The organization behind the chart, an assignment.

Network analysis has permeated the analytical toolbox of many of the world’s most innovative companies. Firms, both large and small, have begun to use the tools of social network analysis (SNA) to understand the collaborative structure within their organizations and the collaborative and competitive structures in their respective markets. In the early days of SNA much of the work was conducted by boutique consultants. Today, many of the largest consulting firms have specialists in this area and many companies such as Google have built robust internal teams with this talent.

Despite the revolutionary change in the practice of SNA over the last decade, the basic workflow of conducting a SNA remains the same. Five steps in particular are universal and do not vary by industry, organizational size, or other firm characteristics. These steps are:

  1. Select a bounded social unit as the target of the SNA. This could be a division in a firm, the whole organization, or a cluster or industry. For examine, one could do an SNA on just the medical school or all of Stanford University. One could also study a single VC or all of the firms on Sand Hill Road.
  2. Once a bounded unit is selected, learn about the context and ask: (1) what are the relevant entities (i.e. who are the people who should be included in the study); (2) what are the relevant relationships (i.e. friendship or co-investing); and, finally, (3) what are people trying to achieve with these relationships (i.e. generating more innovative ideas, getting promoted, or getting in on the best deals)?
  3. Once these are determined, the SNA will require the analyst to ask the relevant entities about their relationships. This is done through what is called a “Network Survey.”
  4. Once the surveys are completed, code and analyze the data. Data coding is relatively straightforward and can be done in Excel by creating a matrix and filling in the relationships between entities. After the coding, analysis will consist of visualization and calculating centrality measures.
  5. Interpret. Now that you have the data, you are likely to see patterns that you may have or have not expected. Why do you see them, do you see people with unexpected centrality in the network—why are they central, what are the implications for the bounded social unit and the person who has that centrality?

That is all it takes to do a SNA. The process can be scaled or scoped down depending on the context. Your task for the Final project is to follow these steps and in a team of 3 or less, conduct a SNA on a bounded social unit of your choice (except this class). In prior years, students have done SNA on their MBA class, their MSx class, their startup, their friend’s startup, among others.

 

Here are the deliverables for this class:

  1. Choose a bounded social context to study. I would recommend—for purely time-related reasons—to choose a social unit that is somewhere between 15-25 people. I am OK with smaller units as well as larger ones, but smaller units may not be as interesting and larger ones may become unmanageable in such a short period of time.
  2. After choosing the setting, describe why it is interesting/important, who will consist of your relevant entities, and what are meaningful relationships that exist between these people (and why?). Finally, describe why you think that networks may matter here and for what?
  3. Develop and conduct survey with two components: Ask two network questions (the simplest are: who do you consider a friend? and who do you go to for work-related advice?). Ask up to 5 questions about people’s background and achievements. These could include: Where did you go to undergrad, how many years of experience do you have. With respect to achievements, you can ask questions about work satisfaction, feelings of success, etc. You can do this survey on paper or using online survey software such as Survey Monkey or Google Survey.
  4. After you have survey, code and analyze it. Once you have the raw data, set up a meeting with me and I will help you calculate the centrality measures and visualize the data. I’ll send out an example of how you should store your data by the next class.
  5. Interpret. What is interesting and unexpected. Make some predictions about peoples outcomes (will someone leave, get promoted, have a brilliant idea), and justify them based on what you know of the context, network theory and your own intuition.

On the final day of class we’ll be presenting our analysis to the class. You have two final deliverables:

  1. Please prepare a 5 minute presentation with your analysis and interpretation.
  2. Write a short report with your findings and submit them to the TA. The report should be at most 3 pages (12pt font, double spaced).

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