Every organisation wants quality but is there a common understanding of what we actually mean by quality in each organisation? This paper explores what we really mean by quality and breaks it down into easy to understand components.

What is Quality, Quality Control and Quality Assurance?

When we work with clients, we tend to come across many roles that have the word ‘quality’ in them. For example, Quality Assurance Analyst, Quality Controller, Quality Manager and Quality Coaches.

Then we come across various systems or applications that have the word ‘quality’ in them, such as Quality Databases, Quality Frameworks and Quality Management Systems.

Companies clearly want to improve their quality, but do they really know what quality means? Do they understand what the customer wants and expects, and how they measure it? Do they understand what is value adding to the customer, or waste? Is there a consistent understanding and application of quality in their organisation?

As an introduction, let us look at what quality, quality control and quality assurance actually mean:

Quality

Before an organisation can declare that they have supplied the customer with a quality product, they need to know the Voice of the Customer (VOC) and what they see as being Critical to Quality (CTQ)

An obvious example of a VOC statement is “I want good customer service”. This is a standard requirement from a customer. But what is good service?

A company must drill down a little further to determine a more specific, measurable requirement to understand what Critical to Quality (CTQ) is in the eyes of the customer.

Here is a CTQ tree:

CTQ

It is a simple diagram that captures the customer’s need or expectation (VOC), and shows how this is translated into a measurable CTQ.

Providing a company can supply a service or product that meets the CTQ’s, then they can declare themselves as being able to provide a quality output i.e. an output that meets the expectations and standards of the customer.

Quality Control

 Every company we have worked with have checks in place for most of their processes. These checks are there to identify any defects with the output, and this is what is referred to as Quality Control.

Quality Control is a reactive process; it is there to try and identify a failure after it has happened, but before it is seen or felt by the customer.

Quality Control should be carried out on activities at the end of the process, but occasionally during the process.

Impartial teams usually carry out Quality Control and test the produced outputs against a specification. The tests can be random, or can have sampling methods associated to them such as systematic, stratified, quota or cluster.

Quality at work

Quality Assurance

 Unlike Quality Control, Quality Assurance is a proactive, quality process, which focuses on the process that is used to create the product.

The purpose of Quality Assurance is to evaluate and develop the process so that defects don’t occur when the product is being created. This evaluation and development is the responsibility of everyone in the team who helps to create the product. Quality Assurance is a managerial tool, and requires a good, quality management system in place for it to be a success.

Quality Control vs Quality Assurance

How do some businesses perceive Quality Control & Quality Assurance?

Let’s start with Quality Control. From experience of working with many clients, Quality Control is often perceived as the Holy Grail; one of the most important roles in an operation, and literally businesses throw millions of pounds at resourcing it.

But why do companies have this perception, and why do they invest so much at a reactive process?

Maybe, this is due to not understanding how Quality Control should work, and not having an appreciation of the value Quality Assurance can bring to a company?

Many organisations we have worked with see Quality Control as checking the product at the end of the process, by people who work in the operation and not by an impartial entity.

The sampling method tends to be either 100% checking or just checking a fixed number (say in a Call Centre – we might just monitor 5 calls per person per month). Contrary to popular belief, these aren’t a sampling method.

Less frequently you may see random or systematic sampling. Rarely will you see any data being used to give a steer on what sampling method is best for which process.

The findings from the Quality Control carried out at the end of the process may find its way back to the Operator or Team Manager. Unfortunately, we have observed on many occasions where this doesn’t happen. There is usually a perfectly acceptable feedback process in place – it’s just that it is often not followed and we certainly rarely see any of the findings being used to develop a quality assured process.

“In one organisation, we found that less than 25% of the completed quality control reviews were being fed back to the employees”

Staying with Quality Assurance, businesses will often see this process being owned and carried out by a separate team; a team of auditors, who will arrange to review a function once, or maybe twice per year. People within the team will not see Quality Assurance as their responsibility.

The team processing will do what they are paid to do, which is to process the product, and not often identify ways and means to develop their process to ensure right first-time output.

Most teams we work with have documented standard operating procedures, however we find that they are rarely used and rarely updated.

What impact does Quality Control and Quality Assurance have on a business if done badly?

In a nutshell, if done badly, companies end up with their own, wasteful cottage industry. Let me explain:

Companies see checking as a pivotal part of their operation. They have little faith in their processes, so they check, double check and even triple check, to make sure that the product does not reach the customer in a state that does not meet their expectation.

In addition to all the repetitive checking, companies also have 100% checking. So, thousands of products get checked, then they get checked multiple times.

Take a look at this checking scenario

When an output is deemed to be correct 2 people have to be paid, the doer and the checker.

checking scenario

Once it is checked and deemed incorrect then the first or a third person corrects the mistake and the second or a fourth person checks it again, which means a minimum of 4 people will have been paid, and this rises in further increments of 2, depending on how many times the job goes around the correction loop.

Finally, some things that are checked and then passed as correct may well, in fact, still be wrong, causing confusion, complaints and penalties later on. This is known as the ‘hidden factory’.

Let’s now think about the impact on the people

When a company develops a culture of checking, and investing a lot of money to pay people to check, what they are actually doing is paying people to find errors that the process has allowed other people to make. Unfortunately, the cause for error is often not seen as the process; it is seen as the person.

We have all made mistakes; it happens, and quite rightly most people get back up and learn from them. However, when you are informed that you have made a mistake, how do you feel, pleased? Generally not. Potentially worse, the people who found the mistake tend to feel pleased with themselves, because that is what they are paid to do; find errors. What motivation do the checkers have in terms of developing the process?

We have heard clients say things like “if the process was mistake proofed we would be out of a job”. This is exactly where companies do not want to be. Teams who aren’t empowered to evaluate and improve their own processes and ‘assure’ the customer that they will receive their product right first time.

How businesses can get the most value from Quality Control & Quality Assurance

Let us not forget – The aim for all organisations should be to provide a product or service to a customer that meets their requirements on time, first time, every time. There is no space for having satisfaction at finding errors; the satisfaction should come from giving the customer what they expect.

Companies therefore need to strive towards having a mistake proofed set of processes; processes that make it as near as impossible for an error to be made, or at the very least, easier to meet the customer requirement than make defects.

So how can Quality Control and Quality Assurance be best utilised to achieve this aim? An easy view could be to move away from Quality Control to Quality Assurance, but firstly that isn’t easy to do, and secondly, we feel here at Lean Consulting that both Control and Assurance are both required, and have strong interdependencies on each other.

The Operational Manager and their team can use data which the Quality Control process has collated to design ‘assured’ quality into their processes. Management should also use other data at their disposal to identify opportunity for process improvement, such as complaint data, skills matrices and their visual management. Root Cause Analysis is performed on the data to help generate improvements.

As improvement plans are put in place and deployed into the process, and the Quality Control team should be utilised to measure the strength of the new process in terms of whether the product meets the customer requirements.

Conclusion

It might not be in every company’s gift to have a set of highly capable processes; however, it is in every company’s gift to promote and invest in Quality Assurance.

By investing more in Quality Assurance and embedding it as part of the team’s culture, will increase the process performance, increase the likelihood of right first-time output, and therefore decrease the amount of activity that takes place by Quality Control.

Quality Control is important, but companies are currently spending more time and money on checking outputs than improving the process. Turn that on its head, and the operation will inevitably be more successful.

Simon Hopley, Lean Consulting

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