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University of Cologne. Department of Information Systems and Information Management, Prof. Dr. Detlef Schoder http://www.wim.uni-koeln.de/. Social Networks: State of the Art – Best Practice Example. Venus Summer School Trends of Social Software and Web 2.0 in Education and Business

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University of Cologne

Department of Information Systems and Information Management, Prof. Dr. Detlef Schoder

http://www.wim.uni-koeln.de/

Social Networks: State of the Art –

Best Practice Example

Venus Summer SchoolTrends of Social Software and Web 2.0 in Education and Business

September 5, 2007

Cologne, Germany


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Trend: Interdependency between Electronic Networks and Social Network Structures is growing…

Collaboration

Sharing

Bookmarking

Communication

Networking


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… and interest in Information Systems and Social Networks is rising! Why?


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Because Information Systems Research boosts SNA in Business

Social Network Analysisdescribes, explains and projects communication patterns in social groups

Information Systems Researchdescribes, explains, projects and designs information systems for business, administrative, and private use

  • Which communication and interaction patterns exist among members of an organization?

  • What is the structural position and role of a person in a network compared with formal hierarchy?

  • Which organizational members have prominent roles like gatekeepers or hubs in a network?

  • Which organizational members should have contact with each other?

  • Do specific network structures correlate with organizational performance?

  • Which impact have informal structures on project and teamwork?

  • Which impact have informal structures on the innovativeness of departments or companies?

  • Can communication analysis filter out prominent topics to identify trends?

  • Which functionalities and tools support specific network structures best?


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Gloor 2005


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Potential Business Application Fields of SNA

Knowledge Management and Collaboration. SNAs can help locate expertise, seed new communities of practice, develop cross-functional knowledge-sharing, and improve strategic decision-making across leadership teams.

Team-building. SNAs can contribute to the creation of innovative teams and facilitate post-merger integration. SNAs can reveal, for example, which individuals are most likely to be exposed to new ideas.

Human Resources. SNAs can identify and monitor the effects of workforce diversity, on-boarding and retention, and leadership development. For instance, an SNA can reveal whether or not mentors are creating relationships between mentees and other employees.

Sales and Marketing. SNAs can help track the adoption of new products, technologies, and ideas. They can also suggest communication strategies.

Strategy. SNAs can support industry ecosystem analysis as well as partnerships and alliances. They can pinpoint which firms are linked to critical industry players and which are not.

Source: Ehrlich and Carboni (2005), IBM


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Latest Academic Developments – Selected Topics of this year's International Sunbelt Social Network Conference

  • Social Capital

  • An Integrative Approach to the Role of Social Capital in Interpersonal Knowledge Transfer

  • Intra-Organizational Networks

  • The Impact of Computer Based Communication on the Emerging of a Social Structure: the Analyses of two Case Studies in Organizations

  • Between Efficiency and Innovativeness: The Dynamics of an Organization as a Social System

  • The Story of the Gold-digger: Career Commitment and Strategic Networking

  • The Dynamics of Intra-organizational Advice Networks

    Inter-Organizational Nets

  • Germany INC 2004: Capital Ties and Directory Interlocks

  • Networks, Economics, & Markets

  • Networks of Inter-firm Collaboration

  • Network Dynamics

  • The Diffusion of Innovations in Large Social Networks Selection, Influence and the Dynamics of Organizational Affiliation

  • Leadership Networks

  • Building Better Teams by Building Better Leadership: The Role of Instrumental and Affective Ties in the Networks of Successful Team Leaders

    Knowledge Networks

  • Effective Knowledge Integration in Virtual R&D Networks

Organizational Performance & Networks

  • Using Network Analysis to Improve Supply Chain Performance: A Case Study

  • Integration of Economic Systems: Interaction between Networks

    Innovation

  • Knowledge Flows in an R&D Network

    Business Networks

  • Network Competitive Advantage: How A Network Perspective Can Point the Way To Winning Strategies in Business

