In Peak Without Pain: The operating blueprint that makes peak predictable, resilient, and boring, we set out a different way to think about peak. In it, we set out a blueprint that – rather than position peak as a short-term capacity challenge – frames it as a system that can be designed, tested, and stabilised well before demand arrives.

This article explains how to test that model. Most peak plans look solid on paper, for example: forecasts in place, hiring underway, and technology investments made. But when you start asking more specific questions, gaps appear quickly and you realise that the operation is often carrying more risk than it realises.

What follows is a simple 5-point starter checklist to pressure-test your readiness where it actually matters.

1- Do you actually understand what’s driving your demand?

Most organisations can tell you how much contact they handled last peak – far fewer can clearly explain what caused it. Ultimately, understanding demand is not about volume. It’s about identifying the handful of drivers that sit underneath it. In reality, the majority of contact is highly concentrated into a very small number of reasons why people need to get in touch.

At peak, these patterns are usually consistent. Customers want reassurance before purchase, visibility during fulfilment, and resolution after delivery. The specifics may vary, but the structure rarely does.

The question is whether you can quantify that clearly. 

• Do you know your top three to five contact drivers?
• Can you size them?
• Can you distinguish between necessary demand and avoidable demand? 

If you can’t answer those questions with confidence, you’re not really managing demand. You’re reacting to it.

2- Have you mapped those drivers to real interventions?

Understanding demand is only useful if it leads to action. So once you know your biggest drivers, the next question is straightforward: what are you doing about them?

In many organisations, there can be a disconnect here. Teams invest in new tools, introduce automation, or deploy AI, but those efforts are not tightly linked to the specific journeys that generate the most pressure. The result is activity minus impact.

A more effective approach is much more deliberate. For each major demand driver, there should be a clear decision about how it is handled. 

• Can it be prevented through better communication or journey design?
• Can it be resolved through self-service
• Should it be automated end-to-end?

This is also where a more specific question comes into play: have you mapped AI agents to those journeys? The value of AI at peak is not in its capabilities, but in how precisely it is applied to high-volume, repeatable interactions such as order tracking, delivery changes, and returns.

If your AI or automation strategy is not explicitly tied to your top demand drivers, it is unlikely to change your peak performance in any meaningful way.

3- Are your assumptions about peak just that – or are they actually grounded in data?

Every organisation expects volumes to increase during peak. The tricky part is trying to work out how that increase actually behaves.

• Does demand double or triple?
• Does the mix of contact reasons stay the same, or does it shift?
• Are volumes concentrated into a short spike, or spread across a longer period?
• How much of what you saw last year was specific to that moment, rather than a reliable pattern?

These questions are often harder to answer than they should be. As highlighted in earlier conversations, even experienced teams do not always have a clear view of how demand evolves across the peak cycle.

This is where the quality of your data becomes critical. Do you have data showing how volume and contact mix shift over time? Can you see how demand behaves across different phases of peak, rather than just at an aggregate level?

If your plan is based primarily on last year’s total volumes, without a deeper understanding of how demand is distributed and how it changes, you are working with an incomplete picture, with all the risks that entails.

4- What support systems are in place to ensure you maximise your investment in temporary workers?

Most operations rely on a temporary workforce to handle increased demand, but this introduces a different kind of risk. Temporary staff are, by definition, less experienced. They are still learning processes, less confident in handling complexity, and often slower to resolve issues.

The question, then, is not how many people you can hire. Instead ask: 

• How well do we support them once they are in place?
• How are you training temporary staff, and how quickly can they become effective?
• Are they relying purely on initial training, or are they supported in real time with access to the right knowledge and guidance?

If your peak plan assumes that temporary staff will perform at the same level as experienced agents, without additional support, you’ll be carrying more operational risk than you think.

5- What processes are in place when problems happen (and they will happen)?

Real-time detection and response is a critical part of maintaining stability under pressure. Because no matter how well you plan, something will go wrong during peak. A product issue, a delivery delay, a system outage, or an unexpected surge in demand can all create pressure very quickly. How quickly can you see them and respond?

The most effective operations have the ability to detect issues in real time. They can identify when specific contact topics are spiking, trace those spikes back to their source, and take action – all before the problem escalates.

Without that visibility, issues are often only recognised once they have already impacted customers, at which point the response becomes reactive rather than controlled.

Now take the next steps

Most of these problems only become clear when you start to examine how the system actually works under stress. This checklist is designed to highlight where risk may be sitting in your current approach to peak.

Individually, each of these questions is straightforward. Together, they reveal something more important.

Peak breaks when demand is not understood, when effort is not aligned to the biggest drivers, when assumptions go untested, when workforce models are fragile, and when issues are identified too late. This checklist hopefully helps you identify some of those issues.

In Peak Without Pain: The operating blueprint that makes peak predictable, resilient, and boring, we go further. The ebook sets out a complete operating model for addressing these challenges, from understanding and reducing demand through to building a more resilient workforce and embedding stability into the system.

If you want to explore how to make peak more predictable, more controlled, and more profitable, you can download the full ebook here.

And if you’re looking at your own plans and want to understand where the biggest opportunities and risks sit, get in touch. We’d be happy to talk it through.