Poorly Defined Laboratory Workflow

A poorly defined laboratory workflow is one of the main sources of inefficiency, rework, and analytical inconsistency. When steps are not clearly structured, each analyst tends to carry out activities based on their own interpretation, which increases variability and reduces the predictability of the process. A common example: without a defined workflow, two equivalent samples can follow completely different paths within the same laboratory, depending solely on which analyst received them first.

In an analytical environment, workflow is what connects every stage, from sample receipt to result release. Therefore, when this flow is flawed, the entire system loses coherence and control.

What ISO/IEC 17025 Requires for Processes and Procedures

The ISO/IEC 17025 standard requires laboratories to operate with documented, consistent processes from sample receipt through report issuance, ensuring that the result does not depend on individual interpretation. This consistency is one of the points evaluated by INMETRO/Cgcre — Brazil’s national accreditation body — during accreditation audits.

What Is Laboratory Workflow?

Laboratory workflow is the organized sequence of steps that guides the execution of analytical activities. It defines how samples are received, logged, prepared, analyzed, reviewed, and released.

In addition, the workflow establishes responsibilities, deadlines, verification criteria, and control points throughout the process. This ensures that every step is executed in a standardized and traceable manner.

A well-defined workflow reduces operational uncertainty, improves communication across the team, and increases the laboratory’s efficiency.

Consequences of a Poorly Structured Workflow

When the workflow is not clear, frequent operational failures arise. Activities may be carried out out of sequence, records may be omitted, and responsibilities can become blurred.

As a result, rework increases. Samples need to be reprocessed, data needs to be reviewed, and deadlines are impacted. In addition, the lack of clarity makes it harder to identify bottlenecks and manage time.

Another significant impact is the loss of traceability. Without a structured workflow, it becomes difficult to reconstruct the history of the sample and the activities performed.

From a quality standpoint, the absence of a defined workflow compromises the consistency of results. Each execution can follow different paths, generating uncontrolled variability.

How to Structure an Efficient Workflow

Structuring an efficient workflow begins with detailed mapping of every step in the process. It is necessary to identify everything from the sample’s entry point through result issuance, including all intermediate activities.

In addition, each step must have defined owners, clear execution criteria, and associated records. This ensures there are no gaps in the process.

Another important point is the definition of control points. These points function as verification steps, where compliance is assessed before the process moves forward.

Communication between steps must also be structured. Information needs to flow clearly and continuously, avoiding data loss or rework.

Periodic reviews of the workflow help identify improvement opportunities and adjust the process as the laboratory evolves.

Integrating Workflow with Quality and Productivity

A well-defined workflow contributes to both quality and productivity. When steps are clear, execution becomes faster and more consistent.

In addition, standardization reduces dependence on individual knowledge and makes it easier to train new staff.

Integration between workflow and the quality system allows deviations to be identified more quickly, since there is a clear reference standard in place.

This way, the laboratory manages to balance operational efficiency with analytical reliability.

LIMS System as Support for Workflow Management

In this context, a LIMS, Laboratory Information Management System, can structure and automate the laboratory’s workflow. The system makes it possible to define activity sequences, assign tasks automatically, and control the progress of analyses in real time.

In addition, the LIMS ensures that steps are executed in the correct order, blocking progression when criteria are not met. As a result, the risk of operational failures is reduced.

The system also centralizes information, giving everyone involved access to analysis status and the data needed to carry out their activities.

Another relevant advantage is traceability. Every step is logged, including who performed it, when, and under what conditions, which facilitates audits and investigations.

However, it is important to emphasize that a LIMS does not replace proper workflow design. If the process is poorly structured, the system merely automates the inefficiency. The foundation must always be a well-defined workflow.

Conclusion

A poorly defined workflow compromises the efficiency, traceability, and quality of laboratory results. Without a clear structure, the process becomes variable, error-prone, and difficult to control.

Structuring the workflow means organizing steps, defining responsibilities, and ensuring that all activities are executed consistently. It also contributes to reducing rework and increasing productivity.

When this workflow is integrated with tools such as a LIMS, the laboratory reaches a higher level of control, organization, and visibility. The process then stops being fragmented and starts operating in a continuous, structured manner.

In an environment where data reliability is essential, a well-defined workflow is not just an operational improvement. It is a fundamental requirement for analytical quality and laboratory maturity.