What is quality assurance (QA)?
Quality assurance (QA) is the process of checking whether your services are meeting your desired quality standards. This often includes monitoring and evaluating customer service calls, chats, and other interactions between your employees and your customers.
Quality assurance assessment ensures the day-to-day compliance of your team with legal and company regulations. It also ensures that your team is offering what you consider to be a “quality” service in a way that’s standardised.
What is quality control (QC)?
Quality control is the term used to describe the process of ensuring that a new product or service meets all the standards that its intended audience would expect of it. This usually involves deciding on a standard and following that as a framework to define what passing quality means.
The quality control stage for a physical product differs slightly from the quality control stage for a digital one, like a website or online service. With physical items, you’d usually take a representative sample of the manufactured product and check them against your quality control standard, and test them to determine a percentage failure rate.
What is Statistical process control?
Statistical process control (SPC) is a method for conducting quality control using statistical methods to monitor the process (rather than spot-checks). This is usually achieved by using a control chart to track the frequency of product failure, either through ‘common cause’ or ‘special cause’ variation.
Either way, the result of quality control is to determine any faults before a product goes into mass production, or makes it into the hands of clients and customers.
By performing quality control, you’re effectively mitigating any issues inherent to a product during the development process – before it has the chance to become a reputational issue among the wider public. In short: it’s how you ensure you’re making high-quality products.
Difference between quality control (QC) and quality assurance (QA)
Unlike quality control, quality assurance is generally focused on how processes are performed, or how service is delivered. It focuses on the prevention of mistakes being made through the creation and evaluation of processes, strategies, and brand policies. Usually, your quality assurance function will have a “checklist” of standards to mark services against.
It’s up to everyone to participate in quality assurance, though having an appointed person or group to monitor the team (customer service team leader or QA team member) helps to maintain standards.
Quality control is focused on the evaluation and management of quality for products – usually during the development process. It focuses on correcting issues, such as product defects, and is concerned with carrying out a quality audit and taking corrective action, rather than deciding what checks need to be made.
There’s usually a dedicated team for quality control that carries out the fixes needed after testing products. Quality control is more common for businesses that have manufacturing processes and mass production to evaluate.
Ultimately, the systems you have in place to ensure quality as a whole should encompass the management of both quality assurance and quality control.
What is quality management?
Total quality management is the strategic approach to quality assurance. This includes planning as well as evaluation, helping to change QA scores from negative to positive through targeted action.
Though quality assurance methods are vital for a business to provide services that are productive and memorable, quality management takes things one step further. It helps you not only to flag potential quality issues but to take action to ensure that other issues across your business are resolved.
For example, your quality assurance team might spot that calls that end with a recommendation for another product increase the chance that the customer spends more than they originally planned. This might not be a factor that they have been instructed to check to ensure quality, but passing along that extra information to management might help change the way staff members are trained for the better.
Ideally, the following approach should be taken to quality management:
- Collect data for analysis
- Analyse your data against your QA criteria
- Make individual suggestions for quality improvement
- Improve your overall criteria and approach by suggesting strategic changes
- Repeat actions that had a positive effect on customer experience
Why is quality assurance important?
Quality assurance is vital when checking to see if your services, products, and team approach are in line with legal guidelines for your business.
However, quality assurance is also about checking to see if you’re providing a consistently good service. Sticking to your own standards for customer experience is important for meeting customer expectations and setting yourself up for growth.
Calibrating your internal teams to ensure everyone’s offering the same service, no matter the delivery route, is key for success. Developing a reputation for reliability and top-quality service can be a differentiating factor when customers are choosing which business to purchase from.
Quality assurance can also help you to pinpoint opportunities for coaching and organisational change. This is where quality management comes to the fore. Rather than quality assurance just being a box-ticking exercise, your quality assurance function can flag areas that need better coaching or structure and can highlight factors that are affecting success.
Taking their feedback into account helps you to develop a QA strategy that is effective and evolves to improve your offering.
The quality assurance process
The quality assurance process usually followed a standard ‘PDCA’ model, in which a testing environment encompasses the following steps:
The planning phase is where the initial quality standards are drawn up and decided upon. Whether you’re following a standardised framework or not, this is where your quality engineer will decide what ‘quality’ means for your product, service, or team.
The ‘do’ phase is simply where you carry out the processes and procedures that you’ve defined in the planning phase.
