Many nonprofits and foundations have been using social network analysis (SNA) and organizational network analysis (ONA) techniques in program assessment, planning, and measurement. This webinar will review a number of techniques that are being used and the ways that the results of network analysis are informing and supporting the ways that nonprofits are leveraging networks to achieve greater good by creating, facilitating, and weaving networks.
Brief description of ONA (Organizational network analysis) followed by a summary and comparison of the emerging SAAS vendors who provide support for network surveys and analysis.
Network analysis methods for assessment & measurementPatti Anklam
Presentation slides for a webinar produced by the Leadership Learning Community. Full audio is available on their site, at http://www.leadershiplearning.org/blog/eleanor-cooney/2012-12-17/2013-webinar-network-analysis-snaona-methods-assessment-measurement
Personal Network Management Km Forum Oct 2009Patti Anklam
Presentation to the Boston KM Forum. Describes how an understanding of networks dynamic and structure can help with the development of one's personal network.
Yes, I still do KM and KM is not dead. I thought I would share the basic deck that I use in workshops that are part of my KM Assessment and Strategy consulting practice. In addition to interviews, surveys, and inventories, it is important during a KM assessment to educate and engage the organization.
The Complete Organizational Network Analysis Handbook_APR2014 #SocialNetworkA...Stephen Tavares
ONA has been around for several years and in the past few, as big data and Internet applications have become more prevalent, it has even turned into a buzzy catchphrase.
This overview presentation will help build the case for ONA and provide insight into the best use of the tools to maximize human capital performance in any organization.
Revision of Previous Show on SNA and Introduction to Tools
The Language of Networks
Introduction to Social Network Analysis/ Cases
Tools for Analyzing social networks, including graphing Facebook, LinkedIn, and Twitter networks
Brief description of ONA (Organizational network analysis) followed by a summary and comparison of the emerging SAAS vendors who provide support for network surveys and analysis.
Network analysis methods for assessment & measurementPatti Anklam
Presentation slides for a webinar produced by the Leadership Learning Community. Full audio is available on their site, at http://www.leadershiplearning.org/blog/eleanor-cooney/2012-12-17/2013-webinar-network-analysis-snaona-methods-assessment-measurement
Personal Network Management Km Forum Oct 2009Patti Anklam
Presentation to the Boston KM Forum. Describes how an understanding of networks dynamic and structure can help with the development of one's personal network.
Yes, I still do KM and KM is not dead. I thought I would share the basic deck that I use in workshops that are part of my KM Assessment and Strategy consulting practice. In addition to interviews, surveys, and inventories, it is important during a KM assessment to educate and engage the organization.
The Complete Organizational Network Analysis Handbook_APR2014 #SocialNetworkA...Stephen Tavares
ONA has been around for several years and in the past few, as big data and Internet applications have become more prevalent, it has even turned into a buzzy catchphrase.
This overview presentation will help build the case for ONA and provide insight into the best use of the tools to maximize human capital performance in any organization.
Revision of Previous Show on SNA and Introduction to Tools
The Language of Networks
Introduction to Social Network Analysis/ Cases
Tools for Analyzing social networks, including graphing Facebook, LinkedIn, and Twitter networks
The Network Approach to Change InitiativesSteven Wardell
Presented by Activate Networks' Rob Cross, DBA and Luke Matthews, PhD
If your company is at any stage of a reorganization, merger or acquisition, you can learn how to:
- find the data you need to strategically plan and monitor your change initiative,
- identify the top connectors in your employee network (the employees you can't afford to lose!), and
- improve knowledge sharing by understanding the current structure of communication to allow for more informed decision making.
Digital Workplace Quick Poll: What's not, what's not!Jane McConnell
Priority topics as voted by 110 organizations worldwide in the July 2013 Quick Poll for the 2014 Digital Workplace Survey.
Lots of food for thought for digital practitioners and their eco-system of partners, consultants, agencies and vendors.
Tools and Services for More Intelligent Meta NetworksDuncan Work
This presentation gives an overview of the importance of meta networks, which are decentralized networks of networks based on shared values and goals.
The presentation also summarizes some of the tools and methods that can make meta networks more visible, intelligent, and useful.
Harnessing Collective Intelligence: Shifting Power To The EdgeMike Gotta
Socially-oriented systems create inter-connections across groups and communities that enable workers to leverage the collective intelligence of an organization. Sense-making tools and decision-making systems are more critical than ever before but need to be re-invented for a net-centric environment.
SEO and IA: The Beginning of a Beautiful FriendshipMarianne Sweeny
Search technology and IA have developed on parallel tracks over the last many years. I propose that they join forces in creating an enhanced user information finding experience and present specific opportunities for deeper IA engagement.
Social network analysis: uncovering the secrets of information flow for our i...Mia Horrigan
Social network analysis: uncovering the secrets of information flow for our information architecture.
ozia09
Mia presents a case study in which she explores the use of Social Network Analysis (SNA) to model her users’ network and map the relationships between people, groups, organisations and information. She will explore how understanding the degrees of centrality and closeness in the network can uncover the flows of knowledge between users to create a deeper understanding reflected in Personas.
Agile Personas are "skinny" and are fleshed out as you uncover more information during the project.
This article originally appeared in Training & Development magazine February 2016 Vol 43 No 1, published by the Australian Institute of Training and Development.
Big Data Social Network Analysis (BDSNA) is the focal computational and graphical
study of powerful techniques that can be used to identify clusters, patterns, hidden
structures, generate business intelligence, in social relationships within social networks
in terms of network theory. Social Network Analysis (SNA) has a diversified set of
applications and research areas such as Health care, Travel and Tourism, Defence and
Security, Internet of Things (IoT) etc. . . With the boom of the internet, Web 2.0
and handheld devices, there is an explosive growth in size, complexity and variety in
unstructured data, thus the analysis and information extraction is of great value and
adaptation of Big Data concept to SNA is vital.
