Key takeaways
See the OEE calculation these C-suite numbers translate.
A typical board-level maintenance report includes MTBF (rising), MTTR (falling), PM compliance (88%), OEE (74%). The maintenance manager presents these with appropriate context. The CFO listens politely and asks "and what does this mean for the budget conversation?" The maintenance manager translates on the fly, usually inadequately, and the conversation ends without the budget moving.
The pattern is not malicious. It is that the operational metrics describe how the maintenance program is performing in operational terms, and the C-suite is making financial decisions. The translation needs to happen before the report, not during the meeting. Three numbers translate cleanly when calculated properly.
The total maintenance spend (labour, parts, contractors, software) for the period divided by the production hours actually produced. The result is a unit cost, currency per hour of actual production, that anyone in finance can compare against other operating costs.
It normalises for production volume. A plant that produces more in a quarter will naturally spend more on maintenance; the cost-per-hour number isolates whether the spend is structurally rising or just tracking volume. A 3% rise in maintenance spend on 5% more production is a 2% efficiency improvement; the raw spend number alone would have looked like a problem.
Include the obvious costs (labour, parts, software, contractors). Include the less obvious costs (shadow maintenance estimated from the OEE-to-work-order gap, parts-cache replenishment, downtime cost when maintenance over-ran a window). Exclude capital costs (those belong in number 3). Divide by actual production hours, not scheduled hours.
The piece on manufacturing KPIs covers the underlying cost components.
Your own rolling 12-month baseline, like every other operational metric. External benchmarks for maintenance cost per production hour vary by industry and are usually quoted in ways that make cross-plant comparison unreliable.
Unplanned downtime in production hours multiplied by the standard cost-per-production-minute, summed for the period, divided by revenue for the same period. The result is a percentage that the C-suite intuitively understands: this is the portion of our revenue we are losing to maintenance failures.
Unlike OEE, this number is denominated in money the C-suite cares about. A 0.8% unplanned-downtime-cost-as-revenue number is a fact the CFO can hold against a 1.2% baseline a year ago and see a real improvement in money terms. The operational team's job becomes translating the percentage gap into prioritised interventions; the C-suite can debate budget allocation against a number that means something to them.
Unplanned downtime, not total downtime. Production hours lost on the lines that were scheduled to run, not on assets that were down by design. Cost-per-production-minute that finance has signed off on rather than the operational team estimating. The piece on production loss analysis covers the loss accounting that makes the number defensible.
OEE is the operational metric; unplanned-downtime-cost-as-revenue is the financial metric. They move together but are not the same. A 1-point improvement in OEE might translate to a 0.05-0.15 percentage point reduction in this number, depending on revenue mix. The C-suite cares about the percentage point; the operations team uses OEE to drive it.
The sum of replacement-asset capex avoided by extending the operational life of existing assets through the maintenance program. Calculated as the difference between the original retirement schedule and the actual life achieved, multiplied by the replacement-asset cost (amortised).
It puts a financial figure on the upstream value the maintenance program creates that nobody usually counts. A plant that successfully extends a packing-line asset's life from 12 years to 15 years has avoided a capex commitment, and that avoidance has a present value. Without this number, the maintenance program looks like pure cost; with it, the program is partially capex avoidance.
For each asset class, the design life and the actual operational life. The gap, if positive, multiplied by the annualised cost of the eventual replacement. Sum across asset classes for the period. The article on the preventive maintenance schedule covers the data that feeds this calculation.
Capex deferral value depends on the assumption that the original retirement schedule was reasonable. If the original schedule was conservative, the deferral value overstates. The right framing is "capex deferral value vs the previously-approved replacement schedule," not against a hypothetical.
The board pack opens with the three numbers. One page, three figures, three trend arrows. Anything below the fold is supporting detail.
The operational metrics (MTBF, MTTR, PM compliance, OEE) become the answer pack for the questions the three numbers raise:
The article on the work order management system covers the data structure that supports both layers of the report.
The three financial-translation numbers depend on linking operational data (production hours, downtime events, work orders, parts) to financial data (cost-per-minute, asset replacement values). The link is straightforward in a unified OEE + CMMS platform with finance integration and laborious otherwise.
Fabrico is built to produce the monthly C-suite pack automatically from the operational data the platform already holds. To see what your three-number report would look like, book a demo .
Safety reports separately, with its own three numbers (incident rate, near-miss rate, days since last recordable). The maintenance C-suite report covers operational/financial; safety is its own conversation.
Internally, monthly. To the board, quarterly with the monthly trend. The C-suite cares about direction more than absolute level; the trend arrow is the actionable element.
Starting with rough estimates beats waiting for perfect data. The first quarter's numbers will be approximate; the act of reporting them quarterly forces the underlying data to improve. Plants that wait until the data is perfect end up with a maintenance report that never produces these numbers.
The maintenance director, with finance as the co-signer on the cost-per-hour and revenue-percentage numbers. Without finance co-signing, the C-suite discounts the numbers as operations-team self-reporting.
Leading with the operational metrics and expecting the C-suite to do the financial translation. The C-suite will not do the translation; they will skip the numbers. The translation has to happen in the report, with the operational metrics in support.
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