d0d8d4d61e91542bf117754f4bfb9b31.ppt
- Количество слайдов: 63
Knowledge emerges through the interaction of people in clusters
Tacit and Explicit: Measure and Map it KM World Wednesday October 31, 2001 Valdis Krebs, Margaret Logan, Eric Zhelka
KNETMAP™ Confirmed Tie Knowledge Artifact!
Knowledge Artifacts “Artifacts are the tangible things people create or use to help them get their work done. When people use artifacts, they build their way of working right into them. ” --- Hugh Beyer and Karen Holtzblatt: Contextual Design: Defining Customer-Centered Systems
Artifact Generator
Armstrong Enterprise Capital Model EFFECTIVITY ( H-S ) = EFFICIENCY X UTILIZATION X = HUMAN CAPITAL EFFECTIVITY ( H-C ) = EFFICIENCY X UTILIZATION X = STRUCTURAL CAPIT EFFECTIVITY ( S-C ) = EFFICIENCY X UTILIZA X CUSTOMER CAPITAL = VALUE IN WAITING
Armstrong Enterprise Capital Model
Business Reality. . . FROM Value added . . . TO Value added Market Demands Organizational Capability Time Hubert Saint Onge Organizational Capability Market Demands Time
Korn/Ferry International Report • “More Than 70 Percent of Employees Report Knowledge is Not Reused Across the Company” • “Importing Knowledge is Key…through effective external partners” • Changing the focus and behaviour of employees at all levels lies at the core
Conductivity vs.
Porosity
Conductivity Connections
Conductivity and Porosity Value Added Organizational Capability Market Demands Time Conductivity H. Saint-Onge Connections
Organizational Networks c Closed Network Entrepreneurial/Open Network • Exploitation • Exploration • Few independent sources of info • Many independent sources of info • Little Diversity (more homogeneous) • Great Diversity • Local • Global
Network Metrics • • Network size Number of relationships Clustering Coefficient Redundancy Effective Network size Reach-In* & Reach-Out* Porosity*
REACH …. a measure of local access in the network i. e. the number of connections that can be reached in one or two steps. • Reveals the influence of a node
REACH-In • High REACH-In means that many people reference this individual • Also applies to knowledge artifacts if it is an influential source document
REACH-Out • High REACH-Out means this individual connects to other individuals who are also ‘good connectors’ • Applies to knowledge artifacts if many influential source documents are referenced
Hubs and Authorities • High Reach-In is known as an “Authority” • High Reach-In AND High Reach-Out is known as a “Hub”
Hansen’s T-Manager Metric • A ratio of how knowledge is shared freely across the organization (the horizontal part of the “T”) against the individual business unit performance (the vertical part).
KNETMAPTM A means to monitor the constantly changing dynamics of our enterprise information flows
An MRI of your organization. . . • All the key players in the various networks • Who’s not well connected but should be • Use and Re-Use of knowledge artifacts • What relationship building beyond the borders looks like
What if you could query your organization?
How to gather data? • • Surveys? Voluntary contributions? Daily Question? Weekly Question?
Question of the Week. TM • Sent via email • Each individual response builds an organizational map • With each submission, it becomes clear who the experts are…the picture comes into focus as data is submitted
Via email From: john@konverge. com To: Margaret Logan Subject: Question of the Week. Sent: 10/4/2001 4: 53 PM Dear Margaret: Please answer the Question of the Week by clicking on the link below To whom do you go for information on Java technologies? Thank You
Case Study: Qof. Week in IT Firm • Konverge Digital Solutions Inc. (Toronto) • 25 developers, programmers and systems analysts • 7 years old
Strategic Objectives • 30% Growth • More reuse of code • Higher awareness of extended expert network • Customer centricity • Faster integration of new staff
Question of Week • Week 1: To whom do you go to solve complex problems concerning. Net technologies? • Week 2: To whom do you go to solve complex problems concerning XML? • Week 3: To whom do you go to solve complex problems concerning JAVA?
