Queueing theory in action: optimizing supply chains from the inside out
Queues are everywhere in manufacturing and logistics—yet they are often invisible and unmanaged. From idle trucks to stalled work-in-progress, hidden bottlenecks cost time, money, and trust. In this i
📝 This article was originally published on the QueueworX blog
Queues aren’t always visible—but in manufacturing and logistics, they are everywhere. They live in the trucks idling at the gate, in pallets stacked for loading, in workers waiting for raw materials, and in product batches stalled mid-process. And yet, they are rarely the focus of transformation efforts.
Queue management works like traffic control for your operations: just as a well-managed intersection prevents gridlock, effective queue management ensures that resources flow smoothly from one stage to the next. For managers or decision-makers, this means minimizing idle time, reducing inventory holding costs, and improving overall throughput. Ignore it, and inefficiencies will snowball—into overproduction, stockouts, and stalled throughput. And that is a problem—because unmanaged queues not only mean delays and waste, but also missed opportunities.
As McKinsey notes, manufacturers and logistics firms that streamline internal flow can improve throughput by up to 30%—often without adding staff or equipment.
You can visualize this as a river: if debris builds up, the flow slows, potentially causing floods downstream. By implementing robust queue management systems, you can ensure a steady, predictable stream that adapts to demand fluctuations.
To fully appreciate the importance of queue management, consider the broader context of supply chain streamlining. According to the World Economic Forum, supply chain disruptions can reduce global GDP by up to 1% annually, with queues playing a significant role in these disruptions. You might be dealing with seasonal peaks, supplier delays, or internal bottlenecks, all of which exacerbate queue issues. For example, a queue of unfinished goods caused by machine breakdowns doesn’t just waste time—it ties up capital in work-in-progress inventory that could be better used elsewhere. This is where proactive strategies come into play, helping you identify and mitigate these pain points before they escalate.
In this guide, we explore how queue management works in industrial settings, where it breaks down, and how smart design can turn flow into a competitive advantage.
Why queues are the hidden bottleneck
In manufacturing, a queue isn’t just a line—it is inventory waiting to become value. In logistics, it is a vehicle, a worker, or a process step waiting for a green light. And while they might not always look like queues in the traditional sense, they slow things down just the same.
What makes queues so powerful—and so risky—is that they are often invisible. Lean practitioners are trained to hunt for waste. Digital teams look to automate workflows. But queues often hide in plain sight, gradually choking throughput.
They are:
At inbound gates, where trucks back up during morning peaks
At packing stations, where goods accumulate faster than they are processed
At shared workstations, where employees compete for limited tools or testing equipment
Or in more subtle forms:
Raw materials staged too early, causing clutter and confusion
Work-in-progress inventory piling up between stations
Poorly timed shifts or truck arrivals, leading to bottlenecks at docks
Each of these creates friction. And the longer they persist, the more they cascade—impacting labor costs, asset utilization, customer SLAs, and even safety.
As lean manufacturing pioneer Shigeo Shingo once said:
The most dangerous kind of waste is the waste we do not recognize.
We saw this clearly in our article on Stuck in Port: Supply Chain Queues, where port congestion and truck delays mirrored the same internal issues many factories and distribution centers face—queues forming where nobody is looking.
The cost—and cause—of inefficient queues
Bad queues aren’t just inconvenient. They cost time, money, and trust. According to Deloitte, supply chains that don’t manage internal flow suffer from:
20–30% more idle time at workstations or docks
Lower resource utilization, particularly during peaks
Missed delivery windows, driving penalties and lost revenue
Higher overtime and labor churn, as staff absorb the friction
The above issues, however, don’t appear out of nowhere. Inefficient queues are usually symptoms of deeper design problems, such as:
Batching processes that release too much work at once
Uncoordinated truck arrivals or shift handoffs that overload docks or stations
Poor layout or floor planning that causes blockages (see: Why layout matters)
Disconnected systems, like Warehouse Management Systems (WMS) or Yard Management Systems (YMS) that don’t sync with planning
Overreliance on headcount as a fix for throughput issues (explained here)
In many facilities, a single underperforming station—such as a shared testing bench—can quietly introduce delays across the entire line. But queue modeling often reveals that even small upstream changes can rebalance flow and improve cycle time significantly.
The result of inaction? Frustrated workers, stressed supervisors, and throughput goals that remain just out of reach.
Principles of smart queue management
Now that we have explored where queues form and why they matter, let’s shift to how to fix them.
The key is not just better scheduling or more floor space—it’s a more systematic, data-informed approach. That is where queueing theory comes in: a mathematical framework for analyzing and optimizing waiting systems. Originally developed for telephone networks, it now powers strategies across manufacturing, logistics, and service industries.
By understanding arrival rates, service times, and resource constraints, you can model real-world processes and predict bottlenecks—before they disrupt operations. Whether you are managing trucks at a gate or work-in-progress on the floor, queueing theory helps you find the right balance between flow and capacity.
The goal isn’t to eliminate all queues (that is impossible), but to make them efficient, visible, and well-managed.
1. Visualize the flow
Start by making queues visible. Map the process end to end—where things wait, how long, and why.
Use heatmaps, dashboards, or sensors to track truck arrivals, work-in-process (WIP) build-up, or peak congestion at shared stations. In some sites, IoT trackers or basic WMS/YMS data can reveal hours of delays.
2. Predict and Plan
Use historical data to anticipate congestion. When do trucks spike? When does shift change stall production?
