Calling Systems Support (It's not what you think)

John Calvin Maxwell - American author, speaker, and pastor - has written extensively on leadership and, in the early 2000s, famously wrote the book “Teamwork Makes The Dream Work”. Let’s re-examine what’s inside (or not inside) the phrase and the process itself…
Calling Systems Support (It's not what you think)

By Scott Jones & Steve Thompson


What exactly is the dream that we are referring to? Whose dream is it? Is there even a dream in mind? These are just some of the questions which come to mind - and there are surely others. 

These are more than ruminations on a lazy afternoon but speak to the need for definition to provide a safe haven for projects to thrive. They draw attention to the framework within which the process of building a shared dream may be completed. This is a much more critical, fundamental requirement than is often understood. We’ll come back to this later. 

Collective Intelligence

Zapnito co-founders Jon Beer and Charles Thiede share the same compelling view about the failure, as yet, of the Internet to make good on its intended purpose of connecting people and cultivating collective intelligence (CI). They observe how the proliferation of fractionalised social media and increasing disinformation agendas have betrayed these objectives.

Jon writes: “As many of our customers have noticed, the saturation of social media and decline of trust in business has made creating ... relationships between brands and their audiences a great deal more difficult.” 

Charles sums it up well: “It really is simple: to get the internet back on track, we need to take a people-first approach. Technology is the means, not the end; its potential is massive, but not as great as our own.” 

Let’s define our terms before we move on. Collective intelligence is shared or group intelligence that emerges from the collaboration of many individuals and informs executive decision-making.

Pierre Lévy, philosopher, cultural theorist and media scholar, defines CI as, "a form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills.” The basis and goal of CI is mutual recognition and the enrichment of individuals working within groups. It enhances collective knowledge by simultaneously expanding human interactions. CI makes a strong contribution to the shift of knowledge and power from the individual to the collective, making it increasingly important to the survival of human civilization. Conversely, fragmented intelligence and know-how act as a drain on CI and negatively impact all participants, regardless of the scale of the system or initiative in question. 

Collaboration and Ideation 

So what does all this mean in the context of brainstorming expertise and product development? In other words, how can CI flourish in the modern environment to best meet our chosen objectives? 

In our article entitled the “Ideation Cascade”, we discussed the importance of creating and leveraging a properly interactive environment in order to encourage the effective deployment of experts and other skilled personnel. Drilling down on this idea and picking up on the benefits of ongoing community engagement, it seems clear that the harnessing of CI in our digital world owes much to Systems Theory. Essentially, this means that efforts may be for nought if not supported by the appropriate “system” to serve the “dream”.

Systems Theory

Systems theory was introduced by biologist Ludwig von Bertalanffy in the 1930s as a modeling device to accommodate the overlap between separate scientific disciplines. It was born of a concern to adopt a more holistic approach to research and to break down the silos that may otherwise impede progress. This is a concern for any organization - and in the modern digital world, the need to ensure that proprietary information is housed, incubated and developed in the appropriate forum is both all the more achievable and more pressing in a competitive marketplace. 

Defining Our System

Let’s look at systems theory in overview to appreciate this more fully. Firstly, its application is universal. As Donella Meadows, who shot to fame with her prescient 1972 book, “The Limits To Growth” says in her later work, “Thinking In Systems”: “There are no separate systems. The world is a continuum.” Nonetheless, if we define our goals, often we can narrow our scope and isolate the specific system in question, thereby identifying both the appropriate team and the conducive environment required. 

Meadows goes on to say: “a system is a set of related components that work together in a particular environment to perform whatever functions are required to achieve the system's objective. ... In an information system, the components include people, procedures, data, software, and hardware.” Systems, however, can be found universally. Let’s look at the components more closely.


Systems thinking is a fundamental change in perception from a linear worldview to a dynamic prism that permits us to see interconnected relationships and feedback loops. As the 16th Century English poet, John Donne, observed in his Meditations: “ No man is an island.” Indeed - nor is anything else. Everyone can surely agree that overly simplistic deductive reasoning in a vacuum is always a poor substitute for an understanding of issues with input from multiple perspectives.

In the 21st Century, how this translates in practice is that the demand for global interconnectedness is both a great incentive and a must-have driver for digital business interactivity. Indeed, this phenomenon is increasing at a speed of transformation which the world has never before witnessed. Properly harnessed, it heightens the competition of ideas, propels the quality and nature of the discussion protocols, enhances the decision-making process, and improves the action steps taken. 


The goal of systems thinking is synthesis, as opposed to analysis which is the deconstruction of complexity into its separate components. Analysis speaks to a reductionist approach, where we break down the whole into constituent parts or categories. But all systems are dynamic and are, generally, complex. In order to advance our thinking, we need a more rounded, holistic approach. Synthesis aids our understanding of both the whole and the parts simultaneously, along with the relationships and the connections that make up the system. 

As a side observation, while data analysis is the norm in the modern economy, and often includes interaction analysis, have we properly considered the appropriate criteria for our evaluation of the data produced? Thomas S. Kuhn, philosopher of science, historian, and physicist at MIT, remarks in his famous 1962 landmark study, “The Structure of Scientific Revolutions”: “Philosophers of science have repeatedly demonstrated that more than one theoretical construction can always be placed upon (any) given collection of data.” Something for us all to think about.