In. Flow 3. 0 • • Organizational Network Analysis software Used by int. /ext. consultants since 1993 Network Visualization Network Metrics – – – Centrality Structural equivalence Cluster analysis Small-world analysis Network vulnerability • Two-way data flow with KNETMAPTM
In. Flow Results Qof. W 1 To whom do you go to solve complex problems concerning. Net technologies? Qo. W 1 : Reach (In) 0. 690 0. 655 0. 621 0. 586 0. 448 0. 379 0. 310 0. 138 0. 103 0. 069 0. 034 Agnelo Dias Young Yang Yuchun Huang Wilson Hu Edna De La Paz Jeremy Brown Eric Zhelka John Morning Howard Thompson Louisa Hu Arik Kapulkin Dino Bozzo Steve Chapman Angelo Del Duca Hugh Mc. Grory John Macdonald Leif Frankling Sherwin Shao Susie Guo
In. Flow Results Qof. W 2 To whom do you go to solve complex problems concerning XML? Qo. W 2 : Reach (In) 0. 783 0. 739 0. 652 0. 609 0. 478 0. 348 0. 261 0. 217 0. 130 0. 043 Agnelo Dias Wilson Hu Jeremy Brown Dino Bozzo Young Yang Alex Bozzo Louisa Hu Eric Zhelka Alex Hodyna Sherwin Shao Yuchun Huang Arik Kapulkin Brian Bennett Howard Thompson Blake Nancarrow Julia Elefano Laura Childs Mahamed Idle Susie Guo
In. Flow Results Qof. W 3 To whom do you go to solve complex problems concerning JAVA? Qo. W 3 : Reach (In) 0. 750 0. 708 0. 458 0. 417 0. 292 0. 208 0. 125 0. 083 0. 042 Young Yang Agnelo Dias Wilson Hu Eric Zhelka Jeremy Brown Alex Hodyna Dino Bozzo Sherwin Shao Steve Webster Arik Kapulkin Brian Bennett Howard Thompson John Macdonald Louisa Hu Alex Bozzo Laura Childs Yuchun Huang
Case 2: Two departments. . . • Two newly merged IT departments • Question: With whom will you seek opinions on best practices in requirements analysis and writing requirement specifications? • We emailed the question at 9 AM. . .
Results after first hour. . .
Not fully integrated yet Boundary spanners
Right-click on a node for a drop-down menu. . .
Who are the 6 incoming links?
The six incoming links. . .
Extended neighbourhood. . .
30 node extended neighbourhood
Use and Re-Use [of knowledge artifacts] • Encourages better objectivity • Encourages better documentation • Can be built into the mindset of programmers • Indicator for peer code approval • A form of ‘signature’
Searchable Expertise • Retrieve previous Qof. Week results on a particular issue of expertise • Qof. Week “institutionalizes” information about expertise
Right-clicking on node links to Yellow Page
Yellow Page
Yellow Page contains Artifact List
Artifact Generator
Reach IN/OUT and Inside/Outside T
What We Learned • 4% respondents entered data (contacts) incorrectly first time (by not understanding the question or by second-guessing the purpose) • subsequent Qof. Weeks went smoothly • Need to make data gathering simple and painless
Next Steps • Repeat questions in 3 month cycles • Develop better questions based on the indicators (see Sveiby’s Intangible Assets Monitor. TM) • Consider automated requests to expert nodes (hubs/authorities) to populate their Yellow Page with artifacts related to their expertise
Conclusions • We can establish quantitative measures for any type of network • 52 weekly questions construct a unique organizational profile in one year • Gathering survey data via email is highly effective
Benefits to Membership • Encourages networking • Excellent feedback system • T-metric a useful indicator for both intra-company and intercompany relationship building • New employees integrate faster
Addresses known KM Challenges • Managing tacit and explicit knowledge simultaneously • Locating internal and external expertise • Managing loss of critical know-how
Addresses known KM Challenges • Visualizing the impact of organizational changes • Encourages knowledge sharing • Exposes expertise & innovation • Provides context to static data (databases)
Further Information • KNETMAP knetmap. com • Valdis Krebs valdis@knetmap. com • Margaret Logan marglogan@knowinc. com • Eric Zhelka eric@konverge. com • Krebs Toolkit krebstoolkit. com(January 2002)
Coming soon… First quarter 2002
We thank and acknowledge the support of IRAP, The Industrial Research Assistance Program of The National Research Council of Canada