This literature survey aims to investigate the usefulness of SNA in the “Big Data
(BD)” arena. This survey report reviews major research studies that have proposed
business strategies, BD approaches to generate predictive models by gratifying contemporary
challenges that have arises from SNA.
My presentation on networks and social media to a group of international managers from multinational organizations as part of IFL training program (www.ifl.se).
Part 1: Concepts and Cases (the language of networks, networks in organizations, case studies and key concepts)
Part 2: (Starts on #44) Mapping Organizational, Personal, and Enterprise Networks: Tools
An update to last year's Social Network Analysis Introduction and Tools...
How to conduct a social network analysis: A tool for empowering teams and wor...Jeromy Anglim
Slides and details available at: http://jeromyanglim.blogspot.com/2009/10/how-to-conduct-social-network-analysis.html
A talk on using social network analysis as a team development tool.
The Network Approach to Change InitiativesSteven Wardell
Presented by Activate Networks' Rob Cross, DBA and Luke Matthews, PhD
If your company is at any stage of a reorganization, merger or acquisition, you can learn how to:
- find the data you need to strategically plan and monitor your change initiative,
- identify the top connectors in your employee network (the employees you can't afford to lose!), and
- improve knowledge sharing by understanding the current structure of communication to allow for more informed decision making.
Digital Workplace Quick Poll: What's not, what's not!Jane McConnell
Priority topics as voted by 110 organizations worldwide in the July 2013 Quick Poll for the 2014 Digital Workplace Survey.
Lots of food for thought for digital practitioners and their eco-system of partners, consultants, agencies and vendors.
Tools and Services for More Intelligent Meta NetworksDuncan Work
This presentation gives an overview of the importance of meta networks, which are decentralized networks of networks based on shared values and goals.
The presentation also summarizes some of the tools and methods that can make meta networks more visible, intelligent, and useful.
Harnessing Collective Intelligence: Shifting Power To The EdgeMike Gotta
Socially-oriented systems create inter-connections across groups and communities that enable workers to leverage the collective intelligence of an organization. Sense-making tools and decision-making systems are more critical than ever before but need to be re-invented for a net-centric environment.
SEO and IA: The Beginning of a Beautiful FriendshipMarianne Sweeny
Search technology and IA have developed on parallel tracks over the last many years. I propose that they join forces in creating an enhanced user information finding experience and present specific opportunities for deeper IA engagement.
Social network analysis: uncovering the secrets of information flow for our i...Mia Horrigan
Social network analysis: uncovering the secrets of information flow for our information architecture.
ozia09
Mia presents a case study in which she explores the use of Social Network Analysis (SNA) to model her users’ network and map the relationships between people, groups, organisations and information. She will explore how understanding the degrees of centrality and closeness in the network can uncover the flows of knowledge between users to create a deeper understanding reflected in Personas.
Agile Personas are "skinny" and are fleshed out as you uncover more information during the project.
This article originally appeared in Training & Development magazine February 2016 Vol 43 No 1, published by the Australian Institute of Training and Development.
Big Data Social Network Analysis (BDSNA) is the focal computational and graphical
study of powerful techniques that can be used to identify clusters, patterns, hidden
structures, generate business intelligence, in social relationships within social networks
in terms of network theory. Social Network Analysis (SNA) has a diversified set of
applications and research areas such as Health care, Travel and Tourism, Defence and
Security, Internet of Things (IoT) etc. . . With the boom of the internet, Web 2.0
and handheld devices, there is an explosive growth in size, complexity and variety in
unstructured data, thus the analysis and information extraction is of great value and
adaptation of Big Data concept to SNA is vital.
This literature survey aims to investigate the usefulness of SNA in the “Big Data
(BD)” arena. This survey report reviews major research studies that have proposed
business strategies, BD approaches to generate predictive models by gratifying contemporary
challenges that have arises from SNA.
My presentation on networks and social media to a group of international managers from multinational organizations as part of IFL training program (www.ifl.se).
Part 1: Concepts and Cases (the language of networks, networks in organizations, case studies and key concepts)
Part 2: (Starts on #44) Mapping Organizational, Personal, and Enterprise Networks: Tools
An update to last year's Social Network Analysis Introduction and Tools...
How to conduct a social network analysis: A tool for empowering teams and wor...Jeromy Anglim
Slides and details available at: http://jeromyanglim.blogspot.com/2009/10/how-to-conduct-social-network-analysis.html
A talk on using social network analysis as a team development tool.
Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities. SNA provides both a visual and a mathematical analysis of human relationships.
Social Network Analysis & an Introduction to ToolsPatti Anklam
This presentation was delivered as part of an intense knowledge management curriculum. It covers the basics of network analysis and then goes into the different types of tool that support analyzing networks.
PROJECT CHARTER TEMPLATE GENERAL PROJECT INFORMATIONProject Na.docxwkyra78
PROJECT CHARTER TEMPLATE
GENERAL PROJECT INFORMATION
Project Name:
Project Sponsor:
Project Manager:
Email Address:
Phone Number:
Organizational Unit:
Process Impacted:
Expected Start Date:
Expected Completion Date:
Expected Savings:
Estimated Costs:
Green Belts Assigned:
Black Belts Assigned:
PROBLEM, ISSUE, GOALS, OBJECTIVES, DELIVERABLES
Problem or Issue:
Purpose of Project:
Business Case:
Goals/Metrics:
Expected Deliverables:
PROJECT SCOPE & SCHEDULE
Within Scope
Outside of Scope
PROJECT RESOURCES & COSTS
Project Team
Support Resources
Special Needs
PROJECT BENEFITS & CUSTOMERS
Process Owner
Key Stakeholders
Final Customers
Expected Benefits
PROJECT RISKS, CONSTRAINTS, ASSUMPTIONS
Risks:
Constraints:
Assumptions:
DISCLAIMER
Any articles, templates, or information provided by Smartsheet on the website are for reference only. While we strive to keep the information up to date and correct, we make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability, or availability with respect to the website or the information, articles, templates, or related graphics contained on the website. Any reliance you place on such information is therefore strictly at your own risk.
