Flow Intelligence: How a WES with Multi-Agent Orchestration Capabilities Unlocks Predictive Throughput

By Justin Ray, Principal, Software, DCS

High-volume fulfillment operations are no longer constrained by individual pieces of automation. Shuttles move faster, robots scale more easily, and storage systems are denser than ever. Yet many facilities still struggle to achieve consistent throughput—not because of equipment limitations, but because of flow.

As order profiles shift, peaks intensify, and operations grow more complex, static execution rules and siloed control systems fall short. Releasing work too early creates congestion. Releasing it too late starves downstream processes. Even when labor, robots, and automation are each performing well independently, overall system performance suffers without coordinated orchestration.

This is where flow intelligence changes the equation. By continuously monitoring performance, predicting bottlenecks, and dynamically optimizing how work moves through every zone, a warehouse execution system (WES) that integrates multi-agent orchestration (MAO) transforms automation from a collection of fast components into a unified, intelligent operation.

What Is Multi-Agent Orchestration?

Gartner defines multi-agent orchestration platforms as:

“…intelligent middleware that integrates and orchestrates work between various business applications, heterogeneous fleets of operational robots, and other automated agents…assigning work in near real time to adapt to changing conditions and demands.”

In practical terms, multi-agent orchestration within a WES coordinates a unified mix of people, conveyors, robots, and automation—treating every resource as part of the same execution model. 

Within a WES, MAO is the mechanism that connects the data contained in a warehouse management system (WMS) to the automated systems the WES consolidates—enabling flow intelligence. Specialized agents represent flow zones, resources, buffers, and operational objectives. Each agent monitors its own performance while collaborating with others to optimize outcomes across the entire fulfillment operation.

Rather than relying on static logic or fixed priorities, MAO dynamically coordinates decisions such as:

• When and where work should be released.
• How priorities should shift as conditions change.
• Which resources should be assigned (or reassigned) to maintain balanced workflows.

The result is a continuously adapting execution environment that responds in real-time to variability, disruptions, and demand shifts. Instead of reacting to constraints after throughput degrades, it anticipates them—unlocking a game-changing operational advantage: predictive throughput.

From Local Decisions to System-Wide Flow Intelligence

Traditional warehouse control approaches optimize locally. A conveyor releases cartons when it can. A picking zone works its own queue. Labor reacts to avoid visible congestion in an aisle. While each decision may be logical in isolation, no single layer is responsible for coordinating flow end-to-end.

Conversely, a WES that integrates MAO enables flow intelligence by shifting optimization from isolated execution to coordinated orchestration. Instead of asking, “Is this resource busy?” the system evaluates whether work is moving through the operation at the rate required to meet throughput, service, and peak-volume goals.

By continuously evaluating how work should be prioritized, released, sequenced, and balanced across all flow zones—both human and automated—the WES focuses on sustaining smooth, predictable movement through the entire operation, not just keeping individual assets occupied.

Dynamic Optimization: Keeping Flow Aligned in Real-Time

At the core of flow intelligence is dynamic optimization—the ability to adapt continuously as conditions change inside the operation. Traditional, wave-based execution releases large volumes of work at fixed intervals, creating artificial peaks and valleys as upstream processes flood the system and downstream areas scramble to catch up. 

Conversely, a WES with MAO replaces that stop-and-start rhythm with a continuous flow model, using real-time data to meter work release, reshuffle priorities, and adjust resource assignments as conditions evolve. Instead of reacting to congestion after it forms, the system continuously balances demand against capacity, keeping work moving at a steady, predictable rate across the entire operation.

This allows the system to balance demand against capacity across all workflows. If one area begins to slow, the system doesn’t wait for congestion to appear on a dashboard. It proactively redirects work, reassigns tasks across human and automated resources, and recalibrates execution plans to protect overall throughput.

The result? An operation that stays aligned to throughput goals throughout the day. Even as order profiles, labor availability, or system performance fluctuate, the WES uses MAO to prevent bottlenecks instead of reacting to them.

Continuous Monitoring and Predictive Insight Embedded in Warehouse Automation System

Flow intelligence begins with visibility into both current performance and future risks. A WES with MAO continuously monitors modeled versus actual performance across all active flow zones, tracking throughput rates, queue depths, and execution timing in real-time.

As work progresses, the system predicts completion times, required processing rates, and resource needs to meet defined service-level and peak-day goals. These predictions are continuously recalculated as conditions change, ensuring decisions remain grounded in reality—not assumptions.

This predictive insight shifts operations from reactive firefighting to proactive control. Bottlenecks are identified early, while corrective actions can still protect throughput.

Coordinating a Unified Mix of People and Warehouse Automation

Modern fulfillment operations rely on a blended mix of people, conveyors, robots, and automated equipment. Flow intelligence brings these resources together under a single execution model, coordinating how work moves across the operation rather than managing each element in isolation. A WES with MAO continuously measures real-time availability and capacity across this unified resource environment.

Using that system-wide view, work is assigned and sequenced based on current conditions and projected needs. Tasks are routed to the right combination of human and automated resources at the right time, minimizing idle labor, reducing congestion, and preventing upstream overload or downstream starvation before they impact throughput.

By treating people and automation as a coordinated resource network—rather than separate systems—flow intelligence breaks down the silos that traditionally limit performance. Humans, robots, and material handling systems operate as one system, aligned around shared throughput and service-level objectives, even as conditions change throughout the day.

Visibility That Proves What’s Working

Flow intelligence isn’t just about real-time decisions. It’s also about understanding performance over time. A warehouse execution system with MAO combines historical and real-time reporting to compare baseline operations against optimized outcomes, making improvement visible and measurable.

By tracking throughput, flow stability, and zone-level performance across shifts and peak periods, operations teams can clearly see how orchestration decisions impact results. Optimization becomes repeatable, defensible, and grounded in data.

This visibility is further strengthened through integration with vision systems, enabling more accurate resource detection and enhanced safety management. Together, real-time insight and historical context support continuous improvement driven by evidence—not intuition.

Turn Flow Intelligence into Your Operation’s Execution Advantage

As fulfillment operations become more automated and more complex, the ability to move work intelligently through the facility becomes a competitive differentiator. Flow intelligence—built on continuous monitoring, predictive modeling, and dynamic optimization—allows operations to anticipate constraints, balance resources, and sustain peak throughput without relying on manual intervention or static rules.

Multi-agent orchestration integrated into a warehouse execution system is what makes this possible at scale. That capability is built directly into DATUM, DCS’s proprietary WES. By coordinating people, robots, and automation as a single system, DATUM delivers flow intelligence—transforming isolated assets into a cohesive, adaptive operation built for variability and growth.

DATUM will be on display at MODEX 2026, Booth B15511, April 13–16 at the Georgia World Congress Center. Attendees will get a firsthand look at how execution software can synchronize and orchestrate an entire fulfillment operation to drive predictive throughput, end-to-end. Connect with DCS to learn how DATUM is redefining what a WES can—and should—do.