Simulation tools (even in Excel or Python) can model flow and test what-if scenarios. We worked with one fulfillment center to redesign their packing zone after a basic queue simulation showed a hidden bottleneck causing 45 minutes of delay each day.
3. Balance supply and Capacity
Smooth flow beats high peaks. Instead of letting trucks or work pile up during shift changes or end-of-week rushes, stagger arrivals and create buffer zones.
Some logistics providers now offer reservation slots for drivers—reducing idle time and avoiding “truck hives” during peak windows. In manufacturing, balanced cell design keeps work moving without starving downstream steps.
4. Prioritize and Segment
Not all work is equal. Use fast-lanes, triage queues, or color-coded staging to differentiate urgent from routine tasks.
This reduces interruptions, protects service-level agreements, and helps floor staff focus on what matters most.
5. Integrate queue logic into tech
Good queue management needs to live inside your systems—not outside. Link your queue strategy to your:
Warehouse Management System (WMS)
Transportation Management System (TMS)
Appointment scheduling tools
Production Planning systems (ERP or MES)
While a complete overhaul may not be necessary, the right hand needs to know what the left is doing.
6. Eliminate the waste
Finally, look for queues that exist purely out of habit. Can a pre-check step be skipped? Can you use a Kanban card instead of batching? Can staff be cross-trained to absorb peaks?
In some plants, raw materials are staged too early—creating floor congestion and prep confusion. We’ve seen cases where simple queue analysis helped reduce unnecessary staging and free up space without sacrificing readiness.
📌 The wisdom of the tortoise
As Taiichi Ohno, architect of the Toyota Production System, once said:
The slower but consistent tortoise causes less waste and is more desirable than the speedy hare that races ahead and then stops occasionally to doze. The Toyota Production System can be realized only when all the workers become tortoises.
In other words, smart operations aren’t about bursts of speed—they are about steady, predictable flow. The same applies to queue management: a rush of trucks, tasks, or parts that overwhelms a system does more harm than good.
Queue discipline is about pacing work to match capacity, avoiding the chaos of surges followed by stalls. That means training your team to recognize early signs of friction, managing inputs proactively, and building a culture that values consistency over firefighting.
Real-world wins
Let’s look at how organizations across sectors have addressed queuing challenges with smart design—not just more resources.
Toyota: building flow into the fabric
Toyota’s production system revolutionized manufacturing with the concept of pull-based flow. Instead of pushing parts downstream, each workstation only requests more when it’s ready. Visual signals like the Andon cord let any operator flag a blockage instantly—ensuring queues are surfaced and addressed in real time.
Amazon: logistics at algorithmic scale
In logistics, Amazon’s fulfillment centers are a benchmark in queue management. Their use of robotics, conveyor systems, and AI algorithms helps optimize the flow of packages—minimizing wait times in sorting, packing, and staging queues. This orchestration enables them to process millions of items daily while maintaining industry-leading delivery speeds. Queue times in certain operations have been cut by as much as 50% through intelligent routing and dynamic load balancing.
But the benefits extend beyond speed. According to Deloitte, effective queue management can lower operational costs by 10–15% by reducing excess labor hours and in-process inventory. It also improves sustainability by minimizing idle equipment and energy waste—critical as logistics firms aim to reduce their carbon footprints.
Girteka Logistics: smart queuing at scale
At a series of high-volume recruitment events, Girteka Logistics, one of Europe’s largest asset-based transport companies, introduced self-check-in stations and SMS-based virtual queuing. Candidates could register remotely and wait in comfort, cutting down hallway congestion and enabling staff to focus on interviews, not line management. Candidate flow increased significantly without requiring more HR staff.
Starbucks: FIFO + parallel processing
Faced with growing wait times, some Starbucks outlets restructured their bar flow using First In, First Out (FIFO) logic and better task segmentation. By enabling baristas and cashiers to work in parallel, and reducing interdependencies, they projected a reduction in average idle time by nearly 2 minutes, and capped customer wait times around 5 minutes. Queue design wasn’t just about order—it was about orchestration.
Manufacturing with theory in mind
A thermometer manufacturer used queueing theory to rework their production schedule—prioritizing based on raw material lead times and component dependencies. This reduced delays during shortages and smoothed production cycles. Meanwhile, an e-commerce fulfillment center used Python-based simulation to compare packing layouts. The most efficient design turned out to be the most cost-effective—proving that data-driven queue modeling pays off.
Dock appointments that work
At a U.S. manufacturing plant, uncoordinated truck arrivals caused daily dock congestion. By implementing a simple appointment board with SMS updates, they reduced wait times by a third in just weeks. A larger distribution center went a step further—integrating their Transportation Management System (TMS) with digital queuing logic. This led to a 30% drop in truck delays and a 20% increase in dock utilization.
From queue to competitive advantage
Queue management isn’t just about shaving seconds, but about designing a system that flows.
As Josh Nelson of the Hackett Group put it:
You don’t just compete on price or product—you compete on the experience of working with you.
That applies just as much to truck drivers and warehouse teams as to customers.
When you streamline queues:
You reduce delays and increase throughput
You lower labor costs without overworking staff
You meet delivery windows without firefighting
You protect safety and reduce stress
More importantly, you build a system that flexes under pressure—and delivers under load.
Conclusion: from bottleneck to breakthrough
The queues are already there. Whether you see them or not.
If you want a more resilient, agile supply chain, start by asking: Where are we waiting? And why?
Queue management is the missing link between process design and real-world execution. Once you make it visible—and measurable—you can start to fix it.
And when you do, you will find what the best operators already know: flow wins.