Quality Management Can’t Be Optional Anymore

No matter how small an organization is, it’s contributing to a resilient, responsible, and sustainable global community

Published: Tuesday, April 20, 2021 - 12:03

Here’s an unfortunate truth: The story of the Covid-19 pandemic is one of epic quality failures in almost every area imaginable. Although there have been some admirable successes, such as the food and beverage organizations that have ensured the continued safe delivery of food supplies to most regions, failures both large and small have caused an untold amount of damage to the infrastructure of society and business. Arguably, these quality failures have worsened the impact of the pandemic, including economic devastation and even a higher death toll.

Here are just a few of the quality failures that will become prominent themes in the Covid-19 narrative.

PPE shortages and quality failures

Almost immediately after the start of the pandemic, healthcare organizations worldwide faced a critical shortage of personal protective equipment (PPE) such as the crucial N95 respirators that would protect doctors, nurses, and other frontline workers from infection. There were two fundamental quality failures that created this scenario: first, global supply chains for PPE lacked resiliency. With most PPE manufacturing based in China, the initial epicenter of the pandemic, production shortages and protectionism quickly devastated supplies. While governments and onshore manufacturers struggled to pivot to meet these shortages, the pandemic quickly raged out of control across the world. Global supply chains must be resilient enough to withstand future crises.

Second, just-in-time supply chains in medical organizations meant that supplies of critical PPE dwindled almost immediately. Although lean manufacturing is not really to blame for this, a misunderstanding of lean might be. Keeping low stock isn’t an input that produces lean; it’s an output that is a result of lean. Medical administrators who kept low stock of PPE thinking that this would result in a lean organization misunderstood this principle and contributed to the crisis.

When medical supplies finally started flowing along the supply chain, the quality of much of it quickly became a problem. Increased pressure on manufacturing facilities, as well as manufacturers pivoting to produce medical supplies for which they had no qualifications or certifications, meant the market was flooded with poor-quality products like masks, gloves, and hand sanitizers.

Lack of systems thinking

From supply chains for PPE to food services to vaccine manufacturing, businesses and governments demonstrated a fundamental misunderstanding of how critical systems-thinking is for creating organizational and societal resiliency. Globalized supply chains are complex systems with multiple points of failure. Prior to March 2020, the weaknesses of this precarious framework hadn’t yet aggregated into disaster. As soon as the pandemic struck, it didn’t take much for this framework to collapse in many regions of the world.

People don’t really understand what risk is

Risk is a term we all use to suggest that something might turn out badly. Yet most of us don’t understand how much risk we actually take on, or how much risk is inherent in the fragile systems we depend on every day. Low-probability/high-impact events like pandemics are rare, but they always happen eventually, and when we don’t understand the risk of not preparing for them, we essentially invite disaster when they do. Risk-based thinking is a fundamental part of ISO 9001:2015 and other quality management system (QMS) standards that use Annex L, which should help to raise the profile of risk. However, certification to an ISO QMS standard alone isn’t the solution. Operational excellence that goes beyond certification must be the future of risk-based thinking in quality management.

Vaccine production and distribution was always going to be difficult

When successful vaccine tests were announced in December, the world breathed a sigh of relief and patted itself on the back for having successfully defeated the pandemic crisis by ignoring lockdown measures and not wearing face masks properly. Vaccines, we cheered, had arrived. Three months later, vaccine production and distribution are in disarray around the world while a third wave of the pandemic rages out of control. The European Union, a major manufacturing center for Covid-19 vaccines, has engaged protectionist measures to prevent international shipments of vaccines while its own distribution programs falter. Quality control problems with major manufacturers and their partners have resulted in large quantities of vaccines having to be destroyed, while the botched messaging concerning the safety of the AstraZeneca vaccine has caused health agencies to deliver conflicting information to confused citizens who consequently become more reluctant to take any of the vaccines.

Data science must do better

Government responses to the Covid-19 pandemic have been evidence-based, relying heavily on modeling projections produced by public and private data-science specialists. Much of this modeling is deeply flawed, which has resulted in unfortunate communication errors and mistaken policies, as well as stoking too much fear where there should be none, and not enough where there should be plenty. Many governments used poor modeling to justify locking down when they didn’t need to or opening up too early while the pandemic was still raging.

Some of this blame can be placed at the feet of news media, which tend to run quickly with headlines based on studies that haven’t been peer reviewed or published. Much of the problem, however, is with data quality, including a lack of reporting standards for healthcare units in different regions, poor data management, inapplicability of historical models, and lack of expertise among data scientists tackling epidemiological modeling. Data have been the foundation of the Covid-19 response, but in many ways, data science has disgraced itself during the last year. As long as data quality remains generally poor, data science will remain a problematic strategy for crisis response.

Conclusion

Quality management programs wouldn’t have prevented all these failures. After all, continuous improvement is built on the principle that perfection is never achieved, only sought. However, broader acceptance of quality management principles could have gone a long way toward mitigating the impact of the pandemic.

Quality management is no longer something that is nice to have. While there is no law mandating that every organization achieve operational excellence through ISO 9001:2015 and the Baldrige Excellence Framework, it is time that we realize that every business, every organization, and every government is part of a complex system in which we are all potential points of failure. No matter how small an organization is, it is contributing to the creation of a resilient, responsible, and sustainable global community. If we don’t achieve operational excellence in our roles as components of a complex global system, we have the potential to be part of the problem. Quality management isn’t an option anymore: It’s a moral imperative.

About The Author

Graham Freeman

Graham Freeman is a writer and editor at Intelex Technologies, ULC in Toronto, Canada. He has written extensively on topics such as quality, health and safety, environmental sustainability, and knowledge organization. Graham works and teaches as a technical writer in Toronto.