INFORMAL NETWORKS

Why You Should NOT Map Networks During Workshops

November 27th, 2025 | Informal networks

The question almost everyone gets wrong is:

If you’re like most companies or organizations, you gather a group for a workshop. You ask them to map networks, nominate “influencers,” or create lists of “key people.” It feels collaborative. It feels democratic. It feels right.

But here’s the uncomfortable truth: You’re asking the wrong people, in the wrong way, and getting systematically biased answers.

Think about who attends your change workshops. They’re typically:

• Senior enough to be invited
• Available enough to attend
• Vocal enough to be noticed
• Already part of the “inner circle”

In other words, the people you’re asking to identify others are themselves a filtered, non-representative sample of your organization or community. They see the world through their particular lens, from their department, their level, and their own social network. They identify people they know, people like them, people they work with directly.

And it gets worse. Even well-intentioned people in these workshops tend to suggest:

• People with formal authority (because we conflate titles with influence)
• People who are extroverted and visible (because we remember them)
• People from our own departments (because that’s who we know best)
• People we personally like (because human nature)

You end up with a list that reflects the social circles of your own world, not the hidden networks that shape how information, trust, and change flow through your organization or community.

Now imagine a different approach. Instead of asking a select group who they think is a change catalyst, you ask everyone in the organization or community a simple question:

We send a diagnostic to every employee, so not just those invited to the workshop room. We ask them to nominate the colleagues they seek out for advice, trust with problems, or rely on when they need help. This is the entire system speaking, not a pre-filtered sample.

Then our algorithm many know is called the #ThreePercentRule does what no workshop ever could: It analyses the complete network of actual connections across your organization. It maps who people really turn to, revealing patterns that are invisible to any single person or group, no matter how senior or well-connected.

The mathematics behind the algorithm then identifies the smallest group of employees who collectively influence 90% of your company. They don’t know each other, because they do NOT have overlapping networks. They are sought out in their tribes or silos and it turns out: They are aren’t necessarily the loudest voices. They’re the 3% who are genuinely perceived as competent and sympathetic by their colleagues. That’s why others actively seek them out.

This is influence measured by the entire organization’s revealed choices, not the limited perspective of a workshop room.

Here’s what makes algorithmic identification fundamentally different:

1. It captures the whole system, not just the visible parts

The algorithm analyzes connections across all departments, levels, and locations. It finds the administrative assistant in Accounting who everyone trusts, the engineer in R&D who people from Sales somehow know to call, the middle manager whose opinion quietly shapes three different teams.

2. It measures actual behavior, not perception

Workshops give you what people think the network looks like. The algorithm shows you what the network actually is—based on who reaches out to whom, who influences whose decisions, who holds real social capital.

3. It’s mathematically optimized for impact

You don’t just get a list of influential people—you get the smallest possible group that reaches 90% of your organization. This is the minimum viable catalyst team. Every person on this list is there because removing them would significantly reduce your change capacity.

4. It eliminates structural bias

The algorithm doesn’t care about:

• Who has the right title
• Who speaks up in meetings
• Who the leadership team knows personally
• Who fits the traditional profile of a “leader”

When you need to drive change through a complex organization or community, you have two choices:

Ask a biased sample of people to guess who’s influential (knowing their answers will reflect their own limited view, their cognitive biases, and the existing power structures you might actually want to change)

Or

Analyze the actual influence network mathematically to identify the smallest group with the largest genuine reach, which is the 3% who are already trusted catalysts, whether or not anyone in the C-suite knows their names.

One approach gives you a popularity contest among the people who were already in the room. The other gives you the true change-makers in your system.

Which foundation would you rather build your transformation on?