Seeing the networks in your company

Thus far we have assumed that we had network data. But data like the “Professionals” was gathered using a survey in a real organization. In this post I will walk you through the process of creating a simple network survey in SurveyMonkey (a web based survey application) and analyzing the responses from the survey using R. Lets begin by going to www.surveymonkey.com.  Here is the landing page (as of May 5, 2017). You will need to purchase a basic subscription to download the data (I purchased an educator subscription for $18).

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I’ve signed up for a free account (for now). After I complete all my signup information. Here is the screen that I get, asking me to start by creating a survey.

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I will call my survey, “Simple Network Survey.” I enter this into the text box, and then press + Add Questions. Pressing this takes me to a new screen.

 

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In order to create the appropriate network data (where we know who considers whom a friend, advice giver, etc.), we will need to begin by asking people who they are. I prefer to do this first using a dropdown menu where an individual can select just one option. The question I ask is: What is your name? Please select from the dropdown menu.  Make sure that the question type is “Dropdown”

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Once I have this, I would like to enter the names of the people who will be taking the survey. My list (of fake people) include: Alice, Bob, Chris, Dina, Elena, Frank, and Greg. I add these using the “Add Answers in Bulk” option:

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Once I click save, I move to the Options tab, and I check off “Require an Answer to This Question.” Next I click DONE. 

I now create a new page (+ New Page). This is where I will place the network survey.

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For the purposes of this example, I will only ask two questions about people’s networks. What questions shall we ask?

Perhaps one of the things that hardest to teach about network analysis is determining the right types of questions to ask people. The questions should reveal something people and their social networks that we might not have been able to assess if we hadn’t asked them those questions.

We can think about kinds of questions in terms of a 2×2 — on one dimension we have questions about networks that provide people with resources (Instrumental) and on the other, we have questions about more personal/social relationships (e.g., Expresssive).  On the other dimension we have questions that are either “Enduring or qualitative” or “Event based.” The table below summarizes some examples.

Enduring/Qualitative Event Based
Instrumental Advice

Task

Information

Asked for advice in the past week.
Expressive Friendship

Trust

Social support

Informally go to Lunch

Talked about important personal matters

Here are some examples:

Questions about who you know:

Below is a list of names of your colleagues at [firm name]. Some of them you may (1) know well, others you (2) may be acquainted with, and still others (3) you may not know at all. Please check the box next to the names of those individuals who are in categories (1) or (2).

Advice (Work-related)

Sometimes it is useful to get help or advice from your colleagues on performing some aspect of doing your work well. Please check the box next to the names of those individuals who you would approach for help or advice on such work related issues.

Advice (Work related) Reciprocal

There also may be people who come to you seeking help or advice about doing their own work well. Please check the box next to the names of those individuals who might typically come to you for help or advice on work related issues.

Advice (Career and Success)

Sometimes it is useful to seek advice from colleagues at work about more than just how to do your work well. For example, you may be interested in “how things work” around here, or how to optimize your chances for a successful career here. If you needed help along these lines, who would you go to for help or advice regarding these issues?  Please check the box next to the names of those individuals who you would approach for help or advice on these non-technical related issues.

Advice (Career and Success) Reciprocal

There also may be people who come to you seeking help or advice about such non-task related issues. Please check the box next to the names of those individuals who might typically come to you for help or advice along these dimensions.

Friendship

Sometimes during the course of interactions at the workplace, friendships form. We are interested in whether you have people at [firm name] who you consider to be friends of yours. Please check the box next to the names of the individuals who you think of as friends here at [firm name].

Event based questions:

Lunch

Below you will find a list of people who work at [firm name]. Please check the names of the individuals with whom you have met with for lunch at least once during the past 30 days.

Event based advice

Below you will find a list of people who work at [firm name]. Please check the names of the individuals from whom you’ve sought out advice about work related matters at least once during the past 30 days.

The problem of recall: People are highly inaccurate when you ask them to recall specific interaction events. They are much more accurate when you ask them to recall enduring and qualitatively meaningful relationships.  Events are highly informative when you know what happens during that event, but otherwise they are harder to generalize from.

