The Bottleneck Fallacy: Why Local Fixes Fail Global Systems

When laboratory turnaround times begin to slip, the instinct is almost always the same: identify the source of the delay and deal with it.

So, you buy a faster analyzer. Hire another technologist for accessioning. Upgrade the centrifuge.

Problem solved? Not necessarily. The delay has simply moved elsewhere.

Speed up one stage of the workflow, and another can quickly become overwhelmed. Increase accessioning capacity and the analytical section may struggle to handle the additional volume. Expanding analytical capacity and reporting suddenly falls behind.

Improving one part of the laboratory rarely improves the performance of the entire system.¹

This is the Bottleneck Fallacy: the assumption that fixing the slowest step will automatically increase overall laboratory output.

Research into organizational performance suggests otherwise. Productivity depends less on the performance of individual departments or pieces of equipment than on how effectively the system functions as a whole.¹

The Illusion of Local Optimization

A critical distinction exists between making one department more efficient and improving the performance of an entire laboratory.

Systems engineering distinguishes between a local optimum – the best possible performance of an individual component – and a global optimum – the best possible performance of the system as a whole.³

Clinical laboratories can easily fall into the trap of pursuing local optimization.

Specimen reception becomes faster. Chemistry becomes more efficient. Reporting becomes streamlined.

Yet overall turnaround time barely improves because each improvement simply shifts pressure somewhere else in the workflow.

If laboratories want to improve total performance, they need to stop optimizing departments in isolation and start improving the flow between them.

The Theory of Constraints (TOC), originally developed for manufacturing, proposes that every complex system has a limiting factor that restricts its overall performance.2

Healthcare research supports the same principle. Studies examining constraint management have found that local improvements do not always translate into better system-wide outcomes. In some cases, they can introduce new pressures elsewhere in the workflow.3

One hospital discovered this when it mapped resource conflicts throughout its operations.4

Managers realized they had become so focused on resolving individual bottlenecks that they were overlooking the structural weaknesses creating those bottlenecks in the first place.4

Identifying the source of a slowdown is only the first step.

Managing it effectively is something else entirely.

Using a technique known as buffer management, a Radiographics study applied TOC principles to diagnostic imaging workflows.5 Rather than immediately investing in faster equipment, researchers monitored the workload waiting immediately before the constraint.

By managing that queue, temporary disruptions could be identified earlier and addressed before they affected the wider system.

The lesson is straightforward: Capability is created by managing flow. Not simply by adding speed.

Laboratories are more than collections of instruments and processes.

They are complex analytical systems built around people.

That distinction matters.

A study published in the American Journal of Clinical Pathology described a Lean redesign project that successfully reduced waste throughout a clinical laboratory.6

Operationally, the project achieved its objectives.

Humanly, the outcome was more complicated.

The implementation placed significant pressure on staff and required additional interventions to restore morale. Some employees eventually left the organization.6

Improvement that does not consider the people delivering the work is unlikely to be sustainable.

Quality management research has repeatedly shown that operational failures often originate from weaknesses in systems rather than shortcomings in individuals.7 Laboratory medicine often does the opposite.

Delayed turnaround times and processing errors frequently lead to additional staffing or retraining, when the underlying workflow itself may require redesign.

“We’re so busy mopping the floor that we haven’t turned off the faucet.”

It is an all-too-familiar feeling for laboratory leaders. Days are consumed by missing samples, delayed approvals, instrument failures and urgent exceptions – while the processes generating those problems remain unchanged.

Productivity is not created by persuading people to work harder. It is created by designing systems that allow them to work smarter. Even the most capable scientists struggle inside poorly designed workflows. High-performing laboratories understand this.

They move beyond constant short-term firefighting and toward sustainable systems where common problems become predictable, manageable, and, wherever possible, preventable.

Join us for our upcoming Activation Session, where we will deconstruct the Bottleneck Fallacy and provide a framework for global system optimization in the clinical laboratory.

[1] Gaulin, M. (2025). Improve Productivity by Building Better Systems, Not Bottlenecks. Lab Manager.

[2] Praxis. (2016). Theory of Constraints: The Illusion of Local Optima. Medium.

[3] Datt et al. (2024). Theory of Constraints in Healthcare: A Systematic Literature Review. International Journal of Quality & Reliability Management.

[4] Taylor, L. J., et al. (2019). Using the Theory of Constraints to Resolve Long-standing Resource Conflicts. PMC.

[5] Rawson, J. V., et al. (2026). Application of the Theory of Constraints to Radiology. Radiographics.

[6] Persoon, T. J., et al. (2010). Laboratory Redesign and Waste Reduction. American Journal of Clinical Pathology.

[7] Zarbo, R. J. (2022). Management Systems to Structure Continuous Quality Improvement. American Journal of Clinical Pathology.

[8] Clark, D. M., Silvester, K., & Knowles, S. (2013). Lean Management Systems: Creating a Culture of Continuous Quality Improvement. Journal of Clinical Pathology.