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| | 2010-02-17 | | 
About a week ago I put up a simple quiz on TwitPic using David Krackhardt's kite network as focal point. The kite network above shows a small group of people with strong symmetric[two-way] communication links. I asked,
"Where would you plant your msg in this net? Why?"
Several of my Twitter followers immediately answered and then the post was re-tweeted by several friends of mine. One friend sent it out to 30+ "social media mavens" -- none of them braved an answer.
This is a toy problem, yet it helps us think about how information and influence spreads in a human network. When I present this problem during one of my many talks on this subject, the first answer from many voices in the audience is usually "Diane." Then there is a period of silence and a few people sheepishly offer "Heather." Finally some joker in the back of the room yells out "Jane" and everyone has a good laugh.
So, what is the right answer? There are several.
The most popular answer of "Diane" is not a bad answer. The eye is attracted to the hub structure around her. She has the most connections and does reach a majority of the network with a direct connection.
The choice of "Heather" is a good one -- my preference. While Heather has only three direct ties, she reaches everyone in the network within two steps. Diane has several longer paths to reach everyone. Information and influence both degrade with each step in a network. After one step the message begins to grow fuzzy, after two it is becoming very noisy, and after three it is basically useless -- background hum. We might be all separated by six degrees but it is the first two steps that really matter.
Another good answer is "Fernando or Garth". They are between Diane and Heather and can also reach many people in the network quickly. Those that know social network analysis come up with this answer because these two guys have the best closeness centrality.
All of the good choices mentioned above are not guaranteed to get your message passed around even this small network. Just like a forest fire depends on one burning tree igniting another tree, or two, Diane, Heather, Fernando, and Garth all depend upon others to continue passing the message. It is not just the seeded node that matters, but the network neighborhood that the seed is embedded in! And... each node has a different threshold of adoption -- for one topic Carol may be a slow adopter, while Ed may be quick, and vice versa for a different topic/idea.
I am reminded of this song by the Alan Parsons Project -- The Turn of a Friendly Card:
"The game never ends, when your whole world depends,
on the turn of a friendly card"
Or in today's world -- the turn of a friendly tweet!
We have a simple problem, with no simple answer. So, how do you work this?
What happens when we try to scale this to real human networks that have dozens or hundreds of interconnected friends or colleagues in a network like below?
The secret is... redundancy! Yes, redundancy, that concept that we tried to eliminate in the 1990s with untold hours and dollars of business process re-engineering. Some redundancy actually helps networks function better.
In the simple kite network above we would use redundancy to seed the message with Diane and Heather! Some people may not hear Diane today, but will pay attention to Heather tomorrow.
In the real human network above we might need to find a dozen or more places to plant our viral visitor. Social network analysis software can help us discover the best soil for planting!
Update...
So, I tweeted the link to this blog post when I finished writing it: evening Eastern Standard Time in USA [GMT -5]. The response was not great. bit.ly showed me that 25 people clicked on the link in the first hour. The next morning I tweeted the link again and now more of my Twitter followers were paying attention -- by Noon bit.ly reported over 300 clicks. Finally I ran another tweet @ midnight, for all of Pacific folks, and early-risers in EU and RU. This added another 100 clicks accroding to bit.ly.
Lesson learned: It is not only the persons you plant the message with, but also the timing of the message. People pay attention at different times -- especially on Twitter. Redundancy in timing works too. | |
| | 2010-01-04 | | 
What do you see when you look out the window above -- the structures or the sky?
The Gartner Group is a well-known, worldwide advisor on information technology issues. They have been a fan of social network analysis for several years now. Recently, they sent out this press release about how social and organizational network analysis fits into their concept of "Pattern-Based Strategy." Gartner describes their approach as focusing on "business patterns to capitalize on opportunities or avoid disruptions." Gartner is expanding their view -- they are not just talking about Windows® any more.
My partners and I have been analyzing networks in, and between, organizations and communities for over 20 years, and we certainly can attest that what Gartner suggests is true -- the key is in the connections! We have repeatedly found patterns in adaptive and agile organizations that are not present in companies that struggle with similar opportunities and disruptions. We are delighted to see an influential firm like Gartner now looking in this direction and seeing what we see.
One of the interesting things about organizational patterns is that they do not follow a strict recipe or design. However, good network patterns do provide highly similar benefits -- the ability of the human system to learn from and respond quickly to both opportunities and disruptions. The structures [both formal and informal] in Company X may not be the same as the structures in Company Y, but each may be optimizing a pattern, uniquely applied to their situation. We focus on the similar patterns we see across diverse organizations. What do they have in common? These organizations are succeeding because of their ability to exchange information/knowledge, learn quickly, and become aware of their environment -- irrespective of their particular hierarchies or business process designs. It is the pattern of the emergent organization –- what happens in the white space on the organizational chart -– that leads to adaptability and agility, and ultimately to success.
We can show you where your organization or community is on that scale of adaptability/agility and help you adjust your patterns for increased success with opportunities and disruptions.
Lets open up a new window in your organization...
What do you see when you look at your organization -- the organization chart or what goes on behind it?
