When an order arrives late, the assumption is that the carrier was slow. Usually it was not. Most peak season delivery delays in Europe happen before the parcel reaches the carrier \u2014 in the hours between the order being paid for and the box leaving the warehouse. That matters, because the causes you can fix are almost all on that side.<\/p>\n\n\n\n
The most common cause, and not technically a delay at all \u2014 it is a lost day. Every warehouse has a dispatch cut-off<\/a>: orders arriving before it ship the same day, orders arriving after it wait for the next dispatch. An order placed at 16:05 against a 16:00 cut-off sits a full working day before anything happens to it, and the customer experiences that as slow delivery even though the carrier performed perfectly.<\/p>\n\n\n\n <\/p>\n\n\n\n In peak this worsens for a simple reason: order volume concentrates in the evening, after the cut-off has passed. A campaign going live at 18:00 generates a day of orders that all start a day behind.<\/p>\n\n\n\n <\/p>\n\n\n\n What to check:<\/strong> your cut-off in local time, whether it holds on Fridays, and what share of orders arrive after it.<\/p>\n\n\n\n The second cause is the one that turns a delay into a refund. The order is accepted, the customer pays, and the item is not on the shelf.<\/p>\n\n\n\n <\/p>\n\n\n\n It happens in two ways during peak. Either stock sold out faster than the system updated \u2014 a synchronisation problem rather than an inventory problem \u2014 or the replenishment you scheduled for mid-November has not arrived yet.<\/p>\n\n\n\n <\/p>\n\n\n\n Real-time stock sync<\/a> prevents the first. Nothing prevents the second except inbounding peak stock before the window opens, which is why late October is the deadline that matters.<\/p>\n\n\n\n <\/p>\n\n\n\n What to check:<\/strong> whether your stock sync is real time or a nightly batch, and when your peak replenishment is physically due to land.<\/p>\n\n\n\n This one is rarely written about and it explains a lot of November.<\/p>\n\n\n\n <\/p>\n\n\n\n A warehouse in peak season is simultaneously receiving inbound stock, dispatching outbound orders and processing the first wave of returns. All three compete for the same floor space, the same equipment and the same people. When inbound arrives during the busiest dispatch week, something gives \u2014 and what usually gives is dispatch speed.<\/p>\n\n\n\n <\/p>\n\n\n\n So peak stock should be received and put away<\/a> before the promotional window opens, not during it. A pallet arriving on 20 November does not only arrive late \u2014 it consumes capacity meant for outbound orders.<\/p>\n\n\n\n <\/p>\n\n\n\n What to check:<\/strong> your inbound schedule against your promotional calendar. If they overlap, they are competing.<\/p>\n\n\n\n The cause everyone assumes is the main one. It is real, but fourth rather than first. Carrier capacity is finite and fills through November: transit times stretch, collections slip, daily volume caps appear. A brand on one carrier has nowhere to send the overflow; a brand with multi-carrier shipping moves it to a network still flowing. We have written about this separately, because carrier concentration<\/a> is a bigger subject than one bullet point.<\/p>\n\n\n\n <\/p>\n\n\n\n What to check:<\/strong> how many carriers are connected and in use for your top three countries \u2014 not how many contracts exist.<\/p>\n\n\n\n The last cause splits in two, and both are about data rather than logistics.<\/p>\n\n\n\n <\/p>\n\n\n\n Customs.<\/strong> Cross-border lanes slow at peak as customs volume rises alongside carrier volume. Incorrect commodity codes, missing values or wrong country of origin turn a slow lane into a held consignment. For Norway, Switzerland and the United Kingdom, this is the biggest variable.<\/p>\n\n\n\n <\/p>\n\n\n\n Address quality.<\/strong> A failed first delivery attempt costs two to three days and is almost always an incomplete address, a missing apartment number or an unreachable phone number. Peak volume does not cause these errors, it multiplies them.<\/p>\n\n\n\n <\/p>\n\n\n\n2. The stock was not where the system said it was<\/h2>\n\n\n\n
3. The warehouse was doing three jobs at once<\/h2>\n\n\n\n
4. Carrier networks filled up<\/h2>\n\n\n\n
5. The parcel crossed a border, or the address was wrong<\/h2>\n\n\n\n