The Law of Few - Data Tipping Point part 2
A few types of people (Connectors, Mavens and Salespeople) have a disproportionate impact on change, engage them and you can create a movement.
This is part two of a series on data tipping points - the point at which a data transformation becomes self-sustaining, change becomes irreversible, and a data-driven organisation is inevitable. For an intro on data tipping points and why they are important, read part one here.
The first thing to understand about change and tipping points is that some people have a disproportionate effect.
Malcolm Gladwell (author of “The Tipping Point”) refers to this as “The Law of the Few” and introduces the idea with the story of Peter Revere’s famous midnight ride in 1775. I say famous. It is a story from the American Revolution that every American schoolchild knows, but one that was new to me (unsurprisingly, a British education doesn’t teach you much about British defeats).
Paul Revere was a silversmith in Boston, and on the afternoon of the 18th of April, he began to hear rumours that the British were preparing to march on Lexington, arrest the colonial leaders, John Hancock and Samuel Adams, and seize local stores of guns and ammunition.
Revere and his friend Warren decided they needed to warn all the surrounding communities of the impending action and inspire local militia to rise up and stop the Brits. Crucially to Gladwell’s explanation of Tipping Points, Revere wasn’t the only person that came to the same conclusion and went out with the same mission. Another revolutionary, William Dawes, set out on the same day and with the same objective, but the outcomes differed completely.
Revere’s message went viral. In every town he passed through, he knocked on doors, created a sense of urgency, and before long, the church bells started ringing in alarm, and towns sent out riders of their own to spread the news. By the time the British started their march, a substantial militia had gathered, took them by surprise and started the American Revolution.
We know the details of this story down to the time that Revere arrived in different towns, thanks to logs that were made. By contrast, historians struggled to piece together Warren’s journey as his identical message didn’t go viral, riders weren’t set out, and few people from the towns he visited joined the militia to meet the British.
Gladwell argues that there are a few people, like Revere, that are responsible for social epidemics, and he groups them into three types; Connectors, Mavens and Salespeople. If you want the transformation you are working on to go viral, it is worth understanding these people and identifying them in your organisation.
Based on Gladwell’s analysis Revere was both a Connector and a Salesperson, whereas Warren had none of the characteristics key to starting a social epidemic. Had Revere lacked these characteristics, perhaps the British march on Lexington would have succeeded.
So who are Connectors, Mavens and Salesmen, and how do you find them?
Connectors and Data Transformations
Connectors are, rather obviously, the people who connect other people and groups. What is less obvious is how much larger their networks are than the average person.
The six degrees of Kevin Bacon game is a good illustration of this. The idea is that you should be able to from Kevin Bacon to anyone else in Hollywood in 6 steps. Here a step is jumping from one person to someone else who worked on the same film as them.
Like many things, this problem has been looked at algorithmically, and the most connected Hollywood star is actually Samuel L Jackson, who is, on average, 2.89 steps removed from other stars. Kevin Bacon is not even in the top 100! See the Oracle of Bacon for the full list.
Stars tend to score highly on this connectedness ranking not only because they have been in a lot of films but because they have been in a wide range of films and therefore worked with a wide range of people.
This is part of what makes connectors. They know a lot of people from a wide range of groups. Beyond this, they take pride in their network. When they sit next to someone new, they get to know them and remember their name, and they connect with people.
Gladwell came up with a simple test to identify if someone is a connector. He chose 250 surnames at random from a phone book and asked people to give themselves a point for every person they knew with one of those names (and you could score multiple times if you knew several people with the same surname). The average person scores 21-41, whereas the top 2% (the connectors) score over 90.
You can do this test here. I scored just 28. Whilst I love networking, I have an awful memory, and I am not a Connector. However, I have definitely seen the incredible value Connectors can add to a transformation.
The best Connector I have worked with turned my interview questions into a demonstration of their networking capabilities and knowledge. By the end of the interview, she’d drawn up a diagram of the key decision-making forums in the organisation, a number of the attendees, identified key people that were in multiple forums relevant to the transformation and identified the key people (often other Connectors) behind the forums that made them a success.
They were an instant hire. Whilst I never really understood how they worked, I didn’t need to. After they joined the team, I saw that our impact went up tenfold. We went from not knowing how to progress certain challenges to getting on agendas of key forums and from having great discussions in the data SteerCo to having action points that were recognised and often picked up elsewhere in the organisation. They even had a great hit rate for suggesting people who would be willing and effective data owners!
My recommendation to find these people is to ask people everyone who the best networkers are, who has had EA roles for board members and who has pulled together successful transformation forums before. By definition, these people are well-connected, and most people will know them.
What’s in it for them? Data is the most cross-functional topic there is - they will have a role dedicated to using their expertise and expanding their network.
Mavens and Data Transformations
Maven comes from Yiddish and is someone who accumulates knowledge. Whilst Connectors know more people than anyone else, Mavens know more facts and details than anyone else and take pride in this.
