The Analog Incident Train Station Lost Signals Locker: Storing Invisible Outage Clues Before They Disappear

In every complex operation—whether it’s a power grid, train network, factory, or data center—serious incidents almost never come out of nowhere. Before the outage, breakdown, or safety event, there were faint signals: tiny oddities, near misses, and small deviations from normal.

Most of those signals vanish. A technician dismisses an odd smell. An operator ignores a warning light that flickers only once. A customer reports a brief outage, but no one logs it because “everything came back up in a minute.”

This is where the idea of an “Analog Incident Train Station Lost Signals Locker” comes in: a metaphor for deliberately storing weak signals and invisible outage clues before they disappear, so they can be examined, connected, and turned into prevention.

This post explores how weak signal theory, sensemaking, near-miss reporting, and a preoccupation with failure can dramatically improve operational reliability and outcomes like SAIDI/SAIFI—and why your organization needs its own lost signals locker.

Weak Signals: The Clues That Arrive Early and Quietly

Weak signals are subtle, early indicators that something might be going wrong:

A slight increase in transformer temperature once a week.
A recurring but self-clearing alarm at a substation.
A train driver who “just has a bad feeling” about how a brake is behaving.
A customer call about “flickering lights” that doesn’t show up clearly in your SCADA or monitoring system.

They are weak because they are:

Sparse (they don’t happen often)
Ambiguous (they don’t clearly point to a known failure mode)
Easy to dismiss (there’s usually a plausible excuse for each one in isolation)

Weak signal theory says: if you pay attention to these early, ambiguous hints, you can see trouble forming upstream—long before it matures into a full-blown incident.

But weak signals only help if two things happen:

People notice them.
The organization has a way to store, share, and interpret them.

That is the function of your “lost signals locker”: a place where small, odd, almost-incident observations can be deposited before they fade from memory.

Sensemaking: Turning Random Oddities into Early Warnings

Simply collecting weak signals is not enough. The real power comes from sensemaking—the process of interpreting and connecting those weak clues into a coherent picture.

Sensemaking is:

Active, not passive: You don’t wait for clarity; you search for meaning.
Collaborative: Different teams compare notes—operations, maintenance, customer service, engineering.
Iterative: Explanations are refined as more signals arrive.

Imagine your weak signals like scattered train tickets left around a station. Each ticket by itself seems unimportant. But when you gather them all into a locker and inspect them, you start seeing patterns:

Multiple “brief voltage dips” on the same feeder.
A cluster of “almost-slips” on the same station platform.
Recurring “unusual noise” from the same gearbox under different operators.

Sensemaking sessions might ask:

What might all these clues be trying to tell us?
If this were the beginning of a serious incident, what would we expect to see next?
What small, cheap actions could we take now to prevent a bigger problem later?

When organizations practice systematic sensemaking, they shift from reactive firefighting to proactive anticipation.

Preoccupation with Failure: Looking for Invisible Clues

High-Reliability Organizations (HROs) are known for their preoccupation with failure:

They assume errors are always possible.
They treat small anomalies as important, not as noise.
They ask, “What almost went wrong?” as often as, “What went wrong?”

Preoccupation with failure means constantly scanning for invisible outage clues:

Parameter readings that are still “in spec” but drifting in a concerning direction.
Procedures that people routinely bypass because “they take too long.”
Alarms that trigger “too often” and are therefore silently ignored.

In a train station, that might look like:

A door that sometimes doesn’t close fully—but always shuts on the second try.
A platform edge light that flickers once a day.
A PA system that occasionally cuts out mid-announcement.

Individually, none of these cause an incident today. But they’re all candidates for the lost signals locker—clues that your system is a little more brittle or error-prone than it appears.

Preoccupation with failure reframes weak signals and near misses from annoyances to valuable, perishable data points.

Near-Miss Reporting: Turning “Almost” Into Insight

If weak signals are faint hints, near misses are loud warnings that didn’t quite hurt anyone (yet).

A near miss is:

A slip, trip, or process error that could have caused harm or outage, but didn’t—often due to luck or last-minute correction.

Examples:

A crew member nearly falls on a wet floor with no sign but catches themselves.
A switching operation is about to be performed on the wrong feeder, but someone double-checks at the last second.
A train passes a signal at danger but manages to stop in time.
A breaker is incorrectly racked in but does not yet fail under load.

