Benchmarking Maintenance Mgmt

1. 1Score the two training subsections of the Chapter 1 survey separately: Section 2 covers supervisory, planner, general quality, craft training format, intervals, instructors; Sections 7-8 of the general practices cover soft-skills and technical class coverage as a percent of appropriate personnel.
2. 2Set the target coverage threshold at 90%+ (4 pts) for both soft-skills classes (communications, leadership) and technical classes; anything below 60% is a gap requiring action.
3. 3Distinguish training that is tied to pay and progression (craft training A = 4 pts) from training that is only on-the-job after hire (1 pt) — build the highest-scoring form: pay-and-progression-linked craft training delivered in a mix of classroom and lab exercises.
4. 4Set craft training frequency to less than 1 year for ALL craft employees (4 pts), delivered by outside contract expert or staff subject expert, not by whoever is available.
5. 5For planners, require all planners/schedulers attend one or more public seminars on planning and scheduling (4 pts) and separately confirm coverage of the four planner subjects: work order planning/execution, material planning, scheduling practices, project planning (1 pt each).
6. 6Verify supervisory training is mandatory on a scheduled basis after salary (4 pts), not optional or infrequent, and extend general quality/productivity training across all four levels: upper management, line supervision, hourly workers, support personnel.
7. 7Assess interpersonal skill separately from technical skill: confirm technicians can communicate with other departments and work in team/natural-work-group environments, since this is the specific gap that blocks maintenance-operations coordination.
8. 8Tie the investment case to money: quantify the downtime cost the untrained workforce is failing to prevent using the passage's ratios, and route those numbers into the training budget justification.

Take the passage's lube-route problem as the training case. Nearly three-fourths of organizations have lube routes, yet the lubrication position (oiler/lubricator) is an entry-level job, and the technician's lack of skills and training produces substandard performance that leads to excessive breakdowns even though a lubrication program exists. A breakdown that costs $10,000 in labor and materials actually costs closer to $50,000 once lost production is factored in at the average 4:1 ratio. So a single preventable lube-related failure per month funds a full year of proper technical training many times over. The move: pull the oiler role out of pure on-the-job status (1 pt) and put it under craft training tied to pay and progression (4 pts) with classroom-plus-lab format on a less-than-one-year interval. That converts the survey score from a 1 to a 4 and closes the specific failure loop the passage identifies.

• If technical or soft-skills class coverage is below 60% of appropriate personnel, then treat the maintenance improvement program as at risk — the passages state that without these skills maintaining current equipment status is barely possible and improvement is inconceivable.
• If craft training is only on-the-job after hire, then it scores 1 pt; move it to pay-and-progression-linked (4 pts) before adding predictive or reliability-centered practices.
• If planners received only on-the-job or 1-month 1-on-1 training, then send them to public seminars and confirm all four planner subjects are covered — 1 point is lost per uncovered subject.
• If maintenance and operations chronically fail to coordinate PM (a problem in ~three-fourths of organizations), then the gap is interpersonal/communication skill, not technical — invest in soft-skills classes, not more wrenching training.
• If nearly one-third of the adult workforce is functionally illiterate or marginally better and apprenticeship programs are absent, then assume the skills-vs-technology gap is real for your site and budget technical training accordingly rather than assuming competence.

• Treating lube routes as the whole of training and stopping there — the tell: a documented lubrication program coexisting with excessive breakdowns and an untrained entry-level oiler.
• Investing only in technical skills while ignoring interpersonal skills — the tell: technicians who cannot communicate across departments and PM coordination problems with operations/facilities.
• Making supervisory or craft training optional or irregular — the tell: survey answers scoring 1-2 pts because 'the majority are trained when salaried' with little follow-up.
• Delivering all training on-the-job or all-classroom instead of a classroom-plus-lab mix — the tell: format scores 1-3 pts and skills do not transfer to the equipment.
• Justifying no training budget by claiming there is no cost to downtime — the tell: an organization that refuses to calculate downtime cost and ignores utility, idle-personnel, late-delivery, and overtime costs.

• ▸Soft-skills class coverage (%): enter percent of appropriate personnel trained in communications/leadership; 90%+=4, 60-89%=3, 30-59%=2, <30%=0.
• ▸Technical class coverage (%): enter percent of appropriate personnel; same scale as above.
• ▸Craft training linkage: mark whether tied to pay/progression (4), formal-experience+OJT (3), OJT-only (1), or none (0).
• ▸Craft training interval: record frequency for ALL craft employees; <1yr=4, 12-18mo=3, 18-24mo=2, some-only=1, none=0.
• ▸Training format: record classroom+lab (4), all-classroom (3), all-lab (2), all-OJT (1), none (0).
• ▸Planner training + subjects: mark public seminar attended (4 base) and check each covered subject (+1 each): work order planning, material planning, scheduling, project planning.
• ▸Supervisory training: mark scheduled-mandatory (4) down to few-trained (0).
• ▸Interpersonal gap flag: note any documented PM coordination or cross-department communication problems (yes/no).
• ▸Downtime cost avoided: enter a representative repair labor+material cost and multiply by 4:1 average to size the training justification.

1. 1Before automating, document each maintenance business process (work order flow, PM triggering, stores issue, purchasing) and define what it should be — systems only manipulate information, they do not supply the discipline you lack.
2. 2Make department users, not just MIS, select the systems: let maintenance, operations, and stores each pick tools that support their way of working, then integrate those selections rather than letting MIS dictate hardware/software preferences.
3. 3Tie every work order to an equipment/asset number so history accumulates against the asset — this is what enables objective repair-or-replace decisions and total life-cycle cost tracking.
4. 4Appoint the planner as keeper of the CMMS data files: gather equipment and stores data plant-wide, develop standardized codes for equipment, stores, and craft task assignments, and continuously audit new inputs for accuracy and completeness.
5. 5Move from batch updates toward integrated, shared databases so CMMS, energy management, and other dedicated systems pass data in real time — eliminate the window where managers act on old or incomplete data.
6. 6Give maintenance systems equal priority to production/financial systems (MRPII, MES, ERP); if maintenance data is treated as lower priority, it will never become accurate enough to trust.
7. 7Verify data integrity through measurable coverage: percent of jobs on work orders, percent tied to asset numbers, percent available for historical analysis, and percent of failure causes accurately captured in work order history.
8. 8Feed integrated data back into the PM/predictive program: have the planner surface repetitive problems from the work order system and route them to maintenance engineering for program adjustment.

