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Why Communication Professionals Must Understand Complexity

It is fashionable these days to think of communication as both art and science; albeit with emphasis increasingly on the latter. No surprise, what with ongoing innovation in the digital space. Expertise in coding, search engine optimization, data analysis and visualization, among others, are elbowing out more conventional knowledge and skills, further tipping the scale. Yet few communication professionals truly understand one of the most essential sciences: complexity.

Complexity is different than other sciences. With physics and chemistry the object is to examine conditions in isolation in hopes of achieving undeniable outcomes. Complexity, on the other hand, explores systems whose different elements interact in multiple ways; with the realization that certainty is nearly impossible to attain. This is because when even the simplest components converge, what ultimately emerges may be quite unlike its original parts (as when gases hydrogen and oxygen combine to form water). Moreover, this process is non-linear, so input and output are not proportional to each other. What first appears as small and inconsequential can quickly become big and burdensome. For every event that occurs there are any number of possible causes, with no clear link between them. And since such systems learn from, and adapt to, their environments, they frequently change. All of which means they are difficult to control, and their consequences are too precarious to predict.

For proof, look no further than the current presidential campaigns. Not only is the nation ostensibly split between two warring political parties, these same bodies are beset by their own discordant and disorderly factions. This is one reason pundits failed to foresee that a reality-TV star billionaire or a self-proclaimed democratic socialist would be taken seriously as a potential commander-in-chief. But politics isn’t the only field to which principles of complexity can be applied. Scientists already employ complexity theory to forecast weather. Epidemiologists have developed means to identify “super spreaders” of disease to prevent or limit contagion. The Financial Stability Board — a panel of central bankers, finance officials, and regulators — has built a framework to audit tightly coupled ties among banks, to gauge risks to the world’s financial system.

Communication is a complex system

As for communication, its association with complexity reaches back more than half a century to the first, and one of the most influential, paradigms of its kind. Originated by Claude Shannon, an engineer and mathematician at Bell Labs, and his colleague Warren Weaver, a scientist and pioneer in complexity theory, the communication model was designed to enable

Shannon-Weaver Communication Model

engineers to find the most efficient way to transmit electrical signals from one place to another. Since then it has been adapted to assorted modes of human interaction. Our brains, for example, are highly complex organisms that manage infinite electrical connections among billions of neurons that keep us alive. Beyond that, they store myriad facts, experiences, impressions, and memories that coalesce to produce ideas. These ideas, in turn, traverse robust digital networks in the form of news, entertainment, social conversations, and data.

Indeed, the proliferation of communication networks has dramatically escalated global interdependence. Today’s most pressing issues, whether immigration, climate change, dysfunctional governments, or a fragile worldwide economy are not only intricate in and of themselves, they are deeply entangled with each other. “Global risks are interconnected, and that can create unexpected consequences,” warns the World Economic Forum (WEF) in its latest report on the topic. “The world has navigated previous eras of profound transitions resulting from converging economic, technological, and geopolitical developments. But with a faster pace of change and more complex interconnections, the stakes have never been higher.” According to the WEF, businesses risk damage to their reputations, loss of market share, and disruption of established models.

Global Risk Interaction Map — World Ec0nomic Forum

If these aren’t enough to compel companies to deal with such problems, growing numbers of consumers demand they do so as well. A recent survey by public relations and marketing agency Cone Communications found that nine-in-10 respondents expect firms to do more than simply make a profit. They also want them to address such concerns. Thus, it falls to PR pros and growing legions of content marketers to help stakeholders make sense of a seemingly chaotic world. But this presents two formidable challenges. First, they must comprehend and coherently explain an array of interlocking issues. Second, they have to do this through processes that are, themselves, becoming more complex.

Traditionally, enterprises have relied on linear, or analytical thinking to diagnose a problem by zeroing in on specific aspects and concocting a strategy to resolve it; assuming the situation is static and merely the sum of its various parts. But successfully managing complex communication entails moving in the opposite direction by stepping back and recognizing what happens when divergent elements come together under constantly changing circumstances. This is complexity, or systems, thinking, which is largely a matter of perception. It is a distinctive way of approaching questions with a more open mind, and requires communication professionals to work at the intersection of diverse knowledge and skills. The following of which should be on every communicator’s shortlist.