Now that we have some examples of questions, lets add one two the survey. I typically recommend having 2 questions, one expressive (e.g., friendship) and one instrumental (e.g., advice). They usually provide different information.

Lets, for the sake of example, add an advice network question to Page 2. We will create a “Multiple Choice” question where the answers are the names of the people in the organization (e.g., Alice, etc.). The question we ask is:

Sometimes it is useful to get help or advice from your colleagues on performing some aspect of doing your work well. Please check the box next to the names of those individuals who you would approach for help or advice on such work related issues.

We will also add a short note telling people not to select their own name and to check as few or as many names as appropriate. Below the options, also check “Allow more than one answer to this question (use checkboxes).

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Let us now save this question by clicking save.

I will now add one more question, this can be our “Dependent variable” which measures the extent to which co-workers have a positive or negative impact.

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After all the questions are in, click “Next” at the top and lets begin collecting responses.

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We will use the “Get Web Link” option. The web link for the survey I made is:

https://www.surveymonkey.com/r/QZ5KG3S

Lets quickly fill out the survey. I will also fill in responses for everyone in the roster.

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After all the responses are in for all the people in the organization (e.g., Alice…) we can download the data. I have downloaded the excel file. It comes as a zip file and a resulting csv file with the data. These are respectively attached here and here.

The raw CSV file that is exported from Survey Monkey looks like this:

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Lets clean this up so that we get a 7×7 matrix. Note that there is an ordered list of names on the left (Alice…Greg on the rows) and a similarly ordered list of names at the top (columns). The rows are the respondents (senders) and the columns are the people with whom they do and do not have a relationship. With the names, the matrix looks like:

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Without the names, it looks like:

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Try to match it up to the survey response in our original file. The matrix is now saved as surveyexample.csv.

The following code imports the data (the cleaned up version above) and plots the network:

# This file provides some simple code to get you started on your Network Analysis Journey

library(data.table)

library(curl)

library(sna)

#(Q0) “who do you know or know of at [the firm]”,

#Load the “Survey Monkey” network data from Dropbox.

survey <- fread(https://www.dropbox.com/s/nd13m6szn8d8lto/surveyexample.csv?dl=1&#8217;)

#Convert the data.table objects into matrix format so they can be

#analyzed using the sna package.

survey = as.matrix(survey)

# this creates the no

names = c(“Alice”, “Bob”, “Chris”,“Dina”,“Elena”,“Frank”, “Greg”)

# Rename all the rows

rownames(survey) = names

# Rename all the columns

colnames(survey) = names

# Plot the survey network

gplot(survey, label = names)

Here is the resulting network.

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We can calculate each person’s centrality and also correlate the network positions with the final question we asked. We need to first convert it into a numeric and then import it into R.

# This file provides some simple code to get you started on your Network Analysis Journey

library(data.table)
library(curl)
library(sna)

#(Q0) “who do you know or know of at [the firm]”,

#Load the “Survey Monkey” network data from Dropbox.
survey <- fread(‘https://www.dropbox.com/s/nd13m6szn8d8lto/surveyexample.csv?dl=1&#8217;)

#Convert the data.table objects into matrix format so they can be
#analyzed using the sna package.
survey = as.matrix(survey)

# this creates the no
names = c(“Alice”, “Bob”, “Chris”,”Dina”,”Elena”,”Frank”, “Greg”)

# Rename all the rows
rownames(survey) = names

# Rename all the columns
colnames(survey) = names

# Plot the survey network
gplot(survey, label = names)

#Load the “Survey Monkey” network data from Dropbox.
surveyoutcome <- fread(‘https://www.dropbox.com/s/we2dvevfejte8ov/surveyoutcome.csv?dl=1&#8217;)

#Convert the data.table objects into matrix format so they can be
#analyzed using the sna package.
surveyoutcome = as.matrix(surveyoutcome)

# rename rownames and create a variable which is the integer
# version of the numeric response
colnames(surveyoutcome) = c(“name”,”response”,”respval”)
respval = as.integer(surveyoutcome[,3])

# Calculate outdegree for the survey response
survey.outdegree = degree(survey, cmode = “outdegree”)

# Estimate a model regressing the respval on the outdgree
m.0 = lm(respval ~ survey.outdegree)
summary(m.0)

Here is the regression outcome:

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The above walk-through should give you a way to collect network data, and then analyze it using R.