Picture above is from my favorite young photographer -- Alice Merkel. See more of her portfolio on Flickr.
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| | 2009-12-21 | | After seeing this cartoon by Ed Hall, I started to think about personal networks. What will your personal network activity be like this holiday season?
What will your presence be, after the presents are opened?
Here or There?
Let's look in on a typical family gathered for their holiday celebration. Mom, dad, kids, and grandparents. Where will the conversations be? In the room or outside the room? Local or Global?
With digital tech on the wish lists of all age groups, will each withdraw into our own world, focused on their new device... even while they sit within arms length of their close ones? Or will the conversations span local and global, with everyone in the room sharing what they are seeing/hearing out on the Net? Will the local/global perspective change as the family sits down to their holiday meal? Or will that red-blinking Blackberry be right next to the wine glass?
Will your conversations be with others in the room? In the social network analysis map below the family members all gathered in the same space. Dark red links show who is talking to whom F2F via voice.
Or will your family look like the cartoon above? In the same room, but not necessarily with each other? Each off in their own world? Grey nodes are friends and acquaintances accessible via social media. Blue links show who is interacting with whom via text.
Maybe the outside can be connected to the inside... diversifying the conversation? Interesting items from the periphery are brought into the core conversation.
Think about the digital technology in your family this holiday season... where does it enrich and where does it exclude? How do you get it to include and invigorate? | |
| | 2009-11-30 | | 
Recently, the White House revealed who has visited with members of the Obama Administration and when and how long that occurred.
Above is a network map of the who visited with whom in the White House: Visitor --> Visited. The larger the node, the more visitors received. POTUS is short for President of the United States. The links show only the smaller meetings of less than 1 dozen people in attendance. Our assumption is that you have to be more important to be invited to a small, focused meeting than to a large general gathering. Small meetings tend to reveal personal or business relationships. As we now know, even fakesters can sneak into large social affairs.
There is more data with more connections to be mapped in the White House data, but this map shows what is going on in the thick of things.
Too bad previous administrations did not have the cojones to provide the voting public a peek into the workings of government. Glad to see data transparency on the march!
A more detailed view of all of the players...
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| | 2009-11-22 | | One of the basic building blocks of weaving networks is "closing of triangles". A triangle exists between three people in a social network. An "open triangle" is where there is an opportunity to introduce two people, who do not know each other yet, by a third person who knows them both. A "closed triangle" is where all three people now know each other.
Here we see our friend and colleague Ed Morrison, of iOpen, connected to two of his clients -- the economic development folks in both Lexington, KY and Oklahoma City, OK. He knows each of these groups, but they do not know each other. Much could be learned if both of these groups shared their economic development experiences with each other -- innovation happens at the intersections.
But you can't introduce groups to groups, or organizations to organizations -- it works better by introducing people to people. So, Ed picked two leaders from each group to close the triangle. He picked Cynthia Reid at the Oklahoma City Chamber of Commerce[OKC] and Lynda Brabowski of Commerce Lexington[CLX]. This triangle is illustrated below.
When Lynda expressed a desire to Ed for CLX to visit another region that they could learn from, Ed immediately knew the answer -- visit OKC, who previously had faced similar issues and handled them very well. Ed, also knew which introduction to make -- a network weaver needs to know WHOM to connect by knowing the people, the groups, and the dynamics involved in the connections that are being made. The closed triangle -- after Ed's introduction -- is shown below.
This was not the end of this weaving opportunity. Ed accompanied the CLX folks on their visit with OKC. During the trip he closed a few more triangles. Ed introduced the CLX group to two of the key architects of the economic blossoming in Oklahoma City, Ron Norrick -- the former mayor that started the effort, and Burns Hargis a key OKC board member. Those closed triangles are below.
The cool thing about closing triangles is that anyone can do it, and you do not need anyone's permission to do it! Close triangles around you wherever and whenever you see an opportunity. You and your community will benefit.
Just do it!
The above was taken from a June 23, 2006 post of mine on the Network Weaving blog. The original thinking on Network Weaving was created by June Holley and I in this 2002 white paper. Enjoy! | |
| | 2009-11-12 | | Inspired by my favorite Talking Heads song: "Once in a Lifetime".
We often wonder "how did I get here?" when we look around and reflect on our personal networks. Where did all these connections come from? Did I do all this? Who helped weave my network? What can I do with these connections? Where can I add more?
I will go through key growth stages of a network that evolved this past decade. Many of the connections have already resulted in creative collaborations. Other connections are just bearing fruit now. Networks are like that -- a new connection does not always bear instant fruit, sometimes the growing season for some links is very long. Yet at the end, the fact that the link is already established, an opportunity is spotted and acted upon using the resources that the link provides.
Many years ago the network looked like this. Two people are connected if they interact with each other as friends and/or colleagues. ONet represents a now defunct on-line group: The Omidyar Network. This was a gathering place to help people discover how they can make a difference.
People on ONet got to know each other from their on-line activity and Jerry introduced Tom to Valdis -- he closed the triangle amongst himself, Tom and Valdis.
Next, Tom introduced Jean to Valdis at a seminar he organized in Boston. Soon after that, Steve reached out to June after doing a web search on "network weaving."
