Peak never arrives as a surprise. What surprises most warehouses is which part of the operation breaks first. Usually it is not the racking or the people. It is the small process gaps that were tolerable at normal volume: a pick face that runs dry twice a day, a label printer that jams, a stock count nobody quite trusts.
Six weeks out: fix the data
- Run cycle counts on your top-moving SKUs first, not the whole site.
- Clean up locations that hold more than one product without a reason.
- Check that every fast mover has a reserve location and a replenishment trigger.
Four weeks out: fix the flow
Walk a pick wave with a stopwatch. Where does the picker wait? Where do they walk back on themselves? Small changes here, such as moving the top 20 SKUs closer to packing, often do more than adding another person to the shift.
- Sequence pick lists by location, not by order line.
- Agree cut-off times with dispatch so waves match delivery runs.
- Pre-print or pre-stage packaging for your most common order sizes.
Two weeks out: rehearse the bad day
Pick your worst day from last year and run it again on paper. If a supplier delivery is late, who re-plans the waves? If a scanner fails, is there a spare charged and paired? If a driver calls in sick, does the warehouse know which orders to hold?
Peak rewards the warehouse that already knows where everything is.
During peak: watch exceptions, not averages
Averages hide problems until they are too big to fix. A short daily look at short picks, damaged receipts and orders waiting to ship tells you more than any end-of-week report.