A plant evolving from stand-alone systems asks the diagnostic question the text prescribes: are we using the best available computer tools to stay competitive? Rather than buying an off-the-shelf package expecting it to solve everything, they first map their work order and PM processes. They discover only 50% of work orders are tied to an equipment/asset number and only 50% are available for historical analysis — meaning repair-or-replace decisions rest on incomplete data. The planner is assigned as keeper of the CMMS files: he gathers equipment and stores information for the entire facility and builds standardized codes for equipment, stores, and craft assignments. As the tie-to-asset rate climbs toward 100%, work order history becomes accurate enough to identify failure causes, and the planner begins spotting repetitive problems and routing them to maintenance engineering, who adjust the preventive and predictive programs. They then integrate the CMMS database with energy management so data is shared in real time instead of batched, closing the window where managers acted on stale numbers.

• If you cannot describe and discipline a process manually, then do not automate it — installing a system over an unmanaged function will likely fail.
• If MIS is dictating system choice based on its own hardware/software preferences, then stop and require every using department to participate in selection and integration, or you will regress to stand-alone systems.
• If systems update in scheduled batches rather than real time, then flag that managers may be deciding on old data and prioritize an integrated shared database.
• If fewer than 100% of work orders are tied to an asset number, then you cannot track life-cycle cost or make objective repair-or-replace decisions — fix data linkage first.
• If maintenance systems are given lower priority than other business systems, then expect chronically inaccurate data regardless of software quality.

• Buying technology as a cure-all — the tell: an off-the-shelf package is purchased before anyone has documented what the underlying business processes should be.
• Letting the MIS department take ownership and dictate the integrated system — the tell: other departments' philosophies are ignored and the platform reflects MIS's preferences, not users' needs.
• Relying on batch updates and not noticing the data-age gap — the tell: managers make costly decisions between update cycles on incomplete records.
• No single owner of CMMS data integrity — the tell: inconsistent codes for equipment, stores, and craft, and work orders not tied to asset numbers, so history is unusable.
• Treating maintenance as a lower-priority system than production/finance — the tell: maintenance data never reaches the accuracy other systems enjoy and is distrusted for decisions.

• ▸Process documented? — state the maintenance process and whether its 'should-be' is defined before automation
• ▸Percent work orders tied to asset number — enter current % (target 100%)
• ▸Percent work orders available for historical analysis — enter current %
• ▸Failure-cause history accuracy — % of asset history where failures are clearly identified
• ▸Data owner named — record who is 'keeper of the CMMS files' (typically the planner)
• ▸Standardized codes built — yes/no for equipment, stores, and craft/task assignments
• ▸Selection participants — list every using department involved (not just MIS)
• ▸Update mode — batch or real-time integrated shared database; note stale-data risk
• ▸Maintenance system priority — equal to production/financial systems? yes/no

1. 1Audit the current attitude by scoring your organization against the Chapter 1 assessment item: Maintenance organization effort and attitude, where 'Excellent, pride in workmanship at all levels' scores 4 and 'Constant disagreements within maintenance and between maintenance and operations' scores 0. A low score is your baseline evidence, not an opinion.
2. 2Reframe maintenance to senior management as a core business process that lowers costs and increases profits, not a necessary evil, cost, insurance, or disaster-repairing function. Anchor the case with the waste figure: roughly one-third of maintenance spend is wasted, and at trillion-dollar national spend that is the profit management is discarding.
3. 3Measure the resource gap that reveals the real attitude: track hands-on wrench time. If craftsmen spend fewer than 4 hours (often as low as 2) of a possible 8 on hands-on work, present this as management's failure to provide resources, not a workforce failing — at ~$20/hour you are utilizing a paid resource at only 50%.
4. 4Prove attitude through resource dedication decisions, since Chapter 3 states attitudes are shown by how maintenance is treated at resource time. Inventory tools (VOM vs. oscilloscope), shop locations, shop layouts, and incentive plans, and score each on the 4-to-0 scale.
5. 5Install a planner: only about one-third of organizations employ a job planner, yet planned vs. unplanned work carries a cost ratio as high as 1:5. Use this ratio to convert an abstract 'respect' argument into a spend argument management acts on.
6. 6Build operational involvement so production takes ownership — inspecting before start-up, filing work requests, doing lubrication and routine adjustments — which frees maintenance resources for predictive work and signals that maintenance is a shared core process.
7. 7Tie a portion of maintenance pay to output (uptime, production rates, departmental performance) so the workforce sees financial upside to higher productivity, and re-score the incentive item until more than the 'less than 50%' floor is covered.
8. 8Re-assess quarterly against the same scored items to show movement, treating attitude as an enabler that is relative, not absolute — it can always be improved.

Take the passages' own arithmetic on planning to convert attitude into money. The source states a $100 planned job could cost as much as $500 if left unplanned, a 1:5 ratio, meaning $400 is wasted per job when management refuses to fund planning. Separately, a craftsman paid ~$20/hour who does only 4 of 8 hands-on hours is delivering $10/hour of productive value — a 50% utilization loss driven by missing resources, not laziness. Combine these with the foreword's claim that about one-third of maintenance spend is wasted with no change in trend since 1979. When you present this trio to senior management, the 'necessary evil' framing collapses: the waste is the size of the entire maintenance budget of 25 years ago. That reframing is what shifts budget from a nominal yearly increase or decrease toward funding planners, tools, and predictive work.

• If maintenance reports to production/operations (scores 1 pt) or lines of authority are unclear and jurisdictional (0 pts), then treat organizational attitude as structurally low and fix reporting/authority before chasing metrics.
• If hands-on wrench time is under 4 hours per day, then diagnose it as a management resourcing failure and stop blaming the workforce.
• If less than 50% of maintenance personnel are on an output-based incentive, then attitude improvement will stall — add incentives tied to uptime or production rates first.
• If the organization is in fire-fighting mode (fix it fast to just get by), then expect workmanship and pride to erode, and address the environment, not the individual craftsman.
• If management denies resources (oscilloscope vs. VOM, adequate shop location/layout, quality tools) at budget time, then read that as the true attitude regardless of stated words.

• Managing maintenance with standard production or facilities-oriented methods; the tell is that costs never come down because maintenance is a unique business process requiring a different approach.
• Blaming low productivity on lazy craftsmen; the tell is 2-4 hands-on hours per day being read as effort rather than as management's failure to supply resources.
• Treating maintenance as a line item adjusted by a nominal yearly increase or decrease; the tell is that no one can name where the one-third waste occurs.
• Buying tools/CMMS but ignoring the hidden enablers (leadership, motivated workforce, management vision, organizational focus); the tell is good statistics on paper with constant disagreements between maintenance and operations.
• Expecting precision work from worn-out tools and unsuitable shops, then judging the crew as low-skill; the tell is a maintenance organization with a low sense of self-worth and fix-to-get-by habits.