Before, I conclude I want to discuss the various survey approaches used by network analysts

Types of Network Surveys

Roster based surveys: Roster based methods are perhaps the most common approach. This is what we just completed above. With roster surveys, you provide the respondent with a list of names of people or organizations. Then you ask them to indicate (by checking off the boxes next to the names) which of these people they have a certain relationship with. The nice thing about roster based surveys is that they tend to be quite accurate because people don’t have to recall the names out of the blue. Further, the roster allows you get longer network lists than if people had to recall names from memory. The down-side of this is that if the organization has too many people (say in the 1000s) it would be too hard to make people go through a list of 1000 or even worse, 2000 people.

List based surveys: The other type of survey is a list survey. Here you ask the question and then request that your respondents list the names of people in the organization that they have this relationship with. What might be some concerns with a survey method like this? 

Ego-network surveys:  This is a slightly modified version of the list-based survey. Here you ask the people to list up to five people (or k people) that they have a certain relationship with. Then you ask them to indicate whether the people listed also have a relationship of a certain type with each other. 

Position generator surveys: This is perhaps the least structural of the network surveys. Here what you do is the following: You provide a list of the “positions” that people can potentially occupy – so in an organization you list the different functional areas, levels of seniority, etc.  And then ask people whether they have a no relationship with someone in such a position, acquaintance in that position, a friend in that position, etc.  This is a very indirect measure of networks, but it provides a broad understanding of the “range” of a persons network.

In addition to these classical approaches to collecting network data, organizations have more modern methods available to figure out potential sources of interaction between their employees. These include:

Email:  IT administrators know every email you send to everyone else and what it contains. This is true in most cases in the vast majority of organizations. Scary, yes. True, yes. But this is information that everyone knows exists and some organizations are using it to understand informal interaction and trying to make better decisions with this information.

Mailing list/Groups activity: Another source of information about networks and interaction are the mailing lists that people are a part of.

RFID:  Most of our ID cards have RFID these days – we use these cards to enter/exit buildings. RFID censors can also be placed in strategic locations to understand interactions that are face-to-face between people. Conference organizers are also using RFID tags to understand interaction among attendees.

Online data sources:

LinkedIn —  LinkedIn has a massive economic graph. Their data include where people got their degrees, where they worked, who they worked with, etc.

Facebook: This is the largest social network in the world. Period.

About firms:  The websites of Venture capital firms tell you who their partners, etc. are and where they attended college and when they graduated.  It also tells you that some may be investing in similar projects.

 

More: In a future post, I will walk through how to create “network” data using text in documents. The “ties” here are measures of similarity between the text descriptions of entities.

 

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).

Creating value for others

One of the most important resources you have for creating value is your social network. And one of the most important ways that you can create value is by understanding the goals and needs of people you know and using your own network to help them meet those goals in ways that only you can do. In so doing, you create value for the person being helped and also you.

This assignment’s goal is to help to reason more carefully about the unique value that your network holds for other people (and, of course, yourself). Using LinkedIn (I imagine that you have a LinkedIn account) I want you to begin by choosing 3 people in your network that you know are trying to accomplish something, whether it be finding a job in a specific industry, starting a business, or something else. Next, I want you to find for each of these three people, 2 other people to whom these first three are not connected to, are unlikely to know and who are likely to be useful to them in achieving their goals.

Once you have done this, please write a short report totaling no more than 2 pages with the following information about the three potential brokering opportunities you just described.

  1. Describe the goals and needs of each of the three individuals you listed; describe also how you know these people, how/why they are connected to you, and how you discovered that they had the goals you described.
  2. Next, describe the two other people in your network that might have the “resources” (i.e. a job opportunity at their firm, the connections to people who can provide financing for a venture, etc.) that would be useful for the people you listed, how you know these two people that can help the person, and why you think they would help you help the first person (e.g. is it a win-win situation, will they be repaying a debt to you, or will you be asking for a favor from these people that you may need to repay later).
  3. Third, describe how you will broker this connection and more importantly describe why this is the unique value that you provide and why it is unlikely that other people would not be able to make these same types of brokering connections.
  4. Finally, based on your answers to these questions. Describe what you think is the unique value that you can bring to the table with your network. Are you better at brokering one type of connection vs. another, etc.

