How Utilities Can Capture Retiring Employee Knowledge

Utilities capture retiring employee knowledge by identifying their highest-risk roles, recording expert judgment during daily work, and turning that raw know-how into searchable runbooks, mentorship plans, and a shared knowledge system before the expert leaves. The goal is not to document everything at once. It is to make hard-won expertise discoverable and tied to the systems, assets, people, and decisions it explains.

Retiring workforce expertise preservation is the practice of capturing, organizing, and reusing the operational judgment, asset history, and relationship knowledge that experienced utility employees hold. That knowledge is rarely just standard operating procedures. It includes field judgment, undocumented workarounds, seasonal failure patterns, storm-response decisions, safety habits, and knowing who to call when the plans break down.

The timing is urgent. The American Water Works Association estimates 30 to 50% of the utility workforce will retire in the next decade, and many utilities already struggle to hire and train replacements fast enough. Utilities that treat this as operational continuity, not just HR paperwork, protect reliability, speed onboarding, and avoid repeating preventable mistakes. The stakes are measurable: knowledge attrition costs large companies an estimated $31.5 billion a year, a figure projected to double by 2030.

How to preserve retiring workforce expertise before it walks out the door

Utilities preserve retiring workforce expertise by working through a clear sequence: identify the highest-risk roles, capture tacit knowledge during daily work, structure it into runbooks and decision trees, pair experts with successors, centralize everything in a permission-aware system, and use AI to make it easy to find and reuse. The order matters because most knowledge loss happens for predictable reasons.

Utilities start too late, lean on a single exit interview, or scatter critical information across tools that new hires cannot search with confidence. A field example makes the stakes concrete. An operator named Dale ran one water system for 32 years and knew which pump seized every winter, why one treatment tank ran hot, and when to call the contractor before a failure. Three months after he retired, that pump died and no one saw the signs.

Framing the work this way keeps it grounded in outcomes that matter to a utility: outage response, compliance, safety, maintenance quality, and time-to-productivity for new staff. The steps that follow move from assessing risk to measuring whether the transfer actually closed the skills gap.

1. Identify the roles, systems, and decisions with the highest knowledge risk

Start knowledge transfer with a retirement-risk map: list the employees who may retire in one, three, and five years, then rank their roles by operational criticality, how unique their knowledge is, and how hard the role is to fill. Line supervisors, operators, dispatchers, planners, field technicians, customer operations leads, and compliance specialists often carry outsized context, especially anyone managing aging infrastructure with undocumented history.

Go deeper than job titles. Capture the decisions each person makes that no manual teaches, such as how they diagnose a recurring failure, when they escalate, and which meter readings they actually trust. Build a short matrix for each priority role so the risk is visible to operations, HR, and frontline leaders.

A single risk map often reveals how concentrated this exposure is, with a large share of critical roles held by employees who are already retirement-eligible. The Center for Energy Workforce Development notes that much of the utility workforce is at or near retirement age, which is why this ranking cannot wait. The output of this step is a ranked list of knowledge-transfer priorities that operations and HR have approved together.

2. Capture expert knowledge in the flow of daily work, not in a one-time exit interview

Capture expert knowledge continuously while people still do the work, because a last-month interview rarely reaches the context behind years of decisions. Ask experienced employees to document one recurring task, one exception, and one decision rule each week, so the record grows as a byproduct of normal work over a few months rather than a scramble at the end.

Use the format that fits each type of knowledge. Short written notes work for troubleshooting tips, recorded walkthroughs suit field procedures, annotated diagrams explain infrastructure quirks, and Q&A logs preserve the reasoning behind a call. Tie every entry to the real work object it describes: the asset, location, outage type, work order, or compliance task.

Point the prompts at action. Ask what the next person should know before touching an asset, what to check first when a specific alarm appears, which signals to trust, and what exceptions matter. An operator who logs each valve turned against the map, noting where the field differs from the plans, builds a living record and treats capture as part of engagement rather than a compliance chore.

3. Turn tacit know-how into structured runbooks, decision trees, and role-based playbooks

Convert raw expert notes into formats a new employee can follow under pressure, because loose notes alone will not hold up during an outage. Build role-based playbooks for the moments that matter most: outage triage, switching preparation, water-quality response, leak escalation, storm mobilization, meter exceptions, and planned maintenance on aging assets.

Pair each playbook with decision trees that explain why an expert chooses one path over another, so successors inherit judgment instead of a flat checklist. Give every playbook the same structure so it stays predictable:

• Trigger and first checks
• Required systems and safety constraints
• Escalation points and known pitfalls
• Related experts and supporting sources

Separate stable policy from local nuance, and include a source reference for every critical instruction, since trust is non-negotiable in utility operations. Assign an owner to each runbook so it stays current. A successor should inherit a working map of decisions, exceptions, and source-backed guidance, which is what sustainable succession planning actually looks like.

4. Pair retiring experts with successors through mentorship, shadowing, and teach-back loops

Structured mentorship transfers judgment that documents cannot, so assign successors early and define exactly what they must observe, practice, and explain back before the expert retires. Move past casual ride-alongs to a phased plan: the successor observes the work, performs it with supervision, performs it independently, and finally teaches it back to prove understanding.

