1. Knowledge Mapping: An Overview Prof Elaine Ferneley

2. 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
Focus, resources are limited
KM has its own tools &
techniques
Prof Elaine Ferneley

3. 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

4. Practices & Processes Our focus today Creating & Discovering
creativity techniques
data & text mining
knowledge elicitation
business simulation, content analysis
Sharing & Learning
communities of practice, learning networks
share fairs, share best practice
cross functional teams, action reviews
Organizing & Managing
knowledge centres, knowledge audits
expertise profiling, knowledge mapping
measurement of intellectual capital
Prof Elaine Ferneley

5. 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

6. 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

7. 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

8. How & Where Should I be Looking
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

9. How & Where Should I be Looking
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

10. How & Where Should I be Looking
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:
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

11. 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

12. 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

13. Explicit model of who has what knowledge
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

14. SBS Staff Expertise – figures are fictional!
Prof Elaine Ferneley

15. Useful as brainstorming tools
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:
Prof Elaine Ferneley

16. Assistum Knowledge Editor - http://www. assistum
Prof Elaine Ferneley

17. STELLA http://www. iseesystems
Prof Elaine Ferneley

18. Examples
Prof Elaine Ferneley

19. Examples
Prof Elaine Ferneley

20. 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

21. Hand Drawn Mind Map
Prof Elaine Ferneley

22. MindJet Mindmap
Prof Elaine Ferneley

23. 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

24. Consider further mechanisms to encourage:
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