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Title: The Hidden Power of Social Networks: Developing Knowledge Maps Using Social Network Analysis


1
The Hidden Power of Social Networks Developing
Knowledge Maps Using Social Network Analysis
  • Dr. Jay Liebowitz
  • Professor
  • Graduate Division of Business and Management
  • Johns Hopkins University
  • jliebow1_at_jhu.edu

2
Sharing Knowledge is Power?!(December 10, 2004)
3
Where is the Business Intelligence?
4
How to Battle the Coming Brain Drain(Anne
Fisher, Fortune, March 21, 2005)
  • By 2010, more than half of all workers in the
    U.S. will be over 40. Tens of millions of
    baby-boomers turn 60 this year, and the decade
    ahead will see vast numbers of people retiring,
    or at least leaving their current full-time
    careers.
  • General Electric, Dow Chemical, Northrop Grumman
    capture their oldsters knowledge disseminate
    it to younger workers before its too late

5
Lost Knowledge
  • In sectors such as government, manufacturing,
    energy, health care, education, and aerospace,
    knowledge retention will become an overriding
    concern in the years ahead. David DeLong, Lost
    Knowledge Confronting the Threat of an Aging
    Workforce, Oxford University Press, 2004

6
Keynote Address Medical Informatics and
Emergency Medicine (Dr. Feied, 2004 AEM Consensus
Conference on Emergency Medicine Informatics)
  • Work to reduce institutional dependence on
    specialized personnel with secret knowledge
    that allows them to complete tasks nobody else
    can perform. If the unit secretary is the only
    one who knows how to place or cancel an order,
    every coffee break can put a congested department
    further behind.

7
The Hidden Power of Social Networks (Cross, 2004)
  • Networks of informal relationships have a
    critical influence on work and innovation
  • Research shows that appropriate connectivity in
    well-managed networks within organizations can
    have a substantial impact on performance,
    learning, and innovation
  • Actors/nodes (individuals/units) and links/arcs
    (relationships/ties)

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Conducting a Social Network Analysis
  • Step 1 Identify a Strategically Important Group
  • Integrating networks that cross core processes
  • Promoting innovation through connectivity in new
    product development or process improvement
    initiatives
  • Facilitating post-merger integration and
    large-scale organizational change
  • Supporting CoPs
  • Forming strategic partnerships and alliances
  • Improving learning and decision making in top
    leadership networks

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Size of the Network
  • Typically limit to 250 people for visualization
    purposes (but could have more for analysis
    purposes)
  • Ask each person to rate his/her interactions with
    other members of the group

10
Step 2 Assess Meaningful and Actionable
Relationships
  • Relationships that reveal collaboration in a
    network (e.g., Communication, Information,
    Problem solving, Innovation)
  • Relationships that reveal the information sharing
    potential of a network (e.g., access)
  • Relationships that reveal rigidity in a network
    (e.g., decision making, influence)
  • Relationships that reveal well-being and
    supportiveness in a network (e.g., liking,
    friendship, trust)

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Survey
  • Confidentiality
  • Full disclosure of the results via an
    all-employee debriefing or other communication
  • Allow only one person or a select group to see
    the full results so that helpful action can be
    taken
  • Disclose no names whatsoever

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Step 3 Visually Analyze the Results
  • UCINet-Netdraw
  • Pajek
  • Netminer
  • Inflow
  • International Network of Social Network Analysts
    (INSNA)

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Staff for General Advice Questions
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Junior-Senior Staff Relationships
15
Network Diagram General Advice (Individual)
16
Network Diagram Subject Matter Expertise
(Department)
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Social Network Analysis (www.orgnet.com)--Org.
Mapping
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Step 4 Quantitatively Analyze the Results
(Indiv. Network Measures)
  • In-degree centrality (the number of incoming ties
    a person has for a given relationship (such as
    communication or trust)
  • Out-degree centrality (the of outgoing ties a
    person has for a given relationship)
  • Betweenness centrality (the extent to which a
    particular person lies between the various
    other people in the networknetworks that contain
    individuals with high betweenness are vulnerable
    to having info flows disrupted by power plays or
    key individuals leaving)

19
Indiv. Network Measures (cont.)
  • Closeness centrality (the extent to which a
    person lies at short distances to many other
    people in the network. Persons highly central
    with respect to closeness tend to hear info
    sooner than others)
  • Brokerage measures
  • Coordinators (people who broker connections
    within the same group)
  • Gatekeepers (people who broker connections
    between their own group and another)
  • Liaisons (those who broker connections between 2
    different groups)

20
Group Measures
  • Density (the of individuals who have a given
    type of tie with each other, expressed as a of
    the maximum possibleif each person were
    connected to every other person in the network,
    the density would be 100)
  • Cohesion (the average of the shortest paths
    between every pair of people in the
    networkaverage cohesion score should be around 2
    in groups where managers are interested in
    employees leveraging each others expertise)