In the same way that Connectors don’t just have a wide network, Mavens aren’t just people who know a lot. They also take pride in growing and sharing that knowledge.
For UK readers, Martin Lewis is a classic Maven. As a journalist, he specialised in personal finance issues. But he didn’t stop there. He obsessed over the details of personal finance, the minutiae of terms and conditions and created the MoneySavingExpert website to provide this knowledge for free in the form of ethical and unbiased consumer finance information. Because of Lewis’ obsession with detail, his audience instantly trusts his advice and doesn’t feel the need to shop around further for more information. For non-UK readers, his approach has become so successful that Martin Lewis is probably one of the most respected and trusted voices in the UK today.
Data is a natural career path for a Maven. Many people work in data because, in a rapidly evolving and complex world, they can take comfort in the solidity and permanence of facts. But remember, a Maven is about more than knowing things, they also have a desire to cultivate and share that knowledge. It is for this reason that I have loved every encounter with someone like this. If you create the time, they will love nothing more than to talk you through the minutiae of data in their area and do so with precision and passion.
I remember the first Maven I came across in the last data transformation I worked on. They worked with the sales datasets and knew just how many other teams valued that data. They also knew how complex the data was - different definitions of the sales point, region etc., different versions of forecasts etc. Completely unprompted, they had created an internal site with a data dictionary, contact page, process map describing when updates happened etc. It was so good that, as the central data team, we pointed everyone to it as the best practice in documenting and sharing data.
Mavens that have been in an organisation for a while build up an immense amount of knowledge. I have met Mavens, who have documented issues in complex cross-functional data processes so well that it would take a £500,000, 6-month consulting engagement to even get close to their level of documented knowledge. Work like this is invaluable for kick-starting a data remediation or management programme.
These people bring huge value to organisations that are often overlooked and lost overnight if they leave. The role of a data transformation team is to find and sing the praises of these people. Use your comms to highlight their portals and documentation, bring them into senior meetings where challenges with data are being discussed and recruit them into your team if they are a flight risk. And, of course, invite them to form the working group if you are starting a Data Catalogue project.
Salespeople and Data Transformations
For any transformation to succeed, you will need to persuade people, both believers and cynics, to believe in the transformation. This is where Salespeople come in. They are experts in the art of persuasion.
Why some people are naturally more persuasive than others is hard to nail down. But we all know (and studies have measured) that some people build a rapport with others in seconds, some take minutes and some struggle. Those people who build a rapport quickly tend also to be people we find ourselves agreeing with a lot and “harmonising” with - people literally end up mimicking their gestures.
Like everything, this has been studied. The Affective Communication Test, by Howard Freidman, measures the ability to send emotion and to be socially contagious. There are just 13 questions on the test (below), and whilst the scoring mechanism for it isn’t public, we can likely infer it.
When people assessed themselves against these 13 questions (on a 1-9 scale) the average score is around 71 (out of 117) but the best salespeople score near 117. The salesperson that Gladwell wrote about laughed at the question on charades and said “I’m great at that! I always win at Charades!”. Salespeople, it seems, are gifted in all forms of communication, including Charades.
Like it or not, you need these people in your transformation network and team. I say, like it or not, as we all have our biases, and as a data person who likes facts, I am naturally suspicious of people with the ability to persuade and sell without facts and data. Therefore it took a Maven (who understands networks and people) to convince me to put more effort into building my relationship with some very effective Salespeople in my last organisation. I didn’t regret it.
What I found is that once I’d convinced a Salesperson about the importance of data transformation, it was only a matter of weeks before they’d won over board members and senior forums that I was struggling with. Once I put my biases aside, I actually learned a lot from these people, and the transformation went up yet another gear.
Conclusion and next article
Data Transformations are hard because few, if any, topics are as cross-functional and as transformative as data. To succeed, you will need the support of far more people than you can ever connect with yourself.
Fortunately, Malcolm Gladwell’s work on Tipping Points and his “Law of the Few” says that you don’t have to connect with everyone to start a movement. There are a small number of people who have a disproportionate effect on movements and change. They are Connectors, Mavens and Salespeople. If you start identifying those people in your organisation and working with them, you will be well on the way to a successful transformation.
However, not everything comes down to these people. Malcolm Gladwell wrote about the three rules of Tipping Points. The Law of the Few, the Stickiness Factor and the Power of Context.
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I saw a great example of a Maven this morning at CrossFit. A few of the 5:30 AM class members were drinking coconut water, and it turns out that a Brazilian man named Doug who doesn't even go this class has started drinking it as well. Every guy admires Doug and would love to have his build. He has immense knowledge about CrossFit. He's also one of the sweetest people at the gym. Definitely a Maven.
By the way, you mention "Peter Revere" in your second paragraph. That was Paul's brother. He went on to become a CDO. ;-)
Love the article Benny. I am a terrible Connector - I’ve got better with online rather than traditional techniques, but a Maven/Sales Person probably sums me up.