By the same token,
though, another argument would be you'd like to be number 11.
Why?
Number 11 is right next to number 9.
9's spending a lot of effort to get all this information.
11 can get it all from 9.
So in some ways, 11's in a great situation because they don't have to work as hard
for the information but by the same token, they're totally indebted to 9 and
9 can hold them up if they're not going to be fully cooperative.
So with these kinds of ideas in mind, and
this focusing on numbers 9 and number 6 and this volume of information flow.
Now we want to get a little bit more careful and
thinking about which sorts of network positions are most effective.
To do that I'm going to talk about three
different characteristics of high performing networks and
we'll take each them in turn, Diversity, Brokerage and then Trust.
So, this will help us start to sort out
between different sorts of network patterns and relationships.
Let's start by talking about diversity in networks.
Here, I'm portraying a very simple comparison between two people with
the same number of contacts.
1 and 2, in these simple network pictures, each have exactly five contacts.
And I've set it up this way so that we can assume that they're both doing the exact
same amount of work to maintain these contacts.
And I'm talking about real contacts here.
I'm not talking about the people who you can tabulate because you've met them once
at a conference and your gigantic list of LinkedIn contacts or
Facebook contacts or Tweeter contacts and the like.
But instead, these are the people who you really have relationship with.
Who you're spending effort to let them know about the information that's of
value to them.
You're inviting them for coffee, you're staying in touch with them and the like.
So, real contacts.
One and two both have the same number of contacts, so you would assume
all other things equal that they'd get the same amount of information.
Look what happens when we introduce some colors to represent the type of knowledge
that each of your contacts are bringing to the network.
Here we see that number two is getting the same information over and
over again from all the different contacts whereas actor number one
is getting not only purple information, but red, and blue, and green as well.
So right now I'm just using abstract colors to represent different sorts of
knowledge, but this idea of having diverse knowledge inputs coming to you
through your network connections is going to be really important.
Let's make this more concrete.
One of the ways to think about those different colors might be that,
if you're working in an organization currently,
at a particular function, are all of your contacts in the same function as you or
from different functional areas in the organization?
That is, if you're in marketing, are all the people who are providing you with
the information you need to get your job done, are they also in marketing?
Or are they spread more generally through production and R&D and
other parts of your organization?
That's knowledge diversity.
Another way to think about it would be, is everyone in your professional specialty.
Are you a doctor, a lawyer?
Are all of your contacts also doctors or lawyers, or are you looking at a much
broader set of people who might use your services, which would give you again
different knowledge and different inputs that could be really helpful.
And let me be clear, when I use the term diversity, much attention these days is
rightly on demographic diversity, and while your networks may or may not have
demographic diversity, that may or may not be correlated with knowledge diversity.
And here because we're focusing on the knowledge inputs that your network is
creating for you, we're really interested in the knowledge that people have,
regardless of their demographic characteristics.
Because it's the mix of different kinds of knowledge that really is the engine,
is the source of innovation and
that's work from economics that goes all the way back to Joseph Schumpeter.