request and the customer, web screens will guide users to specific answers, follow-up questions, escalation options, opportunities to drill down or just highly relevant search results. The following improvements were achieved:

Increased agent productivity
Reduced aversion to web self-service
Fewer escalations.

Over time the web workflows were tuned to deliver more and more optimized experiences. Good experiences helped to add value to the product and services and this resulted in greater loyalty that in turn increased profits.

Conclusion
A wealth of information exists in most organizations that is not initially thought to contribute to the decision process, but, when used as supplemental to traditional configuration data, can bring the lessons of history into sharp focus. Often this information is in an informal fashion. Marketing, sales, customer and staff information is a commonly overlooked source of valuable trend data that, along with traditional configuration, can paint a larger, more meaningful picture of the landscape and uncover the right 'course corrections' to bring a Service Transition or operational support for a service back on track and keep an organization travelling towards its objectives. Without this clear picture, the effectiveness diminishes and efficiency will decay. By recognizing that this is in place, organizations can more easily justify the resource costs of establishing and maintaining the data, processes, knowledge and skills needed to make it as effective as possible and maximize the benefits.

Implementation of a service knowledge management system helps reduce the costs of maintaining and managing the services, both by increasing the efficiency of operational management procedures and by reducing the risks that arise from the lack of proper mechanisms.

All training and knowledge material needs to be aligned to the business perspective. Materials that can be included are:

The business language and terminology and how IT terminology is translated
The business processes and where IT underpins them
Any SLAs, and supporting agreements and contracts that would change as a result of the new Service Transition - this is especially important for the service desk analysts whose target at support transition will be to sustain service; if classifications are accurate this will facilitate the whole process

For those in the service transition process a good way of consolidating understanding is to either to spend time in the developing areas, taking part in some of the testing processes, or to spend time in the business at the receiving end of Service Transition to understand the process from the business perspective.

Useful materials include:

Process maps to understand all the integrated activities
Any known error logs and the workarounds - again particularly important for the service desk
Business and other public calendars.

Technology for service desks and customer service needs to make it easier for customers, users and service desk agents. Some minimal progress has been made with generic Knowledge Management tools and there are significant developments in the Service Management industry to develop mature, process-oriented business applications supported by comprehensive knowledge bases. Examples of potential benefits are:

Agent efficiency - The largest component of ROI from Knowledge Management is reduced incident handling time and increased agent productivity.
Self-service - A comprehensive SKMS provides the customer with knowledge directly on the support website. The cost of self-service is an order of magnitude lower than assisted service.

4.7.6 Triggers, Inputs and Outputs and Inter-process Interfaces

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.

Service Operations
Errors within the service detected during transition will be recorded and analysed and the knowledge about their existence, consequences and workarounds will be made available to Service Operations in an easy to use fashion.

Operations Staff

Front-line incident management staff, on service desk and second-line support, are the point of capture for much of the everyday IT Service Management data. If these staff do not understand the importance of their role 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 capture by means of developing and maintaining scripts supporting data capture within incident management.

Transition Staff
Service Transition staff capture data of relevance through all lifecycle phases and so need to be aware of the importance of collecting it accurately and completely. Service Transition staff capture data and information:

Relevant to adaptability and accessibility of the service as designed, to be fed back, via CSI, to Service Design
'Course corrections' and other adaptations to the design required during transition. Awareness and understanding of these will make subsequent transitions easier.

4.7.7 Key Performance Indicators and Metrics

A strong Business Case is critical for effective Knowledge Management and it is important that the measures of success are visible to all levels involved in the implementation.

Typical measures for an IT service provider's contribution are:

Successful implementation and early life operation of new and changed services with few knowledge-related errors
Increased responsiveness to changing business demands, e.g. higher percentage of queries and question solved via single access to internet/intranet through use of search and index systems such as Google
Improved accessibility and management of standards and policies
Knowledge dissemination
Reduced time and effort required to support and maintain services
Reduced time to find information for diagnosis and fixing incidents and problems
Reduced dependency on personnel for knowledge.

4.7.7.1 Evaluation and Improvement

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

4.7.7.2 Indicators Relevant To Business/Customers

Knowledge Management is an enabling process and so demonstration of its effectiveness needs to be inferred from indirect measurement. Elements of the service qualiity that will be positively influenced by good Knowledge Management might include:

Reduction in the 'user error' category of errors due to targeted knowledge transfer, coupled with cheaper user training costs
Lower incident, problem and error resolution times influenced by better targeted support staff training and by a relevant, maintained and accessible knowledge base containing workarounds
Enhanced customer experiences such as:
Quicker resolution of a query
The ability to solve issues directly without external support
Less transfer of issues to other people and resolution at lower staff levels
Reduced time for transition and duration of early life support.

Measuring Benefit from Knowledge Transfer

Figure 4.40 Contribution of knowledge to effectiveness of support staff
Figure 4.40 Contribution of knowledge to effectiveness of support staff

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 (effective 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 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 Figure 4.40.

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.

4.7.7.3 Measures Directly Relevant To The Service Provider

Indications of the effectiveness of the Knowledge Management process itself include:

Usage of the knowledge base, measured by:
Number of accesses to the SKMS
Average time taken to find materials
Errors reported by staff or detected at audit (none probably means no one was using it)
Involvement of staff in discussion/query/answer forums providing support through knowledge sharing and capture of that shared knowledge
Degree of re-use of material in documentation such as procedures, test design and service desk scripts
Satisfaction with training courses, newsletters, web briefings etc.

Supporting Material

HDI - Knowledge Mgmt
Kanisa - KM Best Practices
Serviceware White Papwer - KM Best Practices
Knova WP - KM Principles