Modernizing Quality and Risk Management Practices in the Automotive Industry

Automotive manufacturers are leveraging human capital, natural language processing, and enterprise knowledge management tools in new ways to address heightened contemporary concerns about product quality, risk, and recalls.

Quality management, risk management, and Failure Modes and Effects Analysis (FMEA), are standard operational processes that product development organizations rely on to ensure that high quality standards are attained while minimizing risk factors. A step-by-step approach for identifying, as comprehensive a set as possible, of failures or risks in a product, process, or service, FMEA focuses on anticipating and taking actions to eliminate or reduce failures, starting with the highest-priority issues.

Most organizations incorporate quality and risk processes into their routine product development activities, and as such are fairly effective at implementing and using them. However, there remains significant room for improvement. For example, many firms address quality and risk management on a “one-off” basis (i.e., a process that’s performed afresh for each development effort, without systematic capture and carryover of learning from previous efforts). This practice is prevalent because it is often surprisingly difficult, even in the current digital information age, to locate and reuse knowledge regarding previous product lines, from organizations’ data repositories.

The challenges associated with quality and risk management don’t end there. Increasingly, products are integrations of complex subsystems, and while engineering teams have significant expertise within each of those individual subsystems, integration results in complex interactions that can produce unanticipated risks. To minimize the risks of such interactions, organizations need both, a formal way of identifying as many of these unanticipated risks as possible ahead of product launch and a way of continuing to track performance to allow quick reaction to any issues, should they arise.

The High Cost of Ignoring Quality and Risk Management

There are a few good reasons that now is the right time to address the need for improved quality and risk management. First, there are both benefits to a proactive approach and potential risks to reacting after a problem has occurred. When working with complex systems, it’s generally better to address problems before they arise—particularly when they involve regulatory compliance or safety issues. Having to deal with these issues in the field or even after integration into final designs can multiply initial development costs many, many times over. In some cases, such as those that involve significant danger to human safety or large scale environmental damage, the costs can be effectively unbounded, thus threatening the survival of the business itself.

By dealing with quality and risk issues upfront, companies can not only avoid significant future costs, but they can also parlay their experiences into a highly effective development process that results in more reliable and higher quality products and services.  And, they should do so quickly.  A January 2015 Pulse of Engineering survey conducted by IHS among more than 2,000 global technical professionals found that 57 percent of engineers are required to do more with less, 52 percent said pace is increasing, and 44 percent said that pressure to meet deadlines and cost cutting are threatening product quality.         

The good news is that, over the last few years, there have been tremendous and rapid advances in information technology—including the ability to handle large quantities of data, rapidly monitor information, and perform natural language processing (whereby unstructured data can be turned into really meaningful information). Today, companies have the ability to actually solve problems using solid tools and platforms that can be implemented at a cost that would be only a fraction of what would have needed even just a few years ago.

Leveraging Knowledge Across the Enterprise

Enterprise knowledge can effectively help auto and other manufacturers improve product quality and reduce risk. The first step in dealing with these risks is to deploy an effective set of knowledge management tools. But that is just a starting point because simply deploying tools is not sufficient for solving the overarching issue of ineffective quality and risk management. The most effective organizations establish strong processes, in which the tools themselves serve as one part of a larger whole. These processes include regular risk reviews, knowledge capture, and the publication of that knowledge in a manner that can then be retrieved from the knowledge repository and used in the creation of the next generation of products.

For an organization’s quality and risk management approach to be most effective and efficient, the system must leverage the best capabilities of both software tools and human engineers. Software tools are very good at sorting through large amounts of information and rapidly identifying trends, while human beings are excellent at the creative process of brainstorming multiple solutions and selecting among them to meet complex functional, consumer and compliance requirements. Truly effective organizations make use of the best of both worlds in solving their problems and developing systems that take both quality and risk into consideration on all projects.