1. KNOWLEDGE MANAGEMENT SYSTEMS LIFE CYCLE
In this week’s lecture, we will focus on the topic of Knowledge Management Systems Life Cycle.
What are the similarities and the differences between KMSLC and the conventional SLC.
Lecture Two
(Chapter 2, Notes;
Chapter 3, Textbook)

2. Motivation
For any task, from as simple as planning a trip, working on a maths problem,
The process involves a number of steps until you come up with a solution.
In developing a large software system used in industry, the process also follows a number of defined steps which are accepted as best practices by practitioners.

3. Motivation Cont
How many of you have taken a programming unit either here or elsewhere before?
What would be the steps you would take in completing a programming assignment?

4. Motivation Cont read the problem statement
mentally think about how to solve it
select a programming language (if decided, select what kind of data structures)
translate into program code
compile, run and test
modify if program doesn't function as expected
Satisfied!!

5. This week’s Topics Challenges in building KM Systems
Compare CSLC and KMSLC
User’s vs. Expert’s Characteristics
Stages of KMSLC
Today, we will learn about the KMSLC, that is the actual stages involved in the development of a working KMS:
First, I will highlight several major challenges one might face when constructing KM systems. This will set the stage for the remaining discussion on KMSLC.
For some of you, you might be familiar with the system development life cycle for conventional systems. But how about KMSLC? What are the main similarities and differences between the conventional life cycle and the KMSLC that we will be learning today?
Next, we will attempt to understand some characteristics of a user (or person using a system) as compared to an expert who are knowledgeable in an area where we are attempting to apply KM.
Altogether, we can identify 8 distinct stages in a KMSLC (at least as outlined in our textbook by Awad and Ghaziri). For the most part, the stages are sequential. But, there are certain stages that are iterative because of the methodology applied in developing KMS.

6. CHALLENGES IN BUILDING KM SYSTEMS
Culture
— getting people to share knowledge
Knowledge evaluation
— assessing the worth of knowledge across the organization
Knowledge processing
— documenting how decisions are reached
Knowledge implementation
— organizing knowledge and integrating it with the processing strategy for final deployment
Needless to say, there are numerous challenges that one will expect to face when building KM systems.
Here, I have listed four which are considered as universal.
The first challenge is culture. Here, we are not simply referring to culture as in your place of birth, your nationality, etc.
The challenge is more than that. It involves the challenge of getting people to share knowledge, getting people to the point of willing to share what they know. This challenge is more of an art of doing it, rather than technical. For a knowledge developer, one of the primary skills or qualifications is the ability to get the experts share the tacit knowledge related to the domain of the KMS that is to build.
If you are in the position of a manager, what are the ways that you can think of to encourage your subordinates to share what they know with one another??
The next challenge is knowledge evaluation. This involves the assessment of the worth of knowledge (people, files, documents, databases, etc) that exist across the entire organization, in order to determine both domain and scope of KM projects that should be initiated. This will imply a project in itself, the more substantial the larger an organization. This will imply that one has to selective in determining what are relevant knowledge, where they reside, and what benefits they will derive if they are captured and put in a form that can be shared and used.
The third challenge is knowledge processing. By knowledge processing, it is the task of finding out how experts make decision on their tasks based on the knowledge they possess. This is an important challenge that will eventually influence the quality of the KM system that is to build.
Finally, there is the challenge of knowledge implementation. This is most technical among the four challenges, and are related to the activity of organizing knowledge that has been identified and integrating it to the processing strategy being adopted by the organization. Being able to successfully overcome this challenge is like overcoming the last hurdle before final deployment of the KM system.

