(PDCA) is a four-step, iterative by-design method used for control and continual improvement of processes and products. It is also known as the Plan-Do-Study-Act (PDSA) cycle, Deming cycle, Control Circle/Cycle or the Shewhart cycle.
PDCA is an evidence-based participatory approach to problem-solving and is found to be an effective tool for quality improvement.
The beginnings of PDCA emerged from the principles of the ‘Scientific Method’, which originated with Galileo but has its roots in the teachings of Aristotle. It is a method for developing ideas based on observation, then testing them through experiments and finally refining, changing, or eliminating the ideas. [2]
Dr. Walter Shewhart first adapted the scientific method for industry and presented it as a linear flow of ‘specification’, ‘production’ and ‘inspection’. In 1939, he changed the linear sequence to a cycle to show how refinement and change lead to an iterative approach to product development.
The Shewhart cycle was further developed by W. Edwards Deming in what became known as the ‘Deming Wheel’.
In 1950, Deming presented his ideas to the Japanese Union of Scientists and Engineers (JUSE) which then was popularized as the Plan, Do, Check, Act cycle or PDCA. [2]
Organizations often plan and then intend to execute, but the reality is neither linear nor predictable for this approach to be effective in reaching the target conditions.
Regardless of how well a plan is made, they must navigate a zone of uncertainty commonly referred to as the “Grey Zone.” Unforeseen problems, abnormalities, false assumptions, and obstacles will appear along the path to any target.
A good analogy is a person climbing stairs in the dark with a flashlight. Because the target condition lies beyond the reach of the flashlight, the path to attaining it cannot be predicted with exactness. Thus, the person must find that path by experimenting.
This is the central approach of PDCA. To expect uncertainty and pay attention to adjust along the way based on learnings. PDCA provides a practical means of attaining a challenging target condition by formulating hypotheses and testing them with information obtained from direct observation.
The procedure or steps of experimentation in the PDCA cycle are summarized as below:
PDCA’s four stages constitute a scientific process of acquiring knowledge and are explained in more detail as follows:
In the Planning stage, problems are identified and analyzed according to the following order:
At this stage, the team implements an action plan developed in the previous stage to make the desired changes. This involves the following steps:
At this stage, data is collected once again to measure if the actions taken have improved the situation. It involves the following steps:
In the Act phase, interventions that are found to be effective are standardized by developing Standard Operating Procedures (SOPs), which involve the following steps:
At the end of the fourth stage, the PDCA cycle restarts with the aim to solve another problem (or further improve the same problem) to achieve a continuous and uninterrupted improvement.
PDCA cycle consists of seven steps spread over four stages, as shown:
A problem is a brief description/statement of the weakness in the process or an issue to be solved. The tool most often used in this step is a Flowchart [6] . Alternatively, if a single problem is to be selected from a set of problems, a Selection Matrix [7] or a Fish Bone Diagram [8] may be used.
Selecting a problem is an iterative process where subsequent steps could lead to further refinement of the definition. A good problem should:
Problems can be prioritized based on:
In this step, the focus is on gathering facts about the problem. The tool most often used at this point are Checksheets [9] and Pareto Charts [10] . Following are some of the key aspects of situation analysis:
A root cause is the fundamental reason behind negative process outcomes. A fishbone diagram [8] is the primary tool for root cause analysis. The root cause must be controllable and is found using the following approach:
This step brings ideas together to address a problem’s root cause. It is important to be open to options and think creatively. Affected individuals must be involved, and preference must be given to improving existing processes before revamping them entirely. Experiments are run to test solutions.
The proposed intervention must:
Putting the implementation plan into action involves carrying out the ordered steps outlined below, implementing the change itself, and collecting the information that will indicate success.
Teams must establish checkpoints periodically to verify if the implementation is going as planned and update everyone involved on the progress.
Using tracking indicators, effectiveness can be checked through the following steps:
The situation before and after PDCA can also be portrayed using a graph as shown below:
A Run Chart can be used to observe improvements over time. For example, the run chart (below) shows a decreasing trend in the number of patients who did not follow prescribed medication. This indicates the PDCA measures adopted by the hospital to address the issue have shown improvements over time.
At this stage, the activities found to be effective in reducing or eliminating the problems are standardized using the following steps:
Standardization brings several benefits such as:
Discipline is the key to successful standardization of an effective intervention.
No organization has ever come close to matching Toyota’s stellar performance in automobile manufacturing. It has cultivated a culture of excellence, efficiency, and customer satisfaction like no other.
PDCA at Toyota uses “Rapid Cycles,” where individual PDCA cycles are turned as quickly as possible, sometimes even taking only minutes each. The idea is to not wait for a perfect solution but to take the step at the earliest with available resources so that teams can spot the next challenge.
Toyota believes that a provisional step “now” is preferable to a perfect step “later”, and invests in prototypes and experiments up front, which may seem like an extra expense but has proven to reduce cost in the long run.
Toyota uses single-factor experiments, that is, to address one problem at a time and only change one thing at a time in a process. This helps see cause and effect and better understand the process.
Toyota’s success is not due to sudden innovation or having air-tight plans but the ability to execute more effectively in the face of unforeseeable obstacles and difficulties. They spot problems at the process level much earlier when the problems are still small and address them quickly while uncovering information along the way.
Consider the process of getting up and going to work with a target condition of being in the car and ready to drive 60 minutes after waking up.
Here is one possible PDCA cycle for the process:
| Plan | Be in the car 60 minutes after waking up. (Target condition) |
| Do | Wake up and go through the morning routine, get into the car. |
| Check | Once in the car check how long it took. |
| Act | (Next step to be determined) |
Assume that with the above PDCA plan, a person sits in the car to find that the morning routine took 64 minutes, or four minutes over the target condition.
What has he learned about the process from this experiment?
As depicted in the figure above, not much! The total time taken was over 60 minutes (too long), but it cannot be said where in the morning routine the problem lies. Also, it is too late to make an adjustment that would still achieve the target condition.
There are two things wrong with this PDCA experiment:
Many seemingly large and sudden changes develop slowly. The problem is that organizations either fail to notice the little shifts taking place along the way or they do not take them seriously.
No problem is too small for a response. To be consciously adaptive, an organization must recognize abnormalities and changes as they arise and are still small and easy to grasp.
To be able to experiment in shorter cycles, a more detailed target condition is necessary. Such a target condition must generally include the following information:
While a longer overall PDCA cycle must check the outcome, many short PDCA cycles must check process metrics along the way. Every step on the “staircase toward a target condition” is a PDCA cycle. Each step is a hypothesis, where what is learned from testing that hypothesis may influence the next step.
Accordingly, a modified and more effective experiment for the process of getting up and going to work, beginning with a better target condition, will look as follows:
As seen from the figure, the step “Make breakfast” has taken four minutes longer than the planned time. From this, it is not only known where the problem is, but an adjustment can also be made to the remaining steps to still achieve the 60-minute outcome.
PDCA phase of the improvement, after a target condition has been established, needs to answer the following five questions that are built on one another.
The sequence of these five questions acts as a device to give a routine and a mental pattern for approaching any process or situation. These questions distill part of the improvement down to a point where it becomes accessible and usable by anyone.