Without a reporting culture, these near misses vanish. No one logs them because:

“Nothing actually happened.”
“I corrected it myself.”
“I don’t want to get in trouble.”

A systematic near-miss reporting process changes that by:

Making it safe and encouraged to report "almost-accidents".
Treating near-miss reports as gifts, not blame triggers.
Feeding them into the same lost signals locker as weak signals.

Each near miss is a vivid, high-information clue that a defense layer is thin, a procedure unclear, or a design fragile. Analyzing them turns everyday close calls into low-cost learning instead of future high-cost failures.

Real-World Illustration: The Wet Floor with No Sign

Consider a simple near miss: a wet floor with no sign in a station concourse.

Day 1: A cleaner mops, is rushed, forgets the sign. A passenger nearly slips, but recovers. No report, no record.
Day 5: Same thing. Another near fall. People grumble, move on. Still no report.
Day 30: Someone actually slips, hits their head, and requires medical attention. Now it’s an incident.

Looking backward, the signals were clear:

Repeated wet floors.
No signage.
Perhaps understaffing or poor training.

If those near misses had been logged and stored in your lost signals locker, sensemaking might have revealed a pattern:

“We are getting repeated reports of near slips in the same corridor after cleaning.”

Which could lead to small but meaningful interventions:

Mandatory signage procedures and checks.
Adjusted cleaning schedules.
Additional non-slip mats in high-traffic areas.

A similar pattern applies in power systems, rail operations, and industrial plants. Many “out of the blue” incidents had precursors that were simply never captured.

From Clues to Metrics: Improving SAIDI/SAIFI and Reliability

In utilities and other high-reliability operations, performance is often tracked using metrics such as:

SAIDI (System Average Interruption Duration Index)
SAIFI (System Average Interruption Frequency Index)

Both reflect how often and how long customers experience service interruptions.

Capturing and analyzing weak signals and near misses can directly improve these metrics by:

Identifying emerging failure modes early
- Repeated “momentary blips” on a feeder can signal equipment degradation long before it fails outright.
Prioritizing preventive maintenance
- Instead of purely time-based schedules, you can use your lost signals data to focus on the most fragile assets.
Reducing repeat incidents
- Near misses and weak signals often cluster around the same procedures or assets. Fixing those clusters avoids many future outages.
Shortening restoration time
- When you’ve studied near misses and weak signals, your crews already understand likely failure patterns and can respond faster.

In essence, the quality of your weak signal and near-miss data shapes the quality of your risk anticipation and outage prevention.

Building Your Own “Lost Signals Locker”

Turning the metaphor into practice means creating simple, disciplined mechanisms to catch and store invisible clues.

Key elements:

A low-friction capture mechanism
- Quick digital forms, QR codes, or a simple hotline where staff (and even customers) can report anomalies and near misses.
- Make it possible to submit: “Something felt off,” even without perfect details.
A non-punitive culture
- Emphasize learning, not blame.
- Celebrate high-quality near-miss reports as contributions to safety and reliability.
Regular sensemaking rituals
- Weekly or monthly cross-functional reviews of weak signals and near misses.
- Look for patterns across time, locations, equipment, and teams.
Clear feedback loops
- Tell reporters what was learned and what changed because of their input.
- This reinforces the value of contributing to the lost signals locker.
Integration with reliability and maintenance systems
- Link your weak signal database with asset management, incident management, and reliability engineering tools.
- Use it to inform risk scoring, maintenance plans, and training priorities.

With these elements in place, your analog “locker” becomes a living, evolving memory of everything that almost went wrong, but didn’t—yet.

Conclusion: Don’t Let Your Best Warning Signs Disappear

Incidents are rarely truly sudden. The system whispers long before it screams.

Weak signals, near misses, and small anomalies are those whispers—easily overlooked, quickly forgotten, and rarely logged. By the time you’re writing the post-incident report, those early clues have usually disappeared like unclaimed luggage in a busy station.

Creating an Analog Incident Train Station Lost Signals Locker—a systematic way to capture, store, and interpret invisible outage clues—turns:

Ambiguous oddities into early warnings
Near misses into learning opportunities
Preoccupation with failure into a tangible reliability advantage

Organizations that take weak signals seriously don’t just respond better when things go wrong. They prevent more things from going wrong in the first place—and that shows up everywhere from reduced SAIDI/SAIFI to safer workplaces and more resilient operations.

Your systems are already sending you clues. The question is: Do you have a locker to keep them from getting lost?