How to Measure Picker Productivity Before Hiring More Staff

When order volumes increase in a warehouse, the first reaction is often straightforward:
we need more pickers.

In many cases, this decision is taken under pressure, without clear data showing whether the current team has actually reached
its capacity limit. Hiring additional staff may seem like the safest option — but it is also the most expensive and often the
least reversible one.

This page presents a simple, practical method to evaluate picker productivity using real operational data, before deciding
to increase headcount.

The Real Problem Behind “We Need More People”

As a logistics consultant, I was asked to analyze a warehouse where the warehouse manager requested 1–2 additional picker
positions, arguing that order volumes had increased significantly.

At first glance, the argument sounded reasonable:

  • more orders,
  • more pressure,
  • longer picking times.

However, no objective productivity measurement had been performed.
The question was not how many orders we had, but how efficiently they were being picked.

The Measurement Method

Instead of introducing complex KPIs or relying on a WMS, a very simple approach was applied.

For one full working week, each picker was monitored using a stopwatch while performing picking tasks.

The following data points were collected:

  • number of picking lists completed per picker per day
  • total number of order lines processed per day
  • average time per order line
  • effective working time (based on an 8-hour shift)
  • average productivity per picker and for the entire team

No automation, no software changes, no process redesign — just direct observation and measurement.

What the Data Revealed

The results were clear and surprising:

  • roughly half of the pickers had a productivity level at about half of the team average
  • the other half consistently performed above that level
  • if all pickers had worked at the same productivity level as the team average, the warehouse could have handled
    the same order volume with approximately 75% of the existing staff

In other words, the problem was not insufficient capacity —it was high variability in individual performance.

Operational Decisions Taken

Based on these findings, several concrete decisions were made:

  • the team average productivity became the individual target
  • a bonus–malus system was introduced based on this target
  • productivity discussions shifted from “working harder” to “working consistently”

No additional staff were hired.
Instead, performance expectations were clarified and aligned across the team.

A Hidden Issue: Order Waves

The analysis revealed another important factor.

Orders were arriving in waves, with the main peak overlapping the lunch break.
As a result:

  • orders accumulated during the break
  • after lunch, pickers had to work at almost double speed to recover
  • perceived overload increased, even when daily volumes were manageable

Corrective action focused on smoothing order intake throughout the day, reducing artificial peaks and stabilizing
workload over the full 8-hour shift.

Key Takeaways

  • increased order volume does not automatically justify hiring
  • productivity variability matters more than total volume
  • simple measurements often reveal hidden capacity
  • staffing problems are frequently management and flow problems, not workforce shortages

Before adding people, measure first.

Apply This Method to Your Warehouse

To help you perform a similar first-level analysis, you can use the Picker Productivity Check Tool below.

The tool does not replace detailed operational analysis or a WMS, but it helps you answer a critical initial question:

Do you really need more pickers — or do you need better visibility?

Picker Productivity Check Tool

A simple way to evaluate picking capacity before increasing headcount.

Picker Productivity Check Tool

A simple capacity estimate based on averages — useful before increasing headcount.

How many pickers are available on the shift.
Default is 8 hours. Use effective hours if needed.
Total lines to be picked (all orders combined).
Average minutes per line, based on a quick measurement sample.
Capacity usage
—
Enter values and click Calculate.
Total available time —
Required picking time —
Estimated pickers needed (current average) —
Pickers needed if productivity improves by 10% —
Pickers needed if productivity improves by 20% —
Note: This tool provides a simplified estimate based on averages. It does not replace detailed operational analysis or a WMS.

FAQ

How do you measure picker productivity without a WMS?
Picker productivity can be measured by tracking time per order line, total lines picked per day, and comparing
individual performance to the team average. Even simple stopwatch-based measurements can reveal major efficiency gaps.

What is a good productivity benchmark for warehouse pickers?
There is no universal benchmark. The most reliable reference is the internal team average, adjusted for warehouse layout,
product profile, and order complexity.

Should I hire more pickers when order volume increases?
Not necessarily. Increased order volume does not always mean insufficient capacity. Measuring productivity first often
reveals unused potential within the existing team.

Why do some pickers perform much better than others?
Performance differences usually come from experience, work habits, layout familiarity, and task allocation — not from effort alone.

How do order waves affect picker productivity?
Order waves create artificial peaks that force pickers to rush later in the day. Smoothing order intake often improves
productivity without adding staff.

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