 

Understanding Your Network

For this assignment, I want you to draw your advice network and friendship network out to two degrees. That is, enumerate your friends (and advice givers) and the relationships they have among each other, but also try to enumerate your friends’ friends (even the ones that you may not be friends with) and the connections among them. The first degree should be straightforward. The second degree is clearly much more difficult but it is a useful exercise in determining the extent of your knowledge about your own networks. You are welcome to use pseudonyms or initials to label your contacts (and their contacts). Once you have drawn these two networks answer the following questions:

  1. How efficient are your networks?
  2. Relative to your peers, how “entrepreneurial” are your networks?
  3. Why do you think your networks have the structure they do?
  4. Are your networks well suited to accomplish your short and long-term goals?
  5. If so, why? If not, what strategies can you use to improve the quality of your networks so that they help you more effectively?

Seeing networks clearly

A practical challenge people have when they enter a new firm, school or social organization is figuring out how things “work” there. Sometimes you might ask yourself “how do I get people on board with my new idea” or “who really makes the decisions here” or “who should I talk to in order to get the latest gossip”? Our instincts are to answer these questions by resorting to two types of information we can easily gather:

  • Who these people are (e.g., how long have these people been at the firm, their personalities, where they got their degrees, or how smart they are, etc.).
  • What these people are (e.g., their formal positions in the company’s organization chart).

Actually, our instincts are pretty good. People who have been around longer probably do have more interesting things to say or hold more power; people who have a certain personality type might indeed be more approachable, charismatic, or influential; a person who holds a fancy title should be able to get more things done; people who have higher IQs probably do have more knowledge.

But for every example of the above, we have all seen examples of the exact opposite. In fact, some might argue that we see more contradictory examples than we see confirmatory ones. This raises a puzzle: Why are individual traits only sometimes predictive of the things we care about?

Network analysts suggest that answering the who people are and what people are questions is insufficient for understanding power and influence. Answering these questions will give you only crude signals for what you are trying to learn about: power, influence or knowledge. The underlying causal force is actually people’s social networks: the pattern of social relationships that link people together in an organization or community.

Who’s got the power? 

Consider the following R&D unit in a large technology firm called Micron (name changed). Alexis was recently hired to help turn around this unit as Director of R&D. She is a recent graduate of a top MBA program and was previously a product manager for a breakthrough consumer app. Her references all praise her deep technical knowledge and her superb leadership and organizational skills.

Micron has been facing some big challenges in their R&D unit over the past few years. For instance, the R&D team has lost two Directors over the past three years. The unit has also been unable to produce any new breakthrough product ideas or technologies.

Micron is really counting on Alexis to figure out what the problem is and to fix it.

Today, the unit consists of three teams (Design, led by Waylon; Hardware, led by Justine; and Software, led by Chris.) The design team has three additional members (Case, Brogan and Rodrigo), the hardware team includes Frank, April and Kinley and the Software team consists of Leo, Eva, Sasha and Kim.  The formal organizational chart of Micron is depicted below.

Alexis is an astute student of organizational politics. She knows that fixing things in any organization starts by answering the following question: Who has got the power?

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Obviously, I haven’t given you the necessary information to help you answer this question yourselves. But a smart observer might come up with the following answers:

  • The person who has been at Micron the longest (it is Brogan, but he’s not the most powerful)
  • The boss (well, that is Alexis, and no he isn’t the most powerful)
  • The most friendly and outgoing (that is Sasha, no not her either).
  • Someone who has the most technical knowledge (Justine, but it is not her).

To answer this question we must begin by asking: What is power? 

Power is the ability to mobilize resources to get things done.

Breaking that answer down, powerful people are those who can get access to scarce resources faster than others, convince other people to act in a certain way or towards a certain goal, and see the potential political obstacles in the way and have the support but also foresight to avoid these obstacles.

The answer to the power question, according to network theory, is: people who are in central positions in social networks are powerful. They are privy to knowledge (through their social ties) that not everyone holds, they can influence others through their social relationships, and see better than others the political obstacles in their way.

