Knowledge management

A.A. .T.M.T.
S - IS Masters – MIS, 2010

Management

Knowledge Management
for the Digital Firm KMS
Prepared & Presented
by:
Abdullah Rady
Lamis Labib
Mohamed Ismail
Mohamed Zawra
Khalid Zawra

Management
Agenda
Overview
Concept of Knowledge
Defining Knowledge Management
KBDSS
Knowledge Creation & Architecture
KM System Life Cycle
Knowledge Capturing
Knowledge Testing
Case Study
Demo
IS Masters – MIS – Knowledge Management, 2010

Management


KM IN Boeing
 How is Boeing using knowledge management systems to
execute its business model and business strategy?

Management

Management

The Need to access &
Share Knowledge


Sharing Knowledge


Management

KNOWLEDGE


Management

Skills Talents

Experience
Heuristics


Basic K. Related Definitions

 Experience: knowledge acquired over time of
actual practice, leading to superior understanding
or mastery.

 Heuristics: experience-based techniques for
problem solving, learning, and discovery.

 Common Sense: what people in common would
agree on.



 Intelligence: capacity to acquire and apply
knowledge.

Ability Learning
Memory


Key Attributes of Intelligence

 Ability to understand & use language.

 Memory: to store and retrieve relevant
experience at will.

 Learning: is knowledge or skill acquired by
instruction or study.



 Learning: knowledge acquired by:-
– Instruction,
– Study,
– Experience,
– Discovery.


Types of Learning

 Learning by Example: incorporates specially
constructed examples rather than a broad
range of experience.

 Learning by Experience: a function of time
and talent.


Types of Learning

 Learning by Discovery: undirected approach
in which humans explore a problem area with
no advance knowledge of what their objective
is.


“Knowledge is of two kinds,
We know a subject ourselves,
or we know where we can
find information upon it.”
Samuel Johnson


From Data to Knowledge

Data Information Knowledge

+
Processing Experience

+
Interpretation

[Raw facts] [Understanding Relations] [Understanding Patterns]


From Data to Knowledge
[Non-Algorithmic] [Non-Programmable]

Wisdom

Knowledge

Information

[Algorithmic] [Programmable]
Data


Evolution of KM Technologies
Most significant KM challenges

1.Defining the purpose and focus of
a KM strategy for our unique needs

2.Getting leadership to support and
commit to knowledge management plan

3.Getting staff to support and use
knowledge management approach

4. Developing effective human resource
policy to support knowledge workers


Knowledge
 is the confident understanding of a subject,
potentially with the ability to use it for a
specific purpose.

It is “know-how” or a familiarity with how to do
something and perform a specialized task.


Shallow and Deep Knowledge
 Shallow indicates minimal understanding of
problem area.

 Deep indicates knowledge built through years
of experience.


Common Sense as Knowledge
 Its a collection of personal experience and
facts acquired over time.

* type of knowledge that humans tend to take for
granted


Knowledge as Know-How
 Know-how: accumulated lessons of practical
experience.

 Know-how knowledge is represented in terms
of heuristics rules based on experience

Know-how
distinguishes an
expert from a
novice


Knowledge

Facts Rules

procedural heuristics


Knowledge (Cont.)
 Fact: statement of some elements of truth
about a subject or domain.

 Procedural rule: describes a sequence of
relations relative to a domain.

 Heuristic rule: based on years of experience.
*generally operates in form of IF/THEN statements.


Reasoning

Reasoning Case-based
by analogy Formal
Reasoning
Reasoning

Deductive Inductive
methods methods


Reasoning
1. Reasoning by analogy: relating one concept
to another.

2. Formal reasoning: using deductive or
inductive methods.

3. Cased-based reasoning: reasoning from
relevant past cases.

Formal Reasoning
a. Deductive methods: generating new
knowledge from pre-defined knowledge.

It deals with exact facts and conclusions.

> > >

A B C A C

Formal Reasoning
b. Inductive methods: reasoning from a set of
facts or individual cases to general
conclusion.


