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 Focus, resources are limited KM has its own tools & techniques 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 & 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

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 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 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 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

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

SBS Staff Expertise – figures are fictional! Prof Elaine Ferneley

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: http://www.assistum.com/2002/products/examples/java/project.htm Prof Elaine Ferneley

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

STELLA http://www. iseesystems 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

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