As we examined in our ebook download Peak Without Pain: The operating blueprint that makes peak predictable, resilient, and boring, Peak tests people as much as systems.
For most retail operations, it does so in a very specific way. Peak demand hits at the exact moment that businesses scale up with new people who are inevitably undertrained, and only planning to stay for a matter of weeks.
In this article we’re going to take a deep dive into what this seasonal process actually means for how peak is designed and managed.
Because when you look closely, the model starts to feel fragile. We’re asking a temporary workforce to handle multiple complex customer interactions under pressure, often with limited experience and minimal time to learn.
It’s not a criticism of the people, but a reflection of the system they’re being asked to operate within.
Why the temporary workforce model struggles
The real challenge with temporary staffing at peak isn’t scale. It’s the combination of constraints that come with it.
Most temporary agents are only in the role for a short period of time – often six to eight weeks. That immediately limits how deeply they can understand systems, processes, and edge cases. At the same time, the window for training is compressed. There’s pressure to get people live quickly, which means onboarding is often condensed into a few days.
Then peak hits. Suddenly, those same agents are expected to handle high volumes of customer interactions, often across multiple systems, using policies that may not always be straightforward. Simultaneously, they are dealing with customers who are more time-sensitive, more emotionally invested, and less tolerant of delays or errors.
You don’t have to be a genius to know what happens next.
Resolution times increase as escalations become more frequent. Variability in performance widens across the team. Just as demand is reaching its highest point, the operation starts to feel more fragile. It’s not the individuals’ fault. Instead, it’s a consequence of how the system is designed.
The hidden cost: quality drops just when it matters most
When we talk about peak, the focus is often on volume and cost. How much demand will increase, and how many people are needed to handle it. What we talk about less often though, is what happens to quality.
At peak, many organisations experience a drop in service consistency. Customer satisfaction can dip. Resolution becomes less predictable. And customers who are already under time pressure encounter slower, less confident interactions.
This creates a double impact. Costs increase as more people are brought in to handle demand, while at the same time the quality of experience can decline. At the moment when customer expectations are highest, CSAT scores are dropping and red lights flashing on dashboards.
Speed to competence is the real constraint
The core issue here is time. Specifically, the time it takes for someone to become effective in their role. In a steady-state environment, speed-to-competence develops over months of experience. People learn patterns, build intuition, and become more efficient over time.
By contrast, peak demands immediate performance from people who are still at the very beginning of that learning curve. The gap between what is required and what is realistically achievable creates a form of operational fragility.
You can increase the number of people in the system, but if they are not yet competent, the pressure does not disappear. It simply shifts. It shows up in longer handling times, repeat contacts, and increased reliance on more experienced staff to step in and resolve issues.
Why traditional training can’t close the gap
The typical response to this challenge is to invest more in training. Extend onboarding programmes, provide more documentation, or increase supervision during the early weeks.
While these steps can help, they do not solve the underlying problem. Training is limited by time, and time is exactly what peak steals from everyone. There’s only so much information a new agent can absorb in a short period, and much of that knowledge is difficult to apply without real-world context. Under pressure, people rely on what is immediately accessible (rather than
This is where the model begins to break down. You cannot compress months of experience into a few days of training, no matter how well designed the programme is.
From training people to supporting performance
This is where a different approach is needed.
Instead of focusing solely on how to train people better, leading organisations are shifting towards designing systems that support performance in real time. The goal is to reduce the dependency on individual experience and make it easier for agents to do the right thing in the moment.
Agent assist tools play a key role here. By recognising customer intent and surfacing relevant information instantly, they can guide agents through interactions as they happen. Rather than relying on memory or manual searches, agents are supported with suggested responses, next-best actions, and contextual knowledge.
Knowledge systems also need to evolve. Static documents and fragmented information are difficult to navigate under pressure. What’s needed instead is accessible, searchable content directly tied to the task at hand, allowing agents to find what they need without breaking the flow of the interaction.
Guided workflows take this further and embed resolution paths directly into the system. Instead of deciding what to do next, agents are led through a structured process that reduces ambiguity and ensures consistency.
Together, these elements change the role of the agent, who is no longer expected to hold all the knowledge themselves. Instead, the system becomes an active participant in the interaction, providing support at the point of need.
What this looks like in practice
Let’s consider a simple example: a temporary agent receives a query, “Where is my order?”
In a traditional model, they may need to navigate multiple systems, search for the right information, interpret the data, and decide how to respond. If they’re unsure, they may escalate the issue or provide an incomplete answer.
In a more advanced model, the experience is very different. The system recognises the intent of the query immediately. Relevant order information is surfaced automatically and the agent is guided through the appropriate response. In some cases, the interaction might be resolved without requiring human intervention at all.
The difference isn’t just speed: it’s confidence, consistency, and accuracy. The agent is able to deliver a higher-quality interaction, even without extensive experience.
A more resilient approach to peak
When systems are designed in this way, the role of the temporary workforce begins to change too. Organisations still bring in additional people to handle increased demand, but those people are no longer carrying the full weight of the operation. In turn they are supported by systems that reduce complexity, guide decision-making, and handle a significant portion of the workload.
This has several effects. Peak still requires flexibility, but it no longer depends on inexperience. The number of temporary staff required can be reduced. Those who are brought in become effective more quickly. Performance becomes more consistent across the team, and the overall operation becomes more stable under pressure.
Rethinking the workforce model
The temporary workforce model is unlikely to disappear. It provides the flexibility that peak demands, and it will continue to play an important role. What needs to change is how that workforce is supported.
If the system relies on individuals to carry knowledge and make decisions without assistance, it will remain fragile. If, instead, the system is designed to provide the right support at the right time, performance becomes less dependent on tenure and more consistent across the board.
Take the next step
This challenge is just one part of a broader set of issues that shape how peak is experienced in practice.
In Peak Without Pain, we explore how to address these challenges in a more systematic way, from understanding and reducing demand, through to building a more resilient workforce and embedding stability into the operation.
If you want to explore how to make peak more predictable, more consistent, and less reliant on last-minute effort, you can download the full ebook.
And if you’re reviewing your own plans and want to understand where the biggest risks and opportunities sit, get in touch. We’d be happy to talk it through.