7. Conventional System Life Cycle
Iterative
KM System Life Cycle
Evaluate Existing Infrastructure
Knowledge Capture
Design KMS Blueprint
Verify and validate the KM System
Implement the KM System
Manage Change and Rewards Structure
Form the KM Team
Post-system evaluation
versus
Recognition of Need and Feasibility Study
Logical Design (master design plan)
Physical Design (coding)
Testing
Implementation (file conversion, user training)
Operations and Maintenance
Functional Requirements Specifications
Here, I make a comparison between the system life cycle that is often adopted in conventional system development and the version of KMSLC that are proposed by Awad and Ghaziri in their textbook.
Let’s look at the stages that are involved in a typical conventional system life cycle.
In almost all conventional system development project, one will start out with a “Recognition of Need and a Feasibility Study”. Sometimes, this stage is simply abbreviated as Feasibility Study. In this stage, normally a system analyst will have already identified an existing problem in an organization (may be in a department) that can be solved by an application of Information technology. Of course, recognizing the existence of a problem doesn’t necessarily say a solution is possible, within the current resources constraint in the organization. These constraints could be time, money, people, and expertise.
Assuming that the answer is positive after the feasibility study, the next stage would be to come up with software specifications for the system that is to be constructed. This is a sample of elements that will be included in a software requirements specifications document.
When the software requirements specifications have received an “ok” sign from users and from management, the later stage will be straightforward. Logical design (or the master design plan) of the system will commence, usually performed by a group including systems analyst and programmers and users.
Once the master design plan is ready, physical design (or coding) will follow. This is again straightforward in an IT point of view.
Once a version of the system is ready, then testing will begin, followed by implementation, and finally when the system is ready, issues on operations and maintenance will be documented and followed.
The conventional system life cycle is largely sequential, that is one stage following on from the previous one.
However, at the point of testing, when the system to be implemented is found out to not perform according to the initial software requirements specifications or contains logical errors or programming errors, the development team will have to refer back to the logical design to make necessary changes or amendments. However, the software requirements specification remains unmodified.
Compared to this, in the KM system life cycle,
One will start with evaluating the existing infrastructure (knowledge assessment), including both knowledge and system and people, that constitute the essential resources in the company.
If a KM initiative were decided, then the next step will be the formation of a KM team to take on this KM project initiative.
Normally, there will one knowledge developer in the KM team, who will be playing the important role of identifying knowledge sources, capturing the necessary knowledge from experts, and then design the blueprint for the KMS to be constructed. The first 3 stages pretty much resemble the first 2 stages in the conventional system life cycle, while the “design the KM blueprint” corresponds to the logical design.
However, instead of having a sequential stage of physical design, then followed by testing, in KMSLC, the stage of verify and validate the KM system proceeds in an iterative manner, until a satisfactory prototype of the KMS is arrived. By satisfactory, this will involve not just the users as in conventional system life cycle, but the experts who are the sources of the knowledge embedded in the KMS.
Implementation will be the next step, followed by the important yet less noticeable step of manage change and rewards structure. This is a delicate stage as very often users, experts could become anti-support to the KMS and implementation if they feel that their importance is being undermined, or that the existence of the KMS jeopardize their necessity in the company.
Post-system evaluation is to consider all the benefits of the KMS as weighted against its foresee benefits at the time of conception.
Iterative

8. Key Differences
Systems analysts deal with information from the user; knowledge developers deal with knowledge from domain experts
Users know the problem but not the solution; domain experts know both the problem and the solution
Conventional SLC is primarily sequential; KM SLC is incremental and interactive.
System testing normally at end of conventional system life cycle; KM system testing evolves from beginning of the cycle
Here, we list several key differences between the conventional and the KMS life cycle.

9. Key Differences (cont’d)
Conventional system life cycle is process-driven or “specify then build”
KM system life cycle is result-oriented or “start slow and grow”

10. Key Similarities Both begin with a problem and end with a solution
Both begin with information gathering or knowledge capture
Testing is essentially the same to make sure “the system is right” and “it is the right system”
Both developers must choose the appropriate tool(s) for designing their respective systems
These are the similarities.

