Knowledge Mapping: An Overview Dr. Elaine Ferneley
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Transcript Knowledge Mapping: An Overview Dr. Elaine Ferneley
Knowledge Mapping: An Overview
Prof Elaine Ferneley
Revisiting the Definition of Knowledge
Management (Skyrme’s)
Don’t leave it to
serendipity
Surface assumptions,
Codify what is known
Knowledge Management is the explicit and
Systematic management of vital knowledge - and its
associated processes of creation, organisation, use & exploitation
KM has its own tools &
techniques
Focus, resources are limited
Prof Elaine Ferneley
Seven Strategic Levers [Skyrme, 2002]
Customer Knowledge - the most vital knowledge in most
organizations
Knowledge in Processes - applying the best know-how while
performing core tasks
Knowledge in Products (and Services) - smarter solutions,
customized to users' needs
Knowledge in People - nurturing and harnessing brainpower, your
most precious asset
Organizational Memory - drawing on lessons from the past or
elsewhere in the organization
Knowledge in Relationships - deep personal knowledge that
underpins successful collaboration
Knowledge Assets - measuring and managing your intellectual
capital.
Prof Elaine Ferneley
Practices & Processes
Our focus today
Creating & creativity techniques
Discovering data & text mining
knowledge elicitation
business simulation, content analysis
Sharing &
communities of practice, learning networks
Learning
share fairs, share best practice
cross functional teams, action reviews
Organizing knowledge centres, knowledge audits
& Managing expertise profiling, knowledge mapping
measurement of intellectual capital
Prof Elaine Ferneley
What is Knowledge Mapping
Ongoing quest in an organisation (includes supply & customer chain):
Discover knowledge location and ownership;
Identify value and use of knowledge artefacts;
Learn roles & expertise of individuals;
Identify constraints in flow of knowledge;
Highlight opportunities to leverage existing knowledge.
Knowledge mapping activities:
Survey, audit and synthesis;
Identify where knowledge is being acquired and lost;
Personal and group competencies and proficiencies;
Identify how knowledge flows through an organisation.
Knowledge mapping helps organisations:
Appreciate how loss of staff influences Intellectual Capital;
Select teams
Match technology to knowledge needs.
Prof Elaine Ferneley
Key Principles of Knowledge Mapping
Understand that knowledge is transient;
Explain boundaries & respect personal disclosures;
Recognise knowledge comes in a variety of forms:
Tacit ‘v’ explicit;
Codified ‘v’ personal;
Short ‘v’ long lifecycle.
Locate knowledge in processes, people, relationships,
documents; suppliers, customers etc.
Be aware of organisational hierarchies, cultural issues,
reward mechanisms, sharing & value, legal processes &
protections (patents, NDAs, MoUs etc.)
Prof Elaine Ferneley
What is a Knowledge Map & Why Use One ?
Navigation aid to explicit and tacit knowledge;
Portrays sources, flows, constraints and sinks of
knowledge within an organisation;
Encourages re-use and prevents re-invention, saves
search time;
Highlights expertise, discover communities of practice,
helps staff to find critical resources;
Improves decision making, problem solving and customer
response time by providing access to information;
Provides an inventory of intellectual and intangible assets;
The start of a corporate memory or collective mind.
Prof Elaine Ferneley
How & Where Should I be Looking?
Active Knowledge Elicitation Techniques
Formal and informal interviews:
Interviewer asks the expert or end
user questions relating to the
specific topic
Adv: well known, comfortable for
interviewees
DisAdv: time consuming,
expensive, interviewer expertise
required, interviewee cooperation
required
Verbal Protocol Analysis:
Experts report thought processes
involved in performing a task or
solving a problem
Adv: rigorous
DisAdv: time consuming, hard to
analyse
Group Task Analysis:
A group of experts describes and
discusses processes pertaining to a
specific topic
Adv: multiple viewpoints,
concensus building
DisAdv: how to validate
Narratives, Scenarios, Storytelling
Expert or end user constructs
stories to account for a set of
observations
Adv: rich insight, good for ill
defined problems
DisAdv: reliance on self reports
Questionnaires:
Users respond to specific questions
Adv: usually quantitative, easy to
code
DisAdv: low return rate, responses
are difficult to validate
Prof Elaine Ferneley
How & Where Should I be Looking?
