Matt Chinworth
Across industries, companies are investing unprecedented sums in reskilling programs to prepare employees to use emerging technologies.1 The programs are typically built around forecasts of which skills, such as data literacy, digital fluency, systems thinking, and adaptability, will matter most. Each year, when the forecasts are updated, training courses — and their related costs — proliferate.
Yet in the three years we spent studying 10 European manufacturers navigating exactly this kind of technological change, we found that the most relevant new skills workers developed were almost never the ones that had been forecast. They emerged organically, as workers and managers figured out together how to make new tools fit the existing work — or realized that they could not. In most cases, these skills were recognizable as important capabilities only to the few managers who understood where and how to look for them.
At a well-known Italian furniture manufacturer in our study, the head of the varnishing department wanted to identify and support new-skill development. Walking the floor was part of his routine, but what made him unusual was how he responded to what he saw. When workers raised concerns about equipment used on the job or devised their own ways of handling an awkward step, he carried those observations to a newly appointed head of production and negotiated changes to the workflow. He treated the production floor as the site of ongoing capability development, and his job as the connective tissue between the people doing the figuring out and the people with the authority to act on it. What he was watching grow was concrete.
At this company, the rollout of new production equipment, including computer numerical control (CNC) machinery, was steadily turning manual artisans into machine operators and digital production monitors. That meant that craftspeople’s judgment about quality and finish now had to be expressed through digital settings and on-screen interfaces. The varnishing head’s own emerging skill was a form of shop-floor diagnosis and reengineering: spotting where a new machine hindered or disrupted the work and devising a fix for it. It was a bricoleur capability that sat between hands-on craft and process engineering — one that no job description had ever named.2 The workflow changes that he negotiated were the visible trace of that skill taking shape, within both him and the workers.
Our research found that the companies managing technological transitions most successfully were not the ones with the best skills forecasts. They were the ones whose managers had developed a particular habit of attention — one that let them see what was already emerging in the work and to harness it before an employee walked out the door with an emerging skill. We call this practice SPOT. Later, we’ll explain what it is, why it matters now, and how to start doing it within your own organization.
The Forecasting Trap
Walk into a large company today and chances are you will find someone building a future-skills matrix. The rationale is simple: If we can name the skills we will need, we can train for them in advance. But this logic does not survive contact with an actual shop floor.
From 2023 to 2025, as part of the Horizon Europe Up-Skill project, our team conducted ethnographic field work in 10 companies across Europe, from a large automotive manufacturer to small artisanal workshops. Each was adopting advanced manufacturing technologies, such as collaborative robots, mixed-reality training systems, and 3D printers.3 We watched these companies discover that the skills they needed became visible only after the new technology they had introduced collided with work on the ground.
At one company in Sweden, to help workers learn lock-assembly procedures, managers introduced a mixed-reality system — a headset-based class of tools that overlay digital guidance directly onto the physical workspace, blending elements of virtual and augmented reality.4 The visual aspects of the system could show workers what to do but could not convey the reasoning behind the steps. Workers and managers eventually developed workarounds together, and the company found that the tacit understanding of the process the system was supposed to capture was the very thing it could not. At another Swedish firm, a plan to automate a grinding operation fell apart because the automated line could not replicate the judgment of experienced human workers. Only when the automation failed did the depth of the human expertise become visible.
But the more revealing part of each story is what the workers built next. At the lock-assembly company, the gaps in the system became the catalyst for developing genuinely new skills: Workers learned to program, re-sequence, and troubleshoot the system themselves, and they worked out how to teach the unwritten “why” that the headset left out (for instance, why a particular part of the lock should or should not be greased) so that the reasoning could pass from one person to the next. At the firm whose grinding line resisted automation, a new digital system for tracking production had a parallel effect: As operators worked with it, they began to read how their own task fed the wider flow of the line — a kind of systemic awareness that the job had never previously demanded.
It is worth separating two things in these cases. What the machine could not do exposed a skill the workers already had; what the workers built around its limitations was the skill that was genuinely new: the programming, the teaching of the “why,” and the new perspective on the whole production line.
A third firm, a small Italian manufacturer of high-end accordions, watched a competitor adopt robots for a sensitive manual step. It decided not to follow suit because it suspected that the competitor was automating away something the robot could not replicate.
We observed a pattern: The skills that matter most during a technological transition are the ones that surface when the new tool meets the old workflow: when something breaks, when a worker improvises a fix, when a manager notices that the thing the machine cannot do is the thing the customer is actually paying for. You cannot forecast what has not yet emerged. So the question for leaders is not “Which skills will we need next?” It is “Which skills are already trying to grow inside our company, and are we paying enough attention to notice?”
The SPOT Framework: Seeing and Growing Emerging Skills
We developed SPOT — a mnemonic for see, partner, orchestrate, transform — as a framework for capturing the habits we observed among the managers who were best at identifying, stabilizing, and retaining emerging skills. Let’s explore each of the four elements.
See the invisible. Most managers walking a production line look for problems, but an emerging skill does not look like a problem. The head of the varnishing department we mentioned earlier was not scanning for failures. He was scanning for moments when someone was solving a problem the system had not anticipated.
The skills you are trying to see are ones the worker cannot yet fully articulate. If you ask, “What new skill are you developing?” you will get a shrug. The better questions are about the task: What is this machine doing today that it was not doing last week? What are you doing differently since the new line came in? The skill is hiding inside the answers.