Match successors by adjacent capability, not job title alone, and track each transfer against a competency checklist covering core tasks, seasonal activities, emergency actions, safety-critical judgments, stakeholder relationships, and digital systems. Recording teach-back sessions is where hidden assumptions and gaps in the written guidance surface, because a new hire will stumble exactly where the instructions are unclear.

This exchange runs both directions. Veterans bring hard-won judgment, and newer employees spot where procedures and search results fall short. A visible growth path also aids retention, and utilities that connect mentorship to real training programs give younger workers a reason to stay.

5. Centralize utility knowledge in one searchable, permission-aware system

Knowledge transfer breaks down when runbooks sit in one folder, maintenance notes in another system, diagrams buried in email, and expert answers trapped in chat histories no one can retrieve. Create one place to search across policies, procedures, outage postmortems, engineering drawings, work orders, training materials, chat threads, and recorded walkthroughs.

The system has to respect existing permissions so people see only what they are cleared to see, since operational, customer, regulatory, and infrastructure data often carry different access rules. Organize content the way employees actually work, indexed by asset, location, crew, process, incident type, project, and role rather than by the tool it happens to live in.

Preserve source fidelity so a worker can trace an answer back to the original procedure, expert note, or historical record. One caution: do not build a static archive that people must remember to browse. Centralization only pays off when the knowledge layer fits daily workflows, so institutional knowledge stops depending on one person's memory.

6. Use AI to make expertise easier to find, easier to trust, and easier to apply

Once knowledge is centralized, use AI to help employees find grounded answers faster, not to replace the experts who created them. Aim it at the repeated questions that eat a supervisor's day: "What do I check first?" "Has this asset failed before?" "What is the approved escalation path?" and "Who handled the last similar incident?"

Trust is the deciding factor. A utility assistant should synthesize across documents, tickets, notes, and messages while citing the underlying sources and filtering results by existing permissions, so a crew can verify guidance before they act on it. Tools like Glean apply this pattern, returning cited, permission-aware answers to natural-language questions instead of forcing workers to hunt across disconnected systems.

The same capability adds workflow value beyond search. It can draft training summaries, turn a recorded interview into a structured FAQ, flag playbooks that look thin or outdated, and reveal which questions come up most. The effect on the skills gap is direct: supervisors field fewer repeat questions, and new employees ramp faster with human judgment, safety, and source verification still at the center.

7. Measure whether the transfer worked and keep the knowledge system current

A knowledge program earns its keep only when it changes outcomes, so define success metrics before the retirements happen and review them quarterly. Track operational measures such as time-to-proficiency for new hires, repeated questions by role, outage-restoration variance, maintenance rework, incident resolution time, and the percentage of critical roles that have current playbooks and named successors.

Watch content health alongside the operational numbers. Note which runbooks employees use, which answers they search for most, which sources get cited most often, and where people still escalate for help. Refresh the affected content after real events: post-incident reviews, storm debriefs, switching exceptions, safety events, and compliance audits.

Give each critical domain a maintainer, a reviewer, and a set update cadence, then build a review rhythm with operations, HR, and training leaders so retirement workforce planning feeds directly into onboarding and skills inventories. The practical takeaway: start with your highest-risk roles this quarter, capture what only those people know, and build a system that lets every future employee ask, find, verify, and learn.

How utilities can preserve retiring workforce expertise before it walks out the door: Frequently Asked Questions

What strategies can utilities implement to capture retiring employees' knowledge?

Map retirement risk by role, then capture knowledge during daily work through weekly task logs, recorded walkthroughs, and decision notes. Convert that raw material into structured playbooks, pair experts with successors through mentorship, and centralize everything in searchable, permission-aware storage. Capture expertise while people work, not only at the exit.

How can utilities effectively train new employees to fill the knowledge gap?

Blend role-based playbooks, shadowing, and teach-back loops with searchable knowledge access tied to specific assets, incidents, and procedures. Training improves sharply when new employees can ask natural-language questions and verify each answer against approved internal sources, so they build judgment instead of memorizing steps they do not yet understand. When that transfer fails, the cost is real: 47% of U.S. employees have been forced to learn a job on their own after a colleague left without passing on their knowledge.

What role does mentorship play in preserving institutional knowledge?

Mentorship transfers judgment, not just tasks, which is the part of expertise that documents miss. It works best when it is documented, time-bound, and paired with role-specific competency checklists that track core tasks, seasonal work, emergency actions, and safety-critical decisions. Recorded teach-back sessions expose gaps in the written guidance.

What are the best practices for succession planning in the utility sector?

Identify retirement risk early, rank critical roles by operational impact, and assign successors before an exit date is set. Document the key decisions each role owns, integrate that training into broader workforce plans, and review progress with operations leaders. Some utilities also encourage employees to give early retirement notice so successors have time to learn the role before the expert leaves.

How can technology assist in knowledge retention for retiring workers?

Technology connects scattered knowledge, preserves existing permissions, and surfaces cited answers inside the tools employees already use. That keeps expertise available after a retirement without turning it into a static archive. Human judgment, safety, and source verification stay at the center, with technology acting as a multiplier rather than a replacement.

The utilities that keep reliable service through the coming retirement wave will be the ones that start capturing expertise now, while their most experienced people are still on the job. We help you connect scattered runbooks, notes, drawings, and expert answers into one permission-aware layer that returns cited, trustworthy responses in the tools your crews already use. Request a demo to explore how Glean and AI can transform your workplace.