A novel method for identifying and characterising stakeholders in the development of DfAM methodologies based on lead user theory

Imagine a world where the way we build things is shifting from traditional factories to machines that create objects layer by layer, a process known as additive manufacturing. For years, this technology has been a reliable tool for making quick prototypes, allowing engineers to test shapes before committing to mass production. However, as industries begin to use these machines to create the final products themselves, the challenge has moved beyond just designing a single part. The real hurdle now lies in how entire companies organize their work, manage their teams, and decide when to use this new technology. This is the realm of strategic-organizational design, where the focus is not on the shape of a screw or a gear, but on the flow of information, the structure of departments, and the methods used to integrate these machines into the daily rhythm of business. Without the right people to guide this transition, companies risk wasting resources or failing to unlock the full potential of the technology.

A team of researchers at the University of the Bundeswehr Munich has tackled the difficult question of how to find the right people to help build these new organizational methods. In the past, researchers often relied on small, isolated case studies to understand how companies adapt to additive manufacturing. While these stories provide detail, they often fail to show the bigger picture, making it hard to know if a solution works for everyone or just one specific company. The researchers realized that to develop methods that work broadly, they needed a way to systematically identify and understand the specific needs of the most advanced users in the field. They turned to a concept called lead user theory, which suggests that the most innovative people are often those who face needs far ahead of the general market and are motivated to solve them themselves, even before a commercial solution exists.

To put this theory into practice, the researchers conducted a deep dive into the experiences of fifteen experts from various industries who work with additive manufacturing. They held detailed, semi-structured conversations with these individuals, asking them about how their companies make decisions, how they handle design challenges, and where they see bottlenecks. The goal was to listen for two specific signals in their stories. The first signal was a high expected benefit, which in this context meant a strong, urgent need for new organizational tools because the current way of working was failing them. The second signal was being ahead of the trend, meaning these users were already experimenting with new ways of working or had developed their own unique methods to handle the technology, effectively leading the pack rather than following it.

The analysis of these fifteen conversations revealed a clear pattern in what separates the most advanced users from the rest. The experts who were truly ahead of the trend had moved beyond simply using machines for prototyping. They were using additive manufacturing for series production, creating final parts that went into real products. Crucially, they had developed their own systematic methods to figure out which products were suitable for this technology and how to integrate it into their existing workflows. They were not waiting for a manual; they were writing their own. On the other side of the coin, the experts who expressed the highest need for help were those whose companies suffered from organizational fragmentation. In these cases, the deep knowledge of how to design for additive manufacturing was trapped within a few individuals. When these experts were not involved early enough in the design process, or when their knowledge was not shared across the company, the potential of the technology was lost, and designs were often sub-optimal.

Based on these findings, the researchers developed a practical method to identify these key stakeholders in the future. They translated the complex patterns they heard in the interviews into a set of questions and statements that can be used in a survey. These questions ask whether a company has defined approaches for identifying suitable products, whether they have established internal methods to support designers, and whether they are using the technology for final products. They also ask about the pain points, such as whether design potential is limited by poor coordination between departments or if expertise is concentrated in just a few people. This tool allows researchers to screen potential participants for future studies or workshops, ensuring they are working with people who are genuinely at the forefront of the field and have a real, pressing need for new organizational solutions.

The researchers suggest that this method can be used in three distinct ways. It can stand alone as a survey to find the right people for a study. It can be used before a workshop to ensure the participants are the right mix of innovators and those with urgent needs. Finally, it can serve as a way to check if a group of people selected for a study is actually representative of the advanced users the research aims to understand. By using this systematic approach, the field of additive manufacturing can move away from relying on lucky guesses or isolated case studies. Instead, it can build a more reliable foundation for developing the organizational tools that will help companies successfully navigate the transition from making prototypes to making the future of manufacturing. The study does not claim to have solved every problem in the industry, but it provides a clear, evidence-based map for finding the people who are already solving those problems and can help teach others how to do the same.