Using Organizational Network Analysis (ONA)




Featured post by Information Architected Consulting Partner, Patti Anklam.

Organizational network analysis (ONA) uses a subset of methods developed for social network analysis (SNA), a methodology for collecting information about connections among entities (usually people), developing visual representations of the relationships of those connections and applying mathematical analyses to understand patterns and derive insights.

ONA methods are typically used to look at people within organizations and the relationships among them that are vital for knowledge sharing, collaboration, effectiveness, and innovation.

What are the results?

The results of these methods provide information that is useful in a number of ways:

  • Patterns of connectivity within and across organizational groupings. Are there sufficient connections across groups? Are some groups more cohesive internally than others?
  • Who are the people who hold the network together? Are there people whose loss would negatively impact the flow of knowledge? Who are the influential people, and how well are they connected?

Information obtained can be presented as maps (with arrows showing links between people or groups) that are good for helping people see gaps, problems and opportunities.

Data is obtained for an organizational network analysis through the administration of a survey which may have several components:

  • The relationship (social) component
  • A network pulse component
  • An influencers component
  • A social media component

The Social Network Component

The social network component requests respondents to reveal their relationships with others along specific dimensions, for example getting information, seeking out for problem solving, and so on. Typically, people are presented with a list of the names of all the other people in the survey population identified (this can be an entire organization, specific levels in the hierarchy, clearly identifiable organizational groupings, etc.). They are then asked a set of questions about each of the people they know, such as:

  • How frequently they interact with this person
  • How likely they are to receive or share new ideas with this person
  • How well they know what the other person’s area(s) of expertise are

A typical social network analysis provides:

  • A relationship map that shows the connections based on responses to the questions between specific designated individuals in a network (as shown in Figure 1).  The specific links (lines) between people can represent any other possible relationship.
  • Quantitative metrics that indicate the key people in a network, people who bridge subgroups within a network, people well positioned to move information across a network, or the overall connectivity of a network. These metrics can provide baseline data with which to compare changes over time.

Figure 1. Example of Social Network Diagram

A network analysis uncovers the patterns of interactions and helps to highlight key individuals. In the example in Figure 1, it is easy to identify people who are in the core of the network as well as those who are less well connected. Color coding of the individuals (represented by circles) can show different organizational or geographic affiliations; this demographic information is designed to ensure that we can look at possible junctures in communication patterns and flows.

Quantitative analysis can measure the effective size and diversity of an individual’s network, the capacity of the network overall for collaboration, and can provide baseline measures for group-to-group or question-to-question comparisons or for baselines against which to measure change over time. For example, in comparing two networks (or responses to different questions), it is sometimes simple to see from maps that one group may be more cohesive than another, but it is the quantitative data that can be used to measure change over time. Figure 2 shows how a network measure of cohesion differentiates responses to two network questions.

Figure 2. Using Quantitative Measures in ONA

The Network Pulse Component

An ONA can be coupled with a network pulse survey that asks respondents questions about the extent to which the organization, or network, is meeting their needs. Questions are framed as assertions with responses on a Likert scale of “highly disagree” to “highly agree,” for example:

  • It is easy to get access to the information I need to get my work done.
  • The [organization] helps connect me to people and resources we need to improve the results of our research

Responses to these questions provide insight into weaknesses in how an organization supports its network, differences among different parts of the organization with respect to their attitudes and can also provide a baseline against which to measure progress for implementing changes over time.

The Influencers Component

In addition to (or in place of) the social network component, it is also useful to ask people to nominate those who display desired behaviors or qualities. They can be presented with a list of names and nominate from that list, or they can suggest the names of people who display or encourage behaviors such as working collaboratively, creating a positive work environment, and so on. The identification of influencers can be very important when an ONA is used in the context of a change management program or technology adoption — it can identify those people who might be selected to lead pilot projects, communicate results, or to enlist in co-design of collaboration tools and systems.

The Social Media Component

Network analysis can be applied to any entities that have relationships; the data about those relationships can come from many sources. ONA typically uses surveys because the data contains a qualitative aspect that is not always possible. However, as a way to look for patterns of interaction, it has become increasingly popular to look at how social media are used in an organization. Extracting data from email interactions, tweets, comments and notes on collaboration sites, it is possible to create (as in a survey-based ONA) both maps and metrics that can demonstrate the current state of connectivity as well as to measure changes over time.

Working with the Results of an ONA

The results of a network analysis can be used in a variety of ways in support of work transformation projects:

  • Justification. An ONA can be a precursor or justification for a work transformation project. For example, if an organizational goal is to become a collaborative enterprise, the ONA results can demonstrate a current level of collaborative behaviors.
  • Diagnostic tool. ONA maps and corresponding metrics can help guide decisions about implementing knowledge management, collaboration, or change management programs. In conjunction with other cultural surveys, it can help the organization target interventions. For example, if the ONA reveals a high level of collaboration in one organization, it may be useful to use that organization as a source of “good practices” to share with others. Or, the ONA may reveal influencers who are not necessarily well positioned hierarchically, but who may be brought into a more prominent role.
  • Measurement and evaluation. The quantitative metrics for an ONA can show differences across groups and organizations, and can serve as the baseline to measure change over time. Repeating an ONA survey at annual intervals, for example, can demonstrate year-over-year progress in enhancing collaboration and connectivity in the organization.

It should be noted that an ONA, in any of these guises, is also an organizational intervention. As people become aware that there is a survey about relationships, collaboration, connectivity, they become more sensitive to their own interactions with others.

Taking the survey and thinking about individual connections to other people can cause subtle shifts in relationships — and any number of such shifts can start to alter the system dynamics.

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How are you managing your organizational network?

  • Wondering how to tap the brains in your organization?
  • Tired of hoping that installing “social tools” will break down the cultural silos you know are cutting out value from your employees?
  • Eager to learn how to run an entire Social/Organizational Network Analysis project yourself? Soup to Nuts – Process to Tools?

Take advantage of our 4-Hour Online and On-demand eLearning course, “Intro to Social/Organizational Network Analysis” created by Patti Anklam and Information Architected on our learning platform, IAI University.

Intro to Social/Organizational Network Analysis is designed for people who want to understand how to systematically identify and map networks within their organization as well as those who want to learn about the tools and methods to map and analyze networks. This is a practice fundamental to effective collaboration, social networking, Web and Enterprise 2.0 strategy and Knowledge Management.

The course is presented by Patti Anklam, Principal Consultant at Net Work, and author of the best selling book “Net Work.”  She has consulted with hundreds of organizations around the world.

The “Intro to Social/Organizational Network Analysis“ course has four modules and includes a complete walk-thru of the ten steps in planning and running an Organizational Network Analysis project.

Register Now for “Intro to Social/Organizational Network Analysis”

Module 1: Introduction to Social/Organizational Network Analysis (SNA/ONA)

  • Overview of SNA/ONA
  • The Premise
  • Evolution From Science to Practice
  • Core Concepts and Terms
  • Case Study: Ten Steps

Module 2: Network Patterns and Metrics

  • Basic Principles and Patterns
  • Structural and Centrality Metrics
  • Roles

Module 3: Software Tools for Network Analysis

  • The Basics of Inputs and Outputs
  • Collecting Data Using Surveys
  • Analysis Tools
  • Available Resources

Module 4: Managing an ONA Project

  • Managing the Project
  • Organizational Preparation
  • Working With the Results
  • Critical Success Factors

Register Now for “Intro to Social/Organizational Network Analysis”

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