21
Step 5 Create Meaningful Feedback Sessions
  • Conduct interviews with a select number of people
    (8-10 network members) to better understand the
    dynamics behind the network
  • Look at the network analysis to determine who to
    interview (central and peripheral roles)
  • Documentation or workshop with all network
    participants

22
Step 6 Assess Progress and Effectiveness
  • Follow-up (post-audit) 6-9 months after network
    analysis is first conducted
  • SNA research areas
  • Improving the calculation of interval/ratio
    scales for measuring the strength of ties between
    actors (AHP)
  • Effective representation of complex network
    information (IBMs Raison, data mining tool)

23
Identifying Types of Individuals in the Network
  • Central Connectors most arrows pointing to them
  • Unsung Hero Invisible work but critical to
    the network and can consume many hours each day
    (may be completely unrecognized by senior
    management)
  • The Bottleneck some people become so central to
    the organization that they end up holding the
    group back

24
Boundary Spanners
  • Provide critical links between 2 groups of people
    that are defined by functional affiliation,
    physical location, or hierarchical level
  • Can play important roles in large-scale change
    efforts

25
Information Brokers
  • Indirect connections
  • For example, Ian and Frank have no direct
    connection, but each has a relationship with
    Gayle (so they are connected through her) people
    such as Gayle play a brokering role that can hold
    together entire groups

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Peripheral Specialists
  • Have one connection each and are not linked to
    each other
  • Some people are stuck (e.g., newcomers) on the
    periphery and others may choose (e.g., experts)
    to be on the periphery

27
Case Study Examination of Raw Data
  • All data downloaded to Excel spreadsheet
  • 225 respondents answered questions 1, 2, and some
    portion of 13, identifying other employees from
    whom they sought a form of knowledge advice
  • All others were removed, including duplicates
  • All cells containing names were examined
    identifying abbreviated names, the use of
    initials, variations in spelling, etc.
  • Numbering of all names yielded 698 employees

28
Examination of Raw Data
  • The data identified 1,621 knowledge advice
    connections or communications between the 698
    employees
  • Each connection between employees was assigned a
    weight based on the frequency of the knowledge
    being sought and the importance of the knowledge
  • Complete employee data for respondents,
    non-respondent employee numbers, employee
    connections and connection weights were loaded
    into NetMiner 2.5 for social network analysis.
  • Analysis was conducted across 6 defined advice
    communication areas

29
Social Network Analysis Schematic
Employee
Adjacency Advice Communication Matrix
Advice Communications
Employee
Employee Attributes
Communication Measures
30
Social Network Analysis Schematic
Employee
Adjacency Advice Communication Matrix
  • Advice Communications
  • Context K Advice
  • Expert Process K Advice
  • General K Advice
  • Process K Advice
  • Strategic K Advice
  • Relationship K - Advice

Employee
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Knowledge Types
Context K of what applications
Expert Process K of how networks and systems work
General K of non-work related questions
Process K of how the business works
Relationship K of who has information
Strategic K of why business opportunities reduce cost and other strategic decisions
32
Social Network Analysis Schematic
Employee
Adjacency Advice Communication Matrix
  • Employee Attributes
  • Department
  • Level (Position Hierarchy)
  • Tenure

Employee
33
Social Network Analysis Schematic
Employee
Adjacency Advice Communication Matrix
  • Communication Measures
  • Centrality (in and out degree)
  • Closeness
  • Betweenness
  • Cliques
  • Density
  • Brokerage

Employee
34
Is there much intra-departmental communication?
  • This can be measured by examining the amount of
    communication within each department in two
    areas density and cohesiveness
  • Density is the proportion of possible lines that
    are actually present in the network. It is the
    ratio of the number of lines present to the
    maximum possible.
  • Cohesion Index is the extent to which ties are
    concentrated within a subgroup, rather than
    between subgroups.

35
Is there much inter-departmental communication?
  • Departments blocked and then examined for
    degree and density measures
  • As with individuals, departments yielded low
    density of communication with other departments
  • Some departments have no communication with
    others within certain knowledge areas
    (structural holes)
  • XYZ department unconnected from all others in 4
    of the 6 knowledge types, including the knowledge
    of who has the organizational information
  • JKL department not connected within 3 of the
    knowledge types including the what of
    applications and the how of network and systems
    work

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Is the organization well connected among
employees?
  • Most communication is occurring between
    non-managerial employees
  • Of the 1,621 knowledge connections, 1,199 were
    connections to non-management employees
  • 74 of reported advice communications were
    employee to employee