• ▸Effort/attitude score (0-4): rate against 'pride at all levels' down to 'constant disagreements'
• ▸Reporting line (0-4): document whether maintenance reports to production or has clear authority
• ▸Hands-on hours per day: record actual wrench time out of 8 and flag if under 4
• ▸Planner ratio: enter planner-to-hourly ratio and note if no planner exists
• ▸Planned vs. unplanned cost gap: estimate dollars lost using the 1:5 ratio on a sample job
• ▸Tool/equipment quality (0-4): list gaps such as VOM where an oscilloscope is needed
• ▸Shop location & layout (0-4): score suitability and note required improvements
• ▸Incentive coverage: enter % of personnel on output-based pay tied to uptime/production
• ▸Operational involvement: check which activities production performs (inspection, work requests, lubrication, adjustments)

1. 1Install a functioning work order system first — without one, you cannot measure or control what fraction of work is reactive versus planned. Most organizations are dissatisfied with or lack this system, so treat it as the precondition.
2. 2Classify every work order at close-out into planned/scheduled versus reactive/emergency, and track the labor cost split, not just job counts. The standard benchmark is percent of maintenance labor costs spent on reactive activities versus planned and scheduled activities.
3. 3Build the PM program as the primary lever, because effective PM is what reduces reactive work to a level where the 80/20 ratio becomes achievable. Only 20 percent of U.S. companies consider their PM effective and only about 22 percent of surveyed companies have PM satisfying their needs — so assume yours needs major work.
4. 4Go beyond lube routes. Nearly three-fourths of organizations have lubrication routes and then stop, wrongly equating PM with lubrication; fully develop condition and time-based tasks and staff/train lubricators (an entry-level oiler position) so substandard lubrication does not drive breakdowns.
5. 5Once PM is functioning, tighten the storeroom to 95-97 percent service level with 100 percent data accuracy, because no inventory process can cost-effectively serve a reactive shop, and planned work several weeks ahead is what lets procurement be optimized.
6. 6Add planners: only about one-third of organizations employ a job planner. Planned work carries a cost ratio as favorable as 1:5 versus unplanned, so staffing planning directly converts reactive spend into planned spend.
7. 7Track overtime as a reactive-state indicator and drive it down from the ~14.1 percent average toward roughly one-third that level; high overtime signals the reactive situation is still standard.
8. 8Set a realistic transition timeline of three to five years and manage it as a culture change, not a technical fix — treating maintenance as a core business process rather than a necessary evil.

A plant runs a $3M annual maintenance labor budget in a reactive mode: overtime near the 14.1 percent U.S. average, PM satisfying only ~22 percent of needs, and storeroom service below 90 percent so more than 10 percent of parts requests hit stockouts. Management installs a working work order system, builds out PM beyond the existing lube routes, and adds planners to schedule work several weeks ahead. As planned work grows toward the 80/20 ratio, overtime drops, outside-contractor use falls, and deferred maintenance gets done without new spending — cutting the labor budget by about one-third. Because studies show the materials budget is similar (~$3M) and can also drop by a third, total efficiency savings approach $2M per year, and those unused expense dollars convert directly to profit. None of it is immediate: the shift from reactive to proactive best practice takes three to five years, most of it spent changing the corporate culture toward the maintenance function.

• If your reactive labor share exceeds 20 percent, then stop adding advanced practices and fix PM and the work order system first — other practices only become effective once the ratio reaches 80/20.
• If overtime runs near 14 percent or higher, then read it as evidence you are still reactive and target roughly a third of that level as you plan the fix.
• If storeroom service is below 90 percent (10 percent-plus stockouts), then technicians will stockpile personal stores and bypass procurement — push controls to 95-97 percent service with 100 percent data accuracy before claiming a proactive state.
• If PM has been reduced to lube routes and effort stopped there, then treat the program as incomplete regardless of coverage, because lubrication is only a fraction of PM.
• If leadership expects savings within a year, then reset expectations to three to five years, since the constraint is corporate-culture change, not technical difficulty.

• Equating PM with lubrication routes: nearly three-fourths have lube routes and quit; the tell is a 'PM program' that is only oiling tasks while breakdowns persist.
• Understaffing lubrication: assigning the entry-level oiler with no proper skills or training; the tell is a documented lube program coexisting with excessive breakdowns.
• Chasing advanced practices before PM works; the tell is investment in tools like RCM or predictive layers while reactive labor still exceeds 20 percent.
• Ignoring the cost of downtime — some organizations refuse to calculate it or claim it is zero; the tell is decisions omitting utility costs and idle production/operations personnel, or buying redundant equipment that lowers return on net assets.
• Expecting instant savings and abandoning the effort; the tell is a program judged failed inside a year against a change that legitimately takes three to five years.

• ▸Reactive labor cost (this period): enter dollars of labor charged to reactive/emergency work orders
• ▸Planned/scheduled labor cost (this period): enter dollars charged to planned work orders
• ▸Reactive percent: divide reactive labor by total labor — target is under 20 percent
• ▸Overtime percent: overtime hours / total hours worked — compare against the 14.1 percent average and aim lower
• ▸PM effectiveness: percent of PM needs satisfied — flag if near the 22 percent survey level
• ▸Storeroom service level: percent of times parts are on hand when needed — target 95-97 percent, note if below 90 percent
• ▸Percent of work completed as planned: from work order system — track upward trend
• ▸Planner coverage: yes/no a job planner schedules work several weeks ahead
• ▸Transition milestone date: set a checkpoint within the three-to-five-year culture-change window

1. 1Define wrench time precisely before measuring: the hours a craft technician physically has hands on tools performing the assigned task — the time they are actually being paid to work. Exclude travel, waiting for parts, waiting for permits, instruction-hunting, and rework from this count.
2. 2Establish your baseline by sampling how many hours out of the paid 8 are spent hands-on. Expect the reactive reality: fewer than 4 hours per day, often as low as 2, meaning you are utilizing a ~$20/hour resource at roughly a 50% level or worse.
3. 3Attack the delay sources rather than the technicians — they are skilled and not shirking; they lack resources supplied by management. Route every job through the work order discipline: request, approve, plan, schedule, perform, record, so delays become visible and removable.
4. 4Install a dedicated planner/scheduler. Only about one-third of organizations employ one, yet better planner use is the largest cost-saving area. The planner reviews, approves, plans, schedules, and records work so technicians arrive to jobs with parts, tools, and clearances staged.
5. 5Drive planned work to at least 80% on a weekly basis with schedule compliance of at least 90%. This is the mechanism that converts wrench time from the 25% reactive floor toward the 60% proactive ceiling.
6. 6Track wrench time as a standing management indicator alongside PM/PDM hours percentage and reactive hours percentage. Report it per hour worked so the number reflects deployment, not activity volume.
7. 7Reinvest recovered capacity: as wrench time rises, cut overtime and outside contracting first, since those are the visible costs planning displaces while service simultaneously improves.

