The document discusses running a large Fortune 500 company with viral marketing. It summarizes that the author studied innovation diffusion, social networks, and psychology. They created a selective amplification network model that can model and predict the spread of social phenomena through global networks. The model segments networks into phrase, concept, and theme networks. It was found that the first "hop" or level of connections directly connected to the source is the most critical for diffusion and viral phenomena to spread.

1. *
“Running an Agile Fortune 500 Company”
Aditya Yadav, aditya.yadav@gmail.com
in.linkedin.com/in/adityayadav76

2. * A Typical Global Company
* Fortune 500/1000
* 200 Divisions
* 40 Countries
* 25000 Employees
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3. *
@ Acme Inc.

4. * Original Question “How can we create and
exploit Viral Phenomenon, nobody seems to get
it, not even Google, Microsoft, PARC, Yahoo, no
one (as yet)”
* The Correct Question - “Its not impossible,
allow me to explain how to go about doing this
right.”
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And The Philosophy Behind The Answer

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Innovation Diffusion (1962)
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The origins of the diffusion of innovations theory
are varied and span multiple disciplines. There are
four main elements that influence the spread of a
new idea: the innovation, communication
channels, time, and a social system. This process
relies heavily on human capital. The innovation
must be widely adopted in order to self-sustain.
Within the rate of adoption, there is a point at
which an innovation reaches critical mass.
Diffusion of Innovations is a theory that seeks to
explain how, why, and at what rate new ideas and
technology spread through cultures. Diffusion is
the process by which an innovation is
communicated through certain channels over time
among the members of a social system.
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7. * We studied Innovation, Diffusion in General,
Social Networks, Sociology, Psychology…
* And came up with a model that allows us to
model and predict spreading of Social
Phenomenon through Global Networks…
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We created a model of Viral Phenomenon using
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Structural elements,
Logic Elements and
Then we overlayed it with the Functional overlay of Selective Amplification.
And then segmented it into
1.
2.
3.
Phrase Networks
Concept Networks and
Theme Networks
And voila we created the Selective Amplification Network Model which allows us not
only to study Viral and Social phenomenon but also Predict Viral Phenomenon
P.S. We had to tag the network nodes into Active and Passive categories
P.S. And we used historical data to Train the Node Thresholds
Selective Amplification is probably the best Metaphor/Model for Diffusion in Networks…
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If we divide a social graph in perimeters or levels using the number of hops from the
source, which perimeter (or #hops/level) would be the most critical for diffusion, viral
phenomenon, etc.?
So obviously there is no correct theoretical/formulaic answer here, so the only way
was Empirical/Real-life-data...
It turns out that the most important level/perimeter is the first Hop, yup! thats right
the people you are directly connected to are the most important for any thing
originating from you...
This has a lot of implications in marketing, collaboration, communication, sociology,
economics, reputation, success, career graph, popularity, stress, peace of mind,
habits, culture...
The most Successful people, the most Popular/Influential people, successful Marketing
Campaigns (or whatever that means!!! !$##@$#@ *wink*) have the strongest and most
supportive first level Inner Circles, or the One Hop Perimeter
P.S. The criticality was determined by studying the impact on a desired output in the
entire network by changing a variable by a small delta in each of the levels/perimeters
Note: Selective Amplification at any node is not related to the #Hops so it would be
naïve to assume that a closed form solution is possible and that it would trivially be
“#Hops = 1 is most critical”
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10. Aditya!!!
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