You are pursuing Quality Intelligence Maturity because you want the quality of your products to be as high and consistently high as possible. You strive for perfection because that is part of your job (just as much as the recognition that perfection is not possible). But realistically you can only make progress if, somewhere in your journey towards Quality Maturity, you demonstrate that you are saving money. And by this, we probably don’t mean cost-avoidance: the hundreds of thousands of euros you did not spend on a product recall, or the crippling cost of reputational damage that would have resulted from such a recall.
Your CFO will want to know, and you will want to know: does the cost of Quality Control come down if you improve the way it is managed? It will, as you’d expect. But by how much? What do we spend on Quality Control anyway? Do we trust our numbers?
It is a chicken and egg situation because insight into costs is one of the hallmarks of Quality Intelligence Maturity. Or to turn this on its head: manufacturers that can make the deepest inroads into what they spend on Quality Control don’t realize this fully for the very reason that their processes are immature.
In our Maturity Grid, we have left the matter of cost to one side. If the CFO is wrong about it (and he or she probably is, unless you have achieved Quality Intelligence Maturity), you can’t expect your co-workers to guess. If you implement a strategy of integration and smart automation, the costs will take care of themselves – that is essentially our view.
The ‘cost attribute’ in our matrix relates to the distribution of Quality costs between corrective and preventive costs. This is not an outcome, or shouldn’t be, but a deliberate Quality Policy – which is why it’s reasonable to survey your colleagues about it.
While this ratio is not arbitrary, it is important to stress that there is no ‘right’ or ‘perfect’ relationship – this will vary from business to business. NASA is an extreme example where preventive cost must account for 100% or virtually 100% of Quality spend; NASA cannot recall its products once they are in space. But for other manufacturers, the ratio is really a balancing act between the costs of remedying and preventing failure. Quality Management can never be efficient unless failure is hardwired into the process.
In principle, the cost ratio tells you nothing about the total cost of Quality Control, although manufacturers who focus on prevention tend to spend less overall. This is not an absolute. To return to our earlier example, you have to assume that NASA spends an awful lot on Quality Control. But so does the manufacturer at the other end of the scale, where all the money goes on remedying failure rather than preventing it. The trick for manufacturers is to find the sweet spot between correction and prevention.
Exploring this ratio, setting a target ratio for your company, is an important first step towards Quality Intelligence Maturity. Manufacturers who haven’t got around to this probably belong to the Ad hoc & isolated group that effectively has a cost ratio imposed upon them. As they lack the tools and processes to prevent deviations, these manufacturers spend most of their time correcting them. They didn’t choose it (and they may not know it), but for Level 1 Quality teams, 80% of total costs tend to be corrective, and just 20% corrective.
You see this ratio shifting as your Quality Intelligence matures. This is not surprising: smarter, deeper automation and the integration of your systems, processes, and people lead to fewer deviations, and so the corrective cost will fall as a percentage of your total quality spend. Note that in our matrix, we have set the ratio for Quality Intelligence Maturity at 20/80 – the reverse of the cost scenario in Level 1.
In Part One of our series on Quality Maturity, we introduced the original quality matrix, devised by Philip Crosby. Crosby is bold enough to estimate the total cost of Quality Control and sets this as high as 20% of total sales for manufacturers who do not have a grip on their quality processes. This shrinks to 2.5% for companies that reach Certainty (as he calls it) – the 1979 equivalent of our Level 4, Smart & integrated. We would say such numbers are indicative only because costs will vary quite a bit from manufacturer to manufacturer. The aspect of Crosby’s matrix that fits in best with our vision is that Quality Maturity gives you insight into cost: with each level of ‘awakening’, the gap between reported and actual cost narrows.
We urge all manufacturers, great and small, to self-assess their Quality Intelligence. In our whitepaper How Mature is your Quality Management? we discuss the stages and key attributes in more detail; our three blogs served as an introduction – or a distraction if you will. Because the important thing is to distribute the survey, encourage co-workers to reflect on Quality, and absorb the results.
What next steps you need to take in the light of your findings will be the subject of our next blog.
Do you want to know how mature your Quality processes are, download our whitepaper Quality Intelligence Maturity Model.
In this era of smart manufacturing, quality will become smart as well. This transition will not happen overnight and this will not happen in a linear way. Our Quality Intelligence Maturity Model presents a springboard to change, and asks organizations to self-assess to what extent they are ready for Quality Intelligence, and to leverage tomorrow’s possibilities.
The Quality Maturity Model is designed to highlight the strengths and expose potential weaknesses of all aspects of your Quality Management, giving you the input necessary to strategize for positive change.