1 September 2025
Logistics Theories Every Modern Hospital Should Master - 1
In this first part of our Logistics Theories series, we explore four foundational ideas that shape how work flows through complex systems: Little’s Law, Theory of Constraints, Just-in-Time (JIT), and Center of Gravity. These aren’t just textbook concepts—they’re practical tools for diagnosing bottlenecks, reducing wait times, aligning operations with demand, and designing smarter team structures. Whether you’re managing a hospital, factory, or logistics team, these theories offer a powerful lens to see your operations more clearly and improve them with precision.
Piyorot Piyachan
CEO of Mutrack
Hospital logistics is no longer a support function. It’s a strategic capability that shapes patient care, staff efficiency, cost control, and long-term scalability. Yet despite its impact, logistics is often misunderstood or treated as an afterthought.
From Little’s Law to the Theory of Constraints, these foundational models help hospitals move with precision, reduce hidden costs, and deliver better care—one smart system at a time. 🐠
To lead logistics today is to master more than dashboards—it requires a deep understanding of the systems that make hospitals work. This article explores foundational logistics theories every hospital should know—from Little’s Law and the Theory of Constraints to Just-in-Time and hub-based design. These aren’t academic luxuries. They’re mental models for designing systems that scale, cut hidden costs, and improve outcomes.
1 - Little’s Law
What It Is:
Little’s Law is a fundamental principle in queuing theory that helps explain the relationship between workload, time, and capacity in any system. It states:
L = λ × W
Where:
- L = average number of items in the system (e.g., jobs waiting or in progress)
- λ = average arrival rate of those items (e.g., how many requests per hour)
- W = average time an item spends in the system
In simple terms: The longer it takes to complete a job, and the more jobs that arrive, the more work will pile up.
Why It Matters in Hospital:
Hospital operations are full of queues: patients waiting for beds, porters waiting for instructions, deliveries waiting to be moved. When a queue builds up, people often blame staffing or motivation—but Little’s Law shows the real issue might be deeper.
You can’t reduce waiting by just pushing people to move faster. You have to change the system: reduce arrival rates, shorten processing time, or increase capacity.
Real-World Example:
In a hospital we observed, there was consistent crowding in the morning hours when porters were overwhelmed by job requests for patient transfers. Leadership believed the team wasn’t moving fast enough. But when analyzed using Little’s Law, the cause was clearer:
λ (Arrival Rate): Most jobs were being requested at the same time (7:30–9:30 AM) after rounds.
W (Processing Time): Each transfer averaged 20 minutes due to paperwork and coordination.
L (Queue Size): Unsurprisingly, backlog grew rapidly.
The solution? Not more pressure—but better distribution of job requests and reduction of non-value activities during peak windows.
How to Deal With It:
Understand your actual arrival patterns. - Use timestamped job request data to visualize which hours have the heaviest traffic. Don’t guess—measure.
Shorten job duration (W). - Simplify handoff procedures. Automate parts of the dispatch. Eliminate unnecessary steps (e.g., redundant forms or approvals).
Distribute the load. - Encourage departments to schedule routine logistics jobs (like non-urgent deliveries or discharges) during off-peak windows.
Right-size capacity. - Use simulation to ask: “If we have 4 porters vs. 6 during this hour, what will L look like?” Use this to inform staffing strategies.
Communicate system limits. - Sometimes, reducing arrival rate is as simple as saying: “We can only take X jobs at a time between 8–10 AM. Please stagger requests.”
Understanding Little’s Law is not just an academic exercise—it’s a way to see your hospital through a sharper lens. When wait times feel long or resources seem stretched, this principle offers a grounded explanation. More importantly, it shows where you can intervene: by reducing the number of jobs in progress, increasing completion speed, or managing flow more evenly. In logistics, perception often distorts reality—but Little’s Law brings clarity. It allows hospital leaders to speak with data, test assumptions, and guide decisions with precision, not guesswork. And when applied correctly, it turns delay into opportunity for better design.
