Even though most businesses have invested in quality management and performance improvement, each organization is unique. People, processes, and machines must be coordinated to achieve desired outcomes. This is not easy.

Whether you’re in discrete manufacturing, a process industry, or a service environment, it’s likely that you face challenges like:
• Variability in customer satisfaction and experience
• Resource constraints that impact quality and performance
• Inconsistent and/or inefficient processes
• Availability, reliability, and timeliness of information for decision-making
• Effectively prioritizing tasks and activities
• Organizational silos that reduce the speed and quality of decision-making

Furthermore, you may have more visionary goals like promoting sustainability throughout your environmental, health, and safety functions, or promoting sustainability in the supply chain. It’s hard to pursue these things when there are problems getting in the way of customer satisfaction, occupying the time of your managers and your staff.

Quality management is not just about getting rid of the bad—reducing defects, eliminating waste, and handling customer complaints and corrective actions. It’s also about building the capabilities of your organizations and your people so they can realize the good. To yield the greatest benefits, quality management must also address continuous improvement, which should be focused on outcomes you want, not just outcomes you don’t want and seek to eliminate.

Disconnected quality events, as well as information that could lead to improvement or growth, can originate anywhere in an organization. A corrective action, for example, could be initiated by an audit finding, a customer complaint, or analyzing a key performance indicator (KPI) over time. Discovering these elements and acting on them requires understanding how the quality management system (QMS) works in functions across organizational boundaries. This concept has been called quality architecture by some authors. Especially when processes are managed manually or in Excel, disconnected data sources (and the inability to access them to use the data) can lead to slow responses or bad decisions. Making bad strategic and tactical decisions is far worse than operating less effectively than the ideal.

“Doing the wrong thing right is not nearly as good as doing the right things wrong,” says Russell Ackoff, speaking at the 1994 Learning and Legacy of W. Edwards Deming conference. “Until managers take into account the systemic nature of their organizations, most of their efforts to improve their performance are doomed to failure. If we have a system of improvement that is directed at improving the parts taken separately, you can be absolutely sure that the performance of the whole will not be improved.”

Though often considered an aspect of operations, quality is inherently strategic. Achieving quality goals requires a systems thinking approach to be effective. Systems thinking means examining the performance of the system as a whole rather than attempting to optimize the performance of the parts in isolation. Less efficient processes can be even more effective at the systems level—especially when the skills and performance of the people who play roles in those processes are taken into consideration.

Achieving this balance requires an effective quality architecture. This requires taking into account which quality tools to use, when and how to use them, and which software systems to implement—or avoid implementing. A robust quality architecture can help you achieve better alignment (making sure everyone has the information and resources to work collaboratively toward shared outcomes) and deliver greater value (while reducing or eliminating nonvalue-adding activity). At the same time, a high-level view of how you manage quality can help you identify high-impact initiatives that will move you toward Industry 4.0/Quality 4.0, whether you are in manufacturing or another industry.

Our Dec. 4, 2018 webinar, “SPC and FMEA: Integrating Systems Thinking Into Your Quality Architecture to Drive Improvement,” will cover all this and more—and you’ll also hear examples of how suboptimal processes may not be that detrimental after all. Focusing on failure mode and effects analysis (FMEA) and statistical process control (SPC) as core tools, we’ll show you how to make the most of your investment in quality systems and quality software.