Take a reactive organization running at 25% wrench time. Under Wireman's figures, good planning and scheduling practices can raise that craft-technician wrench time to as much as 60%. Because the same crew now spends far more of each paid hour hands-on, the organization performs the same volume of work with less overtime and less outside contracting — a direct reduction in overall maintenance cost while service improves. The financial scale of the waste being recovered is shown by the planned-versus-unplanned job data: an identical job cost $30,000 planned versus $500,000 in breakdown mode; another $6,000 versus $60,000. Wireman notes the savings from just three such jobs would fund a comprehensive planning program for a considerable period. At the benchmark extreme, a 20% wrench-time organization is spending about three times the money a 60% Best Practice organization spends to accomplish the same work.

• If measured wrench time sits at or below 20-25%, then treat the organization as reactive and prioritize standing up planning/scheduling before any other productivity initiative.
• If weekly planned work is below 80% or schedule compliance is below 90%, then wrench time will not climb — fix the planning discipline first rather than pushing technicians harder.
• If a job recurs, then run it planned: the documented planned-to-unplanned cost ratio runs as high as 1:5, so scheduling ahead of failure is almost always the cheaper path.
• If wrench time is rising, then reduce overtime and outside contracting before adding headcount, because recovered hands-on capacity substitutes for both.
• If you have hit ~60% wrench time, treat it as the proactive Best Practice ceiling and shift focus to PM/PDM mix (target 50% of hours) rather than chasing further wrench-time gains.

• Blaming technicians for low hands-on time — the tell is disciplinary or motivational programs aimed at the craft while parts, tools, and clearances remain unstaged; the passages state the loss is a management resource-provision problem, not laziness.
• Measuring activity instead of hands-on time — the tell is high reported busyness with no separation of travel, waiting for parts, and permit delays from actual tool time.
• Skipping the work order discipline — the tell is fragmented, useless data because work is not tracked from request through completion, making true wrench-time analysis impossible.
• Running without a planner — the tell is that only one-third of organizations have one, yet expecting wrench time to rise; without planning there is little to convert reactive delays into scheduled hands-on time.
• Under-using the CMMS — the tell is a system used at less than 50% of its capability with incomplete or inaccurate data, so the productivity indicators you need to manage wrench time never become reliable.

• ▸Measured hands-on hours per 8-hour shift — record observed tool time, excluding travel/waiting/rework
• ▸Current wrench time % — hands-on hours divided by paid hours per hour worked
• ▸Loaded labor rate — cost per craft hour (passage reference point: ~$20/hour)
• ▸Weekly planned work % — planned jobs as share of total (target 80%+)
• ▸Schedule compliance % — jobs completed as scheduled (target 90%+)
• ▸Dominant delay source — name the top loss: waiting for parts, permits, travel, or instructions
• ▸Planner in place? — yes/no; if no, this is the first corrective action
• ▸Target wrench time % — set toward the 60% proactive Best Practice ceiling
• ▸Recovered capacity plan — state overtime/contract hours to cut as wrench time rises

1. 1Calculate overall equipment availability on your key assets, processes, and facilities first — you cannot manage what you don't measure. Target 90% or more coverage; scoring less than 30% coverage means you are effectively blind to your own reliability position.
2. 2Build the failure-history foundation: ensure work order history accurately tracks causes of failures on 90% or more of each asset's history, and that failures are clearly identified. Without this, chronic problems that damage equipment efficiency are never discovered and only surface as breakdowns.
3. 3Feed predictive maintenance data (vibration analysis, oil sample analysis, infrared heat monitors, sonics/whistle) into the CMMS as an integrated (not merely interfaced) system, then use that data to generate preventive/corrective work orders so degrading conditions are addressed before failure.
4. 4Shift PM frequency logic toward condition-based intervals (4 pts) rather than fixed calendar intervals (1 pt), and run RCM analysis annually to adjust and refine the PM/PDM program using why-tree, fishbone, and Pareto tools for consistency.
5. 5Cover 90% or more of critical equipment with a PM program, complete 90% or more of PMs within one week of due date, and check the PM program against each equipment item's history annually to confirm coverage remains valid.
6. 6Report reliability outcomes weekly or monthly: equipment downtime ranked highest-to-lowest by total hours AND by lost production dollars, maintenance cost per equipment ranked descending, and MTTR and MTBF per asset.
7. 7Embed availability into decision-making and pay: ensure operational decisions account for equipment reliability/availability 90% or more of the time, and include equipment availability or life-cycle costing in supervisor compensation so good maintenance is not sacrificed to production targets.
8. 8Make the financial effect explicit — confirm the financial effects of equipment availability/reliability are understood and communicated to everyone, framing maintenance savings as direct contributions to profit and ROFA.

A plant scores itself against Section 12. Question 5 (availability calculated on key assets) returns 'less than 30%' — 0 pts — because availability is only tracked on a handful of machines. Question 6 shows operational decisions account for reliability less than 30% of the time — 0 pts — so production runs equipment to failure. The team traces the root cause using the Section 11 gaps: work order history tracks failure causes on less than 40% of assets (0 pts) and failures are not clearly identified. They install detailed inspection checklists and predictive diagnostics (vibration, oil, infrared), integrate PDM into the CMMS, and begin generating corrective work orders from predictive data. Within the review cycle they produce the downtime-by-lost-production-dollars report and find a few chronic problems accounting for most lost hours. Solving those with RCM/fishbone analysis lengthens run times without damaging equipment, cutting downtime — which, as the source notes, is more costly than maintenance expenditures.

• If overall equipment availability is measured on less than 30% of key assets, then stop optimizing tasks and first extend measurement coverage — reliability improvement is unverifiable without it.
• If PM frequency is set purely on calendar intervals (1 pt) and failures recur, then move that PM to condition-based triggers (4 pts) informed by predictive data.
• If work order history tracks failure causes on less than 90% of an asset's history, then treat RCM output for that asset as unreliable and fix data capture before adjusting the PM program.
• If supervisor compensation rewards only production throughput, then add equipment availability or life-cycle cost to the compensation metrics, or maintenance will be sacrificed to hit output targets.
• If predictive maintenance data is collected but not tied to work order generation, then it is diagnostic decoration — connect it to the CMMS so findings convert into scheduled corrective work.