Nature of Knowledge

1. Explicit (codified) knowledge digitized in
books, documents, reports, memos..

2. Tacit (implicit) knowledge embedded in
human mind through experience and jobs.


The Nature of Knowledge
Explicit Easier to document and share
[clear] Contributes to
Easier to replicate
efficiency
20%

Leads to competency
Tacit
80% [implied]

Harder to articulate
Harder to steal
Higher
competitive Harder to transfer
advantage
IS Masters – MIS – Knowledge Management, 2010 31

From Tacit to Explicit

- KM - KM

My total What I can What I can
Knowledge tell or show write or record

- KM

My Knowledge
transferred to readers,
watchers or listeners


From Explicit to Tacit

+ KM + KM

What I read or What I can Knowledge
observe connect to, from practice,
What I know coaching

+ KM

Knowledge from
reflection & dialogue
with practitioners/
mentor


EXPLICIT AND TACIT
KNOWLEDGE
50 – 95%

Oral Communication
“Tacit” Knowledge

Information
Request “Explicit”
Knowledge
Information
Feedback

5%

Knowledge Transformation
Processes
Socialization Externalization

Combination
Internalization

Nonaka’s Model of Knowledge
Creation and Transformation
TACIT TO TACIT TACIT TO EXPLICIT
(SOCIALIZATION) (EXTERNALIZATION)

e.g., Individual and/or Team e.g., Documenting a Team
Discussions Meeting

EXPLICIT TO TACIT EXPLICIT TO EXPLICIT
(INTERNALIZATION) (COMBINATION)

e.g., Learn from a report and e.g., Create a Website from
Deduce new ideas some form of explicit
knowledge; Email a Report


Tacit to tacit communication (Socialization):
Takes place between people in meetings or in team discussions.
Tacit to explicit communication (Externalization):
Articulation among people trough dialog (e.g., brainstorming).
Explicit to explicit communication (Communication):
This transformation phase can be best supported by technology.
Explicit knowledge can be easily captured and then
distributed/transmitted to worldwide audience.
Explicit to tacit communication (Internalization):
This implies taking explicit knowledge (e.g., a report) and deducing
new ideas or taking constructive action.
One significant goal of knowledge management is to create
technology to help the users to derive tacit knowledge from
explicit knowledge.

IS Masters – MIS – Knowledge Management, 2010 4-37

From Procedural to Episodic
Knowledge
Shallow
Knowledge
1. Procedural Knowledge
2. Declarative Knowledge
3. Semantic Knowledge
4. Episodic Knowledge
Deep
Knowledge


Procedural Knowledge
 Is an understanding of how to do a task, or
carry out a procedure.


Declarative Knowledge
 An awareness knowledge in which the expert
is conscious.
 E.g. the electrical system of a car, if the
headlights are dim then the battery is faulty.


Semantic Knowledge
 A deeper knowledge, highly organized,
Include major concepts, facts and
relationships.
 Back to the electrical system of a car
example; Semantic knowledge about the
system would consist of understanding
about the battery, battery cables, lights,
ignition system…etc.
 as well as the interrelationships among
those things.


Episodic Knowledge
 Knowledge based on experiential information.

 The longer a human expert takes to verbalize
his knowledge, the more episodic it is.


WHAT IS KNOWLEDGE
MANAGEMENT?
 Process of capturing and making use of an organization’s
collective expertise anywhere in the business.

 Doing the right thing, NOT doing things right.

 Knowledge creation, dissemination, upgrade, and apply
toward organizational survival.

 Part science, part art (intangible assets use), part luck


Knowledge Management

Systematic approaches to help
information and knowledge emerge
and flow to the right people at the
right time to create value.

45

Knowledge Management in
Action
Use
Adapt Create

Share Identify

Review Collect
The chain won’t work if any link is broken.