In the next phase, June introduced Steve to Valdis to work on network mapping, and Valdis introduced June to Tom to speak at his next seminar in Europe. Notice as people start "closing triangles" via introductions, the original meeting place for a portion of the group -- ONet -- starts getting pushed to the periphery.
Next, Valdis introduces June to Jean to share similar interests and goals, and after working with Valdis on network maps Steve introduces Daniel, who is also interested in network mapping, to Valdis.
Finally, Jean meets Jerry at another event and the network as it stands today is now in place.
When we make introductions, and close triangles, we are not doing it to merely create new connections. Network weavers usually have a goal in mind when connecting two new people -- a project, a mentorship, a future collaboration. The links between Daniel, Jean, and Valdis were in place several years ago but only this year did they all collaborate around a common project. Jean and Valdis were working on thrivable networks and Daniel was organizing a conference around building networks to help inner-city kids -- all three were going to be in Chicago the same week. After a few emails it was agreed, Jean and Valdis would do a workshop on building thrivable networks @ Daniel's Tutor/Mentor Conference.
So, networks are built in many ways. First, by being in the same physical or virtual space, and second by active network weavers who make strategic introductions for the benefit of those they connect and for the benefit of the entire network. Networks are also activated in many ways. Sometimes by the initial introduction and connection to an immediate need, and other times, existing links need a little nudge to activate -- like an obvious opportunity. Our themes in the workshop will be:
• Know the Net - map the existing connections of your community/ecosystem
• Knit the Net - weave and support new connections, build a thriving network
• Nudge the Net - activate the network toward self-organization and action
Register here online and join us in Chicago on November 20th!
How did we get here?
Letting the days go by...
Many years of knowing, knitting and nudging.
Same as it ever was... Same as it ever was...
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| | 2009-10-05 | | There are many theories on why Chicago lost the right to host the 2016 Olympics. Some blame the International Olympic Committee and its anti-US bias, others blame the US Olympic Committee and its ineptitude, still others claim it is the "security theatre" at U.S. airports. Every one is looking for a single reason for failure, and most are looking for external entities and events to blame.
The list of names on the the Chicago 2016 Olympic Committee is very impressive -- intelligent people from important organizations. But as we have seen before, super stars do not necessarily make a super team. Chemistry is key to victory. Not only did Chicago have an all-star committee, they brought in other local Chicago stars, like Oprah, President and Michele Obama, et. al. to add their appeal to the effort. Yet, the Chicago 2016 Committee did not get the job done. Chicago was the first city eliminated in the rounds of voting. Was there no Chemistry in the Committee?
To gain insight into the group's chemistry I did a social network analysis looking for internal patterns of cooperation or competition. Is this group set up to win? The smart folks over at LittleSis.org have provided a relationship analysis around the Chicago 2016 Committee. They have gathered data on organizational memberships and interlocks amongst the committee as well as data on their donations. This is enough information for a two-mode [people to organizations] network analysis. I took the two-mode data and converted it to one-mode [people to people]. Links were formed based on the interlocks between each possible pair -- the more two people share organizational memberships and targets of donation the stronger their tie.
The strongest ties amongst Chicago 2016 Olympic Committee members is shown below -- these folks shared many organizational memberships and donated to many of the same individuals and groups. Notice two distinct clusters have formed.
Next we lower the bar for what a link is, and allow in more links. We see each cluster grow, in size and connectivity, but the two clusters do not connect.
Finally, we allow in even more ties and get a connection across cliques. Samuel Zell and Michael Sacks are the boundary spanners that connect the two cliques together. Doing a Google search we see that they are also connected via Helen Zell, Samuel's wife. Helen and Michael are both directors on the After School Matters board.
Our choices reveal who we are. The choices of the committee reveal that they may be two different groups with different interests, values, and approaches. Can they work together? Maybe this internal divide was another factor that contributed to the failed hosting bid?
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| | 2009-09-30 | | 
We continue our mapping of the social graph around the health care reform process with this map of the the six key senators [Gang of Six] in the debate and the cocoon of lobbyists they are embedded in. An interactive network map along with more information is available over at orgnet.com.
Thanks to opensecrets.org and the Center for Responsive Politics for the lobbying data!
Enjoy! | |
| | 2009-09-28 | | 
Health Care Reform continues to limp along in our nation's Capital. There are many voices and many opinions. Which ones will win out? The citizens may not be heard. The politicians working on the problem are embedded in a network of lobbyists who have as their clients various health care and insurance firms. [Click on the social network map for an expanded view].
Max Baucus is often viewed as the key node in the health care debate. Many firms are trying to access and influence Max. Max is the magenta-colored node in the middle of the network map. The lobbyists are the green nodes. Their clients [those who want to influence Max] are the blue nodes along the edges. The clients [blue nodes] who have hired multiple lobbyists get pulled in from the edge and toward the multiple lobbyists [green nodes].
Some sources are reporting that lobbyists are writing pieces of the proposed bill. Somehow I don't remember the chapter on lobbying in my American Government class -- must have been sick that week. [Can't afford to get sick now!]
