Last year, I prepared several articles reflecting discoveries I found in my quest to identify a quality body of knowledge which adequately represented the concept of Quality 4.0. Along the way, my journey of discovery found many forks in the road. It became apparent that many approaches were applicable in attaining my goal of quality, as a body of knowledge in support of digital transformation organizational excellence. This article summarizes my previous discoveries and new information supporting this evolving topic.

My search for Quality 4.0 body of knowledge discovery began with an extensive literature review for me to better understand the Digital Industry 4.0 Transformation environment. This initial review included analyzing post 2017 published peer reviewed books, conference proceedings, and white papers. This literature provided a foundation for determining the basic critical elements to be evaluated for inclusion in a Quality 4.0 body of knowledge. From this research, it was evident that quality, as a functional requirement in digital transformation, was not a factor receiving attention. The term “quality” rarely appeared in any of these publications. The concept of quality was frequently “loosely” referred to in an early developmental stage. By an early developmental stage, lessons learned from several decades of quality management systems were ignored. It is implied that new quality management was not a factor in digital transformation.

By applying my knowledge of quality management system best practices, I developed an outline directing me where to proceed in my research. This Quality 4.0 research began with a detailed examination of the basic tools of quality and their adaptability to potentially address the type of data collection which would be needed in this environment was the topic of my first published article.

The foundation of a Quality 4.0 body of knowledge includes two major elements, the human factors and the technological factors. My second article on this topic included a summary of the human side of Quality 4.0. The philosophies of Deming and Drucker were refreshed with a correlation of how Deming and Drucker’s concepts are applicable to Quality 4.0 in 2025. New environmental factors such as the multi-generational workforce, along with the significance of recognizing the value of human diversity in employees were discussed.

This third contribution of developing a Quality 4.0 body of knowledge examines the technology aspect of digital transformation. Technology presents a serious challenge since it continues to evolve. The content of the Quality 4.0 body of knowledge needs be agile and flexible, while continuing to provide a foundation for continuous improvement in a structure process. There are an abundance of well-prepared articles and webinars communicating aspects of digital transformation. One area that is receiving attention is artificial intelligence (AI). My concern is that the high exposure to the element AI is going to influence the thought process of future leaders that digital transformation is primarily AI. An article prepared by ASQ in 2024 addressed this issue by explaining how tools of enabling technologies are needed to support Quality 4.0. Included in these tools are AI, big data, deep learning, machine learning, and data science. These additional areas may not be developing as rapidly as AI, but they should not be overlooked.

An industrywide consensus exists that there is no shortage of data available for organizations to make decisions. We have data, but don’t know how to use it. This need is where the Quality 4.0 body of knowledge should provide guidance. The term “real world data” is emerging to capture this challenge for further discussions.

My journey to discovery found me in another part of this jungle of digital transformation factors. The area of data science and how data science contributes to digital transformation requires further investigation. Data science is defined as the extraction of insights using statistical methods, machine learning, and other techniques. It is an interdisciplinary field that uses scientific methods, process algorithms, and systems to extract knowledge. A correlation to the quality body of knowledge is developed by this definition. Statistics have always been a critical element of quality. In 2024, an ASQ article identified machine learning and several other enabling technology tools, which further strengthens the quality body of knowledge correlation.

Data science is a critical element of digital transformation, but how data science functionally contributes to the process was not clearly explained. This question directed me to investigate the concept of what a data scientist is. Research indicates that there is no typical data scientist. When searching for a data scientist, many companies emphasize the skills needed are the knowledge of contemporary programming computer languages such as R or Python. These companies require the data scientist basic job requirement is finding, cleaning, and organizing data.

The functional aspects of a data scientist are more complex than a solid knowledge of a programming language. Data scientists interact in an interdisciplinary setting. The ability to solve problems is a skill required of a data scientist that is even more important than programming skills. Additional skills required of a data scientist include good communications skills, the ability to build and facilitate teamwork, mathematical expertise (statistics), and a business acumen. Except for the need for programming skills focus, the successful data scientist needs to possess skills of quality professionals that have already been developed in the Quality 3.0 body of knowledge.

My extensive journey through technology, which is not yet complete, seems to be leading me back to the significance of the contribution human factors provide to the Quality 4.0 body of knowledge.

The next phase of my research journey involves an attempt to gather some experiential information from companies that are utilizing a data scientist in their digital transformation. A final clearly defined Quality 4.0 body of knowledge might never be accomplished since this topic continues to evolve. My research journey continues. Opportunities for improvement will always exist.