After a big ad push, check that fulfilment held up, not just that orders went out. Compare the 30 days before, during and after the campaign across dispatch, accuracy, stock, goods-in and cost. Then take the three KPIs that worsened most, find the cause and assign an owner.
After a big ad push, a 50–100 orders/day brand should run a quarterly fulfilment healthcheck that verifies service levels, inventory accuracy, and unit economics. The goal is to confirm you can sustain higher volume without rising errors, stockouts, or margin erosion. Track a small set of KPIs across order flow, warehouse execution, inventory, and customer impact, then act on the few that moved most.
Start with KPIs that reflect customer experience and execution quality. Compare the 30 days pre-campaign vs. the campaign period vs. the 30 days after. Look for sustained performance, not just a single-week recovery.
If on-time dispatch holds but WISMO rises, the issue is often carrier scan latency, incomplete tracking events, or poor delivery promise logic rather than warehouse speed.
Demand spikes amplify every weakness in stock accuracy. Measure both “system truth” and “floor truth,” then quantify the cost of being wrong.
Segment by SKU type: fast movers, long tail, bundles, and subscription-critical SKUs. A small number of SKUs usually explain most oversells and cancellations. Those SKUs need tighter replenishment triggers, more frequent cycle counts, or safer buffer stock.
After a campaign, replenishment tends to arrive in smaller, more frequent drops. If inbound processing lags, “in transit” inventory cannot be sold, and shelves stay empty even when stock exists.
A practical benchmark is consistency: dock-to-stock should not spike during high order volume weeks. If it does, you have a capacity conflict between outbound picking and inbound receiving that needs scheduling or staffing changes.
As ranges grow, complexity often causes hidden fulfilment drag. Validate that your operational model supports the way you sell, especially if subscriptions create predictable surges.
If lines per order rises after a campaign, your “orders/day” headline understates the workload. Use labour-normalised KPIs (per line, per unit) to compare periods fairly.
Close the loop with unit economics. Add a small set of cost and quality metrics to prioritise fixes that protect margin and LTV.
Turn the healthcheck into a quarterly action list: the top three KPIs that worsened, the likely root cause, and the owner. If you are scaling and need predictable dispatch, accurate stock, and resilience during spikes, a specialist fulfilment partner such as Zendbox can help standardise processes and reporting so these KPIs stay stable as volume grows.
We've seen a huge surge in growth this year and whatever we throw at Zendbox, they work to support us. Order accuracy, shipping and communication has been spot on.
A simple routine to confirm fulfilment held up after a campaign, and decide what to fix.
Compare the 30 days before the campaign, the campaign itself and the 30 days after.
Review on-time dispatch, cycle time, pick accuracy, first-attempt delivery and WISMO tickets per 100 orders.
Measure inventory accuracy, stockouts, oversells and dock-to-stock time, split by fast movers, bundles and subscription SKUs.
Add cost per order and returns data, then assign owners to the three KPIs that worsened most.
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