Why a Modern Warehouse Execution System (WES) Must Optimize Labor—Not Just Automation

By Justin Ray, Principal, Software, DCS

The role of warehouse execution system software (WES) is shifting as fulfilment operations grow more complex. While warehouse automation has advanced rapidly, labor planning has not always kept pace. As operations layer in goods-to-person systems, robotics, and high-speed conveyance and sortation, many still rely on manual staffing decisions or disconnected labor management tools to keep everything running. 

The result? A set of challenges familiar to many operations—overtime spikes, bottlenecks at handoff points, underutilized automation, and supervisors constantly reallocating people on the fly. 

This gap highlights a broader shift happening across fulfillment operations: the constraint is no longer automation—it’s flow. And flow cannot be optimized if labor and automation are managed separately.

To truly unlock performance, a warehouse execution system must move beyond coordinating equipment. It must orchestrate a unified mix of people and automation, aligning both in real time to protect throughput and maintain flow.

The Traditional Disconnect Between WES and Labor

Historically, warehouse execution system platforms evolved to orchestrate automated systems—routing cartons, sequencing picks, releasing waves, and balancing machine throughput. Labor planning, by contrast, has lived outside that execution layer.

Some operations rely on standalone labor management systems (LMS). Others depend on supervisor experience, static reports, or prior-day data to make staffing decisions. Meanwhile, the warehouse management system (WMS) tracks order demand, and the WES manages automation flow. But no single system is responsible for coordinating all three together.

That separation creates inefficiencies. A WMS may know what needs to move. A WES may know how fast automation can run. But neither fully accounts for how labor availability, system capacity, and incoming volume must work together as a single, coordinated system. Modern fulfillment operations don’t run in silos. Execution software shouldn’t either.

Why Labor Optimization Belongs Inside the WES

A warehouse execution system sits at a unique vantage point in the warehouse. It has a real-time, system-wide view of inbound orders, wave plans, batching logic, automation capacity, and downstream constraints. That system-wide perspective enables something more powerful than static staffing models: flow intelligence.

Flow intelligence continuously evaluates three critical variables:

• The inflow of work entering the system.
• The processing capacity of available resources (both labor and automation).
• The required throughput output to meet service-level and peak-volume goals.

When these variables are coordinated within a unified execution model, the WES can generate labor recommendations that align staffing with real-time demand. Instead of asking, “Where do we need people right now?” operations can answer, “Where will we need capacity next?” and, “How should we balance people and automation to maintain flow?”

This is a fundamental shift from reactive labor management to predictive, system-wide orchestration.

From Isolated Decisions to Unified Execution

Traditional approaches optimize locally. A conveyor releases cartons when it can. A picking zone works its own queue. Labor is shifted based on visible congestion. But these decisions, while logical in isolation, fail to coordinate flow across the entire operation.

Warehouse execution system software with multi-agent orchestration (MAO) changes that.

By coordinating a unified mix of people, conveyors, sortation, automated storage and retrieval systems (AS/RS), autonomous mobile robots (AMRs), and any other automation in use, a warehouse execution system with MAO evaluates how work should be prioritized and released. It assigns balances and assigns tasks across all resources—not just individual subsystems. Labor is no longer managed separately from automation. Instead, both are treated as part of a single resource network, dynamically balanced based on real-time conditions.

The result is not just better utilization. It’s predictive throughput. Work moves through the system at the rate required to meet operational goals, even as conditions change.

Moving Beyond Static Staffing Models

Today, most staffing models are built on averages: average picks per hour, average order size, average volume per shift. But real operations rarely behave like averages. Order profiles shift. Stock keeping unit (SKU) complexity varies. Labor performance fluctuates. Automation speeds change based on system conditions. These variables introduce constant variability into the operation.

A warehouse execution system with embedded flow intelligence accounts for that variability in real time.

By continuously monitoring actual performance—comparing expected versus actual throughput across manual and automated flow zones—the system refines its recommendations over time. Labor is not assigned based on static assumptions, but on how the operation is actually performing in the moment.

This allows operations to move from rigid staffing plans to adaptive execution—where labor and automation are continuously rebalanced to maintain flow.

Smoothing Flow Instead of Reacting to Disruptions

One of the most common breakdowns in fulfillment operations occurs at handoff points—especially consolidation and shipping.

Automation may complete work faster than downstream labor can process it. Or labor-heavy areas may fall behind, starving automated systems upstream. Without coordination, these imbalances create congestion, delays, and unnecessary overtime.

Flow intelligence addresses this by synchronizing work across the operation. Instead of releasing work in large waves or reacting after bottlenecks form, the warehouse execution system meters flow continuously. It aligns release timing, resource availability, and labor recommendations to keep work moving at a steady, predictable rate.

If one area begins to slow, the system doesn’t wait for performance to degrade. It proactively adjusts priorities, reassigns resources, and rebalances workloads across both people and automation.

The goal is not just efficiency. It’s stability. A system that maintains flow under variability delivers more consistent throughput, better service levels, and less operational stress.

Turning Labor Constraints into a Coordinated Advantage

Labor remains one of the most constrained and variable elements in fulfillment. But when managed as part of a unified execution system, it becomes a powerful lever for performance.

With flow intelligence and real-time labor recommendations, operations gain visibility into critical questions:

• Where is capacity misaligned with demand?
• Which areas are at risk of bottlenecks or starvation?
• How should resources be rebalanced to protect throughput?
• How can existing labor be maximized without increasing headcount?

Because these insights are grounded in real-time system conditions—not static reports—decisions can be made proactively, not reactively.

The Next Evolution: From Recommendations to Interactive Labor Planning

As fulfillment operations become more automated and more complex, success depends on how well organizations coordinate people and automation—not just how fast individual systems can run.

This is the direction Designed Conveyor Systems (DCS) has been driving toward: shifting execution from siloed control to unified, system-wide orchestration.

That vision comes to life in in DATUM, DCS’s proprietary warehouse execution system. Today, DATUM enables this unified approach through real-time labor recommendations—guiding operations on how to balance labor and automation based on current conditions and projected demand.

With embedded multi-agent orchestration and flow intelligence, DATUM coordinates a unified mix of people, conveyors, sortation, AMRs, AS/RS, and automated systems. This transforms fragmented processes into a cohesive, adaptive operation. 

The result is more than efficiency. It’s predictive throughput: the ability to anticipate constraints, rebalance resources, and protect performance before service levels are impacted.

But this is only the beginning. The next evolution of DATUM’s flow intelligence will introduce a dedicated labor planning capability within the warehouse execution system. This provides operations with a more interactive way to visualize, adjust, and optimize labor allocation across the entire system. Operations using DATUM will experience a unified execution model that connects inflow, capacity, and throughput. In turn, they gain even greater control and flexibility into labor planning and deployment.

If your operation is investing in automation but still managing labor separately, it may be time to rethink how execution happens. Connect with DCS to learn how DATUM is redefining what a warehouse execution system can—and should—do.