As the manufacturing workforce continues to age and approach retirement, manufacturing leaders are searching for ways to retain their institutional knowledge.
Various studies have quantified the urgency of the situation: more than 91 percent of manufacturers are hiring right now, mostly for skilled roles. Gen Z is largely uninterested in manufacturing roles.
Median tenure in manufacturing roles has fallen 17 percent in the last decade, but that number hides the true scope of the shift. We’ve also seen a rise in workers who stay at jobs just one to two years—generally not enough time to get the kind of institutional knowledge that’s essential for high-skilled manufacturing work.
Manufacturing leaders are, as a result, feeling the urgency of capturing institutional knowledge before it walks out the door. In most cases, this is framed as a defensive move: capture knowledge or risk weakening. But done right, that effort can actually create a competitive moat.
In this piece, I’ll explain why and lay out how manufacturing leaders can approach the task of preserving knowledge so that it positions them for technical dominance in the years ahead.
Technology can help preserve and democratize institutional knowledge
The idea that tech can help preserve institutional knowledge may seem like a no brainer. But it’s worth acknowledging. That’s because, done right, the technologies and underlying infrastructure used to preserve institutional knowledge can set the stage for innovation and growth in the years to come.
Naturally, there is some cost involved in building that infrastructure. But those costs should be considered in relation to the cost of letting institutional knowledge leak out:
Mistakes by inexperienced workers that lead to rework and lost time
More equipment damage due to inexperienced operators
Declining quality of outputs
Unplanned downtime (e.g., when workers don’t recognize warning signs)
Ongoing recruitment and training costs
So the question for manufacturing leaders is not whether to invest in technology to help preserve workers’ knowledge; it’s which technologies make the most strategic sense for the organization in the long term.
For example, there are off-the-shelf technologies available today that let experienced workers coach their less-experienced colleagues via interactive video call. Some industrial leaders have found that this tech can supplement in-person training while also letting older workers enjoy the benefits of semi-retirement (e.g., part-time WFH roles as remote video coaches).
Other off-the-shelf technology lets experienced manufacturers document their knowledge via voice recording and then makes that information searchable, alongside user manuals and other documentation, to all workers.
While both of these technologies might be helpful in preserving and transferring knowledge, neither offers much benefit beyond preserving institutional knowledge. To achieve the larger benefit of democratizing knowledge, any solution—off-the-shelf, custom, or some combination—has to be part of a larger strategic vision.
And if the vision is to democratize knowledge so that it becomes a core strategic advantage, any solution has to be built so that the knowledge transmitted from one worker to another can also be accessed in perpetuity by all future workers.
For that to be possible, industrial companies need to start by establishing a solid underlying data layer.
Democratized knowledge is a significant competitive advantage
Before I get into that data layer, let’s take a moment to consider the benefits of democratizing knowledge across your organization.
When you systematically capture, structure, and deploy institutional knowledge (ranging from what's in equipment manuals to what Fred and Bill have in their brains from 30 years on the floor), you can…
Onboard workers faster. When workers have access to the entire company’s knowledge via a digital interface, they can query that resource rather than waiting for a supervisor to be nearby. While such queries won’t always replace one-to-one instruction, they can reduce the number of people a worker needs to interact with to solve a problem (typically five to seven). This leads to faster issue resolution, quicker returns to work, and faster learning.
Maintain quality standards more consistently. When information is easy to access, anyone can refer to it at any time. Whether a worker needs to verify that a machine has punched holes in the wrong place before trouble-shooting, for example, or they’re looking for a refresher on a workplace safety procedure like lockout-tagout, democratized, easy-to-access knowledge puts the answer at their fingertips. Again, the result is more efficient teams and faster solutions.
Respond to production challenges more effectively than competitors who rely solely on human experts. With democratized knowledge, workers don’t have to wonder whether anyone has ever dealt with a similar problem. They can look it up—and discover which solutions worked in the past. For new problems, they can gather necessary background information faster so they can more confidently pursue potential solutions.
Put differently, when you democratize access to knowledge, it becomes a compounding, rather than revolving, asset for your organization.
When anyone in your organization has access to the cumulative knowledge and wisdom of everyone who’s ever worked there, you become a titan. Turnover becomes much less expensive. “Weak links” become much less threatening. Time lost to uncertainty is minimized and workers at every level are able to move forward with best steps more confidently.
So how can an organization make that happen? It starts with your underlying data infrastructure.
Data infrastructure will drive the future of industrial operations
Here’s the good news: the data infrastructure you need to democratize knowledge in this way (i.e., to capture it, structure it, and make it accessible) is also the infrastructure you need to build virtually every other type of advanced digital tool: AI / ML, digital twins, etc.
That’s because a unified data layer brings together data that is currently siloed—in various software applications, departments, and (you guessed it) people’s brains.
Once you’ve built a data foundation that makes the knowledge that exists across your organization accessible, you open yourself to a whole new era of problem-solving. Rather than thinking in terms of, say, “how can we train new workers to recognize the smell that means an extruder is malfunctioning,” you might shift the question to “how can we prevent more maintenance issues before they happen?”
You can start to not simply replace the workers who are leaving or retiring, but also transform the way you operate as an organization to take advantage of technology that didn’t exist a generation ago.
As you shift your thinking in this way, you may also be able to address linked issues: when new workers recognize that your organization grants them access to and encourages them to work with cutting-edge technology and keeps them at the forefront of their industry, they may be more likely to stay longer.
Attacking knowledge transfer head on can create a competitive moat for manufacturers
There's an old joke about a customer complaining that the electrician’s bill is too high. The homeowner says the electrician only worked for five minutes – why are they charging hundreds of dollars?!
So the electrician writes an itemized receipt: cutting the wire: $5; knowing which wire to cut: $495.
The point, of course, is that any job can look easy if you’ve got enough experience to know what you’re doing. But it’s almost impossible to appreciate the cost of gaining that experience over years of work and learning because so much of that process is invisible from the outside.
As manufacturing firms consider how to preserve institutional knowledge amidst a wave of retirements and high turnover, they’re faced with a related challenge: how can they not only train new workers in the day-to-day job tasks but also in the frameworks, problem-solving approaches, and heuristics that guide experienced professionals on which work to do?
With an approach that starts with an organization’s underlying data infrastructure, industrial organizations can turn the operational necessity of preserving knowledge into a competitive advantage that fuels their work for years to come.
About the author
Jason Hehman is Industrials vertical lead at TXI, a boutique agency whose core competency is designing digital products that people love using—exactly what industrial software lacks. Jason and the TXI team bring consumer-grade design thinking to manufacturing environments, creating interfaces frontline workers find intuitive, helpful, and preferable to manual alternatives. The result: technology adoption isn't mandated but voluntary because the digital experience genuinely improves how work gets done.