Test for Understanding Study Guide
PSYC 3003 Week 6
This test contains 45 items with a time limit of 60 minutes. Because there is not a written Application Assignment covering quasi-experimental designs this week, approximately 2/3 of the test items are drawn from Chapter 14, and 1/3 are drawn from Chapter 7.
This study guide is available to help you organize your focus and preparation as you prepare to take the Test for Understanding on the content presented in the Learning Resources assigned for this week. Read the assigned chapters and take notes as needed on the topics listed within this guide.
Please note:The Course Instructor is available throughout the courseto assist you in your achievement of a better understanding of the course content; however, the Instructor will not provideyou with the answers to the study guide.
Chapter 7 – Naturalistic Methods
1. Be able to distinguish among examples of the following naturalistic research designs and corresponding methodology:
a. Observational
b. Case studies
c. Archival
2. Be familiar with how the following sampling methods are conducted:
a. Time
b. Event
c. Individual
3. What is systematic observation? Which of the above listed sampling methods involves this approach?
4. Be able to identify examples of methodology that involves the use of behavioral categories.
5. Be able to distinguish among the differences, and identify examples of, the following terms:
a. Acknowledged participant
b. Unacknowledged participant
c. Acknowledged observer
d. Unacknowledged observer
6. Why is interrater reliability important when collecting naturalistic observation data? How is interrater reliability conducted?
7. What is a ...
Strategies and tools to map and analyse developing networks: The case of usin...SarahG_SS
My input into a longer workshop action lab session given at the Open Education Global 2017 Conference held at the CTICC from 8-10 March 2017. This presentation provides a very brief introduction to social network analysis (SNA) and covers how this type of analysis has been used in the ROER4D project evaluation. A few ideas of how other projects can use the NodeXL tools to visualise their networks is also presented.
OSFair2017 Workshop | Impact Data Services on the CloudOpen Science Fair
Mappet Walker talks about research impact data services and presents opportunities to improve and the OpenUP impact data services on the cloud | OSFair2017 Workshop
Workshop title: Open metrics on the cloud
Workshop overview:
Impact metrics have a strong influence on the scientific community, affecting the assessment of institutions of higher education and research as well as decisions concerning who gets promoted or hired, who receives grants, and who publishes where. In this situation, it is essential that the methods used to calculate metrics should be transparent, and reproducible and that their integrity should be auditable, and beyond question. This workshop will discuss the limitations of current systems and platforms, presenting a use case from Usage Statistics platform, and the recommendations of creating an open platform for Impact Data.
Presentation Abstract:
Impact metrics have a strong influence on the scientific community, affecting the assessment of institutions of higher education and
research. In this situation, it is essential that the methods used to calculate metrics should be transparent, and reproducible and that their integrity should be auditable, and beyond question.
This workshop aims to provide an overview of the potential impact on the market. Open Access repositories, research data repositories, and publisher platforms are not standardized. But they are an important complement to other (traditional and alternative) bibliometric indicators to provide a comprehensive and recent view of the impact of scholarly resources. In particular, use data from non-traditional output types are available on the Internet. A key challenge is to achieve a similar, consistent, standards-based usage across different platforms Web resources or files and the use of resources among different repositories.
This workshop combines three thematic blocks:
- Motivations and outcomes from the European Commission Expert Group on Altmetrics report on "Next-generation metrics" report
- Current usage statistics initiatives (OpenAIRE, IRUS-UK): services standardization efforts
- Opportunity for an Impact Data Services Cloud (OpenUp)
The presentation builds on the results of the OpenUP landscape scan, and an analysis of how research results are measured today, the limitations of current approaches, and a proposed solution: a new platform for Open Metrics that gives users the information they need to understand and reproduce current metrics, to create and share their own metrics of research output and to take account of research outputs (e.g. data, code, laboratory equipment, animals, cell-lines, research protocols).
When: DAY 2 - PARALLEL SESSION 4 & 5
Graph enhancements to Artificial Intelligence and Machine Learning are changing the landscape of intelligent applications. Beyond improving accuracy and modeling speed, graph technologies make building AI solutions more accessible. Join us to hear about 4 areas at the forefront of graph enhanced AI and ML, and find out which techniques are commonly used today and which hold the potential for disrupting industries. We'll provide examples and specifically look how: - Graphs provide better accuracy through connected feature extraction - Graphs provide better performance through contextual model optimization - Graphs provide context through knowledge graphs - Graphs add explainability to neural networks
Speakers: Jake Graham, Alicia Frame
Slides of the paper "Generating LADs that make sense", presented at the 15th International Conference on Computer Supported Education CSEDU2023, Prague (Czech Republic)
An annotated slide deck from a webinar hosted by Stilo International and conducted on June 24, 2014.
The talk introduces tactics for moving a content solution project forward quickly while also attending to essential details.
