In the field of medicine, we can find thousands of case in which people succumbed to diseases because they weren’t diagnosed in time to save them. We may assume that diseases and conditions announce themselves through pain or other explicit physical symptoms, but that’s not so. There are some that may show up on the medical radar very quickly (exposure to poison ivy, for example), but many others that are diagnosed when it is too late when the disease is out of control.
This situation resonates with every Quality Assurance professional. Anomalies like recalls or many other breakdowns in quality often follow the same pattern. Somewhere in the supply chain (feeder plants, distant suppliers or even remote sub-suppliers) something begins to go out of specification, but there is no “pain” at that point. It is only after an entire process has become “infected” by the out-of-spec material that the “pain” shows. Often, the “disease” is difficult to diagnose, because its effects are far removed from the cause in both time and space.
Of course, even in medicine, it’s unlikely that anyone can be one hundred percent proactive. It’s not possible or even advisable to test for every possible condition or disease on a regular basis. Best medical practices use protocols that point testing based on percentages, i.e., on the likelihood of the occurrence of a disease by gender, by age group, or by other demographic (or even geographic) indicators. Not performing tests when protocols are sending a loud and clear warning signal about the potential for a problem is considered medical malpractice.
The Contexts of Testing
Similarities between medical practice in the area of diagnosing and illness, and the practice of Quality Assurance, revolve around the use of Certificates of Analysis (COA.)
A Certificate of Analysis is a document issued by Quality Assurance that confirms that a regulated product meets its product specification. They commonly contain the actual results obtained from testing performed as part of quality control of an individual batch of a product.
The question, then, relates to how, or whether, a company uses the COA in its Quality Assurance practice. Specifically, what is the context in which COAs are held by company management?
Since a COA, in its simplest form, is a document, one possible context for it is just as simple: it is documentation. By itself, it is a document that shows one test was performed on one sample of a material at a specific point in time.
In this context, the form the COA takes is immaterial. It can be a piece of paper, whether a physical paper or a scan of a document. It also doesn’t need to be in any particular format, as long as it has the necessary information on it. The format might even be unique to each supplier who sends you a document because it is about what is convenient to the supplier, or what is customary in the supplier’s home environment.
Quality Assurance Management
In the Quality Assurance context, the COA is not seen as a single document; it is seen as data that instantly indicates a certain lot of material matches/exceeds your specifications. If analyzed over time, the COA also provides an indication of the direction in which the COA provider’s process is headed. Although it might be a single data point, it doesn’t remain that. Its meaning is amplified relative to a number of other data points, quickly indicating a trend: is it going up, down or continuing the way it was? In other words, it is not entirely meaningful as a document. It is meaningful as data against the background of comparisons. Although it appears to be one item, it is offering knowledge, not just information. It is not just about what has happened (the function of documentation) but also about what will happen (is likely to happen, given the trend, the function of data being read through Statistical Process Control).
In a sense, the COA is a noun in the context of documentation, and more of a verb in the context of QA management, since it provides early diagnosis of a potential material health issue, which should lead to action, rather than to the proper filing of documents. Of course, it may also signal improvement, which can also lead to action such as rewarding performance improvement among suppliers.
In the context of higher expectations, the format itself is key. Unless the COA is standardized and put into a digital format, it has no power of diagnostic value. Standardized, electronic COAs can be subjected to Statistical Process Control (SPC while other formats cannot. SPC makes diagnosis possible in real time and allows management to quickly notice variations in quality, differentiating normal variability from something requiring immediate attention.
The advantages of using electronic COAs include:
- Protection of production assets and optimization/efficiency
- Improvement of supplier reliability
- Access to data mining tools to power various scorecards (including the Balanced Scorecard)
- The ability to examine and adjust not only the materials themselves very quickly, but also to very quickly adjust the measurement systems being used at various links of your supply chain.
- Reduced compliance costs.
- Creation of a foundation for continuous improvement by offering quick feedback to the precisely identified links of your supply chain.
- The ability to analyze key processes within your own company and in your supply chain (including in other functional areas beyond QA that are impacted by it, such as operations and marketing.)
- Demonstration of your commitment to quality and reliability to customers, investors, employees and within your industry.
Before versus Aftermath
The difference between these contexts is the difference between preventing a “disease” before it is out of control, and an after-the-fact explanation/excuse.
There’s a good reason to invoke the medical model when discussing COAs. The deaths, injury, and illnesses that poor QA data management has caused place COAs firmly in that domain
Is it time for your company to reconsider how it relates to, and manages, COAs?