  • Corporate Social Capital and Performance

    Politics and Interlocking Directorates

  • Corporate-Government Networks in the Netherlands: Interlocks Between Business and Politics

    Networks, Economics, and Markets

  • Network Analysis as a Marketing Tool: Using Network Parameters to Identify. Brand Zealots in Online Consumer Environments

    Communication Networks

  • Social Network Analysis on Overlapping Multiple Mailinglists in a Company

    Network Dynamics

  • Network Evolution and Firms’ Performance: Exploring the Effects of Dynamic Multilevel Embeddedness


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Potential benefits of SNA in Business

  • Observation, understanding, and design of workflow and organizational structure

  • Studying the diffusion and adoption of knowledge and innovation

  • Discovering lead users

  • Researching best practices for behavior in virtual teams

  • Discovering Web trends by looking at changes in link patterns between blogs (Trend Detection, Cool Hunting Project at MIT)

  • Competitive intelligence through analysis of communication patterns in large e-mail (among other) archives


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Potential benefits of SNA in Business (cont’d)

  • Opportunity to identify and reward key contributors

  • Creation of more transparent environments

  • Identification of people acting as sources of tacit knowledge

  • Better agility to react to market and technology changes

  • New and improved communication analysis tools

  • Enhanced knowledge worker productivity


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Further Readings

  • CARRINGTON, P.J.; SCOTT, J.; WASSERMAN, S. (2005), Models and Methods in Social Network Analysis, Cambridge University Press.

  • CROSS, R.L. (2004), The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations, Harvard Business School Press.

  • EHRLICH, K.; CARBONI, I. (2005): Inside Social Network Analysis, IBM.

  • GLOOR, P.A. (2006), Swarm Creativity: Competitive Advantage through Collaborative Innovation Networks, Oxford University Press.

  • HAYTHORNTHWAITE C. (1996), Social Network Analysis: An Approach and Technique for the Study of Information Exchange, in: Library & information science research (LISR), ISSN 0740-8188, 1996, Vol. 18, No. 4, pp. 323-342.

  • MITCHELL, J. C. (1969): The Concept and Use of Social Networks. In: MITCHELL, J. Clyde (ed.): Social Networks in Urban Situations. Analyses of Social Relationships in Central African Towns. Manchester, pp. 1-50.

  • MORENO, J.L: (1978, 1934), Who shall survive?, Beacon NY.

  • SCOTT, J. (1994): Social Network Analysis – A Handbook, Sage, London.

  • WASSERMAN, S.; FAUST, K. (1994): Social Network Analysis: Methods and Applications, Cambridge University Press.


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Part II: Social Networks – Best Practice

Social Networks in Enterprises

Media – Relevance – Implementation

Daniel Oster (University of Cologne, Kreissparkasse Cologne)


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Media of Social Networks – Ties

Medium vs. Content

Medium: How to measure the network

Content: What to measure in the network

  • Personal Interaction (Face-to-Face)

  • E-Mail

  • Phone

  • Instant Messaging / Chat

Actor

Actor

 Content: Communication flow / Information flow

Requirement for Organizational Network Analysis:

Don‘t interfere with employees’ work but assure privacy and data security

 Automatic logging of communication in the background


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Media of Social Networks – Actors

  • Personal Interaction (Face-to-Face)

  • E-Mail

  • Phone

  • Instant Messaging / Chat

Actor

Actor


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Relevance for Enterprises

  • Are Social Networks in Organizations really relevant?

  • Do they have an economic impact?

    Case:

  • Social Networks and Performance at Kreissparkasse Cologne

  • Time: 6 months

  • Actors: 4,000 employees, 400 business units (branches + staff divisions)

  • Ties: E-mail-communication (4 million mails)

  • Performance:

    • economic: growth in credit volume per branch

    • personal: individual rated motivation


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Performance Model

Intra-BU

Network

Economic

Performance

H1

H2

H3

Inter-BU

Network

Individual

Motivation

H4


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The Inter Business Unit (BU) Network

  • The whole enterprise

  • Every actor (dot) is a Business Unit.