Knowledge extraction and incorporation is currently considered to be beneficial for efficient Big Data analytics. Knowledge can take part in workflow design, constraint definition, parameter selection and configuration, human interactive and decision-making strategies. Here we present BIGOWL, an ontology to support knowledge management in Big Data analytics. BIGOWL is designed to cover a wide vocabulary of terms concerning Big Data analytics workflows, including their components and how they are connected, from data sources to the analytics visualization. It also takes into consideration aspects such as parameters, restrictions and formats. This ontology defines not only the taxonomic relationships between the different concepts, but also instances representing specific individuals to guide the users in the design of Big Data analytics workflows. For testing purposes, two case studies are developed, which consists in: first, real-world streaming processing with Spark of traffic Open Data, for route optimization in urban environment of New York city; and second, data mining classification of an academic dataset on local/cloud platforms. The analytics workflows resulting from the BIGOWL semantic model are validated and successfully evaluated.
Networks come in all shapes and sizes. However, if you want to be a system shifting network you will need to put in place scaffolding so that transformation can emerge easily and quickly. In nature, billions of soil organisms and mycorrhizal fungal mats work together to form this type of scaffolding to distribute resources and support the growth of plants and trees as they create a forest. There are 6 basic structures that work together to create an environment for rapid change. Some, such as innovation funds, have been prototyped by many different networks. Others, such as communications systems and governance systems, are still in their infancy. Join June Holley and Yasmin Yonis from Network Weaver for a discussion about the necessary scaffolding for truly transformational networks.
Networks thrive on the initiative of members who see a need and invite others to take action with them. This is leadership in networks and in the best case scenario its widely distributed. And yet, supporting self-organizing is not easy. In this webinar we will share common obstacles to self-organizing and better yet, two things we have tried that seem to be working. Come hear about using Network Activation Funds and Facilitator Pools to help activate your network.
Everyday Equity is both a realization of and a path from power, love, and justice. In leadership practice, we consciously and unknowingly embed and enact principles and practices that embody and resist community well-being. This mindfulness-based webinar offers leaders perspectives and practices for compassionately awakening power, love, and justice. This webinar includes practicing tools, applying concepts, and reminding us of our loveliness – allowing us to contribute to community well-being by understanding and healing from harmful conditions toward transformative change.
Dr. Renato P. Almanzor is a transformation catalyst, whose experience emerges from over 25 years developing leaders committed to equitable communities, multicultural organizations, and social justice. As a leadership expert, he has delivered leadership development programs, keynote addresses, workshops and seminars on issues related to leadership for equity, cultural diversity, and social change. Much of his work has been dedicated to supporting community leaders working with and in low-income communities and communities of color. He has a PhD and MA in organizational psychology, an MS in counseling, and BA in psychology, as well as certifications in coaching and Zumba Instruction. He is a proud alum of the first Practices in Transformative Action, a mindfulness-based program for social justice activists through the East Bay Meditation Center in Oakland, California, where he also served as an apprentice the following year.
In this webinar, Lynn Fick-Cooper, Managing Director of Societal Advancement at the Center for Creative Leadership, will share the 5 critical leadership strategies CCL has learned from their vast experience developing the leadership capacity of nonprofit leaders and collaborative groups. During this webinar, Lynn will also take us through a deeper exploration of the first of those 5 strategies, Moving Beyond the Heroic Model of Leadership, by explaining and helping us all apply CCL’s Direction-Alignment-Commitment (DAC) leadership framework.
People who are putting their time, energy and resources into supporting and cultivating leadership are for the most part doing the work to advance meaningful change and social justice. Our learning about this work is struggling to keep up with our change aspirations. It's not enough to know that participants believe they are better leaders without answering questions about the ways in which leadership development work is creating equity and contributing to concrete changes in the health, education, and wealth of all. This webinar will share findings from a collaborative research efforts between leadership Funders and Evaluators to understand what we can achieve through leadership investments, how we can know, and what we are learning about the kind of leadership we need to contribute to greater equity.
The Network Mindset Trainings offer the building blocks for what a network mindset is, and how such mindsets show up in practice. There are only two sessions; Basic and/or Intermediate. The content for all the Basic sessions is the same; the content for all the Intermediate sessions is the same.
Our thinking about leadership is evolving as is the world in which greater numbers of people are coming together to take actions that will create greater equity. To keep pace, those who are supporting leadership for racial equity and social justice must pause, reflect and reconsider our approaches to leadership development. Because most leadership programs receive positive feedback from those participating in them, it can be hard to try something different...who wants to mess with what works, even if the payoff could be more dramatic results. It takes courage to do this and we are excited to have our friends from LeaderSpring share their "reset" process and what they are learning.
Join us as June Holley, Tracey Kunkler and Steve Waddell dive back into sharing the importance of Network Governance and Structures. We'll be learning how networks are experimenting with and co-creating innovative network governanceand structures that are self-organizing, encouraging and supporting the formation of collaborative circles.
Join us for 90 minutes of hands-on virtual practice! June will bring questions and you will be in practice breakout groups. Please plug in your webcams and have earphones ready to roll up your sleeves and practice with us!
Studies consistently show that less than 20% of nonprofit executive directors/CEO’s are people of color. The recent Race to Lead report offers a new story for how we think about and address this leadership gap: to increase the number of people of color leaders, the nonprofit sector needs to address the practices and biases of those governing nonprofit organizations.
This shifts the leadership development narrative to one that incorporates transformation at the individual and structural levels in pursuit of racial equity. One model is the California School-Age Consortium’s Leadership Development Institute fellowships. Within the year-long, cohort based model for emerging leaders in the out-of-school time field, power, privilege and oppression are elevated alongside traditional leadership competencies development. The model focuses on the unique experiences of people of color in the out-of-school time field, while simultaneously challenging the environments and structures that create racialized barriers toward advancement.
