Why industrial engineering holds the answer to a problem American business keeps reinventing
A role called the Forward Deployed Engineer has been generating significant attention in technology circles. The scope is that of an engineer who embeds directly with customers, builds in the field, and makes software work in the messy reality of operational environments rather than the clean conditions of a development lab.
It is presented as an innovation. It is not. And understanding why we keep needing to rediscover a job function that is almost as old as the American Industrial Revolution points to something deeper: a persistent misunderstanding of what operational excellence actually requires, and a cultural resistance that has cost the American industry more than it knows.
The Myth of Separation and the Story We Tell Ourselves
The birth of the textile industry in America and, later, the Ford model of mass production are often cited as foundational myths at the source of American industrial philosophy: the belief that separating design from production yielded more efficient use of labor and materials. In the 1940s, Professor W. Edwards Deming challenged this thinking by building quality frameworks and control methods into systems through statistical methods and human factors principles. American industrialists, confident in their postwar dominance, were largely uninterested. Japan, on the other hand, adopted his ideas and made them their own. The consequences of that divergence shaped the competitive landscape of the second half of the twentieth century and beyond.
Most of us in industrial engineering know this story well, but the story doesn’t end there. Throughout the twentieth century, additional scholarly work echoed Deming’s conviction and adapted to new methods of product design and execution. At Penn State, Professor Inyong Ham formalized Group Technology — the insight that manufacturing systems outperform when you organize around similarity of products / product families. In New England, at the University of Massachusetts Amherst and then at the University of Rhode Island, Professors Geoffrey Boothroyd and Peter Dewhurst gave engineers quantitative tools to design for manufacturability before costs locked in. Robert Winner and the Institute for Defense Analyses coined the term “Concurrent Engineering” as a formal mandate to integrate design and production from the outset. Karl Ulrich, Steven Eppinger, and, later, Carliss Baldwin and Kim Clark extended this to product architecture and modularity, arguing that the way a product is structured determines how well it can be made, scaled, and evolved.
The work of these scholars is enduring and backed by empirical evidence. The organizations that have most consistently dominated in execution- meaning building products with the lowest defect rates, the highest throughput, the most resilient supply chains understand something that the separation myth obscures. Execution is not the absence of thinking. It is where the most consequential innovation happens.
Be it on factory floors, deployment sites, customer environments, execution phases are not endpoints where a design gets passively realized. These are information-generating systems where unexpected constraints are signals. The question is then whether an organization is effectively structured to receive, interpret, and act on them.
The Cultural Problem Underneath
In the face of such overwhelming evidence backed by American scholarship, why is the “over-the-wall” design culture still running so deep in American businesses? Strategy is prestigious. Execution is not. Design commands premium compensation and organizational status. Operations is where costs get cut, not where value gets created. This hierarchy shapes hiring, career paths, investment decisions, and organizational structures in ways that are rarely made explicit but are consistently consequential.
The result of this bias? Organizations are excellent at conceiving things and poor at delivering outcomes. Not because they lack talented people, but because they have systematically underinvested in the capability to learn from their own operations. The root cause is not a technology problem or a skills problem. It is a cultural one. It requires recognizing that the distance between design and execution is not a sign of sophistication but a source of risk. That the professionals trained to close that distance, to sit at the seam between system design and operational reality and build feedback into the structure of the work itself are not support functions. They are the operational edge. For those responsible for improving operations in manufacturing businesses, this is not an abstract observation. It is a hold-period risk with a measurable cost.
This is what separates outcome optimization from product optimization. A product can be perfected in a lab. An outcome only exists in a system inherently dynamic, variable, context-dependent. You cannot optimize for an outcome from a distance. You have to be in it.
What Technology Is Relearning
The forward-deployed engineer, the outcome-linked solutions engineer, the embedded implementation specialist; these roles are, in different ways, attempts to solve the same problem. How do you make complex systems actually work in the environments where they have to perform, rather than the environments where they were designed?
The answers these roles are converging on- embed deeply, generate feedback, adapt continuously, measure outcomes not deliverables- are the same answers Deming, Ham, Boothroyd, and so many other scholars worked out decades ago and are largely embedded in product design courses in many engineering courses and certainly in industrial engineering curriculum around the country.
This begs the question. How does knowledge move, and how often does it have to be independently rediscovered? The discipline exists. The methods exist. The practitioners exist, and yet optimizing outcomes, rather than perfecting artifacts, still somehow requires, after almost 100 years, a fundamentally different relationship between the people who design systems and the people who operate them. Not a handoff, a perfect loop where input is equally valued, no matter the provenance.
The question worth sitting with is not whether feedback loops matter. The evidence on that is settled. The question is why it takes so long and costs so much to remember. The answer matters most to those whose returns depend on getting it right.
Marième Doukoure-Amoa is a founder @ Senvoice, a venture focused on value chains in advanced manufacturing and powder metallurgy. She writes on the intersection of operational strategy, industrial systems, and emerging manufacturing technologies.
A few References:
W. Edwards Deming: Statistician, professor, and management consultant. Developed statistical process control and the Plan-Do-Check-Act cycle. His foundational text is Out of the Crisis (MIT Press, 1982). Awarded the National Medal of Technology in 1987. The Deming Prize, Japan’s highest quality award, bears his name.
Inyong Ham: Professor of Industrial Engineering at Penn State for 37 years from 1963. Pioneer of Group Technology and cellular manufacturing in the United States. Co-author of Group Technology: Applications to Production Management (Kluwer-Nijhoff, 1985). Co-supervisor of the NEH algorithm, one of the most cited methods in operations research.
Geoffrey Boothroyd & Peter Dewhurst: Manufacturing engineers at the University of Massachusetts Amherst and University of Rhode Island. Co-founders of Boothroyd Dewhurst Inc. (1983). Authors of Product Design for Manufacture and Assembly (CRC Press). Joint recipients of the National Medal of Technology from President George H.W. Bush in 1991.
Robert Winner et al.: Authors of The Role of Concurrent Engineering in Weapons System Acquisition (Institute for Defense Analyses, Report R-338, 1988) — the paper that formally coined the term Concurrent Engineering for the US Department of Defense.
Karl Ulrich & Steven Eppinger: Ulrich: Wharton School, University of Pennsylvania. Eppinger: MIT Sloan School of Management. Co-authors of Product Design and Development (McGraw-Hill, 1995, now in its 6th edition) — the most widely used product development textbook globally. Ulrich formalized product modularity in a 1991 ASME paper.
Carliss Baldwin & Kim Clark: Harvard Business School. Authors of Design Rules: The Power of Modularity (MIT Press, 2000) — the foundational work establishing that product architecture determines organizational structure and innovation capacity.
** ideas and arguments in this article are my own. AI used to assist with drafting and editing.