In this phase, we collect data to see how well things are performing based on the criteria we’ve designed. You’ll compare actual outcomes with your expected ones, and see how that marries up to your overall QA objectives.
Also known as the ‘Act’ part of the overall quality test strategy, this is where you’ll make the changes that your findings point to, to improve whatever it is that your QA testing was tracking.
As we’ve mentioned, the QA process is an ongoing one, so it makes sense that the process for quality assurance – whether it’s for customer support or in software testing – is cyclical. With that in mind, it’s best to think of the ‘Adjust’ phase as leading back into the ‘Plan’ phase.
Software quality assurance and software testing
Software quality assurance differs slightly from other kinds of QA and QC, but the goal is still broadly the same: you’re checking to ensure that everything is up to scratch, works well, and operates without issue. That’s both before your software launches, and as an ongoing process.
SQA vs software testing
Software development teams tend to look at both functional and nonfunctional issues. ‘Functional’ here tends to mean checking the software’s ability to do what it’s been designed to do while looking the way it was designed to look. In the world of agile software development and software engineering, that’s usually referred to as ‘software testing’.
Software testing can involve things like checking its ability to perform against different variables, like web browsers (and browser versions), as well as on different operating systems, and that the software can perform under heavy load.
SQA, or software quality assurance is more about non-functional parameters. The goal here is to look at the processes behind the product to ensure that there’s a ‘quality culture’ built around efficient, maintainable code and that industry-standard methods are being used.
With both, there’s a cyclical nature. Once the software has passed testing and launched, ongoing testing should be undertaken to ensure ongoing functionality, as well as to highlight any features or enhancements that can be added with later versions or patches. SQA, meanwhile, should happen continuously.
Best practices for quality assurance
Quality assurance might be the last stage of your process, but it’s often where issues in products and services are caught. Here’s how to ensure things are working as they should:
Create a specific team for quality assurance
Depending on your business maturity, your customer service team leaders may be carrying out quality assurance checks on your service staff. While this is a good first step, it’s not the most practical way of ensuring you offer a consistent, effective customer experience.
Team biases might become an issue for impartial QA. You need to make sure you’re calibrating one leader’s idea of what quality looks like with everyone else’s. Team leaders already have one job to do, and adding more responsibilities to them is not the most efficient use of their time.
Having a separate quality assurance team means you have a more impartial judge for whether you’re delivering quality or not. With the use of technology, this team doesn’t even have to be extensive. Ensuring you’re consistently offering a great service is made much easier with responsibility passed to a dedicated team.
Develop a robust set of evaluation criteria
If your QA has a rubric to evaluate against that isn’t particularly clear or could be interpreted in more ways than one, your evaluation process is going to be flawed. Make sure your team has a consistent understanding of the criteria you evaluate against, and be open to suggestions around adding new criteria for quality improvement based on their experience.
Use technology to improve your processes
While it is possible to carry out quality assurance without the use of anything more than a spreadsheet, it’s not the most efficient or useful way of proceeding.
Many businesses take a random sampling of customer service calls and chats to evaluate service quality. Given the huge number of calls or chats a business might complete in a week, this can be a significant undertaking, and it doesn’t direct your team to the ones that are likely to be informative.
Technology that can help you evaluate all the data you collect and pick out the statistically relevant calls, chats, and more can not only speed up your QA process but improve it.
Using an experience data platform that includes conversation analytics can automatically evaluate calls and intelligently source them for you. Rather than just scoring the calls that your QA people evaluate, it can score all your calls, chats, social interactions, and more against your quality criteria. With a sophisticated platform, this is made possible using AI and natural language understanding to judge emotion, intent, and effort.
Instead of your team wasting time on irrelevant data, technology can pick out the most useful logs for QA to evaluate, and find pertinent trends by scoring all calls automatically. With the right software, quality assurance will take less time, helping you to focus more on things like people management.
Integrate quality assurance insights into your strategy
Quality assurance is often seen as being a box-ticking exercise, but it can be so much more when you view this process through the lens of strategic management.
When QA flags that there is an issue with how a call was handled, this typically affects only that specific customer service agent’s score on their performance. However, QA members are uniquely able to get a view of where coaching opportunities might benefit the whole team – and this can become part of your overall strategy.