• Running to failure by default: chronic efficiency problems are never solved until a breakdown occurs. The tell — high emergency/urgent work order percentages (greater than 39%) and downtime reports dominated by repeat offenders.
• Production-centric reporting where maintenance 'fights fires': the tell is maintenance resources diverted to production, deteriorating PM completion and rising unexpected breakdowns.
• Engineering-centric structure diverting maintenance to projects on time/budget pressure: the tell is PM completion within one week of due date dropping below target while project work stays on schedule.
• Measuring availability but not acting on it: the tell is high availability calculation coverage but operational decisions accounting for reliability less than 30% of the time.
• Predictive systems not electronically connected to CMMS (0 pts): the tell is diagnostic readings sitting in silos, never converting into preventive/corrective work orders or refining the PM program.

• ▸Overall equipment availability coverage: % of key assets/processes/facilities where availability is calculated
• ▸PM critical coverage: % of critical equipment covered by a PM program
• ▸PM timeliness: % of PMs completed within one week of due date
• ▸PM interval basis: condition-based / run-time+calendar / run-time / calendar
• ▸Failure-cause data quality: % of asset history where failure causes are accurately tracked
• ▸Predictive-to-CMMS status: integrated / interfaced / not connected
• ▸Reliability in decisions: % of operational decisions accounting for reliability/availability
• ▸Reliability reports produced: downtime by hours / downtime by lost $ / cost per asset / MTTR & MTBF (check each)
• ▸Financial effects communicated: are availability/reliability financial effects understood by everyone? yes/no

1. 1Establish the denominator first: pick either estimated replacement value (ERV) of the asset base or total sales, and express total maintenance cost as a ratio against it so year-over-year comparisons stay meaningful despite the 10-15% annual cost inflation.
2. 2Sum all four cost buckets into the total: labor, materials, contractors, and lost production/efficiency losses — do not stop at the labor-and-materials figure that most work order systems capture.
3. 3Capture lost production separately by valuing equipment downtime in lost production dollars (highest to lowest by equipment), because this bucket is usually larger than the direct spend and is the one that overhaul decisions turn on.
4. 4Add efficiency losses that occur without any breakdown — degraded output from age and internal wear — by measuring actual operating efficiency against design and pricing the gap annually.
5. 5Attack the waste third: measure wrench time (target the gap from the 2-4 hours/day observed), overtime (drive down from the ~14.1% average toward roughly a third of that), and planning ratio (planned vs. unplanned work carries a cost ratio as high as 1:5).
6. 6Turn on performance monitoring so you can actually see the total: compare estimated work order labor and materials to actual results (only ~10% of organizations do this), and run failure analysis on breakdowns instead of just changing parts.
7. 7Expand preventive maintenance coverage — currently satisfying only ~22% of surveyed companies' needs — because PM shifts the organization from reactive to proactive and directly reduces total cost.
8. 8Reinvest a fraction of projected savings to fund the improvement, then track the ratio downward; even spending 10% of an identified savings can capture the remaining 90%.

An off-shore operation examined the efficiency of its gas compressors and found that, due to age and internal wear, they were running at only 61% efficiency. That efficiency loss cost approximately $5.4M annually — a pure lost-efficiency component of total maintenance cost that never appeared as a labor or materials line. The overhaul was scoped at $450K including labor, materials, and downtime production losses. To avoid a total shutdown, the compressors were overhauled serially. After restart the overhaul paid back in 28.1 days, and the full $5.4M in increased production was realized over the next 12 months. This shows why lost efficiency must be counted in total maintenance cost: the $450K direct spend was trivial against the $5.4M hidden loss it eliminated.

• If the maintenance portion of downtime is valued (e.g., $38M) and a 50% reduction is achievable, then fund the improvement — even spending only 10% of the savings still nets more than $17M.
• If an overhaul's cost (labor + materials + downtime losses) pays back in days against a large annual efficiency loss, then do it serially to avoid total shutdown rather than deferring.
• If work order estimates are never compared to actuals, then you cannot claim to know total maintenance cost — install performance monitoring before benchmarking the ratio.
• If overtime runs near 14.1% of total hours worked, then treat it as a symptom of a reactive process and target it, since it should be about a third of that.
• If craftsmen log only 2-4 hands-on hours out of 8, then the fix is management-supplied resources and planning, not pressure on the workers.

• Counting only labor and materials as total cost — the tell: your maintenance cost report has no line valuing downtime in lost production dollars or efficiency losses.
• Comparing raw dollar figures year to year and panicking at the 10-15% rise — the tell: no ratio to ERV or sales, so real performance is invisible under inflation.
• Just changing parts after a breakdown — the tell: no failure analysis is performed, so the same failure recurs and total cost stays inflated.
• Assuming the plant runs efficiently because nothing is broken — the tell: no measurement of operating efficiency vs. design, hiding losses like the compressors' 61% efficiency.
• Trying to control maintenance with standard production or facilities methods — the tell: nominal year-to-year budget tweaks with little management control and a persistent ~one-third waste.

• ▸Denominator basis: choose ERV or total sales and enter the dollar value
• ▸Direct labor cost: total maintenance labor dollars for the period
• ▸Materials cost: total materials charged against work orders
• ▸Contractor cost: outside/contracted maintenance spend
• ▸Lost production cost: downtime hours valued in lost production dollars, worst equipment first
• ▸Efficiency loss cost: actual vs. design efficiency gap priced annually
• ▸Total maintenance cost: sum of the five cost fields above
• ▸TMC ratio: total cost divided by the denominator basis
• ▸Waste estimate: portion judged unnecessary (benchmark ~one-third) flagged for reduction

1. 1Calculate ROFA as profit generated relative to the company's fixed asset investment; use it in strategic planning to decide which facility to occupy or which plant to produce a product in.
2. 2Track the two maintenance indicators that directly move ROFA: maintenance cost as a percentage of total process/production/manufacturing cost, calculated as a total (not per-unit) figure because it is generally fixed and therefore a more accurate financial measure.
3. 3Quantify equipment downtime for the assets you maintain; measure current availability against the 10-20% (or higher) downtime range typical of unmanaged operations, since availability and efficiency gains dwarf the pure maintenance cost contribution.
4. 4Build a true cost-of-downtime figure by summing utility costs, cost of idle production/operations personnel, cost of late delivery, and overtime to make up lost production — then anchor it to lost sales for product not made on time.
5. 5Separate the maintenance-correctable portion of downtime from causes owned elsewhere (raw materials, production scheduling, quality control, operator error) so improvement projects target only what maintenance can fix.
6. 6Model the savings from a realistic reduction target, then compare the required investment against that savings to prove the return; drive costs down and availability up to reach a higher ROFA than competitors and become the low-cost producer.
7. 7Plan for a three-to-five year horizon: the transition from reactive to proactive maintenance is not technically difficult but requires cultural change to treat maintenance as a core business process contributing to profitability.