Lets begin by looking at another graph. Below, I’ve plotted a network where the nodes (the ovals with names in them) represent the same people we saw in the organizational chart above. The nodes are connected to each other by edges which in this case represent mutual advice giving and receiving (but could represent other relationships such as trust or friendship). By looking at this graph, who do you now think is the most powerful person in this unit?

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The answer appears to be Eva. She is connected to more people and more of the groups than anyone else. Kim, for instance, is only connected to her little team, and Case, Brogan and Rodrigo are also minimally connected. Alexis, though she is the boss, has connections to the top of each team, but the information she gets is highly filtered. Not surprisingly, Alexis also goes to Eva for advice.

And who is Eva? She’s actually just another software engineer, but one that somehow has built a network that gives her insight and influence. The important thing to learn from Eva is not that Eva has some characteristic or trait (or even a combination of these), but rather that the network provides independent information that helps predict who has got power beyond observable traits. 

Lesson #1: The real way that work gets done in a company is represented by the informal network.

Network Positons

The above example is illustrative of how networks provide different information than the org chart or people’s observable characteristics. There is an entire science on interpreting and analyzing these network graphs (sometimes called sociograms).

Screen Shot 2017-04-25 at 2.24.39 PM.pngAbove is a stylized network, called the “Kite Network” developed by Professor David Krackhardt of Carnegie Mellon University.

Like the “real” network above, the kite network has nodes that are more powerful than others. Which node is the most powerful in the kite network?

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One possible answer is node D. The reason is that it has the most number of connections. Indeed, is powerful. It has a type of centrality in the network called Popularity centrality or Degree centrality. If you want to get many people on board with an organizational change, or organize a party, D is your node. You can calculate degree centrality by merely counting the number of connections that a node has.

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Another answer is either F or G. The centrality of these nodes is a bit harder to see. They have what is called Farness centrality. If you count up the number of “hops” on the network it takes to get from one node (say, A) to all other nodes (B … to … J) and take the average, you get farness centrality. F and G have the lowest farness (or highest closeness) which means it takes a lot less time for information (or disease) to get from F and G to everyone else. Research has shown that Farness/Closeness is correlated to how fast ideas, knowledge, information spread out from a starting point.

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Finally, H has what we call Betweenness centrality. Betweenness measures the extent to which information must travel over a certain node in order to get somewhere else in the network. In other words, nodes high in betweenness are bridges that connect otherwise disconnected parts of the network.  There is a extremely large body of research showing that individuals who are high in betweenness have access to diverse information in their organizations and are often the source of creative ideas, have greater bargaining power, and experience superior career outcomes.

Lesson #2: Power accrues to those who are central in the informal network.

Now that you know some of these concepts, it might be useful to draw out your own network. Here is a short assignment you can do to understand your network better.

How well do managers perceive social networks?

All of the analysis above is premised on the notion that a manager can actually see the informal social networks of the people they are managing.

Research suggests that most people (including managers) do not accurately perceive the social networks in their companies. Indeed, there is growing evidence that people are even wrong about their own friendships—that they think think someone is friend, but that person does not feel the same way. However, research (e.g., Krackhardt 1990) also shows that there is substantial variation in which managers/employees have more (or less) accurate perceptions about a network. Managers with better perceptions are more powerful—i.e., better able to get things done.

Consider Silicon Systems (from Krackhardt (1992)) a technology company undergoing some organizational turbulence because of the not-so-friendly behavior of one of the managers, Ev. The situation at Silicon Systems had gotten so bad that the technicians working under Ev wanted to form a union to protect themselves from him.

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The story of Silicon Systems is interesting and you can find more details hereThe short of it, however, is that a lot of the managerial problems at Silicon Systems were in part due to the poor perceptions of the social network—by the manager in question, but also by the top leadership.

Here is a visualization of the “actual” advice and friendship networks at Silicon Systems. They were constructed by asking people who they sought advice from and who they considered friends at the company.

Advice Network at Silicon Systems

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Friendship Network at Silicon Systems

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By looking at these two networks you notice two things. The networks are different, but also that in the Advice network, Ev, the trouble manager is much more central than in the friendship network. This is because he is smart and a high performer. However, the workers under him are not particularly happy.

