First Step of the Cooplexity Model: Managing Uncertainty

The first step of the Cooplexity model addresses how to manage uncertainty and the anxiety that accompanies it.

Remember your first day at work? You're excited, but butterflies flutter in your stomach. They've explained the company, your role, and the team. Yes, that's true, but when you get to your desk, you feel a void.

That feeling repeats with significant changes: a promotion, a team change, a restructuring, a major new client. Even top executives, CEOs, and presidents experience it. In the end, we're all human.

Every situation of uncertainty is associated with a feeling of unease and anxiety; it's inevitable. But where exactly does that feeling come from? Uncertainty manifests itself in various ways.

That feeling repeats with significant changes: a promotion, a team change, a restructuring, a major new client. Even top executives, CEOs, and presidents experience it. In the end, we're all human.

Every situation of uncertainty is associated with a feeling of unease and anxiety; it's inevitable. But where exactly does that feeling come from? Uncertainty manifests itself in various ways.

Types of Uncertainty

Uncertainty manifests in various forms.

Due to lack of information: We don't know what to do because data is missing.
Due to unpredictability in people: We don't know how someone will react, how a team will act, or what a client will decide.
Due to excess options and interconnections, we don't know what consequences each action will have because everything is interconnected.

In all cases, the common denominator is the sensation of loss of control.

Impact of Anxiety on Decisions

The first challenge a person faces in a change situation is a sense of insecurity, the absence of a preferred course of action, or even a lack of criteria to choose between alternatives. Uncertainty doesn't paralyse us because of a lack of information, but because of the anxiety it generates. Every change process begins with a first obstacle: insecurity—that diffuse sensation that arises when there is no clear line of action or even a criterion to choose between several alternatives.

This fact produces anxiety and creates a state of emotional instability that, in some cases, can lead to a collapse in decision-making. The problem with anxiety is that it distracts us from the objective and focuses our cognitive effort on finding ways to reduce it. Decisions made in anxious situations seek to reduce it, even when they are not entirely accurate.

It's like the joke about the drunk who searches for his keys under a streetlamp, and when asked where he lost them, points far away. The person asking is surprised and questions why he searches under the streetlamp. The drunk replies that it's where he has light. The decision doesn't seek to solve the problem but to reduce anxiety, giving a false sense of security. In a way, it neutralises the symptoms.

Uncertainty not only refers to a lack of information but also encompasses people's expectations about someone's opinion, action, reaction, or decision.

A third case concerns the number of possible options a decision can have, the number of potential consequences of each, or the number of interconnections that make it impossible to predict behaviour or expect a result with reasonable probability.

This last case is closely related to the outcome of human interactions. Each person can have different perspectives and analysis contexts, varying knowledge of a subject, diverse interests or motivations, and ultimately seeks to influence a decision in one direction or another. The result of all interactions is the creation of reality in real time.

Over time, it's possible to explain what was decided or happened by looking back and analysing causes and conditions—this is called retrospective coherence. However, looking to the future makes anticipating the result very difficult, and sometimes impossible.

In complexity science and systems theory, we talk about emergent behaviours, precisely those arising from interactions among multiple system elements. These behaviours result from the multiplicity of interactions and the coupling of different forces.

About the Solution

When knowledge exists, it's sufficient to obtain it through the appropriate means: consulting experts, advisors, or consultants; taking courses or collaborating with universities or specialised organisations; hiring personnel with relevant capabilities or knowledge; or acquiring a company that already has it. However, none of the above is possible if the knowledge doesn't exist beforehand. In that case, it's necessary to generate that knowledge through experimentation and trial and error.

It's true that, after some time, someone will look back and doubt the profitability of the efforts or steps taken. It's always easy to judge the past with present knowledge. However, proactivity and resolve were necessary to make decisions, sometimes based only on intuition.

A key factor in this process will be tolerance for error, both at the individual and cultural levels. It's well known that people, especially the most perfectionistic, develop an aversion to error and try to avoid situations that could produce it. The same happens in some organisations, where error is culturally penalised, discouraging experimentation.

Nevertheless, without experimentation, there is no innovation, adaptation to change, or leadership. And since business, social, political, and economic contexts are constantly changing, without experimentation, there is ultimately no survival.

Dimensions

Personal Dimension

The first dimension of error tolerance is personal. One must know oneself and have enough self-confidence to recognise that, regardless of the errors committed, we usually regret inaction most.

