Knowledge Mapping: An Overview
Prof Elaine Ferneley
Revisiting the Definition of Knowledge
Management (Skyrme’s)
Don’t leave it to
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 &
Focus, resources are limited
Prof Elaine Ferneley
Seven Strategic Levers [Skyrme, 2002]
 Customer Knowledge - the most vital knowledge in most
 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
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
 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
 DisAdv: time consuming,
expensive, interviewer expertise
required, interviewee cooperation
 Verbal Protocol Analysis:
 Experts report thought processes
involved in performing a task or
solving a problem
 Adv: rigorous
 DisAdv: time consuming, hard to
 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
 Adv: rich insight, good for ill
defined problems
 DisAdv: reliance on self reports
 Questionnaires:
 Users respond to specific questions
 Adv: usually quantitative, easy to
 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
 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
 Observation:
 Observe users in their natural
 Adv: see it as it really is (but not
 DisAdv: time, depends on observer note
taking & observation skills
 Ethnographic Study:
 Users culture and work
environment are studied via
 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
 Adv: real time (almost) tracking
 DisAdv: invasive, possible delay in
 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
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
Allows transparency
Encourages people to state their knowledge
and expertise
Cheap and one of the most effective tools
I’ve seen, everyone understands a
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
Prof Elaine Ferneley
Assistum Knowledge Editor
Prof Elaine Ferneley
Prof Elaine Ferneley
Prof Elaine Ferneley
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
 Consider spatial relationships and anticipate
 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
 Allows variable granularity
 Brings formality (validity?)
to the process
 Integration with other
 Cross ref & re-assembly of
elements of the
knowledge base possible
 Slow
 Horde mentality (difficult
to throw away early
 Semantics – in large
implementations is the
same vocabulary being
 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

Knowledge Mapping: An Overview Dr. Elaine Ferneley