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In complex asset environments, that loss rarely happens all at once. It happens quietly, through missed context, incomplete handovers, repeated troubleshooting, undocumented exceptions, and decisions that make sense only to the person who remembers what happened last time.
Maintenance knowledge is often personal before it becomes operational
Every maintenance organization has formal knowledge. It lives in manuals, procedures, technical publications, inspection requirements, ERP records, and maintenance plans. But the knowledge that keeps work moving often lives somewhere else.
Much of this knowledge exists in experience rather than documentation. It is built through years of working with specific assets, understanding how they behave in practice, and learning from situations that fall outside standard procedures.
That kind of knowledge is not always written down because it develops through experience. It is built through years of handling exceptions, seeing patterns, correcting mistakes, and understanding how assets behave outside ideal conditions.
PwC describes this as a serious risk in aerospace, space, and defense, where long asset lifecycles make experience difficult to replace quickly. Some programs run for decades, and technical expertise is built over long periods of time rather than through short onboarding cycles.
The issue is not that experienced people know too much. The issue is that the organization often lacks a reliable way to convert their knowledge into something others can find, trust, and use.
For the broader workforce context behind this problem, see The Workforce and Knowledge Continuity Crisis in Asset-Heavy Industries.
The retiring workforce turns expertise into a continuity risk
The maintenance workforce problem is often described as a staffing challenge. That is true, but it only tells part of the story.
When experienced technicians retire or leave, the immediate concern is headcount. The deeper risk is continuity. A replacement may eventually learn the role, but the asset history, judgment, and practical shortcuts built up over years can disappear before the next person has time to absorb them.
The National Academies’ report on the aging workforce points to the importance of understanding employment at older ages, workplace conditions, and the factors that shape whether older workers continue working or leave. For maintenance organizations, that means retirement should not be treated as a sudden event. It should be treated as a predictable transition that requires structured knowledge continuity before the departure happens.
The Aerospace Industries Association and McKinsey 2025 aerospace and defense workforce study adds further pressure to this picture. It highlights persistent attrition and difficulty sourcing talent in engineering, skilled manufacturing, and other critical program delivery roles.
Skills England’s defense sector assessment reaches a similar conclusion from a UK perspective, identifying hard-to-fill gaps in craft skills such as welders, aircraft maintenance technicians, and electricians, alongside specialist and digital skills.
In other words, organizations are not losing knowledge in a labor market where replacements are easy to find. They are losing knowledge in a market where the next qualified person may already be difficult to recruit, train, and retain.
This is where the “grey-to-green” transition becomes operational, not just demographic. The Grey-to-Green Transition in Aerospace and Defence.
Fragmented workflows make knowledge harder to keep
Maintenance knowledge is not lost only when people leave. It is also lost when the workflow is not designed to capture and retain it.
In many complex asset organizations, the official system does not reflect the real flow of work. The actual workflow may move through spreadsheets, email threads, SharePoint folders, paper notes, local checklists, disconnected databases, and conversations between people who know each other well.
That works until the person who understands the pattern is unavailable.
Internal interviews with Empact’s team point to the same operational reality. Raluca Stanescu, a delivery lead who helps major defence and aerospace companies digitalise their operations, described customers relying on Excel, email, SharePoint, and fragmented databases to coordinate current actions and evidence of future actions. Oana Toma, also a delivery lead and expert in the field of digitalising operations, described maintenance and execution information scattered across documents and systems, with source validation and handover issues. These are not simply documentation problems. They are workflow design problems.
A note in a spreadsheet may explain what happened, but it may not be tied to the asset, task, evidence, approval, configuration, or next action. An email may contain the right answer, but only for the people copied on the thread. A paper checklist may help one team complete the job, but it does not create searchable knowledge for the next team facing the same issue.
When knowledge is captured outside the workflow, it becomes difficult to reuse. When it is captured inside the workflow, it becomes part of how the organization works. For more on the operational risk of fragmented tools, see The Hidden Workforce Crisis Behind Defence Digital Transformation.
Operational memory is more useful than static documentation
Documentation is necessary, but it is not the same as operational memory. A manual can explain the approved process. A work instruction can describe the required steps. A maintenance record can show that a job was completed.
Operational memory adds the missing context. It shows what actually happened, what changed, what evidence was captured, which exception was approved, what was tried before, and what the next person should know before repeating the work.