A company finds a considerable amount of unplanned downtime for the previous year, only part of which maintenance can correct. Other causes trace to raw materials, production scheduling, quality control, and operator error, so those are excluded. The maintenance portion of the downtime is valued at $38M. Management sets a realistic target of a 50% reduction achievable by improving maintenance, which yields $19M in savings. Even if only 10% of that $19M is spent on improving maintenance, the net savings remain substantial. This directly lowers production cost, raises availability, and pushes ROFA above competitors' — supporting a low-cost-producer position that attracts both customers and investors.

• If a company buys backup or redundant equipment to cover downtime, then expect its return on net assets indicator to fall and its investment rating in the financial community to drop — solve the downtime, not the symptom.
• If someone claims downtime has no cost, then force a calculation covering utility costs, idle personnel, late delivery, overtime, and lost sales before any asset decision is made.
• If the market has a volume cap, then downtime still raises cost and blocks the goal of higher margins or low-cost supply — do not treat capped volume as a reason to ignore availability.
• If reporting maintenance cost against ROFA, then use a total-cost calculation rather than per-production-unit, because the fixed nature of the total makes it the more accurate financial indicator.
• If downtime has multiple root causes, then value only the maintenance-correctable share and apply the improvement target to that share alone.

• Refusing to calculate a cost of downtime — or asserting it is zero — so asset and operating decisions are made blind; the tell is that no factor list (utility, idle labor, late delivery, overtime, lost sales) exists.
• Compensating for downtime by purchasing redundant equipment; the tell is a declining return-on-net-assets ratio and weakened financial-community ratings.
• Reporting maintenance cost per production unit instead of as a total percentage; the tell is a volatile indicator that misleads the finance function.
• Attributing all downtime to maintenance and over-claiming savings; the tell is ignored contributions from raw materials, scheduling, quality control, and operator error.
• Expecting the reactive-to-proactive shift to happen fast; the tell is treating it as a technical fix rather than a three-to-five-year cultural change, so the effort stalls when negativity toward maintenance persists.

• ▸Total unplanned downtime last year: record hours/percent of scheduled operating time.
• ▸Cause breakdown: split downtime across maintenance, raw materials, scheduling, quality control, operator error.
• ▸Maintenance-correctable value ($): dollar value of the maintenance portion only.
• ▸Reduction target (%): realistic percent reduction achievable by improving maintenance.
• ▸Projected savings ($): maintenance value multiplied by reduction target.
• ▸True cost-of-downtime components: list utility, idle personnel, late delivery, overtime, and lost sales figures.
• ▸Improvement investment ($): planned spend to achieve the reduction.
• ▸Maintenance cost as % of total production cost: total calculation, not per-unit.
• ▸ROFA effect: note direction of change vs. competitors and impact on investor/customer position.

1. 1Run an internal audit first using the structured survey (16 categories from Maintenance Reporting to Document Management, ~366 total points) and plot results in a spider diagram in Excel to expose the weakest processes — this precedes any external contact.
2. 2Build the ROI business case before benchmarking: quantify the cost of benchmarking against the financial benefit expected, so you only pursue gaps where the return justifies the visit.
3. 3Search worldwide for three or four partners with demonstrably superior performance in the specific process you flagged — reject the 'not invented here' and 'we are already the best' mindsets, and don't settle for status-quo parity.
4. 4Contact partners, secure cooperation, and send a pre-visit questionnaire built around your identified improvement areas so site visits stay disciplined and on-plan.
5. 5Define quantifiable, time-framed gap targets: T-1 (parity goal at their current level), T-2 (real-time parity as they keep improving), T-3 (leadership, where you exceed the partner). Without quantifiable, time-framed parameters, gap analysis is meaningless.
6. 6Follow the Plan–Search–Observe–Analyze–Adapt–Improve sequence; understand the enablers behind a partner's numbers, then adapt the practice to your business conditions rather than copying the number.
7. 7Honor the ethics: never publish a partner's name or data without prior permission — a breach kills ongoing benchmarking and can stop management from ever commissioning future exercises.
8. 8Re-benchmark continuously; treat benchmarking as an ongoing improvement tool, not a one-time audit, and feed adapted practices back into the maintenance management pyramid (stores controls, work flows, planning/scheduling, CMMS).

A reactive maintenance organization runs the internal survey and its spider diagram shows a low score in Planning and Scheduling. The internal audit confirms less than 25% wrench time and heavy overtime (against the U.S. average of 14.1%, roughly three times what it should be). Management builds an ROI case: with 80–90% of work planned and scheduled weekly, waste falls sharply, and the group estimates it is currently wasting about $300,000. They find three or four superior-performing partners, send a pre-visit questionnaire, and set gap targets — parity (T-1) at the partner's current planning level, then leadership (T-3). After adapting the partner's planning discipline rather than copying its metrics, wrench time rises from 25% toward 60%, cutting overtime and outside contracting. Because they achieve 95–97% stores service levels with 100% data accuracy first, planning has the parts it needs to execute the schedule.

• If the goal is only to match competitors (status quo), then stop — benchmarking's value is superior performance, and parity gains little.
• If the parameters aren't quantifiable and time-framed (T-1, T-2, T-3), then don't run gap analysis — it will be meaningless.
• If less than 80% of work isn't planned weekly and schedule compliance is below 90%, then fix the disciplined work-flow and CMMS foundation before benchmarking downstream metrics.
• If you cannot justify the benchmarking cost with an ROI business case, then defer the exercise — benchmarking for the wrong reasons becomes a curse.
• If a partner has not granted permission, then never publish their name or data — protect the ability to benchmark again.

• Copying the partner's numbers without understanding the enablers — the tell: adopted 'best practices' don't fit your business conditions and results don't move.
• Skipping the internal audit and going straight to site visits — the tell: you can't state your mission, current KPIs, or which process is weakest, so visits produce anecdotes not gaps.
• Benchmarking only to reach parity — the tell: goals are framed as 'as good as competitors,' and improvement stalls at status quo.
• 'We are already the best' or 'we are different' mindset — the tell: leadership dismisses external ideas and clings to the not-invented-here paradigm.
• Publishing partner data without permission — the tell: a damaged relationship, no repeat benchmarking, and management refusing to commission future exercises.
• Undisciplined process (no pre-visit questionnaire, no adherence to plan) — the tell: fragmented data and no long-term results.

