From the floor
Using the approach described on this page, a UK pharmaceutical warehouse operation I managed improved lines picked per hour from 103 to 125 — a 21% year-on-year improvement. No new equipment, no capital spend. Read the full case study →
What actually drives low efficiency
Before targeting efficiency improvements, it's worth being specific about what's actually limiting throughput. The most common causes in UK warehouse environments:
- No consistent measurement baseline — you can't improve what you're not measuring. Many warehouses have no reliable LPH figure, making it impossible to gauge progress
- Poor slotting — products stored too far from their pick frequency, forcing unnecessary travel and increasing pick cycle time
- Replenishment gaps — pickers breaking flow to find a supervisor, wait for a forklift, or report a stockout disrupts rhythm and adds idle time
- Imbalanced workload distribution — some pickers overloaded, others underutilised, with no visibility of where the bottleneck sits
- No feedback loops — pickers who don't know how they're performing against a target have no reason to adjust their pace or approach
What works in practice
1. Establish a measurement framework first
Lines picked per hour (LPH) is the most practical throughput metric for most warehouse operations. It's simple to calculate, comparable over time, and meaningful to pickers. Before attempting to improve efficiency, establish a reliable weekly LPH baseline — ideally split by shift, team, and individual where the operation allows.
Don't wait for a WMS to do this. A simple spreadsheet tracking daily pick volume against clocked hours gives you what you need to get started.
2. Identify and target the biggest inefficiencies first
Once you have data, look for the patterns. Which shifts consistently underperform? Which zones generate the most travel time? Where do pickers spend time waiting, querying, or searching? The biggest gains usually come from addressing one or two systemic causes rather than broadly trying to "improve performance."
3. Slotting review
Run an ABC analysis on your product range — A-items (high velocity) should be in prime pick locations (closest to the pick start point, at height, easiest access). Even a partial slotting review for top-moving lines typically delivers measurable efficiency gains within days.
4. Individual performance feedback
Sharing individual LPH data with pickers is one of the most consistently effective interventions — not as a punitive measure, but as a feedback loop. Pickers who can see their own performance relative to the team average and their own previous week typically self-regulate upward. The framing matters: this is information, not a warning.
5. Involve the team in identifying blockers
Pickers know exactly what's slowing them down. Regular short conversations (5–10 minutes, weekly) asking specifically "what's getting in your way this week?" surface practical blockers that management often can't see. These are frequently the highest-impact fixes with the lowest cost to implement.
Tools that support efficiency improvement
| Tool | What it helps with | Limitations |
|---|---|---|
| WMS with pick analytics | Automated LPH calculation; pick path optimisation; replenishment triggers; individual productivity reports | Requires clean setup and ongoing master data maintenance; implementation is a significant project |
| Monday.com | Manual LPH tracking dashboards; visible team performance boards; workflow tracking alongside pick operations | Requires manual data entry; not designed for warehouse operations specifically; no pick path logic |
| Smartsheet | Structured data capture with conditional formatting; weekly reporting templates; integration with other systems via API | Similar to Monday.com — useful for reporting but not for operational pick management |
| Spreadsheet (Excel / Google Sheets) | Free; flexible; most warehouse managers already know how to use them; sufficient for tracking LPH baseline and running ABC analysis | Manual effort; no automation; harder to scale; can become unwieldy without discipline |
Recommendations by use case
Small operation (under 10 pickers)
Start with a spreadsheet-based LPH tracker and a slotting review. These two steps alone typically deliver 10–15% improvement before any software is needed.
Mid-size operation (10–50 pickers)
A WMS with basic pick analytics becomes worthwhile once you're managing multiple teams and shifts. Focus on establishing the measurement discipline manually first so you understand what to look for in a WMS.
High-volume / time-sensitive ops
Pick path optimisation within a WMS has the highest ROI in high-volume environments. Voice picking or scan-to-confirm can also reduce cognitive load and error rates simultaneously.
Operations with high agency reliance
Standardised zone induction and clear LPH targets from day one are more effective than any technology investment. Agency workers perform better with explicit expectations set upfront.