A key player among the technicians working for Ev is Chris. Chris is a nice guy, he’s not particularly charismatic or among the best technically, but people do like him. Chris listens to what people have to say and people trust his judgment and advice. In fact, Chris’s opinion matters to them and the other technicians value his opinion when making their own decisions.

Now that you have seen the advice and friendship networks at Silicon systems. Let’s compare the perceptions of Chris (the informal leader) and Ev (the formal leader).

Chris’ perception of the social network at Silicon Systems

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Consider Chris’ network perception. Note how central Chris is in the friendship network. He’s the guy that most technicians trust (you can see that in the friendship and to some extent the advice network above). Though Chris isn’t 100% accurate in his perception, he’s got a decent understanding of the network at Silicon Systems. He is a bit more popular in his mind than he is in reality, though further away from his group of social connections he is a bit more clueless. But he does have some idea about how things work at Silicon Systems.

Now consider Ev, the problem manager. Below is Ev’s perception.

Ev’s Perception of the Networks at Silicon Systems

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Ev has no clue how things work at Silicon Systems. He has no idea that people are so tightly knit. This affects his ability to manage well and definitely weakens his power within the firm.

Ev is a problem. He’s smart, productive, and critical to the firm. But he is clueless. If you were Ev’s boss, what would you do?

Lesson #3: Power accrues to people who can accurately perceive the informal social networks in their firms.

Managing Social Networks in Organizations, MBA Syllabus

This course is designed to improve your effectiveness as a manager by introducing you to the science of social network analysis. Over the 8 sessions that make up the course, you will learn how to:

  • Evaluate and optimize your own networks for acquiring novel information, exercising influence, and creating value for others.
  • Use networks to assess the reputation, trustworthiness and capabilities of others.
  • Visualize networks within an organization and understand where value lies, power lies, and how to create new value where it is most needed.
  • Understand how to see organizational and business data through the lens of network analysis, and improve the signal-to-noise ratio for sorting through the massive data collected by today’s organizations.

Course Requirements


Schedule

May 8, Seeing Networks Clearly

This session gives you a cheat-sheet to understanding social networks in organizations. Before the class begins, I would recommend reading two articles that will provide you a good over view of the basic things about networks that every manager should know.

Required reading:


May 12, How to Build an Entrepreneurial Network

One of the most important insights about networks is the idea of structural holes. Bridging valuable, but unfilled, holes in social and economic life is the key to creating value for yourself and others. In this class you will learn about how value is created by bridging the “white space” or holes in organizations and markets, and examine whether your networks have ample structural holes.

Required reading:

Assignment 1 Due: Understanding your Network


May 15, Creating Friendships at the World’s Largest Network, Sean Taylor, Facebook

Guest speaker: Sean Taylor, a Research Scientist at Facebook and a leading expert on viral marketing will join us to talk about how he and his team at Facebook use data science and network ideas at Facebook to create value for billions of users world wide.

Required reading:

  • TBD

May 19, Creating Value Through Cross-border M&A, Sanat Rao, IDG Ventures

Guest speaker: Sanat Rao, Partner at IDG Ventures

In 2013, Sanat Rao quit his job as Director of Corporate Business Development at Intel and took a big leap of faith to work for a 1-year old non-profit in India. Mr. Rao will join us in class to talk about how he jump started M&A activity between US companies and Indian startups and helped broker the sale of under-the-radar Indian startups to US giants such as Facebook and Yahoo!.

Required reading:


May 22, Taking the Microscope to your Company

Guest speaker: Steven Huang, Strategist at CultureAmp

Seeing how your organization works might seem like an onerous task, but anyone can do it if they get the right buy-in from the firm and the employees. In this session you will learn how capture and analyze the networks in a company, interpret their structure, and see value where others might not. Steven Huang of the startup CultureAmp will share with us his experiences conducting surveys within organizations at scale and how CultureAmp has been helping companies make the best use of their talent.

Required reading: 

  • Cross and Parker (2004), Chapter 5 —Pinpointing the Problem: Understanding How Individuals Affect a Network
  • Cross & Parker (2004), Appendix A & B—Conducting and Interpreting a Social Network Analysis.

