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Cost of Inaction vs Planned Migration: Calculating the Real Cost of Downtime & Obsolescence Risk

Written by Liberty Automation | Apr 13, 2026 4:55:43 PM

Cost of Inaction vs Planned Migration: Downtime ROI for Legacy Controls  

Most plants do not modernize controls because a PLC “looks old.” Modernization becomes necessary when the control system turns operationally fragile: parts availability becomes uncertain, documentation no longer reflects the machine, recovery depends on a small number of people, and breakdowns become high-stakes events.

The disagreement typically isn’t whether risk exists; it’s how that risk gets translated into a defensible return. The challenge is building a business case that holds up when operations, engineering leadership, and finance ask reasonable questions:

    • What evidence supports the expected risk reduction?
    • Which assumptions drive ROI the most?
    • How sensitive is the model to downtime cost per hour and MTTR?
    • What prevents startup from turning into open-ended commissioning?

This article provides a practical model for comparing Cost of Inaction to a planned migration, using credible downtime benchmarks, plant-specific inputs, and an engineering approach designed to reduce unknowns early (Liberty’s approach: discovery, documentation, verification, and test before cutover).

Why “keep it running” becomes a hidden tax

Legacy controls create cost in areas that often aren’t measured as a single line item:

    • Troubleshooting time increases when prints, I/O lists, and logic documentation do not match current field conditions.
    • Recovery time extends because failures cannot be diagnosed quickly or safely.
    • Emergency work carries premiums (overtime, weekend callouts, expedited sourcing).
    • Spare parts strategy weakens as components are only available via surplus-market or disappear altogether.
    • Future improvement work is blocked (standardization, diagnostics, integration, maintainability).

In practice, the biggest cost is often variability. The same fault that used to be resolved in an hour becomes a multi-shift event, because the system is harder to understand and harder to support.

Downtime benchmarks: useful for validating ranges, not choosing a number

Downtime cost per hour is plant-specific. It depends on throughput, staffing constraints, WIP, scrap exposure, downstream scheduling, and contractual penalties. The most defensible model uses plant history and plant economics.

That said, credible benchmarks are useful as a cross-check, especially when internal estimates exclude recovery labor, scrap/rework, and the ripple effects of missed schedules.

    • ABB reports that 83% of surveyed decision-makers estimate unplanned downtime costs at least $10,000 per hour, and 76% estimate costs up to $500,000 per hour. (new.abb.com)
    • Siemens’ True Cost of Downtime 2024 report cites a large automotive plant at $2.3 million per hour of downtime. (assets.new.siemens.com)

These sources should be treated as reference points, not promises. The practical value is confirming whether internal estimates are directionally realistic.

Reactive maintenance and downtime: state the claim precisely

Reactive maintenance is often correlated with higher downtime because issues are addressed after failure rather than prevented through planned work. When plants are forced into reactive mode, troubleshooting time increases and outages tend to last longer.

NIST reports that establishments in the highest reactive-maintenance group were associated with 3.3× more downtime than those in the lowest group, along with other negative performance outcomes. (nist.gov)

This is relevant to legacy controls because obsolescence and documentation drift push plants toward reactive behavior: troubleshooting becomes more uncertain, the time to identify faults expands, and recovery depends on a shrinking set of experts.

Liberty’s perspective is that modernization is not a “hardware refresh.” It is a deliberate shift back toward a supportable, testable system through discovery, documentation, verification, and structured validation.

H2: Lifecycle and support risk: when supportability becomes the constraint

In some cases, equipment continues to run while supportability erodes. Lifecycle changes can create constraints long before a machine fails mechanically.

For example, certain Rockwell CompactLogix 1769-based controllers are already discontinued, and Rockwell has published End of Life discontinuation dates on specific 1769 CompactLogix catalog numbers. One example is the Armor CompactLogix controller 1769-L37ERMO, which Rockwell lists as End of Life with a discontinued date of September 30, 2026.

The operational impact is rarely limited to the controller alone. Many facilities still run significant installed bases built around the 1769 CompactLogix footprint and associated I/O architectures. Once lifecycle moves into end-of-life windows, the plant’s exposure shifts from “can it run” to “can it be supported under real conditions,” including spare part availability, repair paths, and the ability to standardize around current platforms.

This type of lifecycle constraint introduces a distinct risk category: not just “will the PLC fail,” but “can the plant restore and support the platform under real conditions.”

A business case that stands up to scrutiny: compare scenarios and run sensitivity

A strong ROI case rarely depends on one decisive assumption. It compares two scenarios and makes the key drivers explicit.

