Day-to-day lab operations rely on workflows to manage people, tasks, and systems so that work follows a consistent process every time. Defined workflows help to ensure that all the steps are done in the correct order, are free from errors, and meet regulatory requirements.
But representing lab workflows can be difficult. Without careful definition, you might introduce inaccuracies — such as skipping a step or adding unnecessary complexity — when translating a workflow to a software system or communicating it to a colleague.
Let’s take a closer look at lab workflows and how you can best represent your lab’s processes.
What Is A Workflow? A Brief Definition
The term “workflow” means different things in different situations.
In a general business sense, it refers to “the set of activities required to complete a task.” In a lab environment, it could refer to either “your lab’s business processes” or “processes managed by your laboratory information management system (LIMS).”
At Labbit, we typically define a workflow in the lab as “end-to-end sample processing from accessioning to report issuance."
Why Accurate Workflow Representation Matters In The Lab
When you take the time to represent workflows clearly, you’re not just creating a nice diagram for the wall. You’re laying the foundation for how your lab operates day to day.
Operational Impact: Fewer Errors & Faster Turnaround
Well-represented workflows make it easier for people to do the right thing every time. When the sequence of steps, decision points, and handoffs is clear, you reduce the risk of skipped steps, inconsistent handling, and unnecessary rework. Over time, this translates into fewer reruns, fewer failed assays, and more predictable turnaround times for clients and patients.
Clarity in workflow representation also makes onboarding new team members much easier. Instead of relying on tribal knowledge, you can show how work actually flows through the lab and give technicians a concrete reference they can use while they learn.
Compliance, Traceability & Audit Readiness
Clinical and regulated labs are expected to show that they follow defined procedures consistently. When workflows are well documented and accurately represented, it becomes much easier to demonstrate that you have clear, repeatable processes in place.
Diagrams, SOPs, and other artifacts that align with what actually happens at the bench support your existing quality system. They make it easier to trace what occurred when something goes wrong, to investigate deviations, and to explain your processes during inspections or audits.
A Better Foundation For Lab Software & Automation
Modern lab software, including LIMS and orchestration platforms, need a clear model of your workflows to function correctly. If your representation is incomplete or out of sync with reality, you risk encoding the wrong behavior into your systems.
When your workflow representations match what really happens in the lab, it becomes much safer to configure software, connect instruments, and add automation. You can translate the steps, decision points, and rules from your diagrams directly into a system like Labbit, knowing that you are building on a solid foundation.
The Core Building Blocks Of A Lab Workflow
Even though every lab is different, most lab workflows can be described using the same core building blocks. Making these elements explicit helps you represent your processes more consistently and makes it easier to map them into your software systems.
Inputs: Samples, Reagents & Context
Every workflow starts with inputs. In a lab, inputs include the physical materials you work with, such as samples and reagents, but also the information that travels with them.
This might include sample type, collection details, ordering physician, study identifiers, panel selections, and any special handling instructions. Clearly defining inputs ensures that each workflow step has the information it needs and that the right rules can be applied as samples move through the system.
Actions: What People & Instruments Do
Actions are the steps that move a sample or request forward. They can be manual tasks, such as pipetting, labeling, visual inspection, or review and sign-off. They can also be automated steps performed by instruments or integrated systems, such as sample preparation, incubation, analysis, or report generation.
When you represent your workflows, it helps to be explicit about who or what performs each action, and what “done” means at each step. That clarity is essential when you later translate a diagram into a configured workflow in your LIMS or automation platform.
Data & Rules: How Decisions Drive The Path
Data and rules determine how a workflow branches and when it can move forward. In the lab, this might include QC thresholds, reflex testing criteria, storage rules, batch size limits, or escalation conditions.
For example, a QC step might route samples with acceptable results to the next stage of processing, while out-of-range results trigger a repeat or a different path entirely. When you capture these rules explicitly in your workflow representation, it becomes much easier to configure decision-based routing and to ensure that exceptions are handled consistently.
Should Workflows Be Flexible Or Rigid?
In some business environments, a step-by-step process must always occur in the same way and in the same order. We call these rigid processes. Imagine a production line at a car manufacturing plant. Any deviation or inconsistency could result in a vehicle that won’t pass inspection, or worse, loss of life.
Workflows in the laboratory cannot, and often should not, be completely rigid. A workflow certainly has to have a planned path, but there must be flexibility built in to handle exceptions. For example, a starting entity, such as a sample, may not always go through the same set of activities before completing the workflow. There are often variables, and a workflow needs to be able to handle decision-based routing.
Examples of decisions that will determine the workflow path:
- Sample type (is it blood, saliva, or genomic DNA?).
- Whether a sample passes a quality control (QC) test.
- Whether you need to do automated or manual sample preparation.
- Which sequencer to use based on QC results.
- Whether a sample needs to go into long-term storage.
Rigidity and inflexibility can be your enemy in this case. By not allowing for decision trees and routing in your workflow, you’ve constrained the workflow so much that it cannot deal with exceptions.