Emerging leaders in the out-of-school time field are positioned to influence policies and practices well beyond the field. Many follow pathways toward teacher and school leadership, policymaking, health and wellness, community organizing, juvenile justice and more. Hear directly from the co-designer and fellow of the program about the model, its challenges, successes and hopes toward racial equity and a more just society.
Many networks organize governance and operations with structures that mirror those of organizations: governing boards, committees, and operations staff. Unfortunately, these structures have often been a bad fit with networks, leading to decreased involvement and engagement by network participants who aren't on the governing board and shrinking network size and impact.
More and more networks are experimenting with and co-creating innovative network governance and structures that are self-organizing, encouraging and supporting the formation of collaborative circles for many or all of the operations and coordination functions of the network.
June Holley will share examples and offer several checklists and strategy worksheets to help your network determine if these new structures might be appropriate for them.
July 14, 2016
What does it mean for a foundation to become a facilitative leader? And how can foundation staff make the case for network-based funding approaches to boards and other stakeholders? This two-part series will explore successes and insights from the DentaQuest Foundation’s national systems change strategy Oral Health 2020. Started in 2011, this network-based strategy has achieved notable results—development of oral health leaders across the country, creation of new state partnerships connected to a national health improvement network, and tangible system and policy changes such as the expansion of public benefits in more than 15 states. Come learn about what it took to make this work happen from the perspective of Foundation leaders Brian Souza and Mike Monopoli, initiative evaluator Clare Nolan (Harder+Company Community Research), and network weaver Marianne Hughes (Interaction Institute for Social Change).
Part 2 will dive deeper into what it took to achieve these results, including lessons learned from network building as well as what it means for a foundation to take on a facilitative leadership role.
Working in networked ways is fundamentally different than traditional ways of working. Organizations can commit to a network approach yet not fully realize all the pieces and behaviors needed to make it actually work.
Carole Martin and Beth Tener will share their insights as coaches/facilitators with a wide range of social change network initiatives. They'll explore what they have been learning about which networks get traction and grow and which ones stumble, related to these themes:
What does organization readiness to embrace the network approach "look like"? How do board and staff members organize their time, priorities, and mindset differently?
How does leading look different both within and outside your organization?
What are some key pitfalls and lessons learned that you can keep in mind as you design for a more inclusive, joyous and connected way of working?
If your organization is pursuing networked ways of working, considering going this route or are on your way and hitting some bumps in the road, this will be a helpful conversation to participate in and invite in colleagues who are still learning.
We've all heard the rhetoric. The future is uncertain and complex. We can’t do it alone, and collaboration is critical. The only way to succeed is to learn as quickly as possible through experimentation, which means getting comfortable with failure.
But what does this mean in practice? If this were easy, there wouldn’t be so many pundits telling everyone else to do it.
Learning effectively through experimentation requires specific muscles and mindsets, which take time and practice to develop. Even if your group is already comfortable jumping into the unknown and learning by doing, a little bit of structure and discipline can go a long way in helping you do so successfully.
Eugene Eric Kim and Alison Lin will share their evolving public domain frameworks and tools for supporting effective experiments. They’ll then talk about the work they continue to do with the Social Transformation Project (STP) supporting experiments focusing on internal operational challenges and effective network collaboration. They’ll be joined by Jodie Tonita and Eden Kidane of STP, who will get real about what’s worked, and what hasn’t, and what’s coming next.
In this third webinar of the Network Leadership Series, Professor Angel Saz-Carranza will explore the question of how formal networks of organizations, created to reach a collective goal (also known as goal-directed networks), work to support the overarching network goals. Goal-directed networks often create a separate organizational unit to broker and administer the network as a whole called Network Administrative Organizations (NAOs).
The webinar will answer questions like:
How organizational units lead and broker the work of network members to ensure that the network as a whole achieves a collective network goal. finds the direction it needs, aligns the activities of its members, and helps them stay committed and ready to collaborate
How leadership strategies are different when the work is not internal to a single organization
Drawing from the work of immigration coalitions in the U.S. as examples of an important type of network, Saz-Carranza unpacks the leadership dynamics of formal goal-directed networks. These network member organizations join together to accomplish a common goal that is different from each organizational member but that contributes to advance their individual missions.
Connecting the Dots: Water Shutoffs, Pensions, Emergency Management, Bankruptcy & Beyond
Peter J. Hammer
Professor of Law, Director
Damon J. Keith Center for Civil Rights
Wayne State University Law School
Detroit, Michigan
September 30, 2015
Creating Space XII
When Hurricane Sandy hit, a self organized network quickly emerged from pre-existing networks and new volunteers that resoundingly out performed traditional relief agencies. Why and how was this network able to do this? What does leadership look like in situations such as this that are complex and ever shifting? We will explore the nuts and bolts of self organizing, strategies for supporting such networks and how self organized strategies and leadership can be applied to your work on complex problems.
Welcome back to our networks and leadership webinar series! We host this space for practitioners and researchers in both the leadership and network development areas to connect and learn from each other.
Our presenter Chris Ernst is a four-way player: He is active in both research and practice of both leadership development and organizational network analysis. Chris is VP of Leadership and OE at Juniper Networks and a former senior faculty member of the Center for Creative Leadership.
This second webinar in the Network Leadership Webinar Series is brought to you by the Center for Creative Leadership, NYU Wagner, and the Leadership Learning Community.
Presenting is Chris Ernst from Juniper Networks.
Growing numbers of social change agents are building networks to increase impact. Using real-life case examples, this webinar offers an introduction to basic network concepts and approaches with an emphasis on how practitioners can strengthen their network through systematic monitoring and evaluation. Highlights from a recent framing paper and casebook developed by Network Impact and the Center for Evaluation Innovation include examples of leading evaluation frameworks and practical methods/tools.
