Warehouse Productivity Doesn’t Need More Metrics. It Needs More Context.
Warehouse operations aren’t suffering from a lack of data.
Today’s warehouses generate a constant flow of information across the supply chain from warehouse management systems (WMS), labor management platforms, payroll systems, automation technologies, and countless operational processes. The problem isn’t collecting data. It’s turning that data into decisions.
As discussed during our recent webinar, many warehouse operations already have access to productivity metrics. But too often, managers struggle to translate those metrics into actionable insights that support productivity improvement.
Why 3PL Warehouse Productivity Metrics Need More Context
Many warehouse productivity programs start with simple metrics and KPIs:
- Picks per hour
- Scans per hour
- Tasks completed
- Units processed
In a 3PL environment, productivity varies significantly based on customer requirements and workflows, order and pick type, task complexity, shift length, indirect work, inventory levels and control activities, indirect labor, and other assigned activities that may not appear in transactional WMS data.
Hill Hamrick, Co-CEO at CSW, explained that 220 scans could represent good or poor performance depending on the work performed and the employee’s shift. Without context, the number itself isn’t enough to evaluate productivity.
Warehouse Employees Need to Trust Productivity Data
If employees don’t understand how productivity is measured or believe the data is inaccurate, coaching conversations can shift toward debating the numbers rather than discussing opportunities for improvement.
During the webinar, Glynn LoPresti, Co-Founder and CEO at Takt, shared an example.
Telling an employee they’re operating at 73% efficiency often triggers debate about how the number was calculated. But showing that employee how their performance compares with peers, similar work, or the broader operation creates a different conversation entirely. Instead of arguing about the number, employees begin asking what high performers are doing differently and how they can improve.
The conversation shifts from:
“Your number isn’t good enough.”
to:
“Here’s what happened. Here’s the context behind it. Here’s what we can improve.”
How Productivity Data Can Improve Coaching
At CSW, supervisors and operations managers regularly review individual shift information to understand employee productivity and provide feedback. Rather than relying on assumptions, they can see exactly where gaps occurred, what work was performed, and where coaching opportunities exist.
Coaching isn’t limited to correcting mistakes or addressing order accuracy issues. CSW’s leaders also document positive observations, such as employees catching mislabeled inventory, following procedures correctly, or demonstrating strong operational judgment. These observations become opportunities to reinforce behaviors the organization wants to replicate across the operation.
Better Data Can Help Managers Improve, Too
Most warehouse productivity conversations focus on employees:
- Who’s performing well?
- Who needs coaching?
- Who is falling behind?
But CSW’s experience highlights another opportunity: understanding how consistently frontline managers are coaching their teams.
To address this, CSW uses structured observations to document coaching conversations and employee feedback. That history gives leadership visibility into how consistently managers are engaging their teams and supporting performance improvement.
The result is visibility into something that’s harder to measure: coaching consistency. Productivity data can help organizations understand how consistently managers are documenting observations, providing feedback, and coaching employees.
What CSW’s Second Shift Reveals
One example discussed during the webinar involved onboarding and training.
As one of its busier warehouses experienced an approximately 20% increase in throughput, CSW focused on onboarding and developing new employees, particularly on second shift.
Leadership deliberately focused on training and employee development while using performance data to monitor progress.
Over time, second-shift efficiency trended upward as new employees gained experience and received feedback from supervisors. The data gave managers visibility into performance trends as employees gained experience and moved through the onboarding process. It also provided another way to monitor employee development over time.
What Role Does a WMS Play in Warehouse Productivity?
A warehouse management system doesn’t need to become a labor management platform to improve productivity. What it should provide is a trusted operational foundation.
The WMS captures the transactions, workflows, customer requirements, inventory activity, and operational events that provide the foundation for understanding how work is performed across the warehouse. Specialized labor systems, like Takt, add another layer of detail around labor utilization, efficiency, and workforce performance.
Together, those data sources give managers a broader view of warehouse operations. As discussed in the webinar, WMS billing and revenue information can be combined with labor-cost data to provide additional visibility into profitability across warehouses, customers, projects, brands, and task types.
A Modern WMS Should Make Operational Data Usable
A modern WMS doesn’t have to do everything. But the information it contains should be accessible to the people and systems responsible for improving the operation.
CSW’s approach offers an example. The company uses Datex Footprint® WMS as it’s trusted system of record while leveraging specialized applications and data tools to address additional operational needs. As more systems become part of the technology ecosystem, the role of the WMS becomes even more important. Other applications depend on accurate, accessible operational data, making the system of record the foundation they build upon.
The Goal Isn’t Better Dashboards. It’s Better Decisions.
Generating additional metrics alone isn’t enough to improve warehouse productivity.
The real progression looks like this:
Measure → Understand → Act → Improve
For 3PLs, reaching that outcome requires enough context to understand different customers, workflows, tasks, and labor activities, along with the information managers trust and can use while it still matters.
And as AI and advanced data analytics play a larger role in warehouse decision-making, the quality, accessibility, and context behind operational data will only become more important.
Watch the Webinar
Want to see how Central Storage & Warehouse (CSW) combines WMS data and labor visibility to support frontline coaching, employee development, and continuous improvement?
Watch the on-demand webinar: People-First Productivity: How CSW Uses Real-Time Labor Visibility to Build Stronger 3PL Teams.
Frequently Asked Questions
How does 3PL software improve labor productivity?
3PL software improves labor productivity by optimizing workflows with system-directed tasks, reducing travel time with intelligent picking paths, and minimizing errors with RF scanning validation. Its intuitive user interface also drastically cuts down on training time for new employees, addressing the high attrition challenge.
Can warehouse management software reduce onboarding and training time?
Yes. Warehouse management systems that provide guided workflows, intuitive task execution, and consistent user experiences can help associates become productive more quickly and reduce dependence on tribal knowledge. In environments with seasonal labor fluctuations or higher turnover, easier adoption can improve operational continuity and reduce the burden on experienced team members.
What technology does a modern 3PLs need to stay competitive?
A modern 3PL needs a warehouse management system (WMS) with real-time inventory visibility, multi-client warehouse management, integrated billing, customer self-service and automation support. Together, these capabilities help improve operational efficiency, deliver better customer experiences and scale warehouse operations as customer expectations continue to evolve.