On the other hand, workflows should not be too flexible. If there are 20 ways to accomplish the same task, or if a workflow is completed differently depending on who is performing the tasks, then there is no uniformity. This can also cause a plethora of issues down the line.
Lab assays are not simple. There’s a lot of complicated chemistry and technology behind their execution. Consequently, they require a complex series of steps to complete.
With these considerations in mind, labs need a clear way to talk about workflows so that they can be communicated from one person to the next, no matter what role the person holds.
Common Workflow Types In Modern Labs
While “workflow” is often used as a general term, most labs run several distinct workflow types side by side. Recognizing these patterns can help you decide which processes to model first and where to focus improvement efforts.
Sample Processing Workflows
These are the workflows most people think of first: the end-to-end path a sample follows from accessioning to result reporting. They typically include receiving and logging, preparation, analysis, review, and final sign-out. Within that broad path, there may be multiple variants based on sample type, panel selection, or QC outcomes.
QC & Release Workflows
Quality control workflows focus on verifying that instruments, reagents, and results meet predefined standards. They may include control runs, calibration checks, review of QC charts, and approval or hold decisions. Representing these workflows clearly helps ensure that only valid results are released and that issues are detected early.
Order & Request Workflows
Labs also rely on workflows to handle incoming orders and internal requests. These workflows cover how tests are ordered, how information is captured, how requests are validated, and how they are routed to the appropriate bench or team. Clear representation here supports faster intake, fewer ordering errors, and better communication with clients or internal stakeholders.
Reagent & Inventory Workflows
Reagent and inventory workflows govern how lots are received, qualified, stored, and consumed. They may include vendor checks, lot verification, assignment to instruments or assays, and automated re-order triggers. Modeling these workflows makes it easier to maintain traceability and reduce the risk of stockouts or expired material being used.
Instrument Maintenance & Accreditation Workflows
Instrument maintenance and accreditation activities can also be represented as workflows. These may include scheduled maintenance, calibrations, performance verifications, documentation updates, and periodic accreditation tasks. Representing these processes helps ensure that critical actions are not missed and that you can show a clear trail of maintenance and validation work when needed.
3 Ways To Represent A Workflow Or Process
1. Whiteboarding
We often start with whiteboarding when we work with labs. This is common practice for initial workflow design because it’s an effective way to brainstorm with a group. You can do this in person in front of a physical whiteboard or use an online whiteboard tool if you need to meet with team members remotely. Popular online tools include InVision Freehand, Lucidspark, Miro, Mural, and Stormboard.
2. Write & Maintain A Standard Operating Procedure (SOP)
As we’ve mentioned previously, step-by-step written instructions in the form of an SOP are critical for clinical diagnostic labs. They ensure quality, reduce errors, and support compliance in the event of an audit. Up-to-date SOPs can also help your software vendors and consultants deliver custom software or configure your existing software to meet your lab’s needs, or even build automations to optimize your lab’s processes.
3. Flowcharts & Diagrams
These are commonly used by businesses and labs to demonstrate and codify a process. At Labbit, we think that a graphical representation of a workflow is immensely valuable. A diagram is often the simplest way to represent a complex concept or process — you can print it, post it, or show it to anyone in your organization and they should be able to follow and understand the path of the workflow.
Many of the whiteboard tools listed above let you create flowcharts and diagrams, too. You are likely familiar with Microsoft Visio, but there are many other diagramming tools to choose from, such as Lucidchart, Gliffy, Edraw Max, and Cacoo, or even design tools like Canva.
However, the best tool we have found for this purpose is the Camunda Modeler, a Business Process Model and Notation (BPMN) graphical workflow design tool. This tool lets you design, discuss, and share diagrams using the BPMN graphical notation, the de-facto standard for business process diagrams. If you’re new to BPMN, check out this overview with examples.
How To Turn A Workflow Diagram Into A Working Lab System
A diagram is a powerful communication tool, but the real value comes when you use it to drive how your lab systems behave. Moving from whiteboard to working system is more manageable when you break the process into clear stages.
1. Capture The Real-World Process With The Right People
Start by confirming that your diagram reflects what actually happens in the lab today. This means involving the people who perform the work: technicians, accessioning staff, quality personnel, and operations leaders.
Ask them to walk through real examples while you follow the diagram. Note where they deviate, take shortcuts, or encounter missing steps. Adjust the workflow representation so that it captures the current state accurately before you attempt to implement it in software.
2. Identify Decision Points & Data Dependencies
Next, look for the points where the workflow can branch. For each decision, clarify what data is used and what options are available. For example, a QC gate might branch based on a numerical threshold, a specific flag, or a combination of results.
Write down the conditions in plain language alongside the diagram. This will later become the basis for decision rules in your LIMS or orchestration platform. Being precise at this stage helps avoid ambiguous behavior later on.