2 - Theory of Constraints
What It Is:
The Theory of Constraints (TOC) is a management philosophy that states:
Every system has at least one bottleneck that limits its performance.
Until you identify and address that bottleneck, improving anything else won’t help much—because the constraint will continue to block the overall flow. The core idea is simple: A system is only as fast as its slowest part.
Originally developed in manufacturing, TOC applies perfectly to hospitals, where complex systems (like portering, supply delivery, or bed turnover) must operate in harmony—but often don’t.
Why It Matters in Hospital:
You may add more porters, adopt better software, or buy new equipment—but if your process has a hidden bottleneck, none of that will improve outcomes. What happens instead? Frustration. Blame. Burnout.
In hospitals, constraints aren’t always obvious. They might be:
- A nurse who must approve every discharge job
- A delivery room with only one elevator access point
- A dispatch supervisor manually assigning every task
- A porter team that can’t take jobs during certain hours due to shift rules
If you don’t identify this constraint, you’ll waste energy trying to optimize around it.
Real-World Example:
A large general hospital upgraded to a real-time job tracking system, hoping to reduce delays in medication delivery. The data showed that even with faster porter response times, many deliveries still sat idle for 20+ minutes before pickup.
The culprit? The pharmacy department, which had only two packaging staff preparing medications for multiple wards. That was the real constraint.
So while logistics got faster, the real bottleneck—the place where everything queued up—was untouched. Only after reallocating staff and adjusting delivery windows did delays drop meaningfully.
How to Deal With It:
Find the real constraint. - Don’t guess. Use data. Ask: Where do jobs accumulate? Which part of the process has the longest wait? Which person or station is always at capacity?
Elevate the constraint. - Once found, focus your improvement efforts only on that point. Can you add more capacity? Automate part of the task? Reassign roles or extend hours?
Don’t optimize upstream or downstream—yet. - It’s tempting to improve everything. But if you fix steps that aren’t the bottleneck, you may just create longer queues at the constraint.
Move to the next. - After one constraint is elevated, the next will appear. That’s progress. TOC is cyclical: identify, improve, repeat.
The power of the Theory of Constraints lies in its simplicity: improve the weakest link, and the whole system improves. In a hospital, this means identifying the department, process, or policy that limits overall performance—and giving it focused attention. Too often, hospitals invest in blanket improvements without addressing the true constraint, leading to minimal results and wasted effort. TOC flips that approach. It urges leaders to look closely, act deliberately, and fix the right problem first. Because when the bottleneck moves, everything else flows better.
3 - Just-in-Time (JIT)
What It Is:
Just-in-Time (JIT) is a logistics philosophy that prioritizes delivering exactly what is needed, exactly when it is needed, and in exactly the amount required. It aims to eliminate waste, reduce delays, and create a smooth, efficient workflow. Originally developed in manufacturing, JIT has become increasingly relevant in healthcare—especially in dynamic, resource-constrained environments like hospitals.
Instead of building buffers or relying on guesswork, JIT relies on timely coordination, accurate information, and responsive systems. The closer the timing between a request and its fulfillment, the less waste, idle time, or friction you’ll encounter.
Why It Matters in Hospital:
Hospitals are filled with time-sensitive activities—patient transfers, medication deliveries, emergency prep, and diagnostic procedures. But more often than not, logistics teams operate blind. They dispatch porters without knowing current job loads, or they pre-assign tasks too far in advance, only for conditions to change. The result? Delays, idle waiting, duplicated work, and miscommunication.
JIT directly tackles these problems. When implemented in hospital logistics, especially through smart dispatching, it helps match supply (available porters) with demand (incoming jobs) in real time, creating a more adaptive and efficient system.
Real-World Example:
At a leading private hospital in Bangkok, the porter team previously relied on scheduled dispatching and phone-based coordination. Requests were logged manually, and porters were assigned tasks sequentially by a dispatcher—without clear visibility into which porter was already working, where they were located, or how many jobs were in their queue.