OVERLAPPING FACTORS OF
KM

PEOPLE
ORGANIZATIONAL
PROCESSES

TECHNOLOGY

Knowledge

OVERLAPPING FACTORS OF KM


Knowledge Management Tree


Case Example” WebMD“


Integration across ….
Across sub-systems


Organism (7)

OrganSystem(6
)
Across
Organ (5)
Temporal scales

Tissue (4)

Cell (3)

Across Molecule (2)

dimensional scales
Atom (1)
H H
C C
H H


Medicine
Across Disciplines
BioEngineering

Biology

KM SYSTEM LIFE
CYCLE


KM SYSTEM LIFE CYCLE

Culture
Competition
Collect
Create
Techno- Organize
logy Intelligence
Maintain Knowledge
Organization
Refine
Disseminate

Knowledge Leadership
Management
Process KM Drivers


KM System Development Life Cycle

• Evaluate existing infrastructure
• Form the KM team
• Knowledge capture
• Design KM blueprint (master plan)
• Test the KM system
• Implement the KM system
• Manage change and reward structure
• Post-system evaluation


Comparison of the development life
cycle of a conventional ISLC and
KMLC
Recognition of need Evaluate existing infrastructure

Systems analysis Form the KM team

Logical design Knowledge Capture

Physical design (coding) Design KM Blueprint

Testing (corrections to previous step) Verify and validate KM system
(corrections to previous step)
Implementation (install, user training) Implement the KM system

Conversion, Operation & Maintenance Manage change & reward structure

Post system evaluation
ISLC KMLC

Evaluate Existing
Infrastructure
System justification
 Are experts available and willing to help in building a KM system?
.
 Does the problem in question require years of experience and cognitive reasoning to solve?

 When undergoing knowledge capture, can the expert articulate how problem will be solved?.
 Are the tasks non algorithmic?

 Is there a champion in the house?

 How critical is the knowledge to be captured?
Scoping and evaluating
 Boundaries of the KS
 Limits breadth and depth of the project within financial, human resource, sales n marketing and
operational constraints.
System feasibility
Doable
affordable
appropriate
practicable


KM Team Formation

Experts CHAMPION
Progress
Reports
Prototypes Demos
Support
Feedback
Solutions
Interactive
Interface KNOWLEDGE
User DEVELOPER
Acceptance

Rules Knowledge
Testing

KNOWERS
KNOWLEDGE
BASE


Knowledge Capture and Transfer
Through Teams

Team performs Evaluate relationship
Outcome
a specialized task between action and
Achieved
outcome

Feedback

Knowledge
Knowledge Developer
transfer
Knowledge method
stored in a selected
form usable
by others in
the
organization


Design of the KM Blueprint
Key layers of a KM system
User Interface Via Browser
Part of the Internet
Authentication/ security layer
(includes access identification, Firewalls and user recognition)
Internal layer that the company IT controls
Collaborative Agents and filtering
(intelligent S/W disseminate news and make intelligent searches)
Agent technology is intelligence within a KM system.
Application Layer
(collaborative work tools, video conferencing, group decision support tools etc)
Upper part of the Data communication network layer.
Transport/Internet Layer
(TCP/IP etc)
Manage transmission of data between computers.
Physical Layer
(Cables, physical wires, modems .. for transmission)
Transmission raw data in bit format to destination.
Repositories
H/D and storage devices
Documents and files, Knowledge Base, DB, Legacy Applications


Technical Layers of the KM System
.....

1 User Interface
(Web browser software installed on each user’s PC)

Authorized access control
2 (e.g., security, passwords, firewalls, authentication)

Collaborative intelligence and filtering
3 (intelligent agents, network mining, customization, personalization)

Knowledge-enabling applications
4 (customized applications, skills directories, videoconferencing, decision support systems,
group decision support systems tools)

Transport
5 (e-mail, Internet/Web site, TCP/IP protocol to manage traffic flow)

Middleware
6 (specialized software for network management, security, etc.)

The Physical Layer
(repositories, cables)
7

K bases Legacy applications
Groupware Data warehousing
(document exchange, (data cleansing,
collaboration) data mining) 71

Testing the KM System
• Verification procedure:
Ensures that the system is right that the programs do what they are
designed to do..
Technical performance from the functional perspective
• Validation procedure:
Ensures that the system is the right system
checks reliability of the KM system.


Implementing the KM System
• Converting a new KM system into actual operation

• Updating the existing H/W & network

• Training
• Quality assurance includes checking for:
– Reasoning errors
– Ambiguity
– Incompleteness
– False representation (false positive and false negative)


Manage change and reward structure
Resisters of Change
• Regular employees (users)

• Troublemakers

• Narrow-minded superstars. IT staff resist any change that they did
not initiate or approve in advance.