Another crucial and related aspect from a systems perspective is the emergence of a new larger whole from the work of the smaller parts coming together - in other words, synergy. Multiple interactions and complex relationships can produce outcomes which are greater than the sum of the parts.

A simple example sometimes cited by way of demonstration is the emergence of a snowflake. It forms out of both environmental factors and biological elements. At the right temperature, freezing water particles form in stunning fractal patterns around a single molecule of matter, such as dust or pollen. Emergence at work.

There are surprises too. As Buckminster Fuller, the great inventor and a systems theorist himself, said: “There is nothing in a caterpillar that tells you it will be a butterfly.” The system, however, affords the conditions to support the possibility of unexpected outcomes. Thomas S. Kuhn also noted that innovation doesn’t always occur with the specific outcome in mind - many innovations actually occur purely by chance given a process and environment that support their potential. The long list of inventions stumbled upon by accident - from penicillin to superglue, teflon to the microwave oven, dry-cleaning to dynamite (to name just a few), offer an interesting glimpse into this process. 

What is essential is to set the right conditions for optimal performance. As emphasized tellingly by Donella Meadows once again: "Systems fool us by presenting themselves - or we feel ourselves by seeing the world - as a series of events.....Events are outputs, moment by moment, from the black box of the system."

Feedback Loops - Reinforcing and Balancing

Feedback loops essentially come in two flavours - reinforcing and balancing. What can be confusing is that a reinforcing feedback loop is not generally a positive sign. Think of it as the exponential growth of one element in a system disrupting its balance, such as an exploding animal population or  too much algae in a pond - even the danger of groupthink in an echo chamber. With reinforcing loops, an abundance of one element will continue to refine itself and adapt, which can often lead to it dominating the process.

A balancing feedback loop, however, applies where constituent elements within a system balance things out. Nature has perfected this ecology in the predator/prey dynamic. We understand this as the system of the trophic cascade. If one animal, such as the wolf, is removed from an ecosystem, it creates a domino effect of a population explosion in another, resulting in the other negative type of feedback — reinforcing

feedback loops diagram


To understand fully how we can leverage feedback loops, we need to consider the notion of causality: i.e. inputs to outputs in a dynamic and constantly evolving system. Clearly, the nature and quality of outputs are instructive as to whether the feedback loop process is meeting our objectives. An important distinction here is that the mere correlation of an output is not conclusive as to whether it is caused by the input. 

Causality as a concept in systems thinking focuses on deciphering the way in which constituents influence each other. As such, at the outset, it is essential to have an eye as to whether the conditions within which the system operates are fit for purpose. Understanding causality leads to a deeper perspective on agency, feedback loops, connections and relationships, all of which are vital to the process.

When The Dream Doesn’t Work

Now that we have reviewed systems theory briefly, let’s take stock and consider its relevance to our own enterprises. While systems thinking is a useful prism through which to see the world, it is not offered as a substitute for the all-important human considerations; it is simply there to support them. An operating environment designed to promote collective intelligence and its evolution, while shoring up the value of expertise and human engagement, is clearly a winning formula whether the objectives are in business, science, the arts, economics or society at large.

So, to come full circle, let’s examine when the dream simply doesn’t work - when the vehicle for the realization of the vision is all wrong. We have noted previously, the ill-fitting suit that is social media in the development of ideas, be they for internal purposes or public-facing. 

On some levels, it seems a no-brainer to say that internal endeavours are simply square pegs in a round social media hole. Social media is a small picture, reactive and short-term space when it comes to ideation. In this chaotic environment, so much focus is lost in both marketing and client service efforts. Very often a product or service is misunderstood, question marks can hang over who the key team members are, and an atmosphere of distrust and, hence, brand impairment, can easily unfold. Moreover, in thought-generation efforts, intellectual property may not be protected, product and services ideas can be inhibited, and may not even develop at all.

Worse, experts and other professionals are not properly acknowledged and valued in this arena, with valuable contributions falling on deaf ears, leading to disillusion and low morale. The enterprise cannot properly distinguish itself from the madding crowd, its messaging lost in algorithmic advertising, with data either not captured or, at best, skewed and incomplete. All in all, the use of non-proprietary platforms is a dissatisfying and costly experience for the team as a whole - with the “dream” remaining unrealized. 

A bespoke and proprietary operating environment, on the other hand, is big-picture, proactive and longer-term thinking in application. It is specifically designed to foster true ideation, to uncover new opportunities and to discover unknown unknowns through supported interaction. This has to be the way to go. 

Put simply, all organizations need a discrete platform to leverage expertise, to derive meaningful data and to promote ongoing engagement from a team with a clear identity and a sense of camaraderie. In fact, the paradigm shift towards this new normal is already fully underway, and now propelled by the COVID pandemic. It seems Thomas S. Kuhn was right to suggest that shifts are non-linear and that we should prepare for the unexpected. The time seems right to call Systems Support - in pursuit of a dream.

diagram of different types of system mapping