It’s not only your customer service team that can benefit from insights gathered during your QA process. Your product teams, sales teams and more can see more clearly if there’s a gap between your customer experience and your brand’s expectations.
Quality assurance certifications
There are a number of industry-standard frameworks and certifications designed to help businesses ensure product quality.
ISO 9000 and ISO 9001
Over a million companies in more than 170 countries are now certified to ISO 9001, which is a standard within the ISO 9000 family that defines the criteria for a quality management system. ISO 9000 was established in 1987, and describes seven quality management system principles:
- Customer focus
- Engagement of people
- Process approach
- Evidence-based decision making
- Relationship management
CMMI (Capability Maturity Model Integrated)
This framework works on the principle that organizations willing to put time and resources into process improvement are more mature and capable than others. It describes maturity and capability across several stages:
- Capability Level 0: Incomplete
- Capability Level 1: Initial
- Capability Level 2: Managed
- Capability Level 3: Defined
- Maturity Level 0: Incomplete
- Maturity Level 1: Initial
- Maturity Level 2: Managed
- Maturity Level 3: Defined
- Maturity Level 4: Quantitatively Managed
- Maturity Level 5: Optimising
Quality assurance use cases
Flagging issues and changing strategy to be more quality management focused
Let’s say your company has just implemented a new payment system. Your customer service team might notice an uptick in complaints calls specifying the new system as a problem. This might not automatically be flagged further up in the business, as your customer service team always resolves these complaints.
QA – if instructed – can not only evaluate if your team’s calls are up to standard, but also evaluate if negative interactions are due to this particular issue. They can then flag this to relevant teams, and changing the approach to payments becomes part of your overall strategy.
This may already be something that your QA operation does informally, but making strategic suggestions part of their role can help you to create greater cohesion between your teams and ultimately, a better customer experience.
Updating your approach to customer service based on data
In this example, QA is evaluating customer interactions with Agent A and Agent B.
Agent A’s calls take longer than advised. She takes time to make small talk with the customer. In your evaluation, you can see that Agent A’s ratings for customer service are higher. There are fewer repeat calls from the customers that interact with Agent A.
Instead of penalising Agent A for taking longer than advised, QA suggests that it is more cost-effective to take more time on the original customer service call than to have repeat calls. As a result, you implement a new strategy for your agents that asks them to take time to make small talk to your customers.
Agent B has been instructed that it is acceptable to put customers on hold. Of his own volition, he informs the customer of the estimated time that the call will be held before he puts them on hold. His ratings for customer service are higher than his peers, though they all put customers on hold when appropriate.
QA managers see the benefit of setting customer expectations and implement coaching on expectation-setting for all customer service team members.
What makes a quality assurance program effective?
The best way to judge the quality of your service is to use intelligent sampling. Depending on business maturity, companies might be using:
- Manual sampling: QA picks logs at random to evaluate customer service and team members. There are no criteria for this sampling other than it is a random selection. Only the samples selected are scored against your quality requirements.
- Automated sampling: QA has “guardrails” in place to select their sample. For example, perhaps you automatically disregard calls under or over a certain time frame. Only the logs that are sampled are scored against your quality requirements.
- Intelligent sampling: An experience management platform or similar automatically scores all logs received against your chosen criteria. Using AI and natural language understanding, it determines which samples are statistically significant and delivers them to QA for evaluation.
A dedicated QA team
A dedicated QA team can help to avoid:
- Biased evaluations carried out by team members that have a stake in the score
- Responsibility overload for customer service leaders
- Missing opportunities for coaching and systemic change
- Repeat problems not being flagged for resolution
Using sophisticated quality management systems
Using technology such as an experience management platform offers the following benefits to your QA process:
- Intelligent sampling
- Removal of bias when sampling
- Full evaluation at speed of all the data you collect against your QA criteria
- Reduces instances of human error
- Ability to overlay different types of data in one location for a better understanding of the full customer experience picture
- Ability to identify patterns and trends in customer data
A quality management-focused strategy
Rather than having a static approach to customer experience, a great quality assurance program has strategic thinking built-in. Your QA team should be enabled to flag points of interest outside of the criteria they’ve been asked to evaluate.
By focusing on building a data-driven quality strategy rather than box-ticking, your quality assurance becomes a key part of your business strategy. Intelligently analyse conversations with the Qualtrics XM Platform™.