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The Adaptive Organization Is Driven by Collective Intelligence

The way we talk about businesses has changed. In recent years descriptors like agile, resilient, ecosystems, networks, and disruptions have become a mainstay of modern business vocabulary. Changes in business language are natural, but this time there may be a larger shift involved, where people now view organizations more as living systems.


Photo of Sigbjørn L. Tveteraas

Sigbjørn L. Tveteraas

Data Science

Strategies tailored for complexity 


What insights can we draw by viewing organizations, markets, and economies as living systems, or more specifically, as complex adaptive systems? Two specific insights into how this increasingly holistic and organic worldview remain. These worldviews ask us to reconsider current practices and how we approach choices about resource allocation and information sharing

In a mechanistic worldview, organizations are often linked to machines. Machines have parts that are fixed, maintained, and improved upon. In the extreme, mechanistic approaches lead doctors to exchange phrases like “Will you please check out the kidney in room 104” instead of “will you please check out how Mrs. Smith in room 104 is doing who has the kidney problem”. You decompose things into their parts.

Frederic Taylor, often considered the father of scientific management, was a proponent of the pursuit of ever-increasing efficiency. Today, lean and just-in-time management principles are torchbearers for making organizations more efficient. 

Somewhat exaggerated, these management principles try to squeeze the last drops of juice out of existing resources. Viewed in isolation, it seems like a good idea to not waste resources. However, in a complex world, an overly strong emphasis on efficiency misses out on the bigger picture. 


Trading efficiency for resilience


Modern-day business thinker Roger Martins (2020) begs us to scale back on efficiency. With today’s complexities and uncertainties, he points out, it makes sense to create buffers and slack for the bad times. Such a strategy strikes a better balance between efficiency and resilience.  

In complex adaptive systems, future events are viewed as largely unpredictable. Stuff like financial crises, global climate change, pandemics, inequality is really, really complicated problems. We just do not have good predictive models for the job, and most of the time we do not even know what questions to raise. 

Martin’s advice of creating slack is a way of incorporating into business strategy the inherent uncertainty about the future. His message is particularly relevant now during the pandemic, where surely many businesses regret not saving more for a rainy day. However, long before the pandemic hit, large US companies have firsthand experienced a radical shortening of ‘life expectancy' on the S&P500 list. 


Detecting early signals of game-changers


The higher turnover of companies on the S&P500 is linked to disruptions. In a complex adaptive system, disruptions are events that often are unpredictable. The pandemic is a disruption on a really large scale. On a smaller scale, organizations can be affected by new technologies, trade policies, new competitors, societal trends - really any number of things that affect organizations and how they go about conducting their business. 

At its heart, Martin’s advice on creating slack is rooted in an information problem about detecting game-changers, small or large. In complex systems, where potentially anything affects everything, information is king. Not any kind of information, but the specific one that reveals sources of changes emerging and the channels through it are affecting the system at large. 

Think about the emergence of bad loans and their cascading role in triggering the global financial crisis, the Internet in creating disruptions in industries in so many ways, and the COVID-19 for the current crisis. Similarly, the emergence of unanticipated events on a smaller scale can influence organizations. These disruptions create strong tensions and pressures to adapt.

When exposed to boiling water a frog will jump to safety, but when exposed to lukewarm water that gradually heats up the frog remains and dies. The metaphor captures how in complex adaptive systems events often emerge undetected before they start to disrupt. The frog fails to adapt because it is unable to detect what is happening. In the same way, organizations that do not see what is coming can quickly end up like another ‘Kodak moment’ - in this case, the kind of moment where a company does not realize that they are failing to detect changes in the market before it is too late.  

Siloed information 


The problem of inaction in organizations is often linked to siloed thinking. Silos make it difficult to capture signals about emerging events since they hinder information flow. Traditionally, this has been handled by managers walking around and talking to frontline employees in different parts of the organization. In this way, managers can gather information from the people in the sales, in operations, and in other departments, and start connecting the dots.

Now, the size and busyness of many organizations make management by walking around impracticable. Importantly, a key difference between now and then is the frequency of disruptions. High innovation activity induces changes in markets and organizations to occur with higher speed and frequency than before.  

Improved information flow is the way to get a better grip on emerging game-changers. When people share information across silos, talk more together with different colleagues, and get more involved in each other’s work, information flow increases. This makes it easier to capture signals of emergence. 


The collective intelligence-driven organization 


Collective intelligence is a science suited to get a grip on the problem of siloed information. The key insight from collective intelligence is that we are smarter together; Linking up a diverse group of people leads to better predictions, decisions, and problem-solving abilities. Collectively these groups are able to provide richer interpretations of emergence than, say, an ‘expert’ and her limited set of knowledge and mental models.

In an innovation-driven and highly connected world, small and large game changers do occur. The capability to detect and adapt to game-changers is not only a desirable organizational trait, but a required one today. 



To create an adaptive organization, collective intelligence combined with capabilities for change go a long way (Uhl-Bien & Arena, 2017).  

Even if collective intelligence is naturally part of any organization, it is the systematic design and processes that really leverage the predictive and problem-solving capabilities of people. For example, cross-functional agile teams often have the traits to make them collectively intelligent. Tomorrow's adaptive organizations, however, will harness collective intelligence from all of its employees. The result will be organizations built to last. 



Martin, R. L. (2020). When more is not better: Overcoming America’s obsession with economic efficiency. Harvard Business Review Press. 

Uhl-Bien, M., & Arena, M. (2017). Complexity leadership: Enabling people and organizations for adaptability. Organizational Dynamics, 46, 9-20.



You've just read a blog post from Mindpool - a platform that helps you harness the collective intelligence of employees. Mindpool taps into the knowledge of employees to provide actionable predictions and curated insights. Mindpool is rooted in decades of research in collective intelligence. Read more from our resource universe or contact us here if you'd like to tap into your employees' valuable knowledge.


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