What Kevin Bacon Teaches Us About Measuring Networks

October 17, 2017 by Stacey Barr

The Bacon number is a measure of closeness to Kevin Bacon. Believe it or not, it has some useful applications in business.

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The Bacon number is the number of degrees of separation that an actor is from Kevin Bacon. So, Kevin Bacon has a Bacon number of 0. Any actor who has worked directly with Kevin Bacon has a Bacon number of 1. Any actor who has worked with an actor with a Bacon number of 1, but not directly with Kevin Bacon himself, will have a Bacon number of 2. And so on.

The basic formula for calculating an actor’s Bacon number is this:

“If the lowest Bacon number of any actor with whom X has appeared in any movie is N, X’s Bacon number is N+1.”

However it started, and why ever it persists, the Bacon number is an interesting example of how we can measure closeness. Because so much happens through connections and relationships in business, closeness can be relevant in a multitude of business contexts:

  • Connecting leaders to their employees, to help get more workforce engagement
  • Growing networks, like customers or markets or employees
  • Breaking down silos, and increasing collaboration across structural boundaries

To construct a measure of closeness, let’s call it a Closeness Number, there are three basic things we need to do:

  1. Figure out what our ‘Bacon’ equivalent is.
  2. Figure out what our ‘actors’ equivalent is.
  3. Figure out what our ‘worked directly with’ equivalent is.

Figure out what our ‘Bacon’ equivalent is.

Instead of Kevin Bacon, who or what do we want to be closer to? For example:

  • more closely connected with the CEO in our organisation
  • more closely connected with ideal clients
  • more closely connected across organisational boundaries (silos)

Figure out what our ‘actors’ equivalent is.

Instead of fellow actors, who or what needs to be more separate or close? For example:

  • each employee is more closely connected to the CEO (or any other specific leader) of our organisation
  • sales staff are more closely connected with ideal clients
  • managers are more closely connected with managers who report to a different leader to them

Figure out what our ‘worked directly with’ equivalent is.

Instead of working directly with Kevin Bacon, what is our condition for being close? For example:

  • how close an employee is to the CEO is based on having worked with the CEO, in person, in any way
  • how close a sales person is to an ideal client is based on the number of introductions required from people in their extended network to be introduced to the ideal client
  • how close a manager is to another manager reporting to a different leader to them is based on having co-led a cross-functional project

Figure out our rule for the Closeness Number.

We want to be really clear how will will count the degrees of separateness or closeness. For example:

  • If the CEO’s name is Vince, and if the lowest Vince number of any other employee with whom employee X has worked with is N, employee X’s Vince number is N+1. We’d want the average of our employees’ Vince numbers to be as close to 1 as possible.
  • If an ideal client is denoted as IC, and if the lowest IC number of any other person with whom sales person X is connected to is N, sales person X’s IC number is N+1. We’d want the average of our sales person’s IC numbers to be as close to 1 as possible. LinkedIn is a good example of how this could be monitored.
  • If a manager who has co-led a cross-functional project with another manager is denoted as a Silo Buster, and if the lowest Silo Buster number of any other manager with whom manager X is connected is N, manager X’s Silo Buster number is N+1. We want all managers to have a Silo Buster number of 0.

Then we can construct a measure for our Closeness Number.

The Closeness Number is calculated for each employee, each sales person, and in the case of the Bacon number, each actor. But that means we will have a lot of Closeness Numbers.

A measure can help us combine them so we can see the collective closeness and monitor changes in that over time. For the examples above, good measures could be:

  • CEO Closeness: The average of the Vince numbers, over all employees.
  • Ideal Client Closeness: The average of all the IC numbers, over all sales people.
  • Silo Buster Closeness: The average of all the Silo Buster numbers, over all managers.

Networks, connections and relationships are important today in business, more than ever before. And we have more and more tools to help us measure, monitor and improve them. As a rule, I advise we only design a measure after we’ve got a measurable goal. But sometimes it’s worthwhile exploring a new idea, so it’s ready to use when it’s needed.

Networks are how things happen in business. Why not measure your network, taking inspiration from the Bacon number?
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DISCUSSION:

What are your ideas for where a measure of closeness, in a network of any kind, might be helpful in business?

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