Resistance via projection, avoidance, or aggression


Post system Evaluation of Change”
• How has the KM system changed the accuracy and timely of
decision making?

• Has the new KM system caused organizational changes – e.g. BPR?
How constructive the changes been?

• How has the new KM system affected the attitude of the end
users?

• How has the new KM system changed the cost of operating the
business – low cost leadership strategy? How significant was it?

• Do the solution and advice derived from the new KM system justify
the cost of investment?

A.A. .T.M.T.
S - IS Masters – MIS, 2010

CAPTURING TACIT
KNOWLEDGE

What Is Knowledge Capture ?
• A process by which the
expert’s thoughts and
experiences are captured

• A knowledge developer
collaborates with an expert to
convert expertise into a
coded program

• In simple terms, we want to
“know” how experts know
what they know
4-77

Three important steps
• Use an proper tool or
technique to extract
information from the expert

• understand the information
and understand the expert’s
knowledge and reasoning
process

• Use the interpretation to
build rules that represent
expert’s solutions
4-78

Using a Single Expert
Advantages:
• Ideal when building a
simple KM system
• A problem in a restricted
domain
• Easier to coordinate
meetings
• Conflicts are easier to
resolve
• Shares more confidentiality
than does multiple experts

4-79

Using a Single Expert (cont’d)
Disadvantages:
• Sometimes expert’s knowledge is not
easy to capture
• Single expert provides only a single line
of reasoning
• Expert knowledge is sometimes
dispersed
• Single expert more likely to change
scheduled meetings than experts in a
team

4-80

Using Multiple Experts
Advantages:
• Complex problem domains benefit
from expertise of more than one
expert
• Working with multiple experts
stimulates interaction
• Allow alternative ways of
representing knowledge
• Formal meetings often a better
environment for generating
thoughtful contributions

4-81

Using Multiple Experts (cont’d)
Disadvantages:
• Scheduling difficulties
• Disagreements often occur among
experts
• Confidentiality issues
• Requires more than one knowledge
developer
• Overlapping mental processes can
lead to “process loss”

4-82

Approaching Multiple Experts

•Individual
– An extension of single
expert approach
•Primary and secondary
– Start with the senior expert
first, on down to others in
the hierarchy
•Small groups
Each expert tested against
expertise of others in the
group
4-83

Developing a Relationship With
Experts
• Understanding the
expert’s style
• Prepare well for the
session
• Decide where to hold
the session

4-84

Styles of expert’s expressions
 Procedure type
– methodical approach to the solution
 Storyteller
– focuses on the content of the domain at the
expense of the solution
 Godfather
– compulsion to take over the session
 Salesperson
– spends most of the time explaining his or her
solution is the best


Preparing for the session

 Should become familiar with the project
terminology

 review existing materials

 Learn the expert’s language


Deciding where to hold the
sessions
 Beneficial in recording the expert’s
knowledge in the environment where he
or she works

 An important guideline is to make sure
the meeting place is quiet and free from
interruptions


The Interview As a Tool
• Commonly used in the early
stages of tacit knowledge
capture
• The voluntary nature of the
interview is important
• Interviewing as a tool requires
training and preparation
• Convenient tool for evaluating
the validity of information
acquired

4-88

Types of Interviews
 Structured: Questions and responses are definitive.
Used when specific information is sought
 Semi-structured: Predefined questions are asked but
allow expert some freedom in expressing the
answers
 Unstructured: Neither the questions nor their
responses specified in advance. Used when
exploring an issue


Variations of Structured
Questions
 Multiple-choice questions offer specific choices,
faster tabulation, and less bias by the way
answers are ordered

 Dichotomous (yes/no) questions are a special
type of multiple-choice question

 Ranking scale questions ask expert to arrange
items in a list in order of their important or
preference


Guide to a Successful
Interview
• Set the stage and establish
relationship
• Properly phrase the questions
• Question construction is
important
• Listen closely and avoid
arguments
• Evaluate session outcomes

4-91

Ending the Interview
 Ending the interview requires sensitivity
to the expert’s preferences, use of verbal
and non verbal cues.