This caused repeated delays during peak hours. Dispatchers had no way to tell if someone was truly available, so some jobs were left waiting. Others were double-assigned or repeatedly called in to check on progress.
Then the hospital implemented real-time auto dispatching through the Dispatcher platform. Porters carried devices with location tracking and live job status updates. The system automatically matched each new job to the nearest available porter—not based on shifts or assumptions, but based on who was actually free at that moment and physically close to the pickup point.
Results emerged within weeks:
Job acceptance time dropped by over 40%.
Porter idle time decreased significantly, with fewer agents sitting unassigned during busy periods.
Job turnaround times became more consistent, especially during high-load hours like 10 AM – 12 PM.
This wasn’t a staffing change. It was a timing change. And that’s the core of JIT: eliminating guesswork in when and how work is assigned.
How to Deal With It:
Visualize your real-time capacity. - You can’t do JIT if you don’t know who’s working on what. Invest in tools that provide live visibility into job queues, agent availability, and location context. That’s the foundation for timely dispatching.
Automate job assignments based on real status. - Avoid scheduled or fixed sequences. Use systems that assign work dynamically, matching real-time capacity with incoming demand. When someone completes a job, the system should already know what to send them next.
Avoid over-assigning work upfront. - Porters should never be loaded with 3–4 future jobs they can’t act on yet. Assign only what they can handle now, and let the system sequence future tasks when the moment is right.
Design job request logic to match urgency. - Not all jobs require instant action. Use job types or tags to distinguish between stat, scheduled, and low-priority tasks—so dispatching decisions can reflect urgency and help avoid unnecessary rush.
Train staff to trust the system. - When JIT is new, some teams resist it—fearing chaos or preferring manual control. But once they see how it reduces delays and makes workloads fairer, they come around. Start with a trial floor or department to build confidence.
Balance real-time with real rest. - JIT shouldn’t mean burning out your team. Ensure systems account for breaks and avoid dispatching during protected rest times. The best JIT models optimize both timing and well-being.
Just-in-Time isn’t about cutting corners—it’s about designing a system that responds intelligently to actual demand. In hospitals, where patient needs fluctuate and overstocking can create chaos rather than comfort, JIT encourages precision, coordination, and trust in real-time data. With the right technology and workflows in place—like automated job dispatching for porters based on real-time availability—hospitals can operate leaner without compromising care. The goal is not to reduce resources blindly, but to align resources exactly where and when they’re needed most. That’s when lean becomes smart.
4 - Center of Gravity
What It Is:
The Center of Gravity is a spatial logistics concept used to identify the optimal physical location that minimizes total travel distance or time between multiple points. Think of it as the most efficient “central hub” from which goods or services are dispatched. It is often used in supply chain and distribution planning to determine where to build warehouses, fulfillment centers, or cross-docking facilities.
In hospitals, this concept applies just as powerfully—but instead of shipping goods to customers, you’re moving porters, equipment, samples, or patients between departments. Every additional meter matters. Every extra second of travel time adds up. The goal is to design service hubs that minimize unnecessary movement and support operational speed and efficiency.
Why It Matters in Hospital:
Hospitals are complex mazes of departments spread across floors, buildings, and wings. Yet many hospitals assign porter or logistics teams to locations based on habit, not analysis. You’ll often find a dispatch station tucked into a quiet hallway, far from action. Or linen collection points located closer to storage than to high-use wards.
That creates hidden costs: longer job durations, slower response times, and higher physical strain on porters.
Applying Center of Gravity thinking means asking:
Where should we place our service hubs to best serve the real pattern of movement inside this hospital?
Real-World Example:
Previously, the hospital operated with a single porter base on the 2nd floor, near the reception department—not because it was optimal, but simply because space was available. However, after analyzing over 4,000 job records, they discovered that this one-size-fits-all model created inefficiencies, especially across their sprawling multi-building layout. The data showed that job volume was heavily concentrated in outpatient services, emergency care, and inpatient wards—spread across eight separate buildings.