11. Stages of KMSLC Iterative Rapid Prototyping
Evaluate Existing Infrastructure
Knowledge Capture
Design KM Blueprint
Verify and validate the KM System
Implement the KM System
Manage Change and Rewards Structure
Form the KM Team
Post-system evaluation
Iterative Rapid Prototyping
KM system development life cycle is largely composed of 8 stages, which we will briefly discuss in the remaining slides. You should obtain description of their details in both the lecture notes and the prescribed text.

12. (1) Evaluate Existing Infrastructure
System justifications:
What knowledge will be lost through retirement, transfer, or departure to other firms?
Is the proposed KM system needed in several locations?
Are experts available and willing to help in building a KM system?
Does the problem in question require years of experience and tacit reasoning to solve?
The first stage is to evaluate existing infrastructure.
There are several important questions that you need to ask when making the evaluation.

13. The Scope Factor
Consider breadth and depth of the project within financial, human resource, and operational constraints
Project must be completed quickly enough for users to foresee its benefits
Check to see how current technology will match technical requirements of the proposed KM system
As part of evaluating the infrastructure, you should also consider the scope factor. Very often, the scope is being inappropriately set, either too ambitious or too little to make the KMS impact known.
One should be realistic when considering the scope of the system. A larger goal can almost always be sub-divided into smaller ones. Being able to achieve success in the smaller goals not only can boost confidence in achieving the larger goal, but will also gain recognition and continual support from management. At the end, a KMS will not be successful without gaining the rapport from the top management.

14. Role of Strategic Planning
Risky to plunge into a KMS without strategy
Knowledge developer should consider:
Vision
Resources
Culture
The role of strategic planning cannot be undermined. A knowledge developer should be able to foresee what the business is trying to achieve, how it will be done, and how the new system will achieve goals. He or she should study the company’s resources and culture in a manner that can align the KMS to effectively use these resources to achieve its benefits.

15. (2) Form the KM Team
Identify the key stakeholders of the prospective KM system.
Team success depends on:
Ability of team members
Team size
Complexity of the project
Leadership and team motivation
Not promising more than can be realistically delivered
After carefully evaluating the infrastructure, the next stage will be to form the KM team that will work together to develop KMS from the blueprint to implementation.
The team success will depend on a number of factors, including those shown here.

16. (3) Knowledge Capture
Explicit knowledge captured in repositories from various media
Tacit knowledge captured from company experts using various tools and methodologies
Knowledge developers capture knowledge from experts in order to build the knowledge base
The next stage after forming the KM team will be knowledge capture.

17. Selecting an Expert How does one know the expert is in fact an expert?
How would one know that the expert will stay with the project?
What backup should be available in case the project loses the expert?
How could we know what is and what is not within the expert’s area of expertise?
How to select an expert for the purpose of knowledge capture is also an important challenge for the knowledge developer. Some of the questions that should be asked are listed here.

18. (4) Design the KM Blueprint
The KM blueprint addresses several issues:
Finalize scope of proposed KM system with realized net benefits
Decide on required system components
Develop the key layers of the KM software architecture to meet company requirements
System interoperability and scalability with existing company IT infrastructure
Next, the KM team will need to develop the KM blueprint based on the knowledge captured. This will be very similar to the logical design stage in conventional system development life cycle.
The blueprint should address several issues, including those listed here.

19. (5)Testing the KM System
Verification procedure: ensures that the system has the right functions
Validation procedure: ensures that the system has the right output
Validation of KM systems is not foolproof
As the KM system is under development, it goes through a repetitive iteration of verification and validation as the rapid prototyping process comes out with intermediate version of the test system. This is one of the major difference between the conventional and the KMSLC, as one is process driven while the other is result driven.
Verification (functionality) vs. Validation (integrity)

20. (6) Implement the KM System
Converting a new KM system into actual operation
includes conversion of data or files
also includes user training
Quality assurance is important, which includes checking for:
Reasoning errors
Ambiguity
Incompleteness
False representation (false positive and false negative)
Finally, as in conventional system life cycle, there will be the time when the KMS will be rolled out for users to use.
The elements that are involved in implementing a KM System are given here. The quality assurance part is particularly important for KMSLC. Whereas in conventional system life cycle, the logical design based on the software requirements specification will ensure the quality of the system performing as expected. In KMSLC, due to its iterative nature of verifying and validating, the final state of the KMS will not be foreseen from the very beginning. Detailed checking with the cooperation of the experts to ensure the system is working as expected is inevitable.

