German manufacturers are facing more product recalls than ever before. Across 750 global organizations surveyed in the recent Pulse of Quality in Manufacturing Report, 48% stated product recalls had increased in the last five years.
In Germany, the impact is clear, with 41% of these organizations stating that rectifying their most recent product recall cost between €10m and €49.9m — around $11m to $55.5m.
The Financial and Brand Impact of Recalls
The financial burden goes beyond the direct cost of the recall. There are ongoing effects that can impact a business’s bottom line – even after the problem has been solved. For example, 35% of survey respondents stated that a recall affects brand reputation, and 31% report that they have had to conduct layoffs due to the impact of product recalls. This can have a huge knock-on effect on an organization, with customers losing trust and potentially choosing to buy from competitors.
Additionally, the survey revealed that recalls can delay future product launches—32% of respondents have experienced this. These delays have a ripple effect that can impact customer satisfaction and further damage brand reputation.
The Causes Behind the Recalls
There are many things that could lead to product recalls in Germany. However, these often fall into two categories: supplier-related issues and internal quality management failures.
Manufacturers often rely on suppliers from a range of regions and industries. Issues can surface if a supplier doesn’t have as stringent quality standards and practices as the manufacturer, leading to inconsistent quality across the supply chain.
Automaker BMW recently had to issue a recall for a problem with its braking system. While it stated in a press release that this was not a safety issue, the warranty cost would likely reach the “high three-digit amount.” Continental, one of BMW’s suppliers, makes the affected braking system.
Upon investigating the fault, Continental traced the defect back to a plant in Hungary. As Bloomberg reported, the brakes’ circuit boards were not produced in a clean environment, so workers left smudges and dust on the electronic components.
As manufacturers source from global suppliers, the disparity in quality standards can be significant. BMW’s issues show how difficult it can be to manage a complex, distributed supply chain.
Predictive Analytics for Early Detection
Predictive analytics, driven by artificial intelligence, can detect patterns and anomalies in real time. With networks of IoT sensors, smart devices and connected wearables all providing information on the product process, AI has a wealth of information to analyze. For example, a sensor on a machine might detect excessive vibration or temperature, which could indicate a potential issue. The alert can help a worker identify and fix the problem. However, there’s even more happening in the background to power predictive analytics.
The system picks up and remembers all these anomalies. Then, based on historical data, AI can understand what might happen next when a sensor detects something out of the ordinary. This means it can start to predict outcomes from real-time production information. For example, predictive analytics could signal that a machine needs maintenance before something breaks. This reduces downtime and ensures the quality of products.
Enhancing Supplier Management to Prevent Recalls
Because suppliers play such a large role in quality, proper supplier management is vital. It gives deeper insight into the supply chain while providing manufacturers more control over the quality of components from third parties. This can help to reduce the likelihood of product recalls.
Establishing Clear Supplier Performance Metrics
To properly manage suppliers, it’s important to establish the metrics by which they’ll be measured. Setting clear key performance indicators (KPIs) will ensure consistent product quality while reducing defects. These might include:
- Defect rate
- Order accuracy
- Compliance with standards
- Lead time
- Risk factor
Setting standards and tracking these metrics can help manufacturers negate the issues caused by different quality control processes. Doing so ensures consistency from third parties and enables the organization to spot when suppliers fail to meet quality standards. The increased transparency helps both the manufacturer and its suppliers take corrective actions faster, which helps avoid costly recalls.
Monitoring Suppliers in Real Time with AI
AI-powered technology can also help manufacturers monitor supplier quality in real-time. This allows for quick detection of issues before they affect production. For example, automated visual inspections can quickly pick up on imperfections and quality issues. This reduces the likelihood that a defective part from a supplier makes its way into the production process.
Best Practices for Recall Prevention in German Manufacturing
To overcome the rising recall rate, German manufacturers should focus on using technology to improve internal processes and supplier management. The use of tools such as an eQMS can give more visibility into the supply chain and help manufacturers spot issues before they turn into larger problems.
Implementing Data-Driven Quality Systems
The use of data is key to identifying and preventing possible quality issues before they escalate and become problems for customers. When it comes to using AI in quality processes, 99% of survey respondents stated they are either currently using AI or have a plan to use it for quality management. Of those who plan to use it, 47% state they will do so in the next two years.
That shows the potential AI has to positively impact quality. Integrating these systems into the manufacturing process can reduce the cost of poor quality, reduce waste, and improve customer satisfaction.
Strengthening Supplier Collaboration and Oversight
Along with tracking key metrics and implementing tools to bring more visibility into the supply chain, it’s also important to build strong relationships with suppliers. Fostering a culture of open communication and using data to ensure accountability can improve overall quality.
When suppliers understand a manufacturer’s quality processes and how third-party parts are integrated, they can more easily see their impact. A transparent discussion around areas for improvement, quality standards and KPIs can improve these relationships and reduce the likelihood of supplier-related recalls.
Reducing Recalls With AI-Driven Tools
German manufacturers can reduce product recalls by leveraging AI and improving supplier management practices. The result is improved financial stability and brand reputation, leading to a more resilient business.
Download a copy of “The Pulse of Quality in Manufacturing 2024”.