We are looking at more lobbying data from LittleSis.org and OpenSecrets.org -- we thank them for their public data bases! I also want to thank Jean Russell for assisting with the research and for the design of the map above. Next up, an interactive map of all of the key players in Lobbying "Lollapalooza" 2009. | |
| | 2009-09-24 | | 
The FBI and the Department of Justice have now released three indictments in the ongoing investigation of corruption in the Cuyahoga County Government Offices in NE Ohio. I have written previously on this project called Operation Air Ball.
One of my researchers, Andrejs Van Nostran, and I took the three indictments and mined them for network data. We wanted to do a social network analysis of this complex and unfolding story.
People and organizations were the nodes. Projects, events, relationships and money flows were the links. The network map above shows just the key people in the three indictments. We hid the organization nodes for this view. Links show people that had business ties to each other. Most of the business ties shown had both legal and illegal transactions flowing across them, a few links carried only illegal transactions. Notice the two most central players have not yet been named by the Federal Prosecutor. They are referred to as PO 1 and PO 2 -- Public Official 1 and Public Official 2. More indictments are expected. As we get them we will add the data to our map, and reveal the identities behind the codes, as they are made explicit.
The Cleveland Plain Dealer has done a good job on reporting the corruption probe. Their analysis of the identity of PO 1 and PO 2 is available. The Cleveland public radio station -- WCPN 90.3 FM, ideastream -- had two recent programs on the corruption scandal with local experts and politicians. | |
| | 2009-09-21 | | 
Remember...
The technology that gives You the power to organize,
also gives Them the power to watch.
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| | 2009-09-13 | | 
A little experiment in crowdsourcing...
We are trying to put a new spin on our social network analysis products and services -- expanding our customer base which is now mostly other consultants. We got the above from our new ad agency. What do you think? Should we fire them or increase their fees?
Worst case, we will use this ad every April 1st.
Vote in the Comments section below. | |
| | 2009-08-24 | | First of a series of chats on leading edge ideas in regional economic development with Ed Morrison and Valdis Krebs.
We look at how to find hidden opportunities in business lists. Valdis uses social network analysis and some simple data mining to derive the network of collaboration opportunities below from the list of 350 NE Ohio advanced energy companies above. How did he do it? Watch and listen to this 5 minute screencast!
Next week's chat will focus on Ed's work around ditching organizational charts. | |
| | 2009-08-12 | | People make choices every day -- for themselves and for their organizations.
What to buy? Who to hire? What policy to implement? What stand to take?
The choices we make reveal who we are.
Data is everywhere these days -- often in simple lists. Lists often reveal who chose what or whom. All Internet shoppers know the famous Amazon list -- "people that bought this item also bought these items...". On the surface this appears to be a simple list, but underneath it reveals much about the Amazon customers making choices. Amazon book data can reveal much about the sociology around book purchases, especially political book purchases.
Transparency in government is all the rage these days -- especially in Gov 2.0 circles. Organizations are making all sorts of political and governmental data available to the public. One of the best at doing this is OpenSecrets.org. Recently they provided a list of all of the lobbyists in the health care industry who are busy trying to influence that debate. Although the list itself is useful, there are hidden patterns in the data. The list reveals emergent structures in the health care industry -- it reveals non-obvious connections between the major players.
A map of hidden ties in the pharmaceutical industry is displayed below. The data is from the list of pharmaceutical companies and their lobbyists from OpenSecrets.org. Just like common board members spread similar messages and ideas throughout the corporate and non-profit worlds, do common lobbyists have a similar affect? What does the choice of a lobbyist reveal about the intentions of a corporation?
What is different about this network map is that the links are what we normally consider as nodes -- the links are the lobbying firms that connect their clients into clusters of shared thinking and perspectives. Each group of colored links represent a specific lobbying firm that has been hired by the nodes/clients it connects.
Someone who knows an industry well would be able to spot funny associations in a map like the above:
why are these orgs clustered together? Org X and Y have come out publicly on opposing sides of the issue yet, they use the same advisors, are they really more alike than they pretend to be?
Org Z has always been "no comment" on the issue, yet they are strongly clustered with those who are highly in favor.
Org Q straddles the pro and anti clusters, what does this mean? Are they playing both sides? Are they not sure? Are they having internal pro/anti battles with different divisions choosing different advisors?
Displaying nodes as linking structures is another way to visualize what are called two-mode networks.
An interactive network map of the above is available now! | |
| | 2009-08-06 | | 
As we move into the second hour without Twitter, those of us who have grown to rely on it are wondering what is going on. Some colleagues report an ongoing DOS attack on Twitter this morning [DOS = denial of service]. Appears to be easy to take down single site based services... is Facebook next?
Twitter, Facebook, GMail and all other single site based services play with the Betweenness Paradox -- ultimate power/control when in operation, ultimate fail when not. Single point of failure. Brittleness, not resiliency.
How many points of failure do you see in the diagram above? A point of failure is when one node goes down and disconnects significant parts of the network from each other. More info on Betweenness Centrality in networks.
That giant sucking sound? That's the "trust for Twitter" quickly escaping into outer space. Twitter and cloud computing in general... first it was GMail, now Twitter, what will be "strike three"? | |
| | 2009-07-06 | | The mortgage meltdown was brought on by fraud and corruption at all levels.
