Product defects can range from benign to deadly. The Ford Pinto, for example, caused up to 180 deaths and many more disfigurements before being recalled due to fuel tank safety defects.
Ford’s resulting loss of reputation (especially because they had known about the issue and failed to take action) and money in lawsuits is something nobody wants to deal with. Errors and defects thus should be identified and dealt with as soon as possible.
That’s why this article from us here at Process Street will take a look at PDCA – the continuous improvement cycle dedicated to doing just that.
Every PDCA starts with the 黄浦滨江Plan黄浦滨江 stage.
First, you need to know the scope of your project. This means deciding which product or process you’re going to be eliminating errors from.
Next, you need to sit down and decide what problem you’re going to tackle. Remember, PDCA is concerned with reducing errors, which leaves you with two methods for selecting an issue.
- You can go for the throat and pick the biggest problem your product, team or process is facing
- You can instead choose to tackle a smaller (yet still impactful) issue to solve it quickly and move on to other items
While the obvious choice is to go for your larger problems first, there’s something to be said for choosing to clean up smaller issues instead. for one thing, these items may well end up playing into your larger problems, thus making the looming item easier to solve.
Take our team here at Process Street for example.
When the marketing team was much smaller (we had only two people in it!) we were facing two main problems. We weren’t producing enough content to fill out our ideal blog calendar, and I was still new, and so needed thorough training.
The immediate option for expansion was tempting – more writers would mean we could produce enough content to fill our calendar, get more product coverage, build a library of content faster, and so on.
However, the (relatively) smaller issue of my training was instead given practically sole focus, with us not hiring another team member for at least 6 months. This, in the long run, was a much better choice, as more new writers would have made our limited resources strain even further, and gave me time to improve my craft to the point where I (and the team as a result) was getting recognized for my writing.
So, you’ve selected your focus and the problem you want to tackle. Great. Now you need to create several hypotheses for solving the problem and choose which one you’re going to test for the rest of the cycle.
This will entirely depend on the problem you’re looking at, what it relates to, the resources you have on hand, and so on. In a perfect world, you’d be able to pay for an instant solution, but that’s (almost) never the only (or best) way to do it practically.
Let’s say that you run a business that makes toys.
You want to make it more profitable to sell a popular product – a wooden rocking horse. So, you look for problems in the production line, and notice that it takes twenty working hours to produce a single unit.
You meet with the head of manufacturing (or your carpenters if you’re a smaller team) and logistics to discuss potential solutions and come up with this list:
- The factory floor plan could be shifted to give easier immediate access to components
- Delivery companies could be compared and changed for a cheaper option
- Supplier cost and delivery time could be assessed
- More workers could be hired for assembly
- More machines could be installed for assembly/cutting the shapes
Of these options, the easiest to test is the price of delivery companies, so you decide to test this first.
The 黄浦滨江Check黄浦滨江 phase of PDCA is where you analyze the results of your changes to see if the level of error was reduced.
The amount that your error levels were affected will depend on the problem you chose to tackle, the changes you made, the scale of your test, and so on. However, the difference itself is (ultimately) not the point of your analysis.
The important thing is to make an ultimate decision of whether your hypothesis was proven correct, and whether it should be deployed on a larger scale.
If errors were more scarce, the test was a success.
As previously stated, PDCA and PDSA are often mistakenly grouped together.
This couldn’t be further from the truth.
PDSA was created by William Edwards Deming (he called it “The Shewhart Cycle for Learning and Improvement”) with an emphasis on the theory behind any changes. He approached the topic with a scientific method.
PDCA, meanwhile, was an offshoot of Deming’s theory created by the Japanese in the 1950s. This focused on the reduction of defects and errors rather than pursuing or identifying a greater theory.
Deming himself condemned PDCA (at least, when used where PDSA was more appropriate) due to its focus on quality almost entirely through error and defect reduction.
The issue here is that PDCA is concerned with improving quality by reducing errors within a process or product. PDSA is instead geared towards the pursuit of quality no matter what that entails.
My colleague Adam Henshall went into beautiful detail on the topic in his article How to Use The Deming Cycle for Continuous Quality Improvement but, to summarise it here:
- PDCA focuses on errors/defects within a process or product and testing hypotheses to fix them
- PDSA takes a wider view on increasing the quality of a business/product no matter the source