The Science Behind Why Massive Change Seems To Happen All At Once

Humans tend to think about things in a linear way. We assume progress happens step by step—losing a little weight for the summer, putting money into a college fund, growing a business customer by customer. We measure, plan, and execute accordingly. One day follows the next, and we try to make a little progress towards our goals

Yet many have observed that shifts are often abrupt. Hemingway, quite famously, described change as happening, “gradually, then suddenly.” Thomas Kuhn explained how revolutions unfold in abrupt paradigm shifts. Mathematician Benoit Mandelbrot described change in terms of Noah effects and Joseph effects, with massive shocks disrupting periods of continuity.

Yet these are more than just interesting observations. For decades, scientists have uncovered the natural forces that underlie how change happens. Once we understand these principles, we can learn to notice the telltale signs and anticipate opportunities before events take us by surprise. That can help us work toward the kind of outcomes we want to see.

The Anatomy Of An Instantaneous Phase Transition

Imagine throwing a party for a hundred complete strangers, divided into small groups. There’s some mingling as well. Every five minutes, two people from different groups swap places. As the night wears on, you mention to a guest that you have a nice bottle of scotch in the kitchen cabinet and you’ll serve him a few fingers, as long as he tells no one else.

Network science tells us that your scotch will be gone in record time. Let’s look at some math: The Erdős-Rényi model holds that if there are 40 groups in the room, generating 780 potential links among them all, it only takes 72 links to guarantee a continuous chain. So, if every group in the room makes a connection to another group by exchanging a member every five minutes, then 60 links would have been created after 15 minutes.

Yet because the links between groups form randomly, those 60 links will be unevenly distributed, leaving some groups tightly clustered while others remain completely unconnected. In the next five-minute shift of mixing, however, the 72-link threshold will have been met and the entire party will have formed a continuous chain.

What’s important to understand about this scenario is that, until the very last step, the room remained largely unconnected. Yes, connections were forming, but not in a consequential way. You just had isolated islands of connected people. Yet with only a few more links, a complete phase transition took place and, all of a sudden, a complete network formed.

As I explained in Cascades, it is these networks that form that make genuine change possible. They build up gradually and, as they do, it’s hard to get all of those unconnected clusters to align and coordinate action. Then suddenly, the last link is formed and, all of a sudden, a window of opportunity opens and widespread, collective action becomes possible.

The Threshold Model Of Collective Action

The Erdős-Rényi model is useful, but also highly theoretical. There are several elements that don’t reflect the real world. First of all, it assumes networks are random and we know that they are not. We tend to be connected to people we share some context with, like a school, a workplace, a neighborhood or maybe a common interest.

Another factor that isn’t represented is that people’s preferences can vary widely. For any particular idea or activity, some people will enthusiastically jump in while others will be highly reticent. So whether an idea catches on is going to be highly dependent on the people it reaches. If it reaches people with low resistance it is likely to spread quickly, but if it reaches people with high resistance, it is unlikely to catch on.

In a highly influential 1978 paper, sociologist Mark Granovetter showed the adoption of ideas or behaviors often depends on the distribution of resistance thresholds. Clusters of individuals with low barriers to adoption can influence those with greater resistance. Building on this foundation, Duncan Watts later showed even small differences in the structure of people connected within networks can significantly shape the spread of ideas.

Yet people’s preferences aren’t fixed so, in practice, the spread of an idea or behavior is often triggered by an external event that lowers resistance and increases the concentration of people open to adoption. This creates a window of opportunity for change agents, where what once seemed impossible suddenly becomes within reach.

Real world examples in the US include Hurricane Katrina, which shifted attitudes about the Bush Administration and the murder of George Floyd, which had a similar effect on how people thought about racial justice. Internationally, Mohamed Bouazizi setting himself on fire triggered the Arab Spring and the attack on Oksana Makar in Ukraine solidified opposition to the Yanukovych regime in the lead up to the Euromaidan protests.

The Unveiling Of Unrevealed Preference

At any given time we hold a varied portfolio of opinions. Some are tightly coupled with our identity, such as our obligations to our family. Others, such as those regarding other cultures, we may hold very loosely, rarely thinking out or revealing our preferences unless asked. Still other opinions we hold but don’t reveal, fearing they clash with widely accepted social norms.

For example, a revealing study done in Saudi Arabia found that most men were in favor of their wives working, but believed that other men, even those they knew fairly well, would look down on it. When they learned that most other men actually shared their views, they became far more supportive of their wives working outside the home.

In a separate study, performed before the 2016 election, participants were asked if they would approve a $1 donation to a xenophobic organization. 54% agreed if they would remain anonymous while only 34% would do so if their name might be made public. However, when told that Donald Trump was expected to win, roughly half would authorize the donation whether it was anonymous or not.

As Michael Morris explains in his book Tribal, we have a peer instinct that drives us to synchronize our behavior with others. The best indicator of things we think and do is what the people around us think and do and that effect extends out to three degrees of separation. Whether we reveal our preferences or not is highly dependent on our perception of norms.

The Anatomy of A Cascade

In my book, Cascades, I described a pivotal moment when I awoke one morning in the fall of 2004, surprised to see my fiancée wrapping a bright orange bandana around her neck as she prepared to go out. It seemed particularly early for a Saturday, and she has never been an early riser so I asked, “Where are you going?”

“I’m going out to a demonstration,” she said.

“I thought you didn’t care about politics.”

“I didn’t, but it’s enough already, and it’s time to do something about it.”

And just like everything changed. Ukraine was about to join the wave of popular uprisings that came to be known as the Color Revolutions, which swept across Eastern Europe in the first decade of the 21st century. The movement included Serbia, the Georgian Republic and, of course, the Orange Revolution in Ukraine.

For many years, how that all happened was a mystery, but over time I began to unravel the science behind it all, which is what led to my book. I learned there are natural laws that govern change and that these laws can be learned and applied by anyone, in any context, to overcome the status quo and bring about the change that they want to see.

The Orange Revolution began with a student group called Pora. They didn’t have power or money, but they were fed up with the corruption and incompetence of their leaders. They slowly started forming connections to other students and those students had mothers and fathers, aunts and uncles who became linked through their activities.

Then a cascade triggering event occurred—the poisoning of the opposition candidate, Viktor Yushchenko. That lowered resistance thresholds of all those mothers and fathers, aunts and uncles, who were not students or activists, but marketing managers and accountants and had connections to other professionals like my fiancée, who started attending demonstrations. These triggered peer instincts and even more hit the streets.

That’s why transformational change so often happens gradually, then suddenly. It happens when small groups, loosely connected, become united by a shared purpose and then an unexpected event tips the system into a cascade. Wise leaders build their movement to prepare for that moment, and are able to shape the future in a more positive direction.

Greg Satell is Co-Founder of ChangeOS, a transformation & change advisory, an international keynote speaker, host of the Changemaker Mindset podcast, bestselling author of Cascades: How to Create a Movement that Drives Transformational Change and Mapping Innovation, as well as over 50 articles in Harvard Business Review. You can learn more about Greg on his website, GregSatell.com, follow him on Twitter @DigitalTonto, his YouTube Channel and connect on LinkedIn.

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