At the grassroots in Cleveland, Ohio we see real estate "flippers" who buy bank-owned and other low price property, often at less than $10,000. Then without doing much to improve the properties, and via appraisal voodoo, they turn around and sell the houses for $50,000 - $100,000 to those desperate to get into home ownership. These unsophisticated buyers often end up in foreclosure and the hunt for a new set of suckers starts the process once more.
The blue nodes on the left are the owners of various Slavic Village properties in the early 2000s -- most are banks and other financial institutions. The flippers are the green nodes in the middle. The new home owners are the magenta colored nodes on the right. The flow of sales go left to right -- following the light gray links. A sells to B : A --> B.
From initial sale to foreclosure usually takes anywhere from 12 to 36 months. This process was repeated again and again with blinding speed during the period of 2003 to 2007. Most of the flippers and their collaborators have now been indicted by the Cuyahoga County Prosecutor and will face trial in October 2009.
All data was gathered from public records of real estate sales in the Slavic Village neighborhood in Cleveland and from indictments on the prosecutor's web site. | |
| | 2009-06-14 | | The recent mortgage meltdown had many players in many places. The investment banks on Wall Street needed large amounts of sub-prime loans to package into investment vehicles. To satisfy this need, they found plenty of help in most of America's major cities. Some local banks, brokers and appraisers were more than happy to generate an almost unlimited supply new mortgages. The generals on Wall Street had boots on the ground on Main Street.
One of the bloodiest battles was fought in Cleveland, in the Slavic Village neighborhood. Today the streets of Slavic Village show the scars of the battle -- destroyed homes, destroyed lives and vacant lots. From 2003 to 2007 houses were bought and sold at an alarming rate in this working class neighborhood. Houses were bought cheap and almost immediately sold at multiples of their true worth -- this is commonly called flipping. Most new owners ended up with with sub-prime mortgages that put them on the fast track to foreclosure. A local real estate gang had emerged, and was partnering with mortgage bankers in California. They had the home sales process covered -- seller, broker, appraiser, banker, buyer -- all lined up to feed Wall Street a never ending supply of sub-prime mortgages.
Anthony Brancatelli was the local Cleveland city councilman in Slavic Village. He could not believe what was going on in his neighborhood. He started tracking real estate activity in his neighborhood via a spreadsheet -- the same names and the same companies kept popping up. With the help of public records, soon Brancatelli and colleagues had the details on hundreds of real estate transactions which were compiled in a report by The Slavic Village Vacant and Abandoned Property Task Force.
Brancatelli's spreadsheet looks like this...
The network of sales transactions revealed in the spreadsheet are mapped below. A green line with an arrow shows "who sold to whom": seller --> buyer. The nodes/buyers hi-lited in pink ended up in foreclosure. As you can see, most buyers in these transactions ended up in foreclosure. Nodes in black are organizations, other nodes are individuals. We removed all names from all maps.
Digging deeper into the spreadsheet and into public records, it was revealed who had business ties with whom. The network map below shows a grey link between two nodes if they show a business tie -- working together, owning property together, appear on LLC documents together, etc. The nodes hi-lited in blue where indicted in the first wave in the autumn of 2008. The nodes hi-lited in green were just indicted in 2009. All of the blue and green hi-lited nodes in this network map were big sellers of real estate in the first map [they had many outgoing arrows].
It is easy to see who will be swept up in the next wave of indictments, or who will be on the witness list in the upcoming trials.
Sadly, every major city probably has maps likes this waiting to be revealed. The mortgage meltdown did not just happen on Wall Street. It was a alliance between Wall Street and real estate speculators on Main Street. Cleveland has started rounding up these crooks thanks to efforts of local neighborhood residents and elected officials like Anthony Brancatelli. | |
| | 2009-05-13 | | This morning I appeared on WCPN - 90.3 FM, the Cleveland NPR radio station, on "The Sound of Ideas" with Dan Moulthrop. The program was about searching for a job when you are over 50 years old. Listen to the MP3 here.
When is the best time to plant a tree?
20 years ago.
When is the next best time to plant a tree?
Today!
Chinese Proverb
What is true for trees, is true for networks -- build your network before you need it!
It is best to have been building and expanding your strategic personal network for all of your professional life. Unfortunately, most people don't come to that realization until they are let go from their current job.
Most people have small, dense networks composed mostly of their immediate on-the-job colleagues, friends and family. These networks are the first resource of the newly furloughed employee. Asking around, the job-seeker finds that immediate contacts often do not have much more job information than the job searcher has -- they are all in the same network neighborhood where everyone knows what everyone else knows at about the same time.
Once the job seeker exhausts the obvious job openings that s/he and their immediate contacts are aware of, they become stuck. What to do next? The common advice is send out or post resumes on-line, attend job fairs and start "networking". The first two suggestions get the job seeker onto the overcrowded freeway to the HR office. In today's recession, this route is a clogged artery with little or no movement -- time to get out of this traffic jam and try an alternate path.