The UK Ministry of Defence’s Data Strategy for Defence describes a related problem as the “data paradox.” Defense organizations generate more data than ever, yet still struggle to isolate insight because data is inaccessible in internal or contractual silos, inconsistently governed, and not always treated as an accountable asset.
Maintenance teams face their own version of that paradox. They may have more records, messages, logs, and documents than ever, while still struggling to answer basic operational questions:
- What has already been tried?
- Who approved the deviation?
- Which assets have shown the same pattern?
- What changed between the last inspection and this one?
A mature maintenance knowledge process should make those answers easier to find without asking the same experienced person every time.
“Unknown knowns” are a maintenance problem
A 2026 Military Review article describes “unknown knowns” as knowledge an organization already has but cannot recognize, access, or use when needed. The article discusses tacit knowledge, compartmentalized information, assumptions, and historical lessons that exist somewhere in the organization but do not reach the decision-maker at the right time.
Maintenance teams know this problem well. A technician solved a similar failure last year, but the record is buried in free text. A planner knows that a part substitution caused delays, but that context never made it into the next work package. A previous shift documented a concern, but the note was not connected to the asset history. An original equipment manufacturer (OEM) has useful service insight, but the operator cannot easily connect it to day-to-day maintenance execution.
The organization technically has the knowledge. The workflow cannot retrieve it. That is what makes tacit maintenance knowledge risky. It is not absent. It is trapped in forms that are too personal, too local, or too disconnected to support the next decision.
The same issue affects skilled trades in defense modernization, where practical expertise is often the limiting factor behind execution. Why Skilled Trades Are the Bottleneck in Defence Modernization.
Handover should happen before the exit interview
Many organizations try to capture knowledge when someone is already leaving. They schedule an exit interview, ask for notes, arrange a final handover, or pair the person with a younger colleague for a short overlap period. Those practices can help, but they are too late if they are the main strategy.
RAND’s research synthesis on talent management for U.S. Department of Defense knowledge workers organizes talent management around building and organizing talent, training and developing people, motivating and managing performance, and promoting and retaining the right people. The useful lesson for maintenance organizations is that knowledge continuity should be part of the workforce system, not a last-minute recovery effort.
In maintenance, that means knowledge capture should happen continuously as work is planned, executed, reviewed, and handed over. The best time to capture a decision is when the decision is made. The best time to capture evidence is when the task is performed. The best time to document a workaround is when the exception is approved.
A handover should not depend on one experienced person remembering everything important. It should be supported by a workflow that already shows what was done, what remains open, what changed, and what the next person needs to understand.
For a more tactical article on this topic, see How to Capture Tacit Knowledge Before Experienced Workers Retire.
What repeatable maintenance knowledge looks like
A stronger maintenance knowledge process does not require every technician to become a technical writer. It requires the workflow to capture knowledge in the right structure as work happens.
A maintenance task should carry the asset context, required instructions, evidence, responsibilities, approvals, open issues, and known exceptions. A recurring failure should be traceable across assets, sites, configurations, and previous work orders. A shift handover should show what changed, what was completed, and what needs attention next. A configuration-specific issue should be searchable by asset, serial number, version, location, and maintenance history.
This is where structured execution becomes important. If the workflow only asks people to close tasks, valuable context will be lost. If the workflow also captures why a decision was made, what evidence supports it, and how the outcome connects to the asset, the organization starts building usable maintenance knowledge over time.
Knowledge continuity is not created by storing more files. It is created by making maintenance work easier to repeat, audit, search, and improve.
Knowledge continuity belongs in the maintenance workflow
When organizations recognize that maintenance knowledge is being lost, a common response is to ask experienced technicians to document everything in a separate system after the fact. But that creates extra burden and often produces documentation that is difficult to maintain. A better approach is to design maintenance workflows so that knowledge is captured naturally through task execution, evidence collection, approvals, handovers, and asset history.
This is where asset lifecycle software can play a practical role. Empact Asset Maintenance is designed to structure maintenance execution around tasks, responsibilities, evidence, and reporting, so maintenance context is captured while the work happens rather than reconstructed later.
The goal is not to replace experienced people. It is to make sure their knowledge strengthens the organization beyond their own tenure.
When maintenance knowledge becomes repeatable, searchable, and connected to real work, a retirement no longer has to become a loss of operational memory. It becomes a managed transition.
For a broader operating model, continue with The Knowledge Continuity Playbook for Asset-Heavy Organizations.
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