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Tapping Social Networks to Leverage Knowledge and Innovation Patti Anklam Hutchinson Associates
©2003 Patti Anklam Acknowledgment Work with Social Network Analysis at Nortel was bootstrapped through participation in research with the Institute for Knowledge-Enabled Organizations (IKO)* Rob Cross and Andrew Parker, researchers, provided “above and beyond” support for key projects as well as solo projects during my learning process. *Formerly Institute for Knowledge Management (IKM)
©2003 Patti Anklam Customer StructuralHuman Context: Knowledge Management is about Leveraging Capital Social “Social capital consists of the stock of active connections among people; the mutual understanding, trust, and shared values and behaviors that bind the members of human networks and communities and make cooperative action possible.” Don Cohen & Laurence Prusak In Good Company
©2003 Patti Anklam The Science of Networks Multi-disciplinary research and applications Physics Cell biology Internet and WWW Economics and social sciences Epidemiology Homeland security Supported by mathematical evidence that networks of all types exhibit similar properties and architecture
©2003 Patti Anklam Metabolic Network Source: Albert Laszlo Barabasi
©2003 Patti Anklam A Social Network
©2003 Patti Anklam The Al Qaeda Network
©2003 Patti Anklam The Premise of Social Network Analysis for Knowledge Management Knowledge flows along existing pathways in organizations. To understand the knowledge flow, find out what the patterns are. Create interventions to create, reinforce, or change the patterns to improve the knowledge flow. Successful organizations understand the need to ensure that knowledge and learning are reaching all the parts of the organization that need them.
©2003 Patti Anklam Business objectives for doing an analysis Increased innovation, productivity, and responsiveness through plugging “know-who” gaps Smarter decisions about organizational changes and establishment of key knowledge roles Insight into challenges of knowledge transfer and integration following restructuring, mergers, or acquisitions
©2003 Patti Anklam The Methodology Interview managers and key staff to understand the specific business problems or opportunities Identify the network Survey the individuals in the network to determine existing connections among them Use computer modeling tools to depict the network Identify opportunities for improvement or potential problems (interviews and workshop) Design and implement interventions to change the network Follow up
©2003 Patti Anklam Data Collection and Survey Methods Qualitative Survey members of existing social networks to diagnose problems and identify opportunities Quantitative: Transaction analysis ( s, phone calls) Analysis of information artifacts ( , documents, search strings) to identify similarity of interests
©2003 Patti Anklam Qualitative Survey
©2003 Patti Anklam Survey Questions SNA for knowledge management questions: Frequency of knowledge exchange Value of interactions Knowledge of each other’s knowledge and skills SNA for organizational development: Decision-making paths Trust Energy Development of the questions and delivery of the survey must be sensitive and appropriate to the current context of the organization
©2003 Patti Anklam View of a Network = President = Operations = Product Line A = Small Accounts Functio n = Product Line B = Product Line C = HR/Finance = Large Accounts I frequently or very frequently receive information from this person that I need to do my job.
©2003 Patti Anklam Removing Managers, Administrators, and HR = Operations = Product Line A = Small Accounts Functio n = Product Line B = Product Line C = Large Accounts I frequently or very frequently receive information from this person that I need to do my job.
©2003 Patti Anklam Quantitative Analysis Provides Management Insight Density. Data provides the percentage of information-getting relationships that exist out of the possible number that could exist. It is not a goal to have 100%, but to target the junctures where improved collaboration could have a business benefit. Frequently or very frequently receive
©2003 Patti Anklam Junctures in Information Flow Target Opportunities for KM Density. Data provides the percentage of information-getting relationships that exist out of the possible number that could exist. It is not a goal to have 100%, but to target the junctures where improved collaboration could have a business benefit.