It's while walking that we encounter obstacles and can overcome them. Without movement, there is no possibility of adaptation. Error must be reinterpreted as the obligatory toll of learning, without which the knowledge that reduces uncertainty is not generated.

Personal development, coaching, positive psychology, or exercises from Dr. Albert Ellis's Rational Emotive Behavior Therapy (REBT) can be invaluable.

Cultural Dimension

The second dimension, the cultural one, concerns an organisation's way of understanding and doing things. Just as perfectionism can lead to collapse, a culture characterised by strong judgment and little tolerance for error or criticism ends in inaction. In that context, it's much safer for the individual to stay on the sidelines than to bet on change. It's true that, in the long term, this inaction will take a toll, both collectively and individually, but in this case, the short-term weighs more heavily in the decision. The harm is clearly identified, and one is aware of its cost, implications, and consequences.

By contrast, the benefits of committing, contributing, and assuming responsibilities are only theoretical, not necessarily proportional to the risk, and never immediate. Given that organisational leadership is the fundamental factor in shaping a culture, the top management's commitment to an innovative approach must be evident.

How can a leader shift their team's culture toward greater tolerance for error? Imagine the following situation: the leader micromanages because they believe their team members are not committed. These team members, in turn, avoid making decisions because they perceive risk. Here, we can combine two tools:

Virtuous Circle of Experimentation.

The leader and team members agree on the objective, diagnosis, and desired outcome. The leader sets the evaluation parameters to measure success, but it is the team members who explore action options, anticipate their impact, define the performance criteria, and implement the decision. By identifying the impact of the decision on the parameters, the team members receive the necessary feedback to make adjustments.

Delegation Progress Stages.

The leader and team members agree on a five-level delegation table: from following precise instructions, through proposing options, recommending an action or acting and reporting, to deciding autonomously. By doing so, a public, objective, and known method is established, serving as a reference point, providing security for both parties, and eliminating the need for immediate human interpretation.

The combination of the two tools allows the team to experiment within clear limits, while the leader maintains visibility without intervening in every decision.

Practical Tools

Several elements will help address these problems.

Adaptability Capacity

"Strategy matters, but in changing winds survival depends on how fast we can trim the sails."

It's not about having the solution upfront, let alone a defined success trajectory. It's about having the capacity to modify the status quo when circumstances require it. Despite careful analysis of the extent and depth of the impact of our decisions, there will always be a margin of error in a complex context. Moreover, many solutions will appear as valid alternatives—what we call local optima. What there will hardly be is a solution that provides absolute security—a global optimum.

This has enormous relevance when designing policies or making decisions, as we must build sufficient margin for action and flexibility for quick reorientation. It doesn't necessarily mean varying the action strategy but rather endowing the necessary mechanisms to ensure that flexibility. Otherwise, heavy investments, high fixed costs, or excessive debt can limit it. A paradigmatic case is WeWork, one of the world's largest coworking companies. Its business model was based on signing long-term leases for large office spaces, which it then sublet as flexible workspaces. When the COVID-19 pandemic accelerated remote work and emptied much of those spaces, the company found itself trapped in very rigid real estate and financial commitments. In 2023, it declared bankruptcy with nearly $19 billion in debt and regained manoeuvrability only after renegotiating or cancelling a significant portion of its leases, reducing future rent obligations by over $12 billion. This example illustrates how, in complex environments, a lack of structural flexibility can severely limit strategic adaptability.

In contrast, a case I know personally is Inditex's production and response capacity, led by brands like Zara. It's widely known that its stores receive restocks several times a week, and thanks to a highly integrated logistics network, orders from sales points can be delivered in just a few days. How is this speed of adaptation possible? Inditex secures key raw materials, such as fabrics, through long-term advance purchases and organises production in batches with different finishing levels. Thus, when manufacturing is needed, the process is speedy because it uses already semi-finished garments or fabrics. When it is not, the risk of surpluses and waste is significantly reduced.

Cost of Error

"Experiment freely but always know where the dominoes must stop."

An organisation must allow experimentation while ensuring decisions align with the strategy. There must be space for creativity and innovation, as well as control and correction mechanisms.

If limits are too broad (what we call open systems), divergence can render creativity unproductive. If, on the contrary, limits are too narrow (closed systems), discipline can constrain decisions so severely that innovation is lost. Faced with uncertainty, it's obvious we can't define the limits of experimentation exactly, precisely because knowledge is lacking. If there's no experimentation, no knowledge is generated, and we won't escape the ignorance loop.

