The Plan-Do-Study-Act (PDSA) cycle was first introduced in the 1950s—and it’s still one of the most widely used methods for continuous improvement today. That’s because it works. With PDSA, you can test changes quickly, learn from real data, and adapt fast–without having to do a full-scale rollout at once.
Read on to find out exactly what the PDSA cycle is and how you can use it to drive smarter decisions in your day-to-day operations. Whether you’re already familiar with process improvement or just getting started, this guide will give you a clear, practical look at how PDSA can fit into your work.
What is PDSA?
PDSA stands for Plan-Do-Study-Act. It’s a four-step cycle that’s used to test small changes, measure their impact, and refine processes over time:
Because of this, it’s a core method in continuous improvement and quality management, with a focus on making decisions based on data. It encourages a low-risk approach, where you learn as you go and adapt before scalping up changes.
The method was actually adapted from PDCA (Plan-Do-Check-Act). Both sound similar at first, but PDSA puts more emphasis on analyzing the outcomes (“Study” rather than “Act”) instead of only checking off results. This shift makes it better suited for complex environments that need constant experimentation, feedback, and adjustment.
PDSA originally came from the manufacturing industry, but it’s also widely used in healthcare now, which needs to be efficient and adaptable. Hospitals might use it to improve patient care workflows. For example, health services used it during the COVID pandemic to deliver vaccines better during the COVID pandemic. It even works for education, with school districts using PDSA to test and improve new programs. All in all, it’s adaptable for any industry where you want to run more efficient operations and respond quickly to change.
Four Stages of the PDSA cycle
At its core, the PDSA cycle is about learning by doing. It consists of four clear steps that you loop again: Plan, Do, Study, and Act. Each stage builds on the last:
1. Plan: Define the problem
The Plan phase is where the groundwork happens. You’ll identify a specific problem or opportunity for improvement—something clear, manageable, and ideally measurable. Choose one small change that can lead to better results.
Here are a few key questions to consider:
- What exactly are we trying to improve?
- What’s the expected outcome?
- Who needs to be involved?
- What data do we need to track success?
You’ll also define the scope of your test. For example, if you’re testing a new safety inspection method, limit it to one team or one shift first. The idea is to keep the test small enough to manage, but meaningful enough to learn from.
A good plan also includes a prediction. What do you expect to happen if this change is successful? This gives you something to compare against later—and keeps the cycle focused on learning.
2. Do: Run the test
Once your plan is in place, it’s time to put it into action. The Do phase is about implementing your change in the real world—on that small scale you defined earlier.
The goal here is to observe, document, and learn. You want to see how the change works in practice and start collecting data. That includes both hard data (e.g., time saved, error rate, number of completed tasks) and soft observations (e.g., how the team responded, what went smoother than expected, where confusion popped up).
Keep communication open with the people involved. They’re closest to the work and can offer insights that you might not get from metrics. It’s also helpful to log any unexpected issues that came up during the process. Even if the test “fails,” you can use these observations to inform the next cycle.
Since you’ll be collecting data, don’t rush this step. Give the test enough time to produce meaningful results, even if it’s just a few days or one workweek.
3. Study: Analyze what happened
In this phase, you’ll slow down and process. This is when you’ll look closely at the results of your test. Did the change actually lead to the outcome you expected? Did it solve the problem, make it worse, or reveal something new?
First, review the data you collected during the previous Do phase. Compare it to your original plan and prediction. Were tasks completed more efficiently? Did error rates go down? Did a new process reduce issues for the team—or create new ones?
Going beyond the numbers, talk to the people who were part of the test too. They often have revealing observations, or they might have noticed differences that aren’t obvious. This kind of qualitative feedback is key—especially in industries like healthcare and hospitality, where the human factor has a major role.
Document everything: the outcomes, the learnings, and any unexpected side effects. This becomes your reference point for the final phase.
4. Act: Make a decision
Now that you’ve studied the results, it’s time to decide what happens next. The Act phase is about taking what you learned and either adopting the change, adapting it, or abandoning it altogether:
- If the test worked well and achieved your goals, you could roll it out on a larger scale or make it part of your standard process.