©2003 Patti Anklam Combining Question Results People want to communicate more with those who they already receive information from. Information Communicate More
©2003 Patti Anklam Innovation Group I frequently or very frequently receive information from this person that I need to do my job. = Portfolio = Technology Team = KM
©2003 Patti Anklam Innovation Group – Who Knows Who? I frequently or very frequently receive information from this person that I need to do my job. Separated by “do not know this person.” Everybody knows these people, or knows who they are Colors represent geographical locations
©2003 Patti Anklam Concepts Represented by Mathematics Distance: degrees of separation (also referred to as the diameter of a network) Ties/Degree: in-degree and out-degree represent the number of connections, or ties, to and from a person Centrality: the extent to which a network is organized around one or more central people Density: the percentage of connections that exist out of the total possible that could exist
©2003 Patti Anklam Comparative Metrics Provide Benchmarks
©2003 Patti Anklam Using the Results of SNA Organizational Leadership work Restructuring and process redesign Staffing and role development Categories of Interventions Knowledge Management Tools and technologies (expertise locators, discussion forums, and so on) Collaborative knowledge exchange and getting acquainted sessions Individual action Personal and public Personal and private
©2003 Patti Anklam Addressing Concerns Social Network Analysis practitioners are committed to use SNA in ethical ways, sensitive to individuals. Interviews are used to validate results with managers before displaying to wide audiences Results are presented in context
©2003 Patti Anklam Learning from Research
©2003 Patti Anklam Common Patterns Identified Clusters: dense subgroups Connectors: individuals who link to many people in an informal network (in some cases, bottlenecks) Boundary spanner: individuals who connect networks to other parts of an organization Information broker: connects clusters within an informal network Outliers: people less well connected, may be termed “peripheral specialist” Adapted from “The People Who Make Organizations Go or Stop” Rob Cross and Laurence Prusak Harvard Business Review, June 2002
©2003 Patti Anklam Some Principles from the Science The structure of networks is not random Six degrees of separation are but one proof point Small worlds abound Ties may be weak or strong Strength is a factor of frequency and proximity Weak ties are often more useful than strong ties The rich get richer Nodes with many links tend to get more links Structural holes represent opportunities
©2003 Patti Anklam Tie Strength and Community Memberships Social networks and communities: People who have more ties join more groups The more ties people have to others in the same group, the longer they stay in the group The more ties people have to others outside of the group, the less time they stay in the group Strong ties to many people in the same group increase the duration of membership longer than weak ties Weak ties to nonmembers increase the rate of joining new groups McPherson et al, “Social Networks and Organizational Dynamics”, 1995
©2003 Patti Anklam Let’s Look at Some More Examples
©2003 Patti Anklam Knowledge Problem? I am likely or highly likely to be more effective if I could communicate more with this person. = Process = KM = Technology Group = Manager
©2003 Patti Anklam Communication Problem? I frequently or very frequently receive information from this person that I need to do my job. = Europe = Asia Pacific HR Group = Americas = Manager
©2003 Patti Anklam Quality Problem? Frequently Get InformationNeed to Communicate More
©2003 Patti Anklam Summary
©2003 Patti Anklam Why Do an Analysis? Six Myths about Informal Networks*: To build better networks, we have to communicate more Everybody should be connected to everybody else We can’t do much to aid informal networks How people fit in is a matter of personality (which can’t be changed) Central people who have become bottlenecks should make themselves more accessible I already know what is going on in my network *Rob Cross, Nitin Nohria, and Andrew Parker, MIT Sloan Management Review, Spring 2002
©2003 Patti Anklam SNA Moves People to Action Provides concrete view of flows and relationships: Makes concrete how work is happening in comparison to the formal structure. Makes visible the aspects of a group that we can work with. Qualitative and Quantitative aspects: Graphics are very meaningful to people. Data enable metrics, provide meaningful information when there are very large numbers of people The combination “cracks the code” of delivering this type of diagnostic data to managers Proven uses in: Planning for reorganization (or post-reorganization) Identifying key people prior to mergers or acquisitions Succession planning and retention Knowledge creation and sharing Improving organizational effectiveness
©2003 Patti Anklam SNA Applications Target knowledge management programs based on opportunities identified in junctures Identify and reward individuals for “invisible” work Identify key individuals for retention As part of team kick-off for cross-functional or cross- organizational projects To identify lead users for change management programs
©2003 Patti Anklam Technologies for Identifying and Creating Social Networks Categories of software Discovery Systems – Verity, Lotus, Autonomy Expertise Location – Tacit, Kamoon Technologies Natural language processing techniques used in indexing content detect similarity of concepts in an increasingly sophisticated way Visualization tools aid in navigation of hierarchies and clusters of documents Recommender systems suggest documents and people to contact based on a worker’s current task
©2003 Patti Anklam More Information SNA Reading List:
Social Networks at Work Patti Anklam Leveraging Context, Knowledge, and Networks Hutchinson Associates How work really gets done.
Copyright © hutchinson associates 2005 The Knowledge is in the Network Patti Anklam June Holley Valdis Krebs Using Network Analysis to Understand and Improve.
Social Network Analysis (SNA): Understanding Organizations & Getting Results Eric Lesser, IBM Patti Anklam, Hutchinson Associates Relationships are the.
Chapter 5 Social Network Analysis: Techniques to Discover How Work Really Gets Done.
Networks and KM: Evolving Networking Practices Patti Anklam Relationships are the main activity of business and work. – Theodore Zeldin, Work futurist.
Copyright © pattianklamdotcom 2007 Net Work and KM Leadership Patti Anklam Boston KM Forum June 26, 2007.
© 2008 IBM Corporation ® Atlas for Lotus Connections Unlock the power of your social network! Customer Overview Presentation An IBM Software Services for.