The next suggestion -- "networking" -- sounds good, but is often approached wrong. Networking is commonly defined as quickly connecting with many people -- focus on quantity over quality -- sometimes mockingly called schmoozing. Building strategic connections is much different than just "networking" -- you build trusted relationships that bring you information and access that you currently don't have in your small circle of friends and colleagues. Quality trusted ties are like the trees planted many years ago. Quality trusted ties develop when people work on something together -- they don't develop over a handshake at a conference, a quick conversation over coffee or a speed interview at a job fair.
Networking may get you many new business cards, but are these people willing and able to introduce you to the hiring manager [the route around the clogged freeway]? If I just met you at a conference, or you called me out of the blue "to network", am I going to risk my professional reputation to introduce you to my boss or trusted colleague? Probably not. Yet, if you are introduced to me by a trusted friend, colleague or peer then I will listen and we will both benefit. Better yet, if we work on a volunteer project together, I see you "in action" and we bond -- I feel confident in recommending you.
Once you exhaust your inner circle of people who can make introductions, what do you do? Two things: 1) re-activate trusted ties from the past that are now dormant and 2) build new trusted ties via volunteering and part-time work.
Everyone has dormant connections that can be re-activated. Many people are now getting on Facebook and LinkedIn and re-connecting with former colleagues and college chums. Do so, but be careful. Do not re-connect with a transaction in your back pocket -- "Hi, nice to to hear from you again, do you know of any jobs?" I have a former colleague who re-connects with me every 5-7 years -- but he does so only when he is in the job market! He expects a connection, but is not eager to offer one of his own. Needless to say, he does not get far. Once you re-connect with one or two trusted ties ask them if they have remained in contact with others from your old social circle. You want to be expanding/re-activating your current network out 1 and 2 steps -- your contacts and hopefully their contacts. This will help you reach people with information about jobs you have not heard of yet.
A friend of mine, a job-seeking HR executive in Chicago, has done an amazing job of building her strategic network in the last year. She has dozens of new connections she built in prolonged interactions. She has volunteered on several projects in her field and also sits on several advisory boards. She has helped organize several local HR conferences and meetings and therefore has face-to-face work experience with a totally new cadre of colleagues. She now has a handful of strong trusted ties that she did not have last year. They have seen her in action, they like her work, they trust her, they give out their personal cell phone numbers to be references for her! Like a tree establishing a root system, it has taken her a while to grow this strategic network, but it is now vibrant and ready to provide her with many opportunities.
In addition to job offers and business opportunities, a wide strategic network also provides other benefits. Health and happiness! When I talked to my HR colleague in Chicago this week, she did not come across as a person that had been out of work for a while. She was very upbeat and full of energy -- which comes across in an interview! She was very positive because her network was growing and bringing results. She was meeting new people, sharpening her skills and learning new behaviors -- she was very positive about her future. More and more research is pointing to the health benefits of building social networks. Employers like to hire positive, high energy people.
Out of work? Form new ties -- not casual connections, but collaborative caring connections, built up over time. They will bring you a variety of rewards. Also, when you start your new job, do not stop your network building. Keep expanding your network, make new connections in new places. Keep growing that tree, you planted, with wide-reaching branches.
"Only connect!
Live in fragments no longer."
Howard's End
E. M. Forster
UPDATE: The friend mentioned above DID get the job with glowing references from the strong ties she had formed working on various local HR conferences and events in Chicago. She built a real network and it paid off! | |
| | 2009-04-27 | | The Swine Flu has been in the news during April 2009. Initially it spread amongst pigs, and then made the jump to humans that came in contact with the contagious pigs. From the early data, this appears to have happened in Mexico.
We use the social network analysis software, InFlow, to illustrate the spread of the contagion. Below is a social network map of the connections between employees in a large organization [data is real, names have been hidden]. A grey line indicates face-to-face [F2F] contact between two employees.
Now, one of the employees visits relatives in Mexico, who live on a farm and have pigs. The swine flu virus infects this employee, whose immune system has not been previously exposed to Swine Influenza A -- H1N1. The link of that infection is mapped below. The contagious pig is represented by the pink node. The disease transmission vector is represented by the green link.
If there is no human-to-human transmission of the swine flu virus then the disease stops here. One person sick, no contacts infected. Unfortunately, the CDC now acknowledges that transmission of this virus from person-to-person is possible -- one patient visited Mexico, came home sick, and passed the virus to another household contact who had not accompanied him on the trip.
Now the contact network at this workplace becomes a disease transmission network, as is common with airborne contagions. Also, this workplace network overlaps with other networks -- each employee goes home to a family/neighborhood/social network which also include F2F contact. As the virus spreads in the workplace, it will also be transmitted to other networks connected to the workplace network by common members.
The sick employee may still come to work initially and via coughing and sneezing start to spread the virus to others in the same space/location. The first wave of disease transmission is mapped below. We now show only the disease transmission links in green and hi-lite each node [yellow] that has been infected by the virus. For this simple example we are assuming a 100% infection rate [higher than usual] -- if someone coughs or sneezes in your presence, you will catch the flu after the normal incubation period, typically 1 to 3 days.
