Rob Lowther-Adamson
Getting better outcomes with PDCA
(11 May 2018)
“If only we’d -“
“We should have -“
“How did we miss this -“
What if you could reset the clock?
Photo by PDCA stands for Plan-Do-Check-Act – or Plan-Do-Check-_Adjust_, depending on who you ask. Also called PDSA for Plan-Do-_Study_-Act, the Deming Cycle, Shewhart Cycle, and a number of other synonyms.
The idea comes from Control Theory, and refers to a process of continual improvement of a manufacturing process, but the idea applies widely beyond the field of manufacturing.
Essentially, you start by planning a change to the process, then try it out (the “Do”), then Check or Study the result, and finally Act (Apply or Adjust) on the findings.
PDCA is a cyclic process, which can set you free from perfectionism and analysis-paralysis on the one hand, and chaos, churn and regret on the other.
It does this by providing a clear framework for incremental improvement.
Without such a framework, the tendency may be to dive straight in (“Do!” or even “Act!”) - for impulsive types - or to overthink / overplan (“Plan!”) - for conservative types - or to obsess about the product before shipping (“Check!”) - or to keep tinkering (“Adjust!”).
Each of these activities has its place and is valuable in its own right, but, if there is no opportunity to loop through them multiple times, then the pressure is on to get it right first time (for who wouldn’t want to do that?)
Yet without structure, an iterative process runs the risk of being a random walk - each cycle bringing a new direction.
With some patience and discipline, we can get better outcomes.
Hypothesis Testing
PDCA is similar to the Scientific Method. It reframes change as hypothesis testing - and by doing that, it turns initiatives into experiments. The focus on experimentation and studying the results enables attention to come away from “Right First Time”, and move to generating multiple options: experiments from which we can seek to learn (rather than prove a point), and observations to guide our future activity.
This hypothesis-driven approach requires a certain detachment from the outcome of the experiments, and this - I believe - acts as a corrective to the attachment and striving for specific outcomes by specific means, that causes conflict and stress, and carries a risk of failure.
If we redefine ‘success’ as the diligent planning, execution, and evaluation of multiple relevant experiments, then the risk of failure is that of not learning anything, rather than not delivering anything. Success and failure alike stop being about results and start being about observation and evaluation.
Repeating the process in a loop then allows the learning to be useful. Instead of just learning from past mistakes, we can learn from intentional experiments as we progress. With enough iterations, there are no ‘mistakes’, just probing, sensing, evaluating the future possibilities, and deciding on just enough to progress to the next cycle.
Letting us reset the clock every time.