Network Analysis (SNA/ONA) Methods for Assessment & Measurement
1. Using Network Analysis to
Assess and Measure Networks
January 14, 2012
Patti Anklam
With June Holley and Claire Reinelt
2. Webinar Goals
Share current thinking about how
network analysis is used in designing
and evaluating nonprofit programs
Provide examples of network analysis
used in assessment and measurement
contexts
Stimulate thinking about correlating
network analysis with measurement
and evaluation outputs and outcomes
2
5. What is Network Analysis?
• Social network analysis (SNA) is a collection
of techniques, tools, and methods to map
and measure the relationships among
people and organizations
• Organizational network analysis (ONA)
often refers to the use of SNA methods in
the context of organization dynamics and
development
• In practice, we use these tools to map
connections among people and ideas,
issues, and other entities as well as the
social and organizational connections
5
6. Network Analysis: The Method in a Nutshell
Step Activities/Tools
Design Identify boundaries
Clarify and design questions
Collect Data Surveys
Interviews
Facebook, LinkedIn
Email logs
Analyze data to generate (Netdraw/UCINET, NodeXL, Gephi …
maps and metrics many others)
Review data Validate; look for questions
Prepare evaluation Match network results with context
and stories
Move into action Weaving & other interventions
6
13. Quick View: What an Analysis Can Tell
• Overall very well connected
• One region distinctly
clustered with few
connects to other
regions
• Staff are highly
central
• Identification of
key connectors
13
14. Reasons for a Network Analysis: Examples
1. Assessment, Planning, &
Weaving
2. Measure changes over time
3. Sense-making & story-
finding
4. Positioning and working with
individuals in the network
14
15. Assessment, Planning, & Weaving
Strategic Purpose
• Assess the network’s capacity for collaboration, information
transfer, innovation
• Identify key individuals
• Establish goals for enhancing connectivity
• Create an action plan
15
16. Assessment: Capacity for Collaboration
Current Funder Interaction Network Future Funder Interaction Network
When funders indicate with whom they would like to work in the near future, the network becomes more robust.
Funders are saying they want to work more together.
Source: Transcending Boundaries: Strengthening Impact. The Full Potential of a Justice Network (Research & Network-Building Project Report,
April 2011, Criminal Justice Funders Network). Courtesy of June Holley.
16
17. Assessment: Affiliation Network
Strategic Purpose
• Identify potential
relationships among
people based on
shared events,
meetings, ideas, or
areas of expertise
• Nonprofits use this to
see which
organizations “attach”
to different ideas
• Forms the basis for
network weaving
17
18. Drill Down Into Affiliation Network
• Identify people with
common interest –
basis for building
communities of
practice
• See which people
share interest in
multiple issues or
topics
• A way for the network
to reveal itself and
have rich
conversations
18
20. Analyses Outputs: Metrics
Overall network metrics Individual position metrics
• Look at the whole network • Look at positions of
and its components: individuals in the network:
– Overall cohesion – # of connections
– Degrees of separation – Favorability of position
• Good for comparing • Good for identifying
groups within networks or people who are well
for comparing changes in a positioned to influence the
network over time network or to move
information around
20
21. How the Metrics Enhance the Maps
2011
Year # Density Avg #
ties
2009 55 2.2% 1.2
2010 90 2.7% 2.4
2011 85 5.3% 4.5
2012 82 8% 6.88
2010
2009
2012
21
22. Sense-Making & Emergence
• Barr Foundation Fellows Program
– See changes over time, but really to see how the network has supported
emergence
– Work to shift Barr staff from the center
Pat Brandes
Source: Networking a City, Marianne Hughes & Didi Goldenhar, Stanford Social Innovation Review, Summer 2012
22
23. Sense-Making: New School Development in Boston
• An intentional network may “This person has helped me accomplish
work-related tasks.”
have no other purpose than to
enable emergence
• Maps that show the evolving
relationships within a network
help to identify powerful
network stories
Source: Networking a City, Stanford Social Innovation Review, Summer 2012
23
24. Positioning: The Individual View
Node Betweenness Indegree OutDegree
62 792.67 26 30
80 660.48 17 32
• Centrality metrics 64
23
530.61
333.36
20
20
33
14
identify people with 71 321.42 21 20
56 316.42 20 18
the most ties (in-
degree and out-
degree)
• Those positioned to
move information
around in the
network or be in the
know (betweenness)
• Can identify people to
lead task teams, to
provide resources to,
or to train as weavers
24
25. Tracking Individuals’ Changes
I learned something from this person that made me a better leader. – 2009
2005
2007
2008
2009
2010
25
28. Summary – What We Know
What We Can Measure and Show in an Analysis:
• Measure the cohesion of the network overall:
– High-level structure (stove-piped, core/periphery, highly clustered)
– Average degree of separation
– Average number of connections each person has
• Identify individuals by their centrality to the network:
– Core or periphery? How do you bring people in from the outside?
– Broker? Connector? Facilitator? Bottleneck?
– Number and diversity of connections
• See changes over time
28
29. Things We Can Do With What We Know
Ways to change patterns in Practices from the KM/OD Repertoire
networks
Weaving. Create intentional Convene. Make introductions through meetings and webinars, face-to-
connections face events
Increase the flow of knowledge Establish collaborative workspaces, install instant messaging systems,
make existing knowledge bases more accessible and usable;
implement social software or social network software
Create awareness Provide expertise directories
Connect disconnected clusters Weave: establish knowledge brokering roles; expand communication
channels
Create more trusted relationships Assign people to work on projects together
Alter the behavior of individual nodes Create awareness of the impact of an individual’s place in a network;
foster network literacy
Increase diversity Add nodes; connect and create networks; encourage people to bring
knowledge in from their networks in the world
29
30. Measurement Challenges
• Maps area snapshot in time
• Targets and thresholds
– How much cohesion is “enough?”
