Disruption is in Decline: Two Things You Can Do to Disrupt in Any Industry

A study published in Nature by Michael Park, Erin Leahey, and Russell J. Funk shed light on a concerning trend: a decline in disruptive activity in science and technology. 

While the absolute number of disruptive published papers and patent applications has remained relatively constant, the total number of papers and patents has significantly increased. 

The percentage of disruptive papers and patents has decreased.

In fact, since the 1940s, the percentage of disruptive papers and patents has declined by approximately 75% (for patents) to 90% (for papers). This decrease in disruptive outcomes is a significant shift we need to take into account as leaders and development professionals.

To make sense of this decline, we can turn to the S Curve™. The S Curve is a model that maps your personal growth experience in an S shape—a flat tail at the beginning, a steep back, and a flat plateau again at the top. 

Now visualize a scientific paradigm—the current best theory encompassing a body of knowledge, understanding, and methods—as an S Curve. 

At the low end of the curve, there is a vast unknown, along with numerous challenges and constraints that hinder scientific advancements within the paradigm. As knowledge accumulates, a tipping point is reached, and progress accelerates up the steep back of the curve where fruitful avenues of investigation yield results and breakthroughs occur. As time passes, the advancements become slower, and progress is made in incremental steps rather than significant leaps.

At the high-end of the scientific paradigm curve, the focus shifts to consolidating accepted knowledge rather than pushing boundaries.

As with our personal growth and development, there are benefits to climbing up each S Curve fully in many contexts. When we stay until we reach the top—the mastery phase—we cement our skills and knowledge and fine-tune our approach to the point where it becomes second nature. 

As Max Kozlov reminds us in his response to the original Nature article “disruptiveness is not inherently good, and incremental science is not necessarily bad.” 

The scientific process is intended to ensure replicable results under wide-ranging circumstances—it relies on results that are reproducible, and the duplication of studies is an essential part of that process.

So the increase in the non-disruptive papers is not necessarily bad. They help solidify gains and become the grounds on which the next S Curves will stand. 

But, the pendulum has shifted, and we are at a time when we need to push for disruption.

We need new and novel research and findings. We need to do two things in order to lean into disruption not only in science and technology but also in organizations: 

1. Know how to flag what is new and novel
2. Allocate a certain percentage of the budget toward it

While the study we mentioned earlier primarily focused on evaluating published papers and patent applications, it briefly touched upon a decline in novelty observed in grant applications. This aspect, although not explored in detail in the article, holds predictive value that merits further investigation.

The ultimate results from this study are, to some extent, influenced by the objectives outlined in grant applications. As the study authors highlight, scientific investigations reflect the "shifting interests of funders and scientists." 

Science and technology are not immune to the economic considerations affecting progress in other fields. Scientists focus on research avenues that appeal to funders, who, in turn, prioritize risk reduction. Consequently, grant applications often emphasize familiarity with existing paradigms rather than seeking significant disruption.

Just like in organizations, budgets often determine where the work is done.

So, how can we know at the beginning of a curve, at the grant application or budgeting stage, if something is likely to be disruptive? 

According to the study, disruptive papers and patents exhibit linguistic differences compared to consolidative ones. They tend to use language that suggests the creation of a new paradigm, rather than relying on language familiar to the existing paradigm. 

It is plausible that a similar linguistic evaluation of a grant application could predict whether the associated study will be disruptive or consolidative.

It is no surprise that individuals and organizations providing funding for initiatives often seek to minimize risk. It feels safe. But we must understand that embracing risk is a crucial catalyst for disruption and transformative breakthroughs.

Yes, we need to course correct, but let's not forget the value of what's not new and novel. There is no need for an extreme swing of the pendulum where only disruptive projects receive funding, but we do need to move towards innovation. 

Therefore, it is crucial for us to identify mechanisms that can predict the potential for disruption early in the process, even as early as the funding application stage, or in the case of a business, in the budgeting stage. Such insights can help make informed decisions regarding resource allocation for long-term progress.

How has funding encouraged or discouraged disruption in your field?

How do the cycles between disruption and mastery play out in your life?

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