Take the high-end furniture manufacturer. The useful question its managers learned to ask was not “Can you run the machine?” but “How did you decide on that setting?” The answer revealed a skill that had migrated rather than disappeared. An artisan reads the grain, the density, and the absorbency of a particular piece of wood — judgments that were once expressed through the hand and eye alone — and now translates them into the digital settings that drive a CNC machine, and the on-screen checks that monitor its work. That blend of material sense and interface fluency is itself the new skill, and it lives in the doing, not in any manual that could have been written in advance.
Managers who have been in the same department for years may have difficulty seeing what is emerging without making a deliberate effort to reframe their scanning approach. (See “Four Questions for Your Next Floor Walk.”) Rotating managers into unfamiliar settings, or deliberately hiring from outside the function, may provide a fresh set of eyes that are better able to see an emerging skill. The newly appointed head of production at the furniture company was effective in part because he was able to notice what had become overly familiar to others.
Partner with workers. Seeing signs of emerging skills is only the beginning. An emerging skill lives in the head and hands of the person developing it. The manager’s job is not to diagnose it from the outside. It is to sit alongside the worker and interpret it with them.
At a small manufacturer of brass musical instruments in the United Kingdom, management and workers were actively discussing whether collaborative robots (those designed to work safely alongside humans) could handle delicate components. Rather than making a decision in isolation and rolling out the technology, the company was treating the question as something to be worked out with the people whose work the cobots would affect. What the joint evaluation surfaced, though, was a skill the company had never named. To judge whether a cobot could be trusted with delicate, one-off components, workers had to articulate exactly what they themselves were doing: reading the small irregularities of a handmade piece and adjusting their handling by feel, one piece at a time. That judgment had always been treated as simply “how the work is done.” Putting the skill into words turned it into an explicit capability — one the company could then choose to protect, teach, and build on rather than lose through inattention.
Schedule a conversation whose only purpose is to understand how the work has changed since a new tool arrived. Ask the worker to describe what is different and then ask what they would teach someone who was about to take over the job. The answer to that second question is almost always the emerging skill. Pay attention to where the worker hesitates or gestures instead of describing. Those are the places where capability is forming. At the lock-assembly firm, the answer to “What would you teach your successor?” was not the sequence of steps that the system already displayed but the reasons behind them: the unwritten logic that tells an experienced worker when the standard procedure should not be followed. That is the skill the conversation is trying to surface.
Orchestrate learning in real workflows. Once a capability has been surfaced, the tendency of most organizations is to pull the emerging skill out of its context and turn it into a training course. That rarely works. Skills that emerge in the flow of work tend to die when they are lifted out of it, because they are closely tied to the specific problem they were solving.
At a smoking-pipe maker, an employee with engineering and 3D printing expertise took on a substantial project: developing an in-house solution for producing mouthpieces. He designed a prototype machine and partnered with another company to manufacture it, resulting in a custom lathe integrated with bespoke software. He did not develop this capability in a training room. He developed it while solving a concrete production problem. The project was the curriculum, and it led to a highly specific new capability. It was not simply “3D printing” or “machining” but the ability to combine engineering judgment, hands-on additive-manufacturing experience, and software integration well enough to specify, commission, and program a custom production machine from end to end. That composite skill existed nowhere in the firm before the employee assembled it on the job, and it is now part of what the company can do.
When a worker shows signs of developing a new skill, resist the temptation to let them practice in a sandbox. The skill will develop faster if it is applied to a real production problem with actual stakes. Your job is not to remove the risk but to make the environment around it supportive enough that the worker can learn from what happens. At a specialty print firm, workers migrating a manual engraving process onto a new machine were themselves contributing their tacit knowledge to the digital systems. When tacit knowledge must be translated into something a digital system can use, the person best placed to do the translating is the person whose knowledge is being translated. And the translation is itself the emerging skill, not a preliminary to it. Learning to turn a feel for the work into instructions a machine can follow happens only on the live system, against real material and real consequences, not in a classroom where it is rehearsed in the abstract. The ability to transfer knowledge to digital systems becomes a new skill that the company has at its disposal when new digital technologies come along.
Transform insights into lasting capability. New skills identified and developed in the three steps above can live in the head of the worker and the memory of the manager for a while but will eventually vanish if not transferred to a more robust medium.
Let’s return to the accordion maker. The firm’s refusal to follow its competitor into robotic production looked, from the outside, like a conservative choice. Viewed through SPOT, it was a transformative decision. By drawing a circle around a capability it had recognized but could not yet fully specify, the firm converted a tacit and fragile skill into a strategic commitment the organization could articulate and defend. The subtle feel and sound of handcrafted components was no longer something the firm happened to have.5 It was something the firm was now explicitly protecting as a matter of policy. That stance, not any specific training program, is what locked the capability into the organization’s future — what is sometimes referred to as a company’s DNA.
A parallel example came from the furniture manufacturer’s varnishing department. The newly appointed head of production was actively encouraging employee involvement in technology adoption across the company. What began as one department head’s way of working was being supported and, in the process, normalized by a shift in managerial culture at the top. The transform move was the institutional decision to frame bottom-up innovation as how the company worked rather than as an exception or aberration. What had started as the varnishing head’s hybrid skill — reading where a machine failed to support the work and adapting to that — started as one individual’s practice before it migrated to the rest of the firm. Treating support for bottom-up innovation as established practice turned it into an embedded competence that could deliver competitive advantage into the future.
SPOT is not a new training methodology. It is a reorientation of managerial attention, away from the forecasting of skills and toward noticing the ones emerging quietly right in front of you, if you care to look, as workers solve problems and get on with their day. This managerial work is slower and less visible than delivering training and certainly less dramatic than strategic restructuring. But it is also, based on our study of manufacturers adapting to technological change, what actually works. Start with one floor walk this week, incorporating the SPOT framework, and see what your dashboard never told you.