Is there a point at which
increasing the number of ties
makes the network less efficient?
– Is it reasonable to set a target for
the cohesion metric?
• Tying Network Metrics to
Outcomes
– We have to think of the metrics as
indicators and as correlates of
Source: Dave Snowden, Cynefin Advanced Practitioner’s Course December 2012
other survey questions
30
The last ten years have seen the emergence of network thinking and network analysis into the nonprofit world. LLC, the Packard foundation, and many individuals have built on the work that June did with Valdis Krebs in 2002. We’[ve been inspired by case studies like the RE-AMP case and have had the power of social media laid bare by Beth Kanter’s tireless teaching and evangelism.
Check on the poll at this point…
Here’s a quick example of a survey. I use ONAsurveys, a software program developed by colleagues at Optimice in Australia, specifically for network analysis. You can also use other survey software like SurveyMonkey, but the data format that comes out of Survey Monkey is not as easy to work with. June also has network survey software.The important things to capture in the survey are the demographic information, affiliation information, and relationship information.
The demographic component is really important, as it helps to show things that divide people or might put up barriers to collaboration. This just shows a geographic question.
We like to try to capture information about topics or issues that are particularly important to people in the network we are looking at. This is a fragment from a survey of the Network Weavers Facebook group that June and I have been working on with Ken Vance-Borland.
Last, we ask relationship information. In this case, we just start by asking how people might know each other… how they have interacted. Responses to this question might give us an idea of whether this FB group has attracted a diverse set of people who could be more explicitly woven into a network. The topical information would help with that as well.
What other relationship questions might you ask? In the programs we have worked with, some of the key questions we ask to understand not just how cohesive the network is, but how people are relating to each other. The more questions we ask at the same time, the more perspectives we might have on the network.
When survey data is analyzed, the first views are the maps that show the connections and we can quickly see specific patterns. The patterns that come out of looking at the different questions or different values of response to a question, help us understand where to zero in and look for more context.
My primary mantra in working with SNA is that a map doesn’t represent truth – it’s a snapshot that shows patterns that help us ask good questions.This is from a recent project that I did for a foundation that has funded over 100 grantees in a particular field and has been working on building the network among these grantees for over four years. They had not done an analysis previously. The color coding indicates geographic regions. The yellow dots are the foundation staff who work with the grantees. The size of the dots is a network measure of “betweenness” which is an indicator of how well positioned an individual is to move information around in the network. It’s easy to see quickly that there is one geographic area that is highly connected within itself but that is not integrated with the rest of the network. What will the foundation do? They are not planning to charge ahead and try to get these folks integrated. First, they need to think about what the value of that would be and whether it’s worth investing more effort in weaving. But the map was an good heads up.They also became very aware of the extent to which they, as program staff, were holding the network together. They will take steps to understand how to ensure that the network might survive without the focused attention of the foundation.Last, they saw that one of the key connectors was a person who is soon to retire and are taking steps to capture his expert knowledge and work to make sure that the connections are preserved in the network.
Now, we’re going to walk through a set of examples that illustrate these ways that network analysis is being used – at the outset of network building in the assessment phase, as well as how network analysis can be used through the life cycle of a program to measure overall network changes over time, the positioning and movement of individuals, and the ways that network analysis helps make sense of networks and point to evidence for evaluation.
Those of you familiar with June Holley’s work and that of other network builders know that the groundwork is really important. Understanding the capacity of the network for collaboration as well as the individual needs of members of the network. I’m going to let June tell you the story of how a network analysis provided input for designing a network approach in the criminal justice funders network.
June’s script here.
Thanks, June. In addition to looking at individual and people connections and potential, we can also map the network of what might make people want to connect – the very basis for weaving a network. In this case, we can ask people to identify the topics of interest or major concern and draw the map connecting people to topics. We show people as circles and the topics as squares. (Note you can do this in a spreadsheet or table, but sometimes things pop out more clearly in the map. Or people just like visuals!)
So one thing you can do with these affliation networks (just as you can with any network map) is to drill down and see, for example, what people might be interested in two related topics or people who have cross-over expertise. Here we can see a few people who are interested in the really tightly connected topics of collaboration platforms and change management. Anyone who has ever tried to get a bunch of people to change how they work by introducing collaboration platforms knows what a change management challenge it is!
So let’s shift into thinking about how to use network analysis when you are working with a network over time. At the outset, you may have a map (like the criminal justice map that June talked about) showing current connections. And you have an affiliation matrix that helps you to know which people might “do lunch” and this gives you the basis for weaving.So here’s an example from my colleague Beth Tener, who has worked with a number of nonprofit networks in New England. This network building project was funded by the Barr Foundation who brought together government agencies with nonprofits working on environmental issues and those working in health areas to coordinate their work to develop a new set of building codes for the city of Boston.A network analysis of those brought into the network shows, on the left, the connections as they existed when the network was first convened. Lines of different thicknesses show whether people know each other very well, well, or somewhat. Through the work of Beth’s team, the network grew more cohesive as they worked together and the result is what you see on the right. Just as important to this map, however, is the survey result that Two years after the network began, 95 percent of participants agreed that the network had helped their organization advance their mission.
In addition to the network maps that can show us so much about connectivity, network analysis also produces metrics – quantitative information that reveals aspects of the network that might not be easy to see in the map, or that support what the maps show. The overall network metrics can tell us about the structure of the network – how well connected it is overall. This number is good for looking at changes over time. Individual position metrics show who the people who are most connected, either because of the sheer number of connections that they have or because they are connected to well connected people…. I have an example of individual position metrics later, but first let’s take a quick look at how the quantitative network metrics can enhance presentation of the maps.