Conversely, if limits are too lax, experiments or risky decisions can compromise the organisation's survival. The answer to what margin to allow—or even facilitate—is not clear and never will be, precisely because of that lack of security. What is clear is that the limit must avoid excessive error cost or put survival at risk—the very thing we're trying to ensure.

Identification of Alternatives

"More paths appear when we stop searching for the only ‘right’ one."

Exploring alternatives begins when we stop chasing the perfect answer and start mapping the many possible ones. Each new option we uncover expands our field of vision and reduces the illusion that there is only one correct path.

Something I frequently encounter is executives seeking security in complex or uncertain decisions. Yes, driven by pressure to deliver results, they push against the limits we mentioned earlier, obtaining the opposite of what they seek. The solution is to dedicate intentional, conscious effort to searching for alternatives, expanding options, and avoiding simplification. The problem is that, in complex contexts, we can't precisely know the available decision options due to limited knowledge.

In this case, I propose that Herbert Simon's procedural rationality inspire the decision process. He won the Nobel Prize in Economics in 1978 for his research on decision-making processes in economic organisations. It refers to how people make decisions, focusing not on the result of the decision (what is decided), but on the process by which it is reached (how it is decided). This perspective arises as a critique of classical or substantive rationality, which assumes agents always choose the optimal option using all available information and without cognitive limitations.

Sequence	Substantive Rationality	Procedural Rationality
1.- Identification	List of known options.	Identification of new alternatives.
2.- Consequences	Prediction of optimal result.	Analysis of consequences.
3.- Criterion	Maximisation of the utility or benefit criterion.	Establishment of a decision criterion.
4.- Decision	Selection of the best possible option (optimal).	Making the decision.

Reverse Analysis

"To find the way in complexity, begin at the destination and walk your steps backwards."

Having a vision means glimpsing the desired destination, even when the path is still unknown. Keeping our gaze fixed on that vision helps us take the steps needed to reach it, even when those steps seem illogical.

Finally, reverse analysis can help manage uncertainty arising from multiple options and relationships. Just as emergent behaviours have retrospective coherence but can't be predicted, reverse analysis establishes an action strategy starting from the desired outcome rather than from existing options. It involves exhaustively identifying the desired output and asking what direct cause would produce it.

Since the answer will still be far from reality, repeat the question until you reach the present situation. In each segment, the cause becomes the effect, and we ask again, identifying a new cause, and so on. It's like doing a reverse Ishikawa diagram. If, in the end, we reach a possible option, the decision path is defined. Otherwise, see how to overcome obstacles or, in the worst case, not proceed.

Let's look at the following example. Imagine a customer service manager who receives a vague assignment: "improve the customer experience." A direct analysis leaves her paralysed: where to begin with no budget, no team, and no metrics? A reverse analysis reframes the question. Instead of "what can I do?", she asks: "What would success look like?" She defines the outcome: "The NPS increases by 15 points in six months." Then she works backwards: what would cause this? Customers perceive faster responses. How so? She has identified the three main problems by analysing complaints and interviewing 10 key customers. How so? She has a conversation with her boss to reorganise priorities. The impossible project becomes a call that can be made this afternoon.

Conclusion

Leading Without Guarantees.

Leading in uncertainty is leading without guarantees. Leadership in complex environments requires accepting that not everything is under control. It demands humility in not having all the answers, courage to act without certainty, and flexibility to correct when necessary.

Leading in complexity is leading as a team.

The immediate reflection in a complex environment is that individual capacity is overwhelmed and needs to be complemented. Empowering and delegating are critical to bringing decision-making capacity as close as possible to the need, generating feedback loops to assess decision accuracy or evaluate corrections. Teams must share the diagnosis, objective, and solution strategy—even if tools or techniques vary by actors' knowledge or capacity.

And most importantly, it requires creating cultures where error is not penalised but leveraged as part of learning.

Next step in the model

It's no coincidence that managing uncertainty is the first step in the model. Without a minimum level of security, no evolution of the relationship is possible. As long as there is a perception of risk, our efforts are entirely dedicated to mitigating it. It's a biological rule we can't ignore.

However, once that risk is mitigated, we can interact with others, relax our individuality, and socialise; this will be the second step: managing relationships.