ActKM - Canberra, 14 October 2004 The Future of KM Ross Dawson CEO, Advanced Human Technologies Author, Living Networks and Developing Knowledge-Based.
Copyright © hutchinson associates 2006 Organizational Network Analysis Patti Anklam.
Making Invisible Work Visible: Using Social Network Analysis to Support Strategic Collaboration By Rob Cross, Stephen P. Borgatti and Andrew Parker.
Network Analysis Diffusion Networks. Social Network Philosophy Social structure is visible in an anthill Movements & contacts one sees are not random.
Knowledge Management & Organization Development Regardless of your business, KM is getting the right information to the right people at the right time.
Who Talks To Whom? Analysing Networks Laura Blake 2008.
Core Link Node Cluster Periphery Hub A Few Helpful Definitions.
Its a specific set of linkages among a defined set of persons with the additional property that the characteristics of these linkages as a whole may be.
Copyright © 2014 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education.
Semantic Web Technologies Readings discussion Research presentations Projects & Papers discussions.
BREMEN September 19-21, 2011 European Commission Information Society and Media GaLA Game and Learning Alliance The European Network of Excellence on Serious.
Module 3: Business Information Systems Chapter 11: Knowledge Management.
Keele Management School Harry Scarbrough KNOWLEDGE SHARING AND SOCIAL NETWORKS.
McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved Chapter 15 Creating Collaborative Partnerships.
Social Network Analysis Social Computing Foothill College.
Chapter 9 : SOCIAL NETWORKS Learning Objectives Understand the social network vocabulary Know why social networks and networking are valuable Learn.
EFQUEL 2008 Forum, June 2008, Lisbon 1 Learning2.0 Kirsti Ala-Mutka, Christine Redecker & Yves Punie European Commission, JRC Institute for Prospective.
Copyright © 2010 Accenture, Thomas H. Davenport, and Jeremy Shapiro. All Rights Reserved. Competing on Talent Analytics Jeremy Shapiro Executive Director,
Copyright 2001 © IMD, Lausanne, Switzerland Not to be used or reproduced without permission Maznevski – Virtual Teams – 1 High Performance from Global.
Customs Reform The experience of the World Bank Essential: Cooperation and information Manage by objectives rather than by institution Delegation of.
A National Resource Working in the Public Interest © 2006 The MITRE Corporation. All rights reserved. KM at MITRE Jean Tatalias KM TEM, December 2007.
Chapter 07 Training Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Human Resource Management: Gaining a Competitive.
MANAGING FOR RESULTS Module: Management Day 9. Session outline Managing in changing context: Organizational dynamics and delivery Emerging trends.
Organizational culture and Knowledge management B.V.L.Narayana Sr Professor (T M ) RSC/BRC.
E-Learning, Human Capital Management and the Banking Sector Dimitris Baltas, ATC ROM.
1. Outline the main influences on organisational cultures 2. Describe the features of effective knowledge cultures 3. Describe knowledge culture enablers.
Building social capacity for older people through ICTs Jeni Warburton John Richards Research Initiative La Trobe University Australia.
Technical meeting with the Regional representative offices in Brussels Brussels, 17 March 2009 The INTERACT II Programme – Knowledge Management and Capitalisation.
Multidisciplinary team working Outlines : The definition team, multidisciplinary. The definition of multidisciplinary team The definition of multidisciplinary.
1 Management Information Systems - Class Note # 1 Prof. Yuan-Shyi Peter Chiu Feb
Intelligence Step 5 - Capacity Analysis Capacity Analysis Without capacity, the most innovative and brilliant interventions will not be implemented, wont.
0 Response to Request For Information Bergen Brunswig Corporation W W W. W A T S O N W Y A T T. C O M Financial Executives International Linking HR Practices.
Integrating Knowledge Translation and Exchange into a grant Maureen Dobbins, RN, PhD SON, January 14, 2013.
Organizational Project Management Maturity: Roadmap to Success Project Management Institute Washington, DC Chapter Knowledge Exchange Forum October 26,
Nursing Informatics Anne Cooper Clinical Informatics Advisor (Nursing) Paperclip conference 20 September #StC.
THE RECIPE FOR SUCCESS Partnership between the Organization and the Family Association for relocation success ©WBG & WBFN, March 2010, FIGT.
© 2014 IBM Corporation Smarter Workforce Services Business Process Innovation.
Chapter © 2012 Pearson Education, Inc. Publishing as Prentice Hall.
GyanSys Contact: Phone: Simplified Document Management Faster, Better, Stronger Search Integration - Site Mailbox.
A Professional Development Series from the CDC’s Division of Population Health School Health Branch Professional Development 101: The Basics – Part 1.
1 Chapter 4 Developing and Sustaining a Knowledge Culture.
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