As part of the Quality Leaders Forum, we sat down (virtually) with Steve Diedrich for a primer on compliance vs. quality and how we might use Simon Sinek's framework of "finite and infinite games" to think about quality management. Register now for "Playing the Infinite Game in Quality," an interactive forum with Steve Diedrich.
What is an "infinite game" and how does it relate to quality management?
In his book Infinite Game, Simon Sinek has defined the infinite game of business as one where each player has their strategy, and there is no set of fixed rules (other than the law). There is no beginning, and there is no end. In an infinite game such as business, there are no winners or losers. Rather, players drop out when they run out of the will and resources to continue playing. In this context, business leaders should stop thinking about who wins or who is the best and start thinking about building strong and healthy organizations that can stand the test of time.
We can draw some parallels within the quality world to an infinite game. There is no beginning or end to true quality, it is an ongoing journey. By contrast, compliance represents a finite game in that once it is achieved, the goal for “quality” is seen as completed. In fact, compliance is not the true goal for quality, but is merely a by-product of the quest for true quality, which is infinite in duration and scope.
What is the difference between compliance and quality metrics?
Compliance is a status. It indicates the extent to which a company fulfills the minimum expectations defined within an official guideline (e.g., Regulatory Guidance document), a set of regulations (e.g., 21 CFR Part 210, 211, etc.), or a piece of legislation (e.g., the Food, Drugs, and Cosmetics Act). Compliance is typically assigned due to a point-in-time review of a company, such as from a GMP audit.
Quality metrics are selected key quality performance indicators that are routinely monitored over a period of time as a means to identify and quantify quality trends. Many organizations have recently highlighted the usefulness of quality metrics such as the FDA's Quality Metrics for Drug Manufacturing, the International Society for Pharmaceutical Engineering (ISPE)'s Quality Metrics Pilot Program, and the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH)'s guidelines.
An example of a quality metric might be the number of lots manufactured correctly the first time as an indicator of the effectiveness of processes and controls applied to the manufacture of a drug product or drug substance. Quality metrics typically take the form of a report that presents the information in a meaningful way, permitting the identification of trends as predictors of future performance, or reviewing the effectiveness of continuous improvement initiatives on past performance. For example, an increasing number of lot failures and re-work could indicate issues with the process, materials, personnel, or equipment requiring further investigation and remediation.
In practice, compliance is essential to avoid penalties, increased scrutiny by regulators, loss of business, loss of trust, etc. In contrast, the presence of quality metrics represents an element of a quality mindset, which provides a regulator and, indeed, customers or business partners with the confidence that your organization sees compliance is simply a by-product of quality, and not the goal of it.
What are the biggest opportunities for adopting quality metrics?
We collect so much data in relation to our business practices and products. Sticking to only those metrics required by regulators is truly a missed opportunity. Data can be mined to provide not only business intelligence but also quality intelligence! Rather than just looking at how well a process is doing overall, why not examine which parts of a process actually contribute the most to quality? We can make some fairly accurate predictions using quality risk management tools and validate them with real data.
We can also take it a step further by examining the cost in resources and cash invested into quality, versus the downstream effects of poor or unpredictable quality such as loss of trust, damage to reputation, and worst of all, bad outcomes for patients. If the data is there, right under our noses, why not take advantage of it?
What are the biggest challenges for adopting quality metrics?
While this varies from organization to organization, in general the obstacles tend to be:
- Resources - being able to devote time and invest resources into identifying useful metrics, implementing means of collecting data, analysis of the data, and developing meaningful conclusions that can be turned into something actionable
- Use Cases - there needs to be a recognition that anything beyond the most basic use cases for implementing quality metrics (e.g. what regulators ask for) can actually offer a benefit to the business beyond mere compliance.
- Accessibility - organizations must have mature data governance policies, and actively seek uses for its historical and in-process data beyond simple daily transactions.
How will quality metrics change the role of quality in an organization?
Quality is typically seen as a cost center, policing the organization, and creating obstacles to both efficiency and cost control. However, quality could be seen as a useful business partner, offering insights into the process and product problems, which add to the cost of goods, reduce efficiency, and waste useful data.
Quality culture should be defined across the industry. If not by a regulator who has to determine if it is present or not, then by the industry itself. Of course, that may have to occur one organization at a time, but it should start somewhere for those that have not already done so. Culture comes from people, not rules. Setting values, living the values, and encouraging all employees to embrace it as part of their every day will establish the culture.
I think there is some value in having some fundamental quality metrics across all organizations, but each should determine what value their data can bring. Someone like me could always make recommendations, but the quality metrics’ value can only be recognized and harnessed by the individual organizations.
Do you want your organization to adopt an infinite quality mindset? Join us on September 30th, 2020 for "Playing the Infinite Game in Quality," an interactive forum, including the risk of underreporting and how to avoid it.
About Steve Diedrich
Steve is a 25+ year veteran of the pharmaceutical and third-party logistics industry. His extensive experience with quality systems, 200+ GMP and CFIA audits, specific expertise with CSV, Data Integrity, risk-based qualification of equipment, facilities, transportation, and environmental monitoring systems have made him a valued advisor and consultant to his clients. Steve’s areas of particular interest are the interpretation and application of Data Integrity and GUI-0069 (storage and transportation) guidance. Steve is located in and provides services to clients in Ontario and the Greater Toronto Area.