The supply chain has become a vital process contributing to products and services realized by organizations. It must function effectively to support organizational success. Current quality management systems include best practices for implementing and monitoring the routine functions performed within the supply chain. Quality engineers and auditors apply these best practices to determine how well the supply chain is performing. To support this process, numerous software programs are available with a focus on supply chains. With both the quality professionals and real-time software, supply chains continue to struggle with developing an optimal process performance level. The concern is, should SPC integration be a requirement for the supply chain activities?

The background for asking this question comes from my primary university responsibilities, which are to coordinate all the activities associated with a Master of Science program in Quality Assurance. Occasionally I assist other university professional programs with improving their program processes. Recently, my additional university activities involved assisting the review of the current Supply Chain Certificate program. This investigation aligned with my prior industry work experience since I was a Certified Purchasing Manager before directing my career into quality.

Research into the current supply chain body of knowledge revealed several points of interest from the perspective of a quality professional. The fundamental supply chain body of knowledge, which has been in place for years, includes operations planning and sourcing, along with making and delivering with data science and software integration focus. The area of the body of knowledge that caught my attention was the importance of metrics for measuring supply chain performance.

Critical functions such as customer service, internal efficiency and demand flexibility include a focus on measuring and reporting performance activities. Supply chain performance metrics and diagnostic measures (SCOR Model) administered by the Supply Chain Council is commonly utilized in conjunction with APICS best practices. SCOR model is a matrix with three layers of detail. These three layers include four performance categories: customer service, internal efficiency, demand flexibility and product development. Details of these areas are reported from a strategic, tactical, and operational perspective. There is no specific guidance as to how the data should be gathered or communicated. Data reporting is recommended by using graphics, such pie charts, bar charts and line charts, without any supporting explanations to assist with gathering reliable data and reporting this performance data.

Quality management systems address assessing how well organizations perform in relation to their strategic, tactical, and operational perspectives, like SCOR. Quality metrics, such as the Balanced Scorecard reports, are commonly applied.

The supply chain body of knowledge addresses similar issues as the quality management systems, but with vocabulary inconsistent with the vocabulary of quality. The supply chain body of knowledge only references quality from the Industry 3.0 perspective of quality as a critical aspect of production. Quality as the current basis for organizational excellence is not included. Supply chain professionals are provided with general guidance for data gathering and analysis. This data gathering expertise already exists with quality professionals. Cross-functional collaboration is overlooked.

With a common goal of effectiveness and efficiency for both the supply chain and quality management system, a more collaborative effort would be beneficial. The evolution of the supply chain and quality management followed similar timelines. In the 1990s to the turn of the century, quality evolved from the production foundations in Industry 3.0 to quality as organizational excellence in Industry 4.0. It was about the same time frame that the supply chain evolved from a cost center, necessary to conduct business, to a business unit where the supply chain can add increased value to an organization. The paths of the supply chain and quality did not fully integrate. They continued separately to a common goal.

An effort to move to a more integrated supply chain – quality organizational excellence would benefit not only the professionals in these two functional areas, but the overall organizational performance. To initiate a major operational change requires visible management commitment and a gradual cultural change.

A practical first step to achieve integration for the supply chain and quality is to develop a common glossary of terms for routine activities, especially those key performance measures which are regularly reported. The importance of understanding quality terminology was brought to my attention while teaching a recent supply chain class. My question to the class asked if their company used control charts. The overwhelming response was “yes.” Examples students provided included on-time deliveries, warranty, and reportable first-aid cases. These were not control charts. They were run charts. After a detailed explanation of control chart was made to the class, the question was asked again. They all agreed that there was no control limits for the categories measured and run chart was the proper term. This was only one example where a misunderstood term could lead to future misunderstanding. Quality auditors and quality engineers often ask questions the supply chain professionals do not fully comprehend because the terms are not included in their body of knowledge.

My original question was: Should SPC be integrated into the supply chain activities? SPC, like control charts, is another misunderstood term. SPC does not have a value-added application in most supply chain functional areas. SPC refers to the use of statistical methods to monitor and control processes, typically in high volume applications. Quality engineers and quality auditors should recognize the difference between SPC and statistical analysis. The supply chain collects the data and applies statistical analysis, which is the activity of applying some form of structured equation or analysis to the data. The basic statistical analysis can be as fundamental as adding all the data and calculating an average. It is important that a basic common understanding of terminology and applications is present. Statistics should not be intimidating. It is a critical analysis of data to support improved effectiveness and efficiency in the supply chain. To be effective, common vocabulary and proper usage of this vocabulary are necessary. Integrating a statistical analysis culture is a major first step to supply chain – quality collaboration.

He is also the 2024 Quality Professional of the Year