What quality managers should prioritize in 2023

2023 will not be a boring year either. Not least, quality management is facing major challenges – both in terms of content and organization. You can read about which trends are moving to the top of the QM agenda and how to successfully take the bull by the horns in our latest blog post.

What are the issues trending to the top of the QM agenda? These are the top issues for the coming year: 

  • Top trend 1: Resilience in the supply chain
  • Top trend 2: Deeper integration with engineering
  • Top trend 3: Predictive quality analytics
  • Top trend 4: In-house app development
  • Toptrend 5: SaaS
  • Toptrend 6: New standards for industrial companies

Toptrend 1: Resilience in the supply chain

The pressure on supply chains is constantly increasing. And not just since the pandemic, or the Ukraine war, the call for more resilience has become much more urgent since then. No question about it. Nevertheless, the actual change goes much further. The linchpin of this development is the increasingly intensive agilization of the entire value chain. On the product side, the shortening of product life cycles and the integration of Industry 4.0 solutions are among the most important drivers. From an organizational perspective, it is about the increasing division of labor in partner ecosystems and the conversion of the product portfolio to purely customer-based service models. 

The resulting requirements for the supply organization and quality management could hardly be greater. After all, it is necessary to establish procedures with which new supplier relationships can be set up much more quickly than was the case in the past. OEMs and system suppliers in particular will have to rethink their approach. At least partially. They need a plan B to the qualification procedures, in which they spend a lot of time and energy on auditing the supplier’s production process on site and then checking the achievable product quality on the basis of sample parts.

In view of the worsening supply bottlenecks, it is worth looking at whether, instead of a full product audit, it might not be sufficient to issue approvals for certain specifications and then leave it up to the suppliers to decide how to implement the requirements. Here, it is important to weigh up exactly which features should be part of the specification so that the supplier processes can actually become more agile. For example, you can question whether the tolerances you allow your supplier are correct.

Another approach is for suppliers to send their customers the test results they collect as part of their own statistical process control to a much greater extent than before. This opens up new opportunities for the customer’s quality assurance department to check subsequent delivery quality while the production process is still underway and to raise its hand earlier in the event of relevant deviations. One example is the increased use of predictive quality analytics (see Toptrend 3). Against this background, it is essential that the lead QM system is open to technology and can integrate the different OT systems of the suppliers with the least possible effort.

Top trend 2: Deeper integration with engineering

The integration of engineering and QM is one of the central challenges of every industrial company. Now the topic is getting another boost. The driver is the Industrial Internet of Things (IIoT). More than ever, the benefits of products depend on the smooth interaction of their mechanical, electronic and software components. However, the associated increase in complexity is considerable. And this is happening at all levels of value creation and in all phases of the product life cycle.

The extent to which complexities are increasing is already demonstrated by engineering itself. Let’s remember: In the past, the individual development domains – mechanical, electronic and software engineering – could act relatively independently of each other. Sure, this approach also knew obligatory handovers. No question about it. But development processes have now become too agile to synchronize work results in the usual way, i.e., serially. Ultimately, a much higher degree of change is generated than was the case in earlier times. But it is not even the sheer quantity that is decisive. What pushes the old approach to its limits is the fact that almost every one of these changes has an impact on the overall system and must therefore be processed across domains.

This can only work if everyone involved works with the same system model. Regardless of whether they come from engineering or the value creation that is based on it. All activities must always refer to this one model, which breaks down the entire specification of the product in a standard-compliant manner. The be-all and end-all of model-based development is a 100% homogeneous database. To achieve this, a technology-open IT OT platform is needed that integrates all industrial subsystems bidirectionally – i.e. reading and writing. With Edge.One, such a platform is available. The deeper the integration reaches, the greater the process reliabilit. So that all those involved actually get a 360-degree view of the latest status of the development model and complete their respective tasks in a quality-assured manner.

Top trend 3: Predictive quality analytics

There is no doubt that Artificial intelligence (AI) is one of the trends with the highest staying power. For years now, hardly a day goes by without new application ideas. But which of those ideas is actually ready for the market? Machine learning is currently of particular economic interest. Insiders see this as a precursor to AI. After all, the actual decisions will continue to be made by humans. Nevertheless, machine learning provides a knowledge base for decisions that is almost impossible to obtain using conventional analysis methods. This is especially true when it comes to more complex forms of pattern recognition and the data pool to be evaluated is extremely diverse.

In the QM environment, these strengths can be exploited particularly well. Above all in statistical process control (SPC), where large quantities of different product and process data are generated. Thanks to machine learning, it is now possible to cross product- and process-related quality measurement data with suitable context data. The latter can then provide information on when and why a particular quality problem is most likely to occur. When the room temperature drops below a critical mark? When workers with such and such qualifications are at the machine? Always on odd days? If … The list could certainly be continued for quite a while.

Appropriate actions must then be derived from the analysis knowledge gained. The goal is to eliminate the quality deficiencies before they lead to performance losses in live operation. For example, product owners and quality managers can identify precisely which production steps could benefit from additional audits. Analysis and action are thus inseparable. Their interaction ensures that predictive quality analytics can fully develop its business benefits and that the continuous improvement process (CIP) can look much further ahead than was possible with conventional means of analysis.

