Event professionals are trained to manage two types of decisions: the routine and the emergency. We know where the toilets are. We know how to respond to a fire. But between these poles lies a critical, often overlooked third category — the complex, unexpected, context-specific decision that doesn’t trigger an emergency plan but can have cascading effects if mishandled.

We call this space “the fuzzy middle.” It’s where the decision to open a grandstand during unexpected rain, to redirect crowd flow, or to manage conflicting stakeholder expectations happens — all in real time, with limited information and no playbook. It’s not about firefighting; it’s about foresight, improvisation, and judgement under pressure.

This zone is especially dangerous because its consequences are not immediately visible. A decision that seems minor — such as moving a barrier or reassigning staff — can have ripple effects that undermine safety protocols, licensing conditions, or customer experience. Yet without a structured way to evaluate or explain these choices, professionals risk being blamed if things go wrong, or ignored if they go right.

By identifying this space and framing it as distinct from both routine and crisis, this research gives it the attention it deserves. It reframes complexity not as failure, but as a normal, expected part of live event delivery — and it offers a vocabulary to discuss and improve how we navigate it.

For too long, the events industry has romanticised intuition. We praise the seasoned professional who can “just feel” the right call. But when decisions are based solely on gut feeling — unrecorded, untested, and unshared — we limit our capacity to learn, improve, or protect ourselves when scrutiny follows.

This research doesn't dismiss instinct. In fact, it recognises it as a vital tool in the decision-making toolbox. But it does challenge the idea that it should be the only one we reach for, especially when under pressure. These findings show that many decisions made during live events are influenced by prior experience, personal risk appetite, emotional load, and even fatigue — none of which are visible to others or easily transferable across teams.

Instead of relying on an individual’s instinct, this model proposes a structured way of making intuitive decisions intelligible. Drawing from Gigerenzer’s (2015) research and using the Recognition-Primed Decision (RPD) model, she shows how experienced professionals scan for cues, match patterns, simulate outcomes, and act. It’s instinct — but it’s trained, and it’s explainable.

This reframing allows teams to build a shared understanding of decision-making under pressure. It also enables more transparent evaluation of those decisions after the fact — crucial in a world where legal liability, social media, and stakeholder scrutiny are ever-present.

Events run on plans: safety plans, crowd flow diagrams, wet weather contingencies. These are vital. But as every practitioner knows, no plan survives first contact with live operations. And yet, we continue to design decision-making systems that assume plans will hold.

This research reveals a different truth: professionals don’t throw the plan away — they use it as a launchpad for improvisation. The best decisions emerge not from slavishly following instructions, but from recognising when a situation has deviated from the plan and knowing how to respond without losing control.

In this sense, the plan isn’t the answer — it’s the baseline. The critical moment comes when something unexpected happens, and teams must assess: is this a variance we can tolerate, or one that requires intervention? Do we adapt, escalate, or absorb the risk?

This framework helps formalise this process by encouraging decision-makers to anchor choices to core event goals — typically safety and customer experience — rather than blindly following protocol. This approach creates space for flexibility while maintaining professional accountability.

In short, the plan must remain agile. It’s not a cage — it’s a compass. The real professionalism lies in how we navigate the deviation.

Most event professionals learn to make decisions the hard way: on the job, under pressure, and often through painful mistakes. While experiential learning is valuable, it’s not enough to support a sector increasingly defined by complexity, legal exposure, and reputational risk. We’re relying on individual resilience instead of building collective capability.

This article argues that our current education and training systems barely touch the kinds of decisions event managers face in real time. We teach operational planning, risk registers, and project timelines — but not how to make judgment calls in fast-moving, uncertain conditions. We don't teach students how to weigh conflicting goals, respond to emotional cues, or adapt under stress.

This gap is particularly dangerous as new professionals enter the field amid shrinking teams and tighter budgets. If we don’t provide them with tools to navigate ambiguity, we leave them vulnerable — and risk repeating the same mistakes across generations.

This work calls for a shift in pedagogy: from knowledge transfer to simulated, reflective, decision-making practice. Collaborations with Silverstone and development of AI-driven event simulations are early examples of how this can be done — embedding psychological complexity into event education, without waiting for the next crisis to provide a lesson.

One of the most profound challenges uncovered by the research isn’t just how decisions are made — it’s how rarely they’re discussed. Event teams often move from crisis to clean-up without pausing to reflect, analyse, or learn from what just happened. Decisions are made, actions taken, outcomes absorbed — and then everyone moves on.

The result? A lack of shared language, shared understanding, and shared growth. There are no debriefs on how key calls were made, no frameworks to capture what worked or why. This silence reinforces the myth that decision-making is personal, unteachable, and impossible to interrogate — a myth that holds the industry back.

This framework begins to break that cycle. By adapting models like Recognition-Primed Decision-making and embedding them within the concept of ecological rationality, it creates a structured way to talk about what’s often invisible. This model positions decision-making as a team process shaped by individual traits, event conditions, organisational culture, and real-time cues.

This shared language matters. It allows for critical reflection, fair accountability, and better transfer of knowledge between events, teams, and generations. Without it, we keep solving the same problems over and over — alone, in the dark, and under pressure.