Nonverbal cues for ending an interview;
-Look at watch and uncross legs.
-Put cap on pen, close folder gently and
uncross legs.
-If taping session, stop taping and rewind
tape.
-Stop taking notes and place writing
materials in briefcase.

92 IS Masters – MIS – Knowledge Management, 2010

Ending the Interview
Verbal cues for ending an interview;
-This is summary of the session. Do you
have any suggestions?
-I think I asked all the questions I had in
mind. I appreciate your time.
-My allowed time is up. I know you have
another meeting soon.
-This looks to be an informative meeting.
How about scheduling another one.
-This covers pretty much what I had in
mind. Did I miss anything!
.


Things to Avoid
• Taping a session without advance permission
from the expert
• Converting the interview into an interrogation
• Interrupting the expert
• Asking questions that put the domain expert
on the defensive
• Losing control of the session
• Pretending to understand an explanation when
you actually don’t
• Promising something that cannot be delivered
• Bring items not on the agenda
4-94

Errors Made by the Knowledge
Developer
• Age effect
• Race effect
• Gender effect

4-95

Problems Encountered During
• Response bias the Interview
Questions like; Isn’t it true.. , Don’t you think..
May get a biased answer “Yes”.

• Inconsistency
occur when the knowledge developer interviews two domain experts
and is inconsistent when asking the questions.
The questions and their order should be standardized.
The questions must mean the same thing to all the experts being interviewed.

• Communication difficulties
• Hostile attitude
bad chemistry between expert and knowledge developer,
an expert is forced in participation,
or time wasted on repeated dead ends, etc

• Standardized questions
• Lengthy questions

• Long interview
Duration of the interview should last no more than one hour.
Expert attention begins to breakdown and quality of thoughts
decrease
within long interviews.

Validate Information
 Various validation and cross-checks should be applied
before captured knowledge can be represented.

 For example, one way to cross validate an expert
opinions is to ask another expert and check for
similarities between the two opinions.

 Another way to validate an opinion is to ask the
question again at the next session in a different way
to see if the expert gives the same answer.


On-Site Observation
 Process of observing, interpreting, and recording problem-solving behavior while it
takes place by experts.
 In addition, the knowledge developer asks the expert questions about the problem
solving process.
 The protocol of observation is more listening than talking.
 Dose not argue with the expert while performing a task.
 Avoid giving advices to expert while observing. .
 The problem here is that some experts don’t like to be observed.
 Experts fear of ‘giving away’ their experience in a quick look.
 Observation process can be distracting to others in the setting.


Brainstorming
 Unstructured approach to
generating ideas about a
problem;
 invites two or more experts
into a session in which
discussion are carried out.
 The primary goal of brain
storming is to think up creative
solutions to problems.
 All possible solutions are
considered equally.
 Anything related to the topic
can be brought up, and
99 everything is valued. – Knowledge Management, 2010
IS Masters – MIS

Brainstorming
 Questions can be raised for
clarification, but no evaluation
is made at the moment.
 Idea generation, followed by
idea evaluation.
 In the evaluation phase, the
knowledge developer explains
each idea and treats any
comments or criticism
accordingly.


Brainstorming Procedure
 Introduce brainstorming session;
explain what is to be accomplished, the role of each participant
and the expected outcomes.
 Give experts a problem to consider;
The problem must be in the experts’ domain of expertise.
The knowledge developer must give experts time to think within a
reasonable time limits.
 Prompt the experts to generate ideas;
The experts can do this either by calling out their ideas or by order in
which each expert is given a turn to speak..
The knowledge developer must keep pace with the expert.
 Watch for signs of convergence;
Ideas often trigger counter opinions that should eventually reach a
final
solution. If the experts can not agree on the final solution, the
knowledge developer must
 Call for a vote or a consensus to reach agreement

Electronic Brainstorming
 Computer-aided approach to dealing
with multiple experts.
 U-shaped desks hold PCs networked
through a S/W tool that promotes
instant exchange of ideas between
experts.
 Projector, whiteboards, and printers
are also a part of the infrastructure
environment for electronic
brainstorming.
 Begins with a pre-session plan that
identifies objectives and structures
agenda, which is presented to experts
for approval.