39
Is the organization well connected among the
employees and the managers, directors and
executives?
  • 336 of the 1,621 knowledge connections (21) were
    to persons in management positions
  • 36 of 62 Managers, Directors, and Executives were
    named as sources of knowledge advice 5 or more
    times
  • Communication rate from employee to employee is
    the highest

40
Are the junior employees interacting with the
senior employees?
  • Junior employees have limited contact with senior
    employees (executives)
  • Employee contact is greater with other employees
  • Greatest direct connection between executives and
    non-managerial employees was in the Process K
    area
  • Lowest level Context K

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Are the directors and executives in the Power
positions centrally located?
  • Executives and directors are not present or are
    relatively weak in most power or central
    positions in knowledge advice communications
  • A single executive was prominent in Strategic,
    General, and Relationship knowledge areas
  • Three others in managerial positions appeared in
    central positions, with a single one of these
    appearing in 4 of the 6 K types
  • Most power or central positions are held by
    non-managerial employees or a single expert

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Are there correlations as to those employees
sought based on the different types of knowledge?
  • No evident correlation between knowledge type and
    employee attributes in central or power positions
    within each knowledge area
  • While individual actors hold multiple positions
    across K area, no single department appears
    strongly central with a given K type
  • Common factor for all employees sought for advice
    (with complete attribute data) was tenure greater
    than 1 year (with the exception of employee 188,
    significantly in the power position for Strategic
    Knowledge)

55
Are there more isolates, transmitters, receivers
or carriers in the organization?
  • In all knowledge areas, the greatest number of
    employees are isolates
  • Receivers are generally greater in number than
    transmitters in all knowledge areas
  • Carriers are the fewest in number in all
    knowledge areas

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Node Types by Area
K Area Isolate Transmitter Receiver Carrier
Context 329 133 190 46
Exp. Pr 361 126 171 40
General 378 118 162 42
Process 442 110 109 37
Relation 445 94 121 38
Strategic 396 113 151 38
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How can communication and collaboration be
improved?
  • Further departmental examination of results
  • Follow-up interviews with persons in central or
    power positions
  • Task analysis of these persons performance in
    the positions
  • Positive reinforcement program should be
    developed to create behavioral change in other
    positions, based upon benchmarks set by central
    or power positions
  • Planned insertion of employees or departments to
    fill all structural holes should be considered
    for succession planning and workforce development

58
Organizational Individual Constraints
(Q.25,26,27)
  • 37 Lack of Time/Work Overloads
  • 14 Too Many Silos/Consolidate into Central
    Repository
  • 10 Not knowing who to ask/who has the
    information
  • 6 Job Insecurity/Downsizing
  • 6 Getting People to Share Their
    Knowledge/Culture Doesnt Encourage it/Tie to
    IPEP
  • 6 Search Engine Needs to be Improved/No Search
    Engine for Internal Info
  • Other (21)(in order)
  • Business processes needed/Standardization/People
    to follow processes
  • Politics
  • Rigid hierarchical structures
  • Supervisor is seated away from Dept/Geographic
    Dispersion
  • Limited access, due to security, to access
    intranet from home
  • More communication needed between people
  • Need knowledge capture tool
  • Constantly changing organization with unclear
    roles and responsibilities
  • Need to create a continuous learning culture
  • Need to capture rationale why things dont work

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KM-Related Recommendations Based on SNA,
Q25,26,and 27
  • Portal
  • Central repository
  • Google-type search engine
  • Expertise locator
  • Recognize knowledge sharing in performance
    reviews (extrinsic and intrinsic motivators)
  • Lessons learned/best practices
  • Online communities of practice
  • More cross-training/cross-functional teams
  • Mentoring program
  • Knowledge sharing forums (storytelling)
  • Knowledge fairs around certain key topics

60
Summary
  • Low volume of communications due to an unbounded
    network and low levels of advice seeking
  • Departments have relative cohesions of
    communication but often fail to communicate with
    other divisions across all knowledge areas,
    creating structural holes
  • Within the Process K area, executive level actors
    are most strongly connected to non-managerial
    employees
  • Experts, while present in the analysis, do not
    appear in powerful or central positions (with the
    exception of employee 158)

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Summary (cont.)
  • Other individuals appear in powerful or central
    positions and may be considered experts relative
    to the knowledge area (the most significant of
    these is employee 157)
  • All knowledge areas demonstrate high numbers of
    isolated actors and fewer numbers of transmitters
    and carriers (employees not communicated with
    others within certain knowledge types)
  • Apply knowledge management/knowledge sharing
    approaches

62
Final Comments
  • Social network analysis is a wonderful technique
    to identify knowledge flows and knowledge gaps in
    organizations to help in knowledge
    mapping/knowledge audits
  • The grapevine effect is stronger than the formal
    org-chart effect (i.e., informal networks are
    stronger than formal ones)
  • SNA helps build a basis for developing a
    knowledge management and human capital strategy

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