Top Trend 4: App Development on Your Own

If you want to democratize quality management, you should give QMS users additional freedom. For example, when it comes to determining the course of their workflows and changing the design of the user interfaces. Or to add to it. For example, by adding new forms that address regulatory changes. Until recently, however, users had little chance to make such adjustments themselves. Instead, they had to register their change requests with IT. The IT department, in turn, commissioned the software manufacturers. This often led to project runtimes and expenses that none of the parties involved could really be satisfied with.

But there is now a remedy. Modern IT platforms such as Edge.One offer development tools that end users can also use. Since these tools can be used without having to deal with the actual software code, they are referred to as low-code/no-code development. The programming language is now replaced by graphical design tools that can be operated preferably via drag & drop. QMS users then have the possibility, for example, to design their dashboards in a way that corresponds to their personal way of thinking and working. For example, they can view the progress of the daily QM discussions they have with their colleagues in production.

But there are also advantages for the IT department. After all, democratization of the design also increases acceptance of the software and thus its degree of use. Workarounds with Excel tables and the like are becoming less and less important. With every isolated solution that is eliminated, IT’s design options improve. For example, when it comes to strengthening cyber security throughout the company. In addition, development and maintenance costs are reduced. After all, the more adjustments users make themselves, the less overhead they incur – both in their own IT and on the part of IT suppliers.

Top trend 5: SaaS

Cloud computing is yesterday’s news, or so you may think. But there are areas in IT where the importance of web-based system solutions is still rather low. QMS is one such area. Similar to the ERP environment, many companies stick to running the software in-house. Regardless of this, the cards are now being reshuffled once again. Software as a Service (SaaS) solutions are bringing a breath of fresh air into the game. Here, the code runs on the provider’s servers. Users, in turn, are only interested in the software functions that they receive as services via secure Internet connections.

SaaS solutions are now also ready for the market in the area of eQMS. Increasingly, they are proving to be a worthwhile alternative to on-premise installations. This is especially true when users need a high degree of agility. For example, when a large number of different users need to be integrated into a process as quickly as possible. In the case of complaints, for example. The most important advantage here: QMS SaaS can be used immediately. There is no implementation effort for the user company. Instead, users can start mapping their workflows right away and design the user interfaces according to their working methods (see Toptrend 4). This means that the time between the purchase decision and going live is reduced to a minimum.

For many user companies, SaaS solutions are therefore becoming the means of choice. In the USA, they already own half of the market. It is mainly the laboratories that are making the switch to SaaS-supported laboratory information management systems (LIMS).

Regardless of this, a certain sense of proportion is still required at present when moving to SaaS. This is due to the fact that the gains in agility are partly offset by sacrifices in flexibility. After all, if you want to make adjustments, you will find that a SaaS solution initially only offers standard processes. From a QM perspective, this has both advantages and disadvantages. The advantages are that SaaS solutions are a perfect means of introducing uniform procedures throughout the company. Sometimes, however, this also results in disadvantages. This is when company-specific adaptations are needed that affect the business logic of the SaaS software. Some change requests then take noticeably longer than is the case with cloud solutions that are set up specifically for the company.

However, market researchers such as Gartner assume that SaaS will have made up this development shortfall by 2025. Against this background, it can be assumed that the number of SaaS migrations will rise sharply in the next two years. The main drivers of this development are the agility gains that SaaS will bring.

Top trend 6: New standards for industrial companies 

Cybersecurity is the order of the day. Especially in industry. Because nowhere else is the number of hacks currently growing faster. And hardly anywhere else are the risks of successful attacks higher. The effectiveness of the information security management systems (ISMS) used in companies is therefore becoming the focus of attention.

From a QM perspective, security regulations that for many years were considered purely an IT matter are thus gaining in importance. First and foremost, these are the industry standard ISO 27001 and the automotive standard TISAX. Both standards have a profound impact on the engineering and product lifecycle of software systems. The more software now becomes an integral part of industrial products, the more urgent it becomes for their manufacturers to be certified accordingly. But that is not all. At the same time, the requirements of primarily industry-related regulations are also becoming more stringent. Be it in ISO 9001 (for example in the area of traceability), be it in industry-specific standards such as ISO 13485 for QM in medical technology.

All these developments show that the complexity of regulatory obligations is once again increasing significantly. At the same time, the number of production orders whose quality must be managed in compliance with standards is growing. Because despite all the fears of recession, the order books of most companies are still well filled. The only thing that is continuously decreasing is the number of skilled workers who can organize this growth.

More than ever, companies are being called upon to automate the standardizable parts of their documentation and verification requirements as much as possible. And wherever human interaction remains necessary, to support it in the best possible way. The ideal solution is a database-supported QMS system that offers standard-compliant workflows and whose user interfaces are precisely tailored to the needs of the various user groups. In this way, the eQMS ensures that both old and new regulatory requirements can be met in a process-safe and cost-efficient manner.