21. (7) Manage Change and Rewards Structure
Goal is to minimize resistance to change
Experts
Regular employees (users)
Troublemakers
Resistances via projection, avoidance, or aggression
Finally, during implementation, we will surely encounter resistance from people in the organization that will oppose the system because of fear of losing control. A few of these resistors of change are listed here.

22. (8) Post-system Evaluation
Assess system impact in terms of effects on:
People
Procedures
Performance of the business
Areas of concern:
Quality of decision making
Attitude of end users
Costs of Knowledge processing and update
Finally, during implementation, we will surely encounter resistance from people in the organization that will oppose the system because of fear of losing control. A few of these resistors of change are listed here.

23. Key Questions Has accuracy and timeliness of decision making improved?
Has KMS caused organizational changes?
What are users’ reactions towards KMS?
Has KMS changed the cost of operating the business?
Have relationships among users affected?
Does KMS justify the cost of investment?
Finally, during implementation, we will surely encounter resistance from people in the organization that will oppose the system because of fear of losing control. A few of these resistors of change are listed here.

24. End of Lecture 2

25. Basic Knowledge-Related Definitions
Common Sense
Inborn ability to sense, judge, or perceive situations; grows stronger over time
Fact
A statement that relates a certain element of truth about a subject matter or a domain
Heuristic
A rule of thumb based on years of experience
Knowledge
Understanding gained through experience; familiarity with the way to perform a task; an accumulation of facts, procedural rules, or heuristics
Intelligence
The capacity to acquire and apply knowledge
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

26. Types (Categorization) of Knowledge
Shallow (readily recalled) and deep (acquired through years of experience)
Explicit (already codified) and tacit (embedded in the mind)
Procedural (repetitive, stepwise) versus Episodical (grouped by episodes)
Knowledge exist in chunks
Shallow vs. deep (necessary to make decision/solve problem in complex situations)

27. What makes someone an expert?
An expert in a specialized area masters the requisite knowledge
The unique performance of a knowledgeable expert is clearly noticeable in decision-making quality
Knowledgeable experts are more selective in the information they acquire
Experts are beneficiaries of the knowledge that comes from experience

28. Purpose
Statement of Scope & Objectives 2.1 System functions 2.2 Users and characteristics 2.3 Operating environment 2.4 User environment 2.5 Design/implementation constraints 2.6 Assumptions and dependencies
3. Functional Requirements 3.1 User interfaces 3.2 Hardware interfaces 3.3 Software interfaces 3.4 Communication protocols and interfaces
4. Nonfunctional Requirements 4.1 Performance requirements 4.2 Safety requirements 4.3 Security requirements 4.4 Software quality attributes 4.5 Project documentation 4.6 User documentation

29. Users Versus Experts Attribute User Expert
Dependence on system High Low to nil
Cooperation Usually cooperative Cooperation not
required
Tolerance for ambiguity Low High
Knowledge of problem High Average/low
Contribution to system Information Knowledge/expertise
System user Yes No
Availability for system
builder Readily available Not readily available
In earlier slides, we talked about the differences between conventional system life cycle and KMSLC.
We emphasized the importance of the role of users in conventional life cycle as compared to that of experts in KMSLC. Here, we compare them based on their major attributes.