I depend on this person regularly for important advice and have worked with him/her on more than one projectThe Urban Sustainability Directors Network has been mapping its members since 2009. Here we see the sequence of the maps from this time. This network asks people to describe the extent of their relationships which can be at the minimal level of having been introduced to the highly connected level of working together. Here, percentages of connection are shown. Density is the overall cohesion level, that is the number of ties that exist out of a total possible. The average number of ties is what you might expect – it indicates on average how many people are connecting in the network.But metrics do not tell the whole story and can never be the whole purpose of doing an SNA. What we really need you to take away from this is that the maps and the metrics should be taken as indicators – clues of where to look for stories or to provide evidence of the success of network building.Two other points to make about metrics. We don’t know what a “good” number is. We tell by comparison year over year whether things are improving, but we don’t know when to expect the metrics to level off – when is a network saturated to the point where people are getting what they need, they have enough connections, and so on. At this point we might want to start to look at whether people change their connections --- spend more time with new people, less time with people they know. There are a lot of interesting questions in the area of metrics. [permission from Julia Parzen below]Hi, Patti, I did respond. I am sorry you did not receive a response. I would be happy to have you use this slide identifying it as USDN if you take out the names on the maps. I can't take any risk of having the names on the maps. I would be happy also to talk to you about my experience and to learn from you about your experiences. All the Best, Julia Julia ParzenCoordinatorwww.usdn.org773-288-3596773-315-7427 (Cell)
For example, the Barr Foundation Fellows program has been doing SNA since its first leadership cohort in 2005. One goal of this program was to create a cohesive network of nonprofit Executive Directors in the Boston area. At the outset of the program, the Barr program director Pat Brandes was the connector, but by 2011 when the most recent survey was completed, we could see that the role of the foundation in maintaining the network was diminished.This is one example of a story that network maps can tell. Claire Reinelt, who has been working with the Barr Foundation Fellows program for a number of years, is going to show how she uses the maps in conjunction with telling stories about the network in her evaluation work.
Claire’s script: [Important to note here the importance of other, qualitative assessment & evaluation.]
Now let’s turn to another way of looking at individuals. The individual metrics we can look at in a map that are associated with people are those that can be counted or tracked. Indegree is the number of people who point to a given individual – perhaps in the case of “receive information from this person”. The Out-degree is the number of people that a person points to. There are dozens of metrics that calculate a person’s position in the network. One that is the most often used is the “betweenness” value, that is the extent to which a person is on paths across the network – how many people is somebody “between”. In this example, we’ve made the people nodes sized according to the betweenness value – see #62 and # 80. They also have high in-degree and out-degree values, but not the highest outdegree.We use these maps an analysis to understand what people might be most useful to enlist in helping build the network, work on task teams, or otherwise support weaving in one way or another. This is another kind of drilling-down we use in assessing and working to sustain a network.Individual analysis can also be helpful in looking at how an individual moves in the network over time. The last network analysis example shows how one foundation is using maps this way.
Here’s an example from a leadership development program that has been doing network analysis since 2009. The leadership program is focused on helping individuals become more effective and a foundational technique is to bring the leaders together so they can learn from each other. One of the key questions that is asked in this network is, has your connection with this person made you a better leader? The nodes here are colored by cohort years. Here one individual is circled.
Looking at the same individual two years later, you can see that this person has become more embedded in the network and has an increase in incoming ties as well as outgoing ties.2009 (in: 1, out 5) 2011 (in: 7 out 10)The fund believes that this change in network position is a direct result of an particularretreat . Validation of the importance of the face to face convenings in a retreat setting, and that they should continue to do them. Grantee confirmed this in her reports and she also went on to initiate meetings with other fellows.In another example, a fellow who was not a strong person in-person convenings also made a number of connections. Because he didn’t participate in the convenings, they thought he was peripheral. The mapping process showed that this person was more connected than they thought.Community reporting back helps in the decision-making, much more concrete than the individual perspectives of the fund managers.
I realize that this a lot to digest and I hope you’ll take time to review the slides at some point and see what things you might see in the maps here. The important thing to remember is that a good analysis leads to really good questions – more places to probe, stories to find. And that brings me to some things I’d like to put out to the community for future conversations and work.
In dealing with data for a network analysis, the danger is in thinking that we have something that gives us measures that count. Cohesion, centrality of individuals, their positions in the network and how they change over time.
We use what we learn from probing in the maps and metrics to create a plan for building the network, for weaving. There are not a lot of new tricks out there – people like me who have worked in the knowledge management space, people who have worked with communities of practice, organizational development people – have all acquired a repertoire of ways to bring people together, to convene networks, provide collaborative spaces, and so on. I offer this list as a starting point. There are no answers. There is no “being right” about doing this. But the main question remains: does network analysis give us evidence to point to outcomes in our programs?
Just to add a cautionary note about metrics. They are very appealing but we do have to use them within reason and, as I have suggested, as indicators. It would be good to start to collect and maintain a database of metrics that would describe networks of various sizes and types, by goals and desired outcomes, and compare the metrics over time. I do think that metric comparisons can help us learn how to accelerate network growth.But we do need to be careful that our measures don’t become the targets; as you see in these quotes, it would be dangerous to focus solely on getting numbers. Network building is about relationships and the focus of the work – the goal of network building – should always be on the outcomes.I think there is a lot of interesting work ahead to better understand how to tie network analyses to outcomes. For now we can do very well and be quite content using the metrics and maps as indicators of where to look for meaningful stories that support designing and evaluating networks.