• ▸Process benchmarked — name the single maintenance process (e.g., Planning & Scheduling).
• ▸Internal audit score — survey category score and spider-diagram rank vs. other categories.
• ▸Current KPI baseline — quantified present performance (e.g., 25% wrench time, 14.1% overtime).
• ▸ROI case — benchmarking cost vs. quantified benefit (e.g., $300,000 waste recovered).
• ▸Partners identified — three or four superior-performing companies (worldwide).
• ▸Gap targets — T-1 parity, T-2 real-time parity, T-3 leadership, each with a date.
• ▸Enablers to understand — what makes the partner better, not just their number.
• ▸Adaptation plan — how the practice is modified to your business conditions.
• ▸Ethics check — written permission obtained before using partner name/data (yes/no).

1. 1Score your current PM/PDM state using the survey's four maturity tiers: lubrication checklists, detailed inspection checklists, personnel specifically assigned to PM, and predictive diagnostics (vibration, oil sample, infrared). Award 1 point per type present. Most organizations stall after the first tier.
2. 2Measure critical-equipment coverage: what percent of critical assets sit under a PM program? Target 90%+ (4 pts). Below 40% means you are still reactive on the equipment that matters most.
3. 3Shift PM frequency logic up the ladder. Calendar-only intervals score 1 pt; run-time-based scores 2; a combination of run time and calendar scores 3; condition-based scores 4. Move each critical asset toward condition-based triggering.
4. 4Stand up predictive technologies on critical AND non-critical assets — vibration analysis, thermography, oil analysis, sonics/whistle — each earning 4 pts when applied to both classes versus 2 pts for critical only.
5. 5Integrate the predictive system into the CMMS (integrated = 4 pts, interfaced = 3, not connected = 0) and configure predictive data to auto-generate preventive/corrective work orders. Assign personnel exclusively to PDM and put predictive work on the weekly schedule.
6. 6Close the loop with reliability engineering: capture complete, accurate asset data for RCM analysis on 90%+ of assets, use RCM to refine the PM/PDM program, run RCM at least annually, and ensure work-order history accurately tracks failure causes on 90%+ of assets.
7. 7Fix the two failures the passages flag: coordinate PM with operations/facilities through credible communication (three-fourths of organizations fail here), and perform failure analysis on breakdowns instead of just changing parts (only ~10% of companies do any failure analysis).

A plant has lube routes and inspection checklists but nothing more — the pattern the survey warns about, where organizations believe PM equals lubrication and stop. On Section 5 they score 2 of a possible points for program contents (lube + inspection only, no assigned personnel, no diagnostics), rate 45% critical-equipment coverage (1 pt), and run calendar-only intervals (1 pt). Their PDM section is near zero because no vibration, thermography, or oil analysis exists. Benchmarked against the survey averages — Preventive Maintenance 24.1, Predictive Maintenance 20.0, Reliability Engineering 15.7 — they sit well below par and are trapped reacting to breakdowns. The fix path: add personnel assigned to PM and predictive diagnostics (+2 pts on contents), extend coverage of critical assets toward 90%, move intervals to run-time-plus-calendar, then introduce vibration and oil analysis on critical assets tied into the CMMS to generate work orders. As predictive data flows, feed it into RCM to refine intervals, retiring calendar guesswork.

• If PM is only lube routes and inspection checklists, then you are at the entry tier — add assigned personnel and predictive diagnostics before claiming a real PM program.
• If critical-equipment PM coverage is below 90%, then prioritize the uncovered critical assets before expanding to non-critical equipment.
• If PM intervals are calendar-based only, then move toward condition-based triggering, using combined run-time-plus-calendar as the interim step.
• If predictive data is not tied into the CMMS or does not generate work orders, then the PDM program is diagnostic theater — integrate it and auto-generate corrective/preventive orders.
• If work-order history does not accurately track failure causes on 90%+ of assets, then you cannot run credible RCM — fix failure-cause capture first.

• Believing PM equals lube routes. Tell: once lubrication routes and procedures exist, all further PM development stops — the passages cite three-fourths of organizations having lube routes yet still breaking down.
• Staffing lubrication with untrained entry-level oilers. Tell: a lubrication program exists on paper but excessive breakdowns persist because of substandard performance.
• Changing parts instead of analyzing failures. Tell: only about 10% of companies perform any failure analysis; the rest just swap components and repeat the breakdown.
• No coordination with operations/facilities. Tell: nearly three-fourths of organizations report PM scheduling conflicts rooted in poor communication about PM's need and benefits.
• Applying predictive tools only to critical assets and never integrating the data. Tell: PDM systems not electronically connected to the CMMS and predictive findings that never become work orders (0 pts each).

• ▸Program contents present (0-4): +1 each for lube checklists, inspection checklists, assigned PM personnel, predictive diagnostics
• ▸Critical-equipment coverage %: enter percent under PM; map to 90%+=4 down to <40%=0
• ▸PM completeness checked %: percent of PM checklists verified complete
• ▸Interval basis: condition-based=4 / run-time+calendar=3 / run-time=2 / calendar=1
• ▸PDM technologies applied: mark vibration, thermography, oil analysis, sonics for critical+non-critical (4) or critical-only (2)
• ▸CMMS integration: integrated=4 / interfaced=3 / not connected=0
• ▸Predictive-to-work-order link: does PDM data generate PM/corrective orders? Yes=4 / No=0
• ▸RCM data completeness %: percent of assets with accurate data for RCM analysis
• ▸Failure-cause tracking accuracy %: percent of asset history accurately recording failure causes

1. 1Route every maintenance request through one entry point so nothing gets performed off-system. The work order lifecycle is request → approve → plan → schedule → perform → record; enforce each gate before the next begins.
2. 2Report 100% of maintenance man-hours to a work order number, and charge 100% of maintenance materials against a work order number when issued. Partial capture (75%, 50%, 25%) fragments the data and defeats analysis.
3. 3Tie every work order to an equipment/asset number. Without the asset link, the completed record cannot feed equipment history, and failure analysis becomes impossible.
4. 4Set a priority code on each request and monitor the emergency/urgent share. Keep it under 20%; if more than 39% of orders open as emergency or urgent, the shop is running reactive and the system is documenting chaos rather than controlling it.
5. 5Have a qualified individual check each closed work order for work quality and completeness before it closes, and close orders within eight weeks of the request date to keep backlog honest and history current.
6. 6Generate work orders from PM inspections (target 80-100% of PM-driven work as orders) so preventive findings enter the same tracked flow as reactive work.
7. 7Track the discrete data categories on each order — required downtime, required craft hours, required materials — and preserve 100% of orders for historical data analysis. Then compare estimated labor and materials against actuals to build performance monitoring.
8. 8Format orders into a craft backlog so managers can project work per craft and make staffing decisions on data instead of on 'I think I have enough technicians' or 'let's work overtime to get caught up.'