Nothing in this new century has engendered as much opportunity, and angst, as the ability to join two simple digits in innumerable combinations. Like pairs of molecules in DNA strands that determine the structure and function of almost all living things, strings of ones and zeroes increasingly dictate the workings of modern communications. Digital systems are taking down existing barriers to entry, forcing formerly detached businesses to directly compete, collaborate, or both in newly defined markets. Where the New York Times, CNN, and National Public Radio once operated in substantially separate domains, they now go head-to-head online, relying on comparable sets of text, sounds, and images. Advertising agencies feel the breath on their necks from technology companies, talent firms, and publishers looking to disintermediate them when reaching out to consumers. Something similar is happening on a personal level too, as those in public relations assume roles that were formerly the exclusive province of journalists, while defending their own turf against an onslaught of content marketers.

To stay ahead, individuals and organizations will have to master the latest devices and applications; but that will be a Sisyphean task. “Novel technologies make possible other novel technologies,” says complexity theorist W. Brian Arthur. These beget still newer technologies, and so on. Adds Arthur: “It follows that a novel technology is not just a one-time disruption to equilibrium, it is an ongoing generator and demander of further technologies that themselves generate and demand still further technologies.”

Consequently, competitive advantages gained from any particular tool or technique are likely to be short-lived since digitization allows upstarts to continually link people, processes, and things in entirely new ways. Little wonder that, in a survey of almost 4,000 technology officers in 30 countries, 75 percent of participating CIOs in broadcasting and media named digital disruption as a significant threat; as did 62 percent of those in PR and advertising. Thus, capitalizing on future opportunities will involve more than merely grasping technology. It will warrant deciphering complexity as well.


In the same way astronomers use telescopes to explore the intricacies of the universe, and biologists rely on microscopes to reveal objects once too minute to imagine, data scientists hope to uncover new insights by collecting, dissecting, tabulating, analyzing, and extracting value from trillions upon trillions of bits of information. Complexity, however, isn’t always accommodating. The Internet and the slew of apparatus attached to it have generated massive databases, whether residing on single servers or distributed within “clouds” of computing resources. Every minute of every day, users “like” more than four million Facebook posts; send nearly 350,000 tweets; upload 300 hours of YouTube videos; and download 50,000 apps.

Source — Domo

What is more, as much as 80 percent of the resulting data is unstructured, meaning it lacks any predefined format. And because data regularly change, scientists have to continuously create new models just to keep up.

Further compounding the situation is the fact that companies capture data from disparate sources. It is estimated that better than 70 percent of firms rely

Source: Sisense based on data from Ventana Research and the Aberdeen Group

on at least six separate sources; with 23 percent using more than twenty. In a survey of 1,500 global executives by digital consulting agency Bluewolf, roughly half of all participants admitted having a hard time reconciling data with different origins. Worse yet, a study by Pricewaterhouse Cooper found that two thirds of companies obtained little or no tangible benefits from the information they gathered.

Given the speed and perpetual glut of data, communicators must acknowledge that the responsibility for realizing actual benefits is no longer theirs alone, but one they share with machines. There are algorithms that already gather, organize, and analyze data they turn into rudimentary press releases and quarterly reports. Other programs can automatically edit hours of video footage for images with ideal artistic qualities. Plus a of team of Chinese and American engineers is developing the means to anticipate users’ needs and deliver only the most relevant content. Complex in their own right, algorithms are eminently versatile; so the more they learn, the more they do.


To genuinely appreciate what complexity is, it helps to know what it is not. Arcane language like the kind that fills legal documents is not complex. It is detailed and often convoluted, but nothing some good wordsmithing can’t clarify. Neither is a Power Point complex, no matter how elaborate the bells and whistles. Every slide is designed, organized, and presented in a manner that is readily controlled and repeatable.

A conversation, however, is complex. Person A says something to person B. B responds, and a dialog begins. If they know each other and the parameters are clearly marked, their discourse may go as expected. If not, it is apt to be unpredictable, possibly uncontrollable, and almost always self-adjusting. Now multiply that several billion fold.