The map below shows how the virus spreads via person-to-person contact. Even if the original infected individuals are no longer at work, the density of the network, with multiple paths [and F2F contacts] between individuals, ensures that many employees will be exposed.
The virus spreads because infectious individuals constantly come in F2F contact with those who have not been exposed. Because of local density in a typical human network, a healthy person can be exposed to multiple sick individuals, thus increasing the odds of transmission. We can watch the contagion spread to the rest of the population, but in most cases some action would be taken once a significant portion of a local population becomes ill. Either government authorities or the employer will step in to isolate the sick from the healthy and adjust work locations.
Ironically, the network structure that enhances the transmission of good contagions -- such as ideas, solutions, and knowledge, can also transmit bad contagions such as disease and fear. When the network is transporting ideas and knowledge we want to decrease distance between individuals. When the network starts to transmit disease we want to increase distance and fragmentation in the network to isolate the virus and slow/stop the spread -- natural work groups need to be identified [via SNA/ONA] and physically separated [no F2F contact]. Another solution is for many people to remain at home [whenever possible] and connect over the Internet [i.e. Skype, GoToMeeting, WebEx, etc.] to coordinate and collaborate and get their work done.
For a deeper dive on social network analysis and contact tracing applied to public health issues see this CDC paper.
Be careful how you connect in the next few months! | |
| | 2009-03-09 | | 
The Cuyahoga County corruption scandal in NE Ohio continues forward with tentacles reaching into various suburbs surrounding Cleveland. The FBI has named their project "Operation Air Ball" -- no one quite knows why this basketball term, for a very bad shot, was chosen.
A social network analysis map of the organizations and businesses that have been searched by the FBI/IRS team is shown above. Two organizations are connected by a green link if they have done direct business with each other according to the FBI/IRS subpoenas. If a person connects two organizations, by being associated with each one, that relationship is not shown. Later, we will have a map of individuals and organizations with all of the interconnections.
The data to create the map was gathered from reporting on the scandal by The Cleveland Plain Dealer and WKYC News. No guilt is implied, or assumed, via appearance on the map.
As more data becomes available we will add to this map and also create other maps so that interested parties can track this complex case as it evolves. A citizen's effort called Map the Mess is also tracking this investigation, and "connecting the dots" in the news stories.
For more insight into how these maps are done, read how we first mapped and analyzed the 9-11 hijackers.
Update: network map current as of 04/01/09 | |
| | 2009-02-19 | | This week's PBS Frontline show was fascinating. They discussed the financial meltdown and how it was exacerbated by the massive intra-connectivity of the banking system.
Frontline focused on the trade-offs between "moral hazard" -- punishing the bad guys for bad behavior, and "systemic risk" -- allowing the bad guys to fail and effect the rest of the interconnected system. The main contagion under discussion were the investments created by Bear Stearns, Lehman Brothers -- packaging up sub-prime and other mortgages into mortgage-backed securities which were then sold to other banks and investors.
Using social network analysis, let's take a look at how a contagion spreads through a connected system. Below, is a small-world network that models what the interconnected banking ecosystem may look like. The red nodes represent banks, while the grey links represent who may be doing business with whom. The arrows represent the flow of assets [who pays whom].
We will look at three nodes/banks and the effect they have on the rest of the system. The nodes/banks are labeled: A, B, and C. We chose to examine these nodes because they are in different parts of the network. A is in the thick of things, in the dense center cluster. B is on the periphery of that dense cluster, and C is very lightly connected node at the very edge of the system.
First we look at the best connected node, A -- deep in the dense part of the network. Suppose Bank A is selling toxic assets it has packaged as investments. We ask our social network analysis software to show the immediate connections of node A -- it's direct business partners -- those who are buying the toxic assets. The nodes that show up in yellow, with the red border, below are one step away from the bank selling toxic assets -- they do business directly with the infected bank. We now see that a portion of the banking network is infected -- yellow nodes are infected, solid red nodes are not.
Next we move out two steps from the infectious bank -- the yellow nodes now show both the direct and indirect business partners of the infected bank -- we notice how quickly the contagion spreads as the mortgage-backed securities are packaged and re-packaged and sold and re-sold. Now we have more yellow/infected nodes than red/non-infected nodes -- the system has tipped.
Now we move out three steps -- 3 degrees of separation -- from the infectious bank. We see that just about the whole ecosystem is now infected with some level of toxic assets. With all of re-packaging and re-selling of the securities no one really knows how much everyone is infected, but every yellow node is infected to some degree.
As we expected, the well connected node in the thick of things spread the toxicity quickly to the rest of the system. Do the other nodes also have the ability to poison the well from where they sit?
Next, we look at the bank on the periphery of the dense cluster -- node B, on the left side of the network. How fast will it's contagion spread? At one step, the spread is mostly local.
At two steps there is an quick distribution of the contagion, including our original highly connected node in the dense middle. Once the highly connected node is infected we know the rest of the story from above.
At three steps away from B a majority of the network is infected. We see that a bank on the periphery can also be devastating to any system it is embedded in.
Finally we look at the bank that is barely connected to the system, node C. What effect will it have if it sells toxic assets into the inter-bank network? The initial transactions only infect a few nodes that are also on the edges of the network.