Assignment 2 Due: Creating value for others


May 26, Hidden Value in Data.

In this class we learn the building blocks of a network approach to data science that has transformed modern business. The topics we will cover include: making product recommendations, understanding social influence on the web, effectively using the “crowd” to scale work. Guest speakers Rishab Ladha and Greg Schwartz of SquadRun will talk about how their company leverages two of the biggest innovations today, crowdsourced labor and machine learning, to dramatically optimize challenging business processes.

Guest speakers: Rishab Ladha and Greg Schwartz, SquadRun.

Required reading:


May 29, Memorial Day.

Enjoy Memorial Day!


June 2, Pulse and Beyond, Ankit Gupta, Co-founder of Pulse

Guest speaker: Ankit Gupta, co-founder of Pulse and later the Senior Product Manager of Pulse after its acquisition by LinkedIn will talk about his experiences founding Pulse and his learnings from rapidly scaling one of the hottest mobile apps and subsequently integrating it into the product offerings of an established player.

Reading: With surprise boost from Steve Jobs, news app is a hit.


June 5, Final Projects

Students present learnings from the network analysis of the companies/organizations they consulted for.


 

Stanford University
Graduate School of Business

OB522, Spring (Second half) 2017

Professor: Sharique Hasan, Associate Prof. of Organizational Behavior, Stanford GSB
Office: W239 (KMC, Stanford, CA)
Email: [firstname]@stanford.edu

Textbooks:

The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations (Robert Cross & Andrew Parker), 2004.

Driving Results Through Social Networks: How Top Organizations Leverage Networks for Performance and Growth (Cross and Thomas), 2009.

Teaching Assistant: Solene Delecourt, [firstnamelastinitial]@stanford.edu

Times: Monday/Friday from 10:00 to 11:45 AM
Room: GSB Class of 1968, Room 102

Everyone should learn about social networks

For six years, I have taught network theory to MBA students at Stanford Business School. While there is no doubt in my mind that MBA students (and especially those leading business schools) have excellent networks, the conventional wisdom that students come in with is that having good networks is mainly about two things: (1) being good at “networking” or (2) knowing a lot of important people.

The truth of how networks actually allocate scarce resources and bestow success on individuals and teams, however, is more nuanced, and sometimes pretty counter-intuitive. My argument to students is quite simple, a manager who understands social networks and can “see” them more clearly, can create more value than his or her equally qualified colleagues. Seeing networks is more about seeing the forest, and not just the trees.

My first goal is to get students to see themselves and others, not as bundles of degrees, achievements, job descriptions or even personalities, but rather as people who occupy positions in a network. Network positions are generally invisible to the casual observer, but to anyone who has felt torn between two groups of colleagues, or has failed to break into a career or organization, the impact of networks can be acutely felt.

Seeing and understanding networks is about having the right perspective. The right perspective is about knowing what you want to accomplish and whether you have the support and resources to get there. The class is built around four perspectives that managers usually have to take to be effective. In designing the class, I have drawn heavily on the insights of leading scholars in the field such as Ronald Burt, David Krackhardt, Joel Podolny and many many more.

The four perspectives I will focus on are:

The ME perspective. It is inward looking and is about taking stock of your own social networks, your goals, and whether you are set up to succeed in your career and beyond. This perspective allows you to identify how your network creates value for you, what the nature of that value is, and where it comes from.

The YOU perspective. It is outward looking and is about how you can use your network to create unique value for others. Creating value for others is the bedrock of any successful career or organization.

The US perspective. It is holistic, it asks the manager to understand how work “really” gets done on a team, identify where the bottlenecks are and where value lies, and develop solutions to your team become more effective.

Finally, network ideas have transformed the TECHNOLOGY industry, either by making once individual technologies social or by finding value in the relationships between content, products, and ideas. This task of uncovering hidden value in data is perhaps the central enterprise of the modern technology industry. I try to give students a networks framework for seeing value the in data that organizations already collect.

During the month of May, I will post the key take aways from the  8 modules that make up the class. The modules should give people the basic tools for taking a network perspective on their careers, their teams and their ventures.

If you’re interested, here are the Syllabi for both the MBA Networks Class and the PhD Networks Class.