Electronic Brainstorming
 Allows two or more experts to
provide opinions through PCs without
having to wait their turn.
 The S/W displays the comments or
suggestions on a huge screen without
identifying the source.
 Protects shy experts and prevents
tagging comments to individuals.
 The overall benefits include improved
communication, effective discussion
of sensitive issues, and consider
recommendations for action.


Protocol Analysis
 Think-aloud method.
How each expert arrived at the solution
through verbalization.
Expert keeps talking, speaking out loud
while solving a problem
 Effective source of information on cognitive processes
Makes expert cognizant of the processes being described; it
is a cognitive approach to problem solving.
 Provides rich information that is very useful to knowledge
capture and representation.
 “there are other ways to reach the same solution”


Delphi Method
 “When two or more heads are more
numerous than one”
 Another tool used for tacit knowledge
capture.
 A survey of experts. Experts are polled
concerning a given problem.
 A series of questionnaires used to pool
experts’ responses in order to solve a
difficult problem.


Delphi Method
 Responses are usually anonymous and are
collected asynchronously, either my mail,
e-mail, or online survey.
 During each round the results of the
previous questions is fedback to
participants who are then asked to revise
and consolidate their answers even more.
 After several rounds the solicited experts
may arrive as a consensus or the
researchers may average final responses
toward a conclusion.
 This method is a powerful and efficient
way of drawing on distributed expertise at
low cost, time, and inconvenience

What is Knowledge Base-
Systems ?
 system that uses artificial intelligence techniques in problem-
solving processes to support human decision-making,
learning, and action.
 Is a special kind of database for knowledge management,
providing the means for the computerized collection,
organization, and retrieval of knowledge.


Advantages & Disadvantages of
KB

• make up for shortage of experts, spread expert’
knowledge on available price.

Advantage
• increase expert’ ability and efficiency.
• preserve know-how.
• can be developed systems unrealizable with traditional
technology .
• are available permanently.
• able to work even with partial, non-complete data.
• able to give explanation.


Cont.(Advantage &
Disadvantage)

• Their knowledge is from a narrow field, don’t know the
limits.
• The answers are not always correct (advices have to be
analyzed!).
Disadvantage • Don’t have common sense (greatest restriction) → all of
the self-evident checking have to be defined.


Knowledge-Based DSS
 Advanced DSS are equipped with a component
called a knowledge-based management
subsystem that can supply the required expertise
for solving some aspects of the problem


Traditional DSS Components
User

User Interface

KBS1

DBMS MBMS

KBS2 KBS3


INTEGRATING DSS AND KNOWLEDGE
MANGEMENT 112

Framework for INTEGRATING DSS
AND KNOWLEDGE MANGEMENT


Traditional computing environment vs.
Intelligent Agents computing environment
 Traditional computing
Issue Commend
Display Result

 Intelligent Agents computing
Issue Command & delegate task
(Monitor xx stock price)
Agent Monitor

Share Result Computing Stock
(xx price dropped 1 point)

Request advises
(purchase stock??)


Functions of KB-DSS

 KB-DSS can provide the following:
– An interface to support man-machine cooperation
during problem solving
– Support access to relevant information during
problem solving
– Support problem recognition
– Support problem structuring


AUTOMOBILE DIAGNOSTIC
SYSTEM


computer-based Expert
Systems
• This presentation shows
you how a computer-
based expert system
emulates the behavior
of a human advisor,
introduces the activities
that must be
accomplished to build
expert systems.


Automobile diagnostic system
• To introduce terms like
expert and expertise as
they are relevant to
expert systems, let's
suppose you have been
unable to start your car to
go to work and you call
your favorite mechanic.
The dialog might continue
something like this...


Good morning
this is Sambo
Auto Repair
Hey Sambo, this is Abass
Mahmoud. My car
wouldn't start this
morning and I need
some help...


What happens when you Here is the the beginning of the
turn the key in the diagnostic telephone "interview" with
ignition to try to start the your mechanic...
car?

It turns over OK, but it
just won't start.


