​What Happens When Expertise Outgrows Your Training System

Jerry Dolinsky is the CEO of Dozuki, a leading connected worker solution for enterprise-level manufacturing companies.

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A few years ago, I visited a specialty materials manufacturing facility that produces coated paper products used in everything from food packaging to industrial applications. The operation relied on highly skilled operators running large coating lines where small mistakes could create significant waste, downtime and quality issues.

At the time, one of the facility's continuous improvement leaders was experimenting with a small training initiative. The project involved a summer intern, a shift supervisor and a handful of documented procedures. It was a modest effort designed to improve consistency on a single site.

Recently, I had the opportunity to reflect on how far that effort had come.

What began as a localized pilot eventually expanded across multiple manufacturing divisions throughout the parent organization. What started as a training initiative evolved into a broader connected-worker strategy to preserve, scale and share operational knowledge across facilities.

What struck me most wasn't the growth of the program itself.

It was how clearly the company had recognized a problem many manufacturers fail to see until it's already affecting performance: expertise had outgrown the training system designed to support it.

When Success Creates A New Problem

Manufacturing leaders often focus on hiring, retention, productivity and technology investments. Yet one of the most overlooked operational risks emerges when organizations become more successful.

As employees gain experience, processes become more sophisticated, equipment becomes more specialized and operational knowledge becomes deeper. The organization gets smarter. The challenge is that training systems do not always evolve at the same pace.

Over time, expertise accumulates faster than it can be documented, standardized and transferred. Critical knowledge begins living inside individual workers rather than inside the organization itself.

Every facility has employees who know things that aren't written down anywhere. They can recognize an abnormal machine condition before alarms activate. They know which startup adjustments reduce waste. They understand the subtle decisions that separate average performance from exceptional performance. As long as those employees remain in place, the system appears to work.

The vulnerability becomes visible when those employees retire, transfer, get promoted or leave.

Suddenly, years of operational expertise become difficult to access.

The Warning Signs Were Already There

The coated products facility began seeing early signs of this challenge.

Rapid internal promotions were creating valuable career opportunities but also creating knowledge gaps. In some areas, operators with only months of experience were responsible for training newly hired employees. Nobody was doing anything wrong.

The organization had simply reached a point where informal knowledge transfer was no longer sufficient.

The traditional approach of shadowing experienced employees and learning through observation had worked for years. But as expertise accumulated, the amount of knowledge to be transferred grew larger than the system designed to deliver it.

That realization changed the company's approach.

Rather than relying solely on tribal knowledge, the organization began systematically capturing the expertise of its most experienced operators. Using a connected worker platform, they created a structured process to document operational knowledge and make it accessible to future employees.

The effort focused heavily on some of the facility's most critical coating lines, where operator decisions directly influence startup waste, downtime, throughput and product quality.

Senior operators helped document best practices, identify common failure points and establish clearer performance expectations. Digital work instruction software made that expertise easier to access while creating greater consistency across shifts and departments.

The company paired documented procedures with structured evaluations designed to verify competency rather than simply track training completion.

The goal was to ensure expertise remained available regardless of who happened to be working a particular shift.

From Individual Knowledge To Organizational Capability

Today, the facility uses a dedicated technical training room to support onboarding, safety education and workforce development. New hires and seasonal employees learn from a standardized body of operational knowledge built by the people who understand the work best. What began as a small pilot has since expanded across multiple manufacturing divisions.

For me, the most interesting lesson is not the technology involved. It is the recognition that expertise itself is an asset requiring active management.

Manufacturers routinely invest in maintaining equipment because they understand the consequences of asset deterioration. Yet many organizations allow operational knowledge to accumulate informally without creating systems to preserve it. Eventually, that approach reaches its limits.

When expertise outgrows the training system, organizations begin experiencing slower onboarding, greater variability, longer ramp-up times and increased operational risk.

Five Ways To Prevent Expertise From Outgrowing Your Training System

1. Capture Expertise, Not Content

Most manufacturers already possess extraordinary operational knowledge. The challenge is that much of it remains trapped inside individual workers. Focus on preserving expertise before it disappears.

2. Turn Experts Into Standard Setters

Your best operators should help define standards, training pathways and evaluation criteria. Their experience should become part of the organization's operating system.

3. Measure Competency, Not Completion

Training completion rates tell you who attended. Competency measurements tell you who can perform. Focus on operational readiness, not attendance records.

4. Treat Knowledge Like Infrastructure

Manufacturers invest heavily to maintain physical assets. Intellectual assets deserve the same discipline. Manufacturing knowledge management software is becoming increasingly important because expertise is every bit as valuable as equipment.

5. Start Small And Scale What Works

Most successful initiatives begin with a single line, department or facility. Small improvements in knowledge capture compound over time and often become enterprise-wide advantages.

The manufacturers that thrive over the next decade will not necessarily be the ones with the newest equipment or the largest technology budgets. They will be the organizations that recognize expertise as a strategic asset and build systems capable of preserving it.

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