As a result, they restructured their logistics system by splitting the porter team into four distinct hubs: two dedicated to the busiest OPD buildings, one to the ER, and one to cover the inpatient complex. This hub-based model dramatically reduced internal travel time, improved responsiveness, and ensured that each team was stationed near their primary zones of activity—creating coverage that was both faster and smarter across all eight buildings.
Results emerged within weeks:
Average walking distance per job dropped by 22%.
Turnaround time improved by 17%.
Porters reported feeling less fatigued, as they were no longer “commuting” internally as much.
How to Deal With It:
Map your high-frequency zones. - Use job history data (from Dispatcher or manual logs) to identify where the majority of logistics work begins and ends. Don’t rely on assumptions—data tells the true flow.
Calculate your actual center of gravity. - Plot all origin and destination points for key services (e.g., patient transport, sample delivery, document pickup) on a floor plan. Then simulate a central point that minimizes total movement.
Think vertical, not just horizontal. - In multi-story hospitals, distance is not only lateral but vertical. Consider elevator wait times, stair usage, and how hard it is to move between floors. Sometimes two points that are horizontally close are practically far if floor transitions are difficult.
Consider multi-hub design. - Not every hospital needs one “perfect” center. Larger facilities benefit from zonal hubs, each placed at the center of activity clusters. That enables better coverage and prevents overload at any single node.
Reassess periodically. - Hospital layouts change. Departments grow or shift. Always revisit your service hub positioning every 6–12 months, especially after construction, renovations, or clinical service expansions.
Center of Gravity thinking challenges hospitals to design with intention, not convenience. When porter teams are placed based on available space rather than actual demand zones, inefficiencies compound invisibly—longer travel times, delayed handovers, and exhausted staff. But when hospitals redesign their operations around real activity data—splitting one central team into multiple hubs that align with job hotspots across departments—they unlock speed, clarity, and responsiveness. COG isn’t just about location—it’s about alignment. And in complex environments like hospitals, that alignment is everything.
Bringing It All Together
These four logistics theories aren’t just intellectual frameworks—they’re lenses through which hospitals can see their operations more clearly. Little’s Law reminds us that wait times are not mysterious—they’re mathematical, predictable, and solvable with the right balance of flow and capacity. The Theory of Constraints urges us to stop treating all bottlenecks equally and instead focus energy where it truly matters. Just-in-Time teaches that responsiveness beats overstocking—but only when paired with visibility and discipline. And Center of Gravity design reminds us that proximity isn’t preference—it’s performance.
Individually, these logistics theories offer precision. Together, they offer power. They help hospital leaders break out of reactive mode and move toward intentional design. Logistics may be invisible when it’s working well—but these principles ensure that “working well” isn’t just luck. It’s engineered.
Ready to Apply These Logistics Theories in Your Hospital?
Understanding logistics theories is a powerful first step. But real transformation happens when you start applying them—when your team sees the connection between theory and action, data and decision, structure and service. That’s exactly what our First Run program is designed to support.
First Run is a low-risk, high-impact way to see how Dispatcher works in your real hospital environment. No full rollout. No major budget shifts. Just a focused 30-day trial, grounded in your workflow, designed around your needs. During this time, we apply the very theories you’ve just explored: shortening queues (Little’s Law), identifying bottlenecks (TOC), dispatching in real time (JIT), and optimizing hub placement (Center of Gravity).
First Run was created for this exact reason. It’s a way to try Dispatcher in your hospital without making big commitments or budget shifts. It’s a way to see the cost of delay—in numbers and in experience.
It starts with one floor. One department. One trial. 🎉
You’ll gain not just software—but insight. Not just dashboards—but clarity. And your team will walk away with a stronger foundation to lead the next chapter of your hospital’s logistics transformation.
Let’s help you take that step—intelligently, intentionally, and with full support. Because the best systems aren’t built in theory—they’re proven in action.
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Piyorot Piyachan
CEO of Mutrack
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Piyorot Piyachan
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