Hmmm...are your sure Based on your input that the starter
that you aren't out of operates, your mechanic can abandon a
gas? number of hypotheses related to electrical
problems. Now the expert is evaluating
another possible explanation...

Well, now that you
mention it - I'm not
certain the tank is empty,
but it probably is.


At this point, your mechanic is attempting to
As you crank the starter, confirm the new hypothesis...
do you smell gas?

No, I turned it over for a
long time, but didn't smell
anything.


Based on what you've Your mechanic now has enough evidence to
told me, I'm almost diagnose the problem. Once you've heard
certain your car is out of the recommendation, you might want an
gas. explanation of how the conclusion was
obtained...

Thanks for the advice.
Mind telling me how you
reached your conclusion?


You solved your automotive problem by
When a car won't start my initial consulting with an expert. Let's take a look
suspicion is that the battery is at the definition of expertise relevant to
dead, the starter has failed or expert systems and the attributes of an
some other electrical problem effective consultant a computer will have to
exists. Your input that the starter emulate to substitute for a human advisor...
operates makes it more likely
that no fuel is getting to the
engine. Although you are not
sure that the gas tank is empty,
the fact that you don't smell gas
when the engine turns over
supports my conclusion that you
are out of gas.


What's an expert?
• An expert is one who
possesses specialized skill,
experience, and knowledge
that most people do not have
along with the ability to apply
this knowledge using tricks,
shortcuts, and rules-of-thumb
to resolve a problem. An
expert's advice has to be good
enough most of the time for
the expert to keep his or her
reputation, but is not expected
to be perfect or even the
globally best available to be
considered useful


What are the attributes of
effective consultants and
consulting?
Consulting is goal oriented

A good consultant is efficient

Consultants are able to work with imperfect information

Good consultants justify their recommendations by
explaining their reasoning


the attributes of effective
consultants and consulting
• Here's an illustration of
each of these attributes
from the auto diagnosis
example...


Consulting is goal oriented
The objective in calling your mechanic is to
What happens when you get a very specific answer to a very specific
turn the key in the ignition question. You aren't interested in learning
to try to start the car? how a fuel injection system works or how to
rebuild a starter -- even though your expert
would be quite capable of providing this
information. The objective of the consultation
represents a goal in expert system
terminology, and there can be one or many
goals to be satisfied during a consultation with
a human expert or a computer-based expert
system
It turns over OK, but
it just won't start.


A good consultant is efficient
Your answer to the mechanic's first question
eliminated a large number of possible
Hmmm...are your sure
problems from further consideration. A good
that you aren't out of gas?
consultant will stop asking questions relevant
to hypotheses that can be rejected based on
evidence at hand. Because you said the
starter operates (eliminating battery
problems) it makes no sense to ask you if the
headlights light or the horn blows.

Well, now that you
mention it - I'm not
certain the tank is empty,
but it probably is.


A consultation is adaptive
When the information needed to make a
recommendation isn't available, the expert
As you crank the starter,
will try other lines of questioning that will
do you smell gas?
help confirm the hypothesis. You weren't sure
the gas tank is empty, so the question about
smelling gasoline was posed.

No, I turned it over for a
long time, but didn't smell
anything. .


Consultants are able to work with
imperfect information
Based on what you've told You aren't sure the fuel tank is empty, but
me, I'm almost certain think it probably is. By combining your less
your car is out of gas. than certain information with the evidence
provided by the fact that you don't smell
gasoline while the engine turns over, the
expert can conclude that you are out of gas
with a high degree of certainty.

Thanks for the advice.
Mind telling me how you
reached your conclusion?


Consultants justify their
recommendations by explaining
their reasoning
The application of expertise is not a guessing
When a car won't start my initial game. A real expert should be able to
suspicion is that the battery is explain how evidence was used to evaluate
dead, the starter has failed or rules-of-thumb to develop
some other electrical problem recommendations. Given the nature of the
exists. Your input that the starter consulting process just described, does it
operates makes it more likely that make sense to try to deliver advice without
no fuel is getting to the engine. the physical presence of an expert?
Although you are not sure that the
gas tank is empty, the fact that you
don't smell gas when the engine
turns over supports my conclusion
that you are out of gas.


Knowledge management

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