30. Rapid Prototyping Process?
Structure
the Problem
Repeated
Cycle(s)
Reformulate the Problem
Structure
a Task
Repeated Cycle(s)
Make Modifications
Build
a Task

31. Layers of KM Architecture
User Interface
(Web browser software installed on each user’s PC) 1 2 3 4 5 6 7
Authorized access control
(e.g., security, passwords, firewalls, authentication)
Collaborative intelligence and filtering
(intelligent agents, network mining, customization, personalization)
Knowledge-enabling applications
(customized applications, skills directories, videoconferencing, decision support systems,
group decision support systems tools)
Transport
( , Internet/Web site, TCP/IP protocol to manage traffic flow)
Middleware
(specialized software for network management, security, etc.)
Then, the blueprint should consider how the functions of the KMS can be placed into a KM architecture, consisting of 7 important layers as shown here.
Details of these layers in the KM architecture will be explained in the next lecture.
The Physical Layer
(repositories, cables)
Data warehousing
(data cleansing,
data mining)
Databases
Legacy applications
(e.g., payroll)
Groupware
(document exchange,
collaboration)

32. Knowledge Capture and Transfer Through Teams
Team performs
a specialized task
Knowledge transfer method selected
Evaluate relationship between action and outcome
Outcome Achieved
Knowledge Developer
Knowledge stored in a form usable by others in the organization
Feedback

33. An illustration Zero Low Medium High Very High Knowledge Counting Data
Value
Information
Data
H T H T T
H H H T H …
T T T H T
pH = 0.40
pT = 0.60
RH = +$10
RT = -$8
nH = 40
nT = 60
EV = -$0.80
Knowledge
Counting
pH = nH/(nH+nT)
pT = nT/(nH+nT)
EV=pH RH+ pT RT

34. CHALLENGES IN BUILDING KM SYSTEMS
Culture
— getting people to share knowledge
Knowledge evaluation
— assessing the worth of knowledge across the organization
Knowledge processing
— documenting how decisions are reached
Knowledge implementation
— organizing knowledge and integrating it with the processing strategy for final deployment
Needless to say, there are numerous challenges that one will expect to face when building KM systems.
Here, I have listed four which are considered as universal.
The first challenge is culture. Here, we are not simply referring to culture as in your place of birth, your nationality, etc.
The challenge is more than that. It involves the challenge of getting people to share knowledge, getting people to the point of willing to share what they know. This challenge is more of an art of doing it, rather than technical. For a knowledge developer, one of the primary skills or qualifications is the ability to get the experts share the tacit knowledge related to the domain of the KMS that is to build.
If you are in the position of a manager, what are the ways that you can think of to encourage your subordinates to share what they know with one another??
The next challenge is knowledge evaluation. This involves the assessment of the worth of knowledge (people, files, documents, databases, etc) that exist across the entire organization, in order to determine both domain and scope of KM projects that should be initiated. This will imply a project in itself, the more substantial the larger an organization. This will imply that one has to selective in determining what are relevant knowledge, where they reside, and what benefits they will derive if they are captured and put in a form that can be shared and used.
The third challenge is knowledge processing. By knowledge processing, it is the task of finding out how experts make decision on their tasks based on the knowledge they possess. This is an important challenge that will eventually influence the quality of the KM system that is to build.
Finally, there is the challenge of knowledge implementation. This is most technical among the four challenges, and are related to the activity of organizing knowledge that has been identified and integrating it to the processing strategy being adopted by the organization. Being able to successfully overcome this challenge is like overcoming the last hurdle before final deployment of the KM system.