At two steps, the contagion has touched the dense central cluster.
At three steps from Bank C, a majority of the network is infected by the toxic asset. The "outsider" was able to infect the rest of the network -- it happened more slowly, but as investments were re-packaged and deals were made the contagion moved forward.
There is good news and bad news about slow-moving contagions. The good news is they can be spotted and stopped before they do too much damage. The bad news is they are often ignored early on, because they have not done enough damage to pop up on anyone's radar -- so they spread stealthily.
The key decisions the prior administration needed to make was to decide whether to follow the moral hazard argument or the systemic risk argument. With Bear Stearns they chose systemic risk -- they felt Bear Stearns was too connected to allow to fail. With Lehman Brothers they chose moral hazard -- they did not think Lehman was connected enough to cause systemic risk. They were wrong. As we saw above, a connected system is very vulnerable to any node feeding contagions into it.
Now that the banking system is infected with toxic assets, none of the banks want to trade with each other. They don't know what they are getting from their trading partners. No one trusts each other. The financial meltdown has led to a freeze-up of trust and activity. It is like all of the old links went away and you have disconnected nodes staring at each other... too scared to move. | |
| | 2009-02-16 | | 
Escape the snowy North and come learn something new in sunny San Diego!
Valdis Krebs will be presenting a 1/2 day workshop on practical applications of social network analysis [SNA] at the upcoming Sunbelt Social Network Conference sponsored by INSNA -- International Network for Social Network Analysis.
This workshop will be on the morning of March 11th at the Bahia Hotel @ Mission Beach in San Diego, California. The Sunbelt conference will run until Sunday, March 15th in the same Hotel.
The hands-on workshop will feature a quick overview of social network analysis as applied to organizations and communities. You will get a chance to use social network analysis software to explore a simple data set. Whether you are a consultant, analyst, manager, activist, student, professor, or journalist you will learn how to apply this useful methodology with clients and customers.
Sunbelt is a mostly academic conference but is attended by more and more practitioners every year. Valdis and Erin Kenneally [both practitioners] will give a presentation during the regular conference on Analyzing Networks of Corruption.
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| | 2009-02-06 | | Yesterday a list of the victims of the alleged Bernie Madoff ponzi scheme were released -- 162 pages of 4 point type listing thousands of names and addresses.
What was not released were the social networks that connected these people to Mr. Madoff -- who made the introduction, who closed the triangle to turpitude? This, after all, was a crime based on inclusion and exclusion in select social networks. No one wanted to be excluded from this great deal with one of the wizards of Wall Street -- yearly double digit returns, guaranteed. They used their connections to gain inclusion into the money flow network. And for a while, that inclusion felt good.
Madoff apparently worked with multiple "feeders" into his investment system. A wide network of individuals and funds were set up to pass money to Madoff. Most investors in these funds did not realize all of their money was going to just one place -- a place that is turning out to be one big hole. Inclusion seemed to be the prize, but it ended up being the trap.
Below is an attempt to keep up with this rapidly developing story and map the investors into Madoff's funds. Every day new players and their connections are revealed. The thousands of victims on the 162 page list probably trusted an intermediary institution or feeder fund with their money.
If you would like an interactive map of the above, you can find one on my orgnet.com web site. On the interactive network map you can double-click on any node in the network and get the latest news of that node's involvement with Madoff.
All data for these maps was gathered from news stories and court documents found on major media web sites. | |
| | 2009-01-29 | | Cleveland and NE Ohio have a corruption scandal brewing. The local newspaper, The Plain Dealer, is reporting the corruption story while at the same time it is in the process of downsizing. The PD has done a very good job of reporting the the ongoing investigation -- a team of almost a dozen reporters have been tasked to track the developing story.
Below is an early effort to map the corruption mess by a group of citizen journalists. This map reveals a process we see often in today's corruption cases -- the indirect quid pro quo. An indirect quid pro quo moves the influencer away from the final target of influence, via long paths of multiple intermediaries.
The indirect quid pro quo results in plausible deniability for the influencer because there is no direct connection to the target of influence. The red arrows show both flow of benefit and flow of influence. The data to create this map is taken directly from this published Plain Dealer article. | |
| | 2009-01-22 | | 
We often talk about closing triangles and making introductions as a way to build resilient networks through network weaving.
Here is an example of closing triangles via Twitter. Track the triangle closing process from my Twitter log above -- oldest tweet on bottom. The blank space in the tweet log was from another person I am following that had nothing to do with the closing of the triangle. Starting at the bottom of the above pic...
1) I follow John Robb on Twitter and he tweets about a book he is reading
2) I re-tweet his post so that those who follow me on Twitter can learn about the book.
3) June, who is following me, sees the re-tweet and aims her tweet at John [using @johnrobb] stating she has read the book and found it useful.
Two people that I have known, but did not know each other, can now be connected. They connect by seeing [via Twitter] their mutual interest in a book and in an idea. Maybe June and John can now talk about "resilient communities" and their experiences with them?
Since June and John have some similar interests, yet come from different communities and contexts, we have another example of..."Connect on your similarities and profit from your differences"
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