Audiences of all kinds are dividing and sub-dividing into smaller, more distinct groups, each with the capacity to send as well as receive information. “In this digital age almost anyone can be a stakeholder or commentator, both inside and outside their organization,” notes David Broome, an executive director at the VMA Group, whose Business Leaders in Communications Study 2014/15 concluded that the number and complexity of key audiences was the single most important challenge to communicators.

While unbundling audiences can unleash a bounty of new and different ideas, many people choose to shut them out. Engulfed in a deluge of content, they seek to narrow their options, primarily to those world views that confirm their own. Such biases serve as lens through which to buttress their attitudes and assumptions; and once they have settled on their opinions, if directly challenged they will double down on their decisions.

To penetrate these filters it is critical to understand how different groups access, process, interpret, and use information. Accordingly, advances in cognitive and behavioral sciences merge disciplines like psychology, sociology, anthropology, philosophy, linguistics, economics and political science to explore how humans reason and respond in the context of their sundry state of affairs. Incorporating their findings within powerful databases can reveal previously undisclosed patterns, peculiarities, and even sentiments around which to design and deliver more meaningful messages.

While they are at it, communicators should take into account how their own beliefs and experiences cloud their judgments. Another reason journalists were slow to pick up on Donald Trump’s popularity was because few actually know any Trump followers. “We were not socially intermingled with his supporters and did not listen carefully enough,” concedes New York Times columnist David Brooks, who vows to do better in the future.


As the connectivity within a system increases, it is the relationship between components, rather than the components themselves, that define it as a network; and what then becomes important is how information circulates. Complexity — particularly nonlinearity — is inherent to almost all networks. Though the number of elements grows in linear fashion, the number of connections between them grows exponentially. Online ad markets, for example, generate 100 billion impressions daily, with each one measured against as many as 100 separate variables, culminating in countless possible outcomes. But such aggressive increases can reach a point at which the entire system is at risk of breaking down or completely collapsing under its own weight. According to research by Accenture Digital, 50 percent of marketers already deal with more content than they can effectively handle. Even so, 83 percent expect the volume to expand unchecked over the next two years.

This condition is especially dangerous in hyperconnected networks where trivial events can suddenly turn into full-blown crises. Here, problems can spread as easily as solutions — sometimes more so — through processes that are difficult, if not impossible, to stop. To make matters worse, the Internet of Things may soon bring an additional 25 billion devices online at speeds up to 100 times faster than current platforms.


In light of these circumstances, communication professionals are wedged between a rock and hard place. Complexity doesn’t conform to most peoples’ desire for control, nor to their need for direct lines between cause and effect. Likewise, managers want assurance that once a plan is in place it can be used repeatedly; hence the popularity of templates and best practices. Nonetheless, communicators have little choice but to, at least, understand complexity if not embrace it to successfully tackle the vicissitudes of 21st century society.

In part, this is because value is shifting from technology — be it hardware, software, or the platforms on which they reside — to how technology interacts with its environment. To that end, complex systems design is about connecting people to people, people to machines, and machines to machines, focusing on both the interactions and their implications.

Additionally, since complex systems comprise multiple interacting elements, they require comprehensive strategies. Bringing together people with varied backgrounds and experiences to consider a problem from diverse perspectives enables them to perceive it in ways no single individual can.

Most important, complex systems are dynamic and forever fluid. “You do not compete against competitors ,” says Cisco’s executive chairman John Chambers. “You compete against market transitions.” Therefore, complex strategies must be extremely adaptable. They are patterns of action that evolve from the juncture where an organization’s best laid plans collide with the ever changing realities of the marketplace. Essentially ongoing works in progress, they develop in the absence of specific policies, or despite them, and instead require a willingness to put aside assumptions and learn what can actually be achieved in practice. They will often vary depending on the circumstances. Not everything will be apparent; certainly not right away. And they are bound to change throughout the process. But the goal will always be to recognize how a system’s different pieces interact and influence each other; and with that, continually build ever better strategies.

(An earlier version of this article appeared in ParisTech Review)

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