35. Vision
Foresee what the business is trying to achieve, how it will be done, and how the new system will achieve goals
Needless to say, there are numerous challenges that one will expect to face when building KM systems.
Here, I have listed four which are considered as universal.
The first challenge is culture. Here, we are not simply referring to culture as in your place of birth, your nationality, etc.
The challenge is more than that. It involves the challenge of getting people to share knowledge, getting people to the point of willing to share what they know. This challenge is more of an art of doing it, rather than technical. For a knowledge developer, one of the primary skills or qualifications is the ability to get the experts share the tacit knowledge related to the domain of the KMS that is to build.
If you are in the position of a manager, what are the ways that you can think of to encourage your subordinates to share what they know with one another??
The next challenge is knowledge evaluation. This involves the assessment of the worth of knowledge (people, files, documents, databases, etc) that exist across the entire organization, in order to determine both domain and scope of KM projects that should be initiated. This will imply a project in itself, the more substantial the larger an organization. This will imply that one has to selective in determining what are relevant knowledge, where they reside, and what benefits they will derive if they are captured and put in a form that can be shared and used.
The third challenge is knowledge processing. By knowledge processing, it is the task of finding out how experts make decision on their tasks based on the knowledge they possess. This is an important challenge that will eventually influence the quality of the KM system that is to build.
Finally, there is the challenge of knowledge implementation. This is most technical among the four challenges, and are related to the activity of organizing knowledge that has been identified and integrating it to the processing strategy being adopted by the organization. Being able to successfully overcome this challenge is like overcoming the last hurdle before final deployment of the KM system.

36. Resources
Check on the affordability of the business to invest in a new KM system
Needless to say, there are numerous challenges that one will expect to face when building KM systems.
Here, I have listed four which are considered as universal.
The first challenge is culture. Here, we are not simply referring to culture as in your place of birth, your nationality, etc.
The challenge is more than that. It involves the challenge of getting people to share knowledge, getting people to the point of willing to share what they know. This challenge is more of an art of doing it, rather than technical. For a knowledge developer, one of the primary skills or qualifications is the ability to get the experts share the tacit knowledge related to the domain of the KMS that is to build.
If you are in the position of a manager, what are the ways that you can think of to encourage your subordinates to share what they know with one another??
The next challenge is knowledge evaluation. This involves the assessment of the worth of knowledge (people, files, documents, databases, etc) that exist across the entire organization, in order to determine both domain and scope of KM projects that should be initiated. This will imply a project in itself, the more substantial the larger an organization. This will imply that one has to selective in determining what are relevant knowledge, where they reside, and what benefits they will derive if they are captured and put in a form that can be shared and used.
The third challenge is knowledge processing. By knowledge processing, it is the task of finding out how experts make decision on their tasks based on the knowledge they possess. This is an important challenge that will eventually influence the quality of the KM system that is to build.
Finally, there is the challenge of knowledge implementation. This is most technical among the four challenges, and are related to the activity of organizing knowledge that has been identified and integrating it to the processing strategy being adopted by the organization. Being able to successfully overcome this challenge is like overcoming the last hurdle before final deployment of the KM system.

37. Culture
Is the company’s political and social environment open and responsive to adopting a new KM system?
Needless to say, there are numerous challenges that one will expect to face when building KM systems.
Here, I have listed four which are considered as universal.
The first challenge is culture. Here, we are not simply referring to culture as in your place of birth, your nationality, etc.
The challenge is more than that. It involves the challenge of getting people to share knowledge, getting people to the point of willing to share what they know. This challenge is more of an art of doing it, rather than technical. For a knowledge developer, one of the primary skills or qualifications is the ability to get the experts share the tacit knowledge related to the domain of the KMS that is to build.
If you are in the position of a manager, what are the ways that you can think of to encourage your subordinates to share what they know with one another??
The next challenge is knowledge evaluation. This involves the assessment of the worth of knowledge (people, files, documents, databases, etc) that exist across the entire organization, in order to determine both domain and scope of KM projects that should be initiated. This will imply a project in itself, the more substantial the larger an organization. This will imply that one has to selective in determining what are relevant knowledge, where they reside, and what benefits they will derive if they are captured and put in a form that can be shared and used.
The third challenge is knowledge processing. By knowledge processing, it is the task of finding out how experts make decision on their tasks based on the knowledge they possess. This is an important challenge that will eventually influence the quality of the KM system that is to build.
Finally, there is the challenge of knowledge implementation. This is most technical among the four challenges, and are related to the activity of organizing knowledge that has been identified and integrating it to the processing strategy being adopted by the organization. Being able to successfully overcome this challenge is like overcoming the last hurdle before final deployment of the KM system.