  • Distance represents communication strength (the closer the more mails).

  • Color represents type of Business Unit (branch, staff division, ...)

  • Relevant Network Indicators

  • Actor Betweenness Centrality (ABC)

  • Actor Degree Centrality (ADC)

  • Actor Contribution Index (ACI)


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The Intra Business Unit (BU) Network

  • Zoom in into a single Business Unit

  • Every actor (dot) is an employee.

  • Distance represents communication strength (the closer the more mails).

  • Color and labels represent teams.

  • Relevant Network Indicators

  • Group Betweenness Centrality (GBC)

  • Group Degree Centrality (GDC)

  • Core Periphery Index (CPI)

  • Group Density


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Performance Tests (Regression Analysis)

All Correlations are positive

Intra-BU

Network

Economic

Performance

Correlation (GBC ; Performance) = 0,56 (p < 0,01)

Inter-BU

Network

Individual

Motivation

Intra-BU

Network

Economic

Performance

Correlation(GDC ; Motivation) = 0,62 (p < 0,001)

Correlation(CPI ; Motivation) = 0,61 (p < 0,001)

Correlation(Density ; Motivation) = 0,63 (p < 0,001)

Inter-BU

Network

Individual

Motivation

Intra-BU

Network

Economic

Performance

Correlation(ABC ; Performance) = 0,51 (p < 0,05)

Inter-BU

Network

Individual

Motivation

Intra-BU

Network

Economic

Performance

Correlation(ADC ; Motivation) = 0,58 (p < 0,01)

Correlation(ACI ; Motivation) = 0,38 (p <0,05)

Inter-BU

Network

Individual

Motivation

 Social Networks are highly relevant for enterprises!


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Implementation at Kreissparkasse CologneNetwork Layer Model

Leadership

Knowledge

Employee

Business Unit

Overall View Individual View

Structure Content

First implementations:

Team Building

Knowledge Flow Support

and Org Controlling

Post Merger Integration

Data Collection and Analysis Infrastructure

Privacy and Data Security Arrangements


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Implementation I:Team-building

Combined E-mail and Face-to-Face Network

The Social Badgeautomatically

measures personal interaction

Network Based Team-Structure was implemented


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Implementation II: Knowledge Flow Support and Org-Controlling

  • Network view of Business Unit Collaboration

  • Every actor (dot) is a Business Unit.

  • Distance represents communication strength.

  • Red = Sales Support

  • Black = Sales

  • Green = “Gate Keeper”

  • Performance-Thesis:

  • The better connected a BU – the better is BU’s performance.

  • Approach:

  • Identify not well connected BUs

  • Identify Gate Keepers

  • Check whether network position corresponds to performance

  • Understand role of Gate Keepers

  • Take actions to enhance network position

    • Visualization

    • Coaching

    • Active exchange of Information

    • ...

  • Track network changes over time

  • Control performance


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Implementation III:Post Merger Integration

Network view of a merger process

Every actor (dot) is a Business Unit.

Distance represents communication strength.

Color represents pre-merger-enterprise.

month 1 after merger (Apr. 06)

month 6 after merger (Sept. 06)


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Summary

  • Social Networks in enterprises haven an impact on

  • Business Performance

  • Motivation

  • Creativity / Innovation

  • Social Network Analysis is a powerful Management Tool that supports

  • Organizational decisions / processes / redesigns

  • Information- and Knowledge Management

  • Leadership


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University of Cologne

Department of Information Systems and Information Management, Prof. Dr. Detlef Schoder

http://www.wim.uni-koeln.de/

Thanks for your attention!

Questions?

Prof. Dr. Detlef Schoder | [email protected]

Daniel Oster | [email protected]


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