The book estimates planned work versus unplanned work carries a cost ratio as high as 1:5 — a $100 planned job could cost $400 if done unplanned. That ratio only becomes visible when the work order system captures both the estimate and the actual. Take a shop that reports man-hours and materials to work orders, ties each to an asset, and compares estimates to actuals: it discovers its urgent/emergency orders sit above 39% and its wrench time is stuck at 25%. Once the disciplined request-approve-plan-schedule-record flow is enforced and 80% of work is planned weekly, wrench time can rise from 25% to as much as 60%, cutting the overtime that averages 14.1% of total time worked. None of this is measurable in a shop that only captures 25% of hours — the data is fragmented and useless. The system, used comprehensively, is what converts anecdote into a defensible staffing and cost case for senior management.

• If maintenance work is performed without a work order, then it is off-system and lost — no exceptions; route it back through the request gate before crediting labor.
• If a work order carries no equipment/asset number, then do not close it — an unlinked record cannot feed equipment history or failure analysis.
• If more than 39% of work orders open as emergency or urgent, then the organization is reactive; treat the priority mix as the diagnostic and shift resources into planning.
• If estimated labor and materials are never compared to actuals, then no performance monitoring exists (only ~10% of organizations do this) — install the comparison before claiming control.
• If orders are not held in a craft backlog format, then staffing decisions default to guesswork; build the backlog before justifying headcount to management.

• Owning a work order system but not enforcing it — the majority of shops are dissatisfied with or lack a functioning system. Tell: high dissatisfaction plus man-hour capture well below 100%.
• Capturing labor but not materials (or vice versa) against the order. Tell: material charges issued without a work order number, leaving cost history incomplete.
• Closing orders without a quality/completeness check by a qualified person. Tell: reopened jobs and thin, unusable close-out notes.
• Letting orders age past eight weeks unclosed. Tell: a swelling open-order count that masks true backlog and staffing needs.
• Changing parts without recording failure data — most non-analyzing companies 'just change parts.' Tell: only ~10% perform failure analysis; chronic repeat breakdowns with no captured cause.

• ▸% of man-hours reported to a work order — target 100% (4 pts)
• ▸% of materials charged against a work order when issued — target 100% (4 pts)
• ▸% of total jobs covered by work orders — target 100% (4 pts)
• ▸% of work orders tied to an equipment/asset number — target 100% (4 pts)
• ▸% of orders opened as emergency/urgent — keep under 20% (4 pts)
• ▸% of orders available for historical data analysis — target 100% (4 pts)
• ▸% of orders checked by a qualified individual for quality/completeness — target 100% (4 pts)
• ▸% of orders closed within eight weeks of request date — target 100% (4 pts)
• ▸Categories tracked per order (1 pt each): required downtime, craft hours, materials

1. 1Assign planning to a dedicated maintenance planner, not a supervisor or the craft technician. The scoring rubric awards 4 points for a dedicated planner, only 2 for a supervisor, and 0 for a technician or 'anyone else' — the person who supervises the work should not be the one planning it.
2. 2Build each work order plan to cover four elements before release: craft required, materials required, tools required, and specific job instructions or a job plan. Score one point per element; a plan missing any of these is incomplete and will generate delay.
3. 3Train every planner on a real curriculum, not just the floor. Provide a written training program or send them to public seminars on maintenance planning and scheduling, and cover the four subjects explicitly: work order planning and execution, material planning, scheduling practices, and project planning.
4. 4Stage all resources — parts, tools, instructions — so they are ready before the craftsman starts. This is the mechanism that raises wrench time from the observed 2-4 hours per day toward the full 8, since craftsmen are idle because management fails to provide resources, not because they are lazy.
5. 5Issue job schedules weekly (weekly earns 4 points; daily scheduling scores only 1) and hold a maintenance/production scheduling meeting weekly to match backlog to available craft capacity.
6. 6Make the backlog visible by craft and by area so the weekly meeting can match work waiting against hours available, then commit only the volume the capacity can absorb.
7. 7Measure schedule compliance and plan quality with hard percentages: aim for 90% or more of non-emergency work orders completed within four weeks of request (4 points), and fewer than 10% of planned work orders experiencing delays due to poor or incomplete plans (4 points).
8. 8Plan and schedule through the CMMS, targeting 90% or more of maintenance activities planned and scheduled in the system, and integrate the CMMS with production scheduling so backlog matches production windows.

The passages give the planned-versus-unplanned cost ratio as high as 1:5. Take a specific $100 job that is properly planned: the planner has confirmed the craft, staged the materials and tools, and written the job instructions before the craftsman arrives. If that same job is run unplanned, the craftsman starts, discovers a missing part, walks to stores, waits, and finishes later at up to five times the cost — as much as $500, a $400 penalty on a single job. This is why the passages call better use of planners one of the largest cost-savings areas in maintenance. It also explains the 2-4 hour wrench-time problem: unplanned work forces craftsmen to hunt for resources instead of turning wrenches. Only about one-third of organizations employ a job planner at all, so most are absorbing this 1:5 penalty across their entire backlog.

• If the person planning the work is also the supervisor or the craft technician, then reassign planning to a dedicated planner — the rubric scores those alternatives at 2 and 0 points respectively.
• If a job plan does not specify all four of craft, materials, tools, and instructions, then hold it — release it only when all four are present.
• If more than 10% of planned work orders are delayed by poor or incomplete plans, then the planning process is failing quality and needs correction before adding volume.
• If schedules are issued daily rather than weekly, then move to a weekly issue cycle and a weekly production-scheduling meeting to earn full scoring and stabilize the plan horizon.
• If fewer than 90% of non-emergency work orders close within four weeks, then backlog is outrunning capacity — cut committed scope to match available craft hours.

• Treating the supervisor as the planner. The tell: no dedicated planner headcount, and planning happens in spare moments between firefighting — scoring 2 points instead of 4.
• Releasing plans that name the job but skip materials or tools. The tell: rising percentage of planned work orders delayed mid-job while craftsmen wait for parts.
