Peak 2026 – Part 1: Why your headline forecast may be giving you false confidence

A more uncertain Peak needs more than a volume forecast

The retail picture going into Peak is mixed.

KPMG’s Retail Think Tank describes 2026 performance as uneven. Non-food growth was just 0.4% across March to May, while e-commerce has been growing at around 9%. Retailers are also absorbing continued pressure from wages, National Insurance, business rates and property costs.

Last year’s Golden Quarter showed why this matters. Black Friday promotions produced only minimal overall non-food growth in November 2025, followed by total retail sales growth of 1.2% in December.

So the challenge isn’t simply deciding whether demand will be higher or lower. You need to understand where consumers might spend, when they might spend and through which channels.

The temptation in this environment is to spend more time trying to perfect the forecast. High, medium and low scenarios are useful, but each still needs translating into what it means for your operation.

Don’t just ask:

Can we process this volume?

Ask:

Can we process the way this volume will actually arrive?

Our experience suggests there are several ways those answers can be very different.

Have you tested the timing, not just the volume?

One example from our team’s retail experience involved a business preparing for its first Christmas following a significant expansion through a partner store network.

The total Peak requirement wasn’t the problem. The delivery calendar was.

The retailer was familiar with stores closing over Christmas. Its own stores had enough back-of-house stock to pre-stock ahead of closures and cope with fewer deliveries until the New Year.

The partner stores operated differently. Back-of-house capacity was limited and individual locations might receive only one or two deliveries a week.

When Christmas closures and delivery restrictions coincided with normal delivery days, some stores could face a much longer gap between deliveries than the original plan assumed.

The problem only became visible when the complete order, pick, despatch and delivery cycle was mapped by location and delivery day.

That allowed volume to be pulled forward or pushed later where necessary. It also revealed the artificial peaks this created back in the distribution operation, giving the business time to plan additional labour and equipment and prepare stores for different delivery patterns.

If you’re only looking at an annual or weekly forecast, you won’t see that.

Could your daily number be hiding an hourly problem?

This level of detail becomes even more important in highly automated operations.

Another example from our team’s previous operational experience comes from an automated retail distribution centre where Peak planning had to take account of the maximum throughput of individual parts of the automation.

The daily Peak volume looked achievable against the site’s theoretical capacity. But looking at the day as a whole concealed the real constraint.

Retail delivery profiles are rarely perfectly balanced. Orders and despatch requirements can concentrate work into particular periods. When the workload was modelled by hour, the picking or packing requirement could approach the ceiling of the automation even though total daily throughput remained within capacity.

If your constraint is a piece of equipment or an automated process, adding more people won’t make it run faster.

In this case, the team looked for ways to smooth the workload instead. Replenishment could be brought forward so it competed less with picking at the busiest time. Store delivery profiles could also be adjusted in advance, with stores agreeing to accept deliveries outside their normal windows.

The principle is simple:

Test your Peak capacity at the level where the constraint actually occurs.

For your operation that might be a week. But it could equally be a day, shift, hour, process, piece of equipment or carrier collection.

What happens if your product mix changes?

Two days with identical unit volumes can create very different operational requirements if the product mix changes.

In one major general merchandise operation, the annual demand curve was relatively predictable, building steadily from summer towards Black Friday and Christmas.

But weather could create sudden, highly concentrated demand for individual products. A heatwave could drive exceptional demand for fans. Prolonged rain could do the same for umbrellas.

Overall demand might remain broadly within expectations while an individual SKU suddenly needs to flow at a rate its normal automated route can’t support.

In this example, the response was to move reserve stock into a temporary manual pick face capable of handling the higher rate.

So when you’re assessing Peak capacity, don’t just ask how many units the building can process. Ask which units might need to move, where they’re stored and which route they have to take through your operation.

Is the stock there, but in the wrong place?

A similar issue can occur even when a demand event itself is planned.

In one toy operation, product secrecy meant the logistics provider could receive inventory without knowing which products supported forthcoming launches or promotions.

A major launch could therefore create a sudden SKU-level spike even though the event itself was known about.

The stock might already be in the warehouse, but sitting in deep reserve rather than an accessible pick location. The overall forecast could be sensible while the operation still faced replenishment pressure, additional handling and potential service risk.

It’s worth asking the same question of your Peak stock.

Having enough inventory and enough theoretical capacity does not necessarily mean you’re ready to fulfil the demand.

Five questions to ask of your Peak plan

The answer isn’t to create an ever more complicated forecast. It’s to translate the scenarios you already have into operational consequences.

Before Peak, we’d ask five questions:

1. When does the workload really occur?
   Break your forecast down far enough to expose the constraint. That might mean week, day, shift or hour.
2. What happens if the mix changes?
   Test different SKU, order and channel profiles, not just different total volumes.
3. Is the stock positioned where you need it?
   Check whether reserve locations, replenishment rates and pick-face capacity can support the expected rate of sale.
4. What is your real capacity constraint?
   Identify the process, equipment, labour pool, despatch window, carrier collection or receiving constraint that actually determines throughput.
5. What could you smooth before the pressure arrives?
   Some peaks are created by operational rules rather than consumers. Delivery schedules, replenishment activity, cut-offs and customer requirements can all concentrate work unnecessarily.

The earlier you identify these issues, the more options you have to do something about them.

Don’t plan your Peak around an average

There is no perfect Peak forecast. You aren’t going to predict every SKU, order and hour correctly.

The important thing is understanding where variability becomes operational risk and where you still have choices.

That matters when operating costs are under pressure. Adding labour and capacity everywhere is an expensive way to protect yourself against uncertainty. But running close to theoretical capacity without understanding the profile underneath your forecast creates a different risk.

Good Peak planning sits between those extremes.

You need to know which constraints genuinely need protecting, which workload can be moved or smoothed, which contingencies are worth paying for and which warning signs you need to monitor as actual demand emerges.

So as Peak 2026 approaches, don’t stop when the numbers tell you the forecast fits within capacity.

Ask one more question:

Can our operation handle the way this volume will actually flow through it?

If you can’t answer that confidently, there is still more work to do on your Peak plan.

Is your operation ready for Peak?

Contact us about stress-testing your Peak plan and identifying the operational constraints behind your forecast.