- If the results were mixed, you might revise the plan and run another small test.
- If the test didn’t work at all, that’s okay too. Now you know what doesn’t work—and that’s still progress.
During this last phase, you’ll turn the insights from the Study phase into concrete action. Ideally, document your findings too so the rest of your team—or organization—can learn from them too.
Since PDSA is a loop, you can then go back to Plan and run the next cycle–and keep building better systems. To make that process easier, we’ve collected some ready-to-use PDSA templates—complete with guiding questions and clean formatting to help you stay focused. Feel free to download them and use them as often as you like.
Examples of PDSA
Through PDSA, a small, well-planned test can lead to meaningful improvement. Here are a a couple of practical examples:
Healthcare
Scenario: You manage a hospital ward and want to reduce minor medication errors during shift changes.
Plan: Introduce a short “medication check-in” at the start of each shift, where nurses review time-sensitive meds. Then track how many errors are reported during the week.
Do: The team tests the check-in process for one week on a single ward. They use a quick form on their mobile device during shift handovers.
Study: After one week, you review the results. Medication errors drop from five to two. Nurses say the process helped them prioritize their rounds and reduced miscommunication during handovers. One issue comes up: on especially hectic days, the check-in sometimes gets skipped entirely.
Act: Roll out the check-in on all wards—but tweak the form to make it even faster to complete, and add a reminder to the shift checklist. You also plan to review the process again in a month and adjust as needed.
Manufacturing
Scenario: You’re managing a production line and notice that a specific machine has frequent short stoppages, slowing down output.
Plan: Test whether more frequent maintenance checks will help. Increase checks from once a week to every other day—for just one machine, then track downtime over two weeks.
Do: Roll out the schedule for one machine. Operators log checks using a simple digital form and flag any issues immediately.
Study: After two weeks, stoppages decrease noticeably. Operators say they’re catching small issues earlier. A few say the extra checks are easy to forget.
Act: You standardize the change but also add automated reminders before each check. The next cycle will test it on additional machines.
Best practices for implementing PDSA
PDSA works best when it’s simple, focused, and consistent. Here are some best practices tips to keep your cycles useful:
- Focus on learning, not proving. Don’t worry about trying to “prove” an idea works, especially when you’re the one who suggested it. The goal is to learn something new—even if that means finding out your idea wasn’t the best one.
- Use data, but don’t get buried in it. You don’t need a full analytics team to run a PDSA cycle. Keep the data collection light but meaningful. A few well-chosen metrics or observations are usually enough to guide decisions.
- Keep it visible and well-documented. Whether it’s a dashboard or a whiteboard in the break room, make sure everyone can see what’s being tested, what’s in progress, and what’s been learned.
- Make it a habit, not a project. The most successful teams treat PDSA like part of how they work—not something they do on top of everything else. Keep the cycles regular and part of the normal rhythm.
How to use Lumiform for running your PDSA cycle
PDSA is a proven method for continuous improvement, which is why Lumiform offers a digital solution that helps teams implement and document every step of a PDSA cycle with ease.
Using Lumiform, you can digitize your improvement cycles—from planning small changes to assigning tasks, collecting feedback, and acting on results. The mobile app makes it possible to complete tasks directly in the field. If corrective actions are needed, you can trigger and track them immediately within the platform.
Take advantage of the key benefits of using Lumiform for PDSA cycles:
- The AI form builder allows you to digitize any improvement form or checklist in minutes—no coding required
- Assign tasks to specific team members and track completion in real time
- Collect and organize feedback, photos, and results in one place for clear post-cycle analysis
- Automatically generate reports to review and share results with your team or stakeholders
- Use real-time analytics to identify trends, spot issues early, and continuously optimize your processes
- Work offline when needed and sync data automatically once you’re back online
By digitizing PDSA with Lumiform, you make continuous improvement easier to manage, measure, and scale. Try it out today to see how it can support your PDSA cycles from start to finish!