3. Define States, Queues & Handoffs
Workflow diagrams often show only the main actions, but the “in between” states are just as important. For each step, define what it means for a sample or request to be waiting, in progress, or complete, and who is responsible at each point.
In practice, this might mean defining accessioning queues, batching rules, review states, or storage states. When these states and handoffs are clear in your representation, it becomes much easier to map them to worklists, dashboards, and notifications inside Labbit or another system.
4. Configure, Test & Iterate In Your LIMS
Once the workflow, decisions, and states are well described, you can begin configuring them in your lab software. Start with a limited scope or a small subset of tests, and use real but non-critical examples to validate the behavior.
Walk through the workflow step by step with the team, comparing what happens in the system to the diagram on the page. Expect to make adjustments as you discover edge cases, missing rules, or additional data requirements. Iteration at this stage is normal and healthy, it is how you move from a static diagram to a reliable, executable workflow.
Workflow Representation FAQs
Why Should We Invest Time In Representing Our Lab Workflows If We Already Have SOPs?
SOPs are essential, but they often describe individual procedures in isolation. Workflow representation shows how those procedures connect, how samples move between teams and instruments, and where decisions are made. Together, SOPs and workflow diagrams give you a more complete picture of how your lab operates and make it easier to configure and improve your systems.
How Detailed Should A Workflow Diagram Be For It To Be Useful?
A useful workflow diagram shows the main steps, decision points, and handoffs without getting lost in every minor action. If you cannot follow the diagram from start to finish, it is probably too detailed. If you cannot see where key decisions or handoffs occur, it may be too high level. Aim for a level of detail that a new team member could understand with brief explanation.
Who Should Be Involved When We Model Or Update A Workflow?
The most effective modeling sessions include a mix of perspectives: people who perform the work at the bench, quality or regulatory staff who understand compliance requirements, and operations or informatics staff who configure your systems. This combination helps ensure that the workflow you represent is both realistic and implementable.
How Do We Decide Which Workflows To Model First?
A good starting point is to focus on workflows that are high volume, high risk, or currently causing frustration. For many labs, this means core diagnostic workflows, key QC processes, or frequently changing test panels. Starting where the impact is greatest helps you demonstrate value and build momentum for further modeling work.
How Often Should We Revisit Our Workflow Representations?
You do not need to review every workflow on a fixed schedule, but it is helpful to revisit representations when something significant changes. This includes new assays, major changes in volume, new instruments, or updates to regulatory requirements. When your diagrams and SOPs match what happens in practice, your lab is in a much better position to scale and improve.
How Does A Platform Like Labbit Use Workflow Representations?
Labbit uses your workflow representations as a blueprint for how work should flow through the system. The steps, decision points, and states you define become configured workflows that coordinate people, instruments, and data. When your representations are clear and accurate, it is much easier to translate them into reliable, automated behavior inside the platform.
Things To Remember In Workflow Representation
Document What Really Happens In The Lab
The most important thing to do when representing a workflow is to capture what actually happens at the bench, not just what is written in your SOPs. Even if your lab already has a documented process, technicians might be skipping steps, working around bottlenecks, or following a more efficient pattern that has never been formalized.
When you whiteboard a workflow, make sure the people who perform the tasks are in the room. They can point out where reality diverges from documentation and where small changes could make day-to-day work smoother. In a future post, we’ll talk more about how change management fits into updating documentation and systems when these gaps are uncovered.
Draw The Workflow To Reveal Inefficiencies
Our second recommendation is to draw the workflow so that you can literally see it from start to finish. Turning a process into a visual representation often reveals hidden inefficiencies: unnecessary loops, unclear handoffs, or steps that no one feels truly responsible for.
If you find that you cannot draw the workflow because the steps are different every time, or the path is too complex to fit into a diagram, you are not ready to model it yet. That is a red flag and a sign that you need to simplify, standardize, or clarify before you move forward. On the other hand, if you can draw the workflow in a way that everyone recognizes, you can be more confident that it is well defined and understood, and ready to be transformed into a working system.
Think Beyond Sample Processing
Workflows in the lab are not limited to sample processing. The same principles apply to sample and reagent lot accessioning, stability studies, and even instrument maintenance and accreditation activities. Whenever you have a repeatable set of steps with a clear start and end, you can benefit from treating it as a workflow.
We often say that “there is no single workflow that rules them all” and “in the end, everything is just a workflow.” Thinking this way helps you see more opportunities to bring consistency, visibility, and automation into areas that may currently rely on informal habits or one person’s memory.
Ask For Help With Complex Workflows
Some lab processes are genuinely complex, especially when they span multiple teams, instruments, and systems. If your lab has a particularly challenging workflow that you are struggling to represent clearly, get in touch.
We have worked with many labs that need to comply with regulatory requirements while still keeping their operations flexible and efficient. That experience helps us model and refine workflows so they are documented, followed, and understood by stakeholders across the organization. We also use these same methods for our own internal workflows, so we know what it takes to represent complicated processes in a clear, practical way.
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