Scenario A: Cost of Inaction (12–36 month horizon)

Model expected annual cost of staying in place:

    • Controls-related unplanned downtime hours (CMMS / downtime logs)
    • MTTR trend (especially where documentation drift exists)
    • Overtime tied to controls breakdowns
    • Expedited parts and outside support spend
    • Scrap/rework during recovery and unstable operation
    • Probability-weighted major event exposure (low/likely/high range is usually sufficient)

Scenario B: Planned Migration

Model the cost of doing the work intentionally:

    • Engineering effort: discovery, documentation, verification, design
    • Build and offline validation effort
    • Planned downtime window (the only “certain” downtime assumption)
    • Commissioning/SAT and stabilization
    • Training and as-built documentation deliverables that reduce future MTTR

Stakeholders typically evaluate planned migration cases based on whether the approach reduces uncertainty early. While claims of “no surprises” may not be trusted, what is credible is a methodology that reduces unknowns and proves behavior through structured test before startup. Liberty’s framework is built around those gates.

What leadership typically needs to see to approve a planned migration

In most organizations, the business case is built around a concise summary of exposure and expected risk reduction, built as a short, defensible summary that makes two things clear:

    • what the plant is currently exposed to (downtime, recovery risk, supportability constraints), and
    • what becomes predictable with a planned migration (downtime window, scope, and validation approach).

The most effective summaries usually include a small set of plant-specific facts:

Key inputs decision-makers rely on

    • Downtime exposure tied to controls issues (frequency, duration, worst-case events)
    • MTTR trends, especially where documentation drift exists
    • Overtime and emergency support tied to controls recovery
    • Expedited parts sourcing and outside support costs
    • Quality and schedule impacts during recovery (scrap, rework, missed shipment exposure)
    • Supportability constraints (software and licensing constraints, spare part availability, internal knowledge concentration)


What the decision ultimately compares

    • Expected annual cost of continuing as-is
    • Planned migration cost plus planned downtime exposure
    • A risk-reduction narrative tied to deliverables: verified I/O, accurate as-builts, test evidence, and recovery procedures


Presented this way, the “payback” discussion is grounded in plant reality rather than generic ROI claims, and it sets a clear basis for evaluating whether a planned window is justified.

Operational approval depends on execution credibility—not just ROI

Even a strong financial case can stall if the execution plan is not credible. Operations typically needs clear answers to:

    • Downtime window duration and justification
    • Evidence that startup will not become open-ended commissioning
    • Defined rollback conditions and contingencies
    • Post-migration outcomes that prevent recurring pain (documentation, standards, maintainability)

This is where Liberty’s approach is practical rather than promotional: migrations become predictable when the work starts with discovery and verification, and when behavior is proven through test; rather than discovered for the first time during a shutdown.

Where Liberty typically starts

Liberty’smodernization methodology begins with discovery and verification: documentation audit, reverse engineering where required, and I/O verification, so the migration plan is based on verified current state rather than assumptions.

That starting point supports three outcomes stakeholders consistently require:

    • A scoped plan anchored in verified facts
    • A defensible downtime window assumption
    • Reduced probability and severity of startup surprises through structured validation

 

FAQ's

How can downtime cost be estimated when there isn’t a formal “cost per hour” number?
A defensible estimate usually starts with production reality rather than a single finance figure. The calculation typically considers lost throughput during the event, labor costs associated with recovery, scrap or rework generated during unstable restart, and any downstream schedule or customer impacts. External benchmarks can be used as a sanity check, but the most credible inputs come from plant history: documented downtime duration, the recovery resources required, and what is consistently affected when a line stops. ABB’s survey results illustrate how widely downtime cost can vary across industrial environments. (new.abb.com)

What should be included in downtime cost beyond “lost production”?
In many plants, the larger cost drivers include recovery labor, scrap/rework during restart, expedited sourcing, and the schedule disruption that follows the event. Reports on downtime economics emphasize that costs extend beyond production loss alone and can escalate significantly depending on industry and facility scale. (assets.new.siemens.com)

Is the proactive vs reactive maintenance relationship causal?
NIST reports a strong association: reactive-heavy establishments were associated with 3.3× more downtime than those with low reliance on reactive maintenance. The most accurate way to present the finding is as an association, while still recognizing its operational relevance to risk decisions. (nist.gov)

What reduces migration “surprise” risk most effectively?
Discovery and verification (validated I/O and accurate documentation), followed by structured test and acceptance criteria before startup. Liberty’s modernization approach is built around those gates.

When does lifecycle risk become urgent?
Lifecycle risk becomes urgent when supportability constraints start to affect recovery options: limited component availability, constrained repair paths, and diminishing ability to standardize around current platforms. This can happen even with platforms that are still common on plant floors. For example, Rockwell lists the Armor CompactLogix controller 1769-L37ERMO as End of Life with a published discontinued date of September 30, 2026. (Source: Rockwell Automation product lifecycle page for 1769L37ERMO.) When lifecycle windows close, the practical question shifts from whether the system runs today to whether it can be supported and restored predictably under real outage conditions.

 

For teams preparing to justify a planned modernization window internally, Liberty can start with a discovery + verification audit that produces scope, downtime-window assumptions, and test criteria needed for a defensible Cost of Inaction vs Planned Migration case – before an emergency forces an unplanned decision.