Active Knowledge Elicitation Techniques
Focus Groups
A group discusses different issues
Adv: allows exchange of ideas, good for
generating complete lists
DisAdv: an individual may dominate,
not good for discovering specific
problems
Wants & Needs Analysis:
Users brainstorm about what they
want/need from a system
Adv: exchange of ideas, determines
areas for focus, allows prioritisation
DisAdv: wants and needs may not be
realistic
Observation:
Observe users in their natural
environment
Adv: see it as it really is (but not
ethnography)
DisAdv: time, depends on observer note
taking & observation skills
Ethnographic Study:
Users culture and work
environment are studied via
emersion
Adv: see it as it really is over a long
time period
DisAdv: time consuming, hard to
distance yourself from the domain
User Diary
Users record and evaluate their
actions
Adv: real time (almost) tracking
DisAdv: invasive, possible delay in
recording
Concept Sorting
Users determine relationships
between concepts
Adv: helps structure information
DisAdv: grouping is user specified,
structure may be too elaborate
Prof Elaine Ferneley
How & Where Should I be Looking?
Passive Knowledge Elicitation Techniques
News feeds:
Discussion groups;
Company magazines;
Bulletins.
Contact addresses
Organisation charts;
Home pages.
Network transactions:
Email tags;
Semantic analysis.
Helpdesks and CRM systems:
Interaction logs;
Process scripts.
Asset and HR databases
(company CVs);
LAN directory structures:
Who has access to what;
Why do they have access.
Library & record archives
Process descriptions:
QA documents;
Procedure manuals.
Meta-data directories:
Standardisation documents;
Meta-tags on electronic data
sources.
Prof Elaine Ferneley
What do I do with the information?
Compile:
Yellow pages/register of interests;
Best practice/lessons learnt databases;
Prototype ontology/taxonomy
Identify:
Knowledge stewards/gatekeepers;
Isolated islands, narrow communication channels;
Critical sequences/dependencies.
Explore reuse opportunities:
Attempting to create a knowledge network of people,
processes and data.
Prof Elaine Ferneley
We Will Now Look at Some Specific Examples
Spreadsheets – great and simple to use,
disseminate and for all to understand
Cause and effect models
The example we will use is from ISEEE
Prof Elaine Ferneley
Simple Spreadsheets
Explicit model of who has what knowledge
Value of various knowledge items can be
weighted
Allows transparency
Encourages people to state their knowledge
and expertise
Cheap and one of the most effective tools
I’ve seen, everyone understands a
spreadsheet
Prof Elaine Ferneley
SBS Staff Expertise – figures are fictional!
Prof Elaine Ferneley
Auditing Tools
Tools that allow you to classify expertise,
apply some sort of rating or ranking to
knowledge domains;
Useful as brainstorming tools
Strongly encourage you to download
Assistum:
http://www.assistum.com/2002/products/example
s/java/project.htm
Prof Elaine Ferneley
Assistum Knowledge Editor http://www.assistum.com/2002/products/examples/java/project.htm
Prof Elaine Ferneley
STELLA
http://www.iseesystems.com/community/downloads/Education
Downloads.aspx
Prof Elaine Ferneley
Examples
Prof Elaine Ferneley
Examples
Prof Elaine Ferneley
Mind Mapping – For Brainstorming, Knowledge Elicitation
and Knowledge Mapping
Mind Mapping is a technique developed by Tony
Buzan to help individuals organise, generate and
learn ideas and information
Pictorial representation – detail and overview
together
Consider spatial relationships and anticipate
consequences
Supported by visual processing – improved recall,
aids understanding
Explicit representation acts as a creativity trigger
Prof Elaine Ferneley
Hand Drawn Mind Map
Prof Elaine Ferneley
MindJet Mindmap
Prof Elaine Ferneley
Why Mind Map Software – the Pro’s and Con’s
Supports continuous
refinement
Allows variable granularity
Brings formality (validity?)
to the process
Integration with other
tools
Cross ref & re-assembly of
elements of the
knowledge base possible
Slow
Horde mentality (difficult
to throw away early
versions)
Semantics – in large
implementations is the
same vocabulary being
used
Common understanding
Maintenance – especially
due to the transitory
nature of the output
Prof Elaine Ferneley
The Next Step
Consider further mechanisms to encourage:
Relinquishing of knowledge;
Creation of new knowledge;
Brainstorming tools;
Capturing of the brainstorming activity.
Representing knowledge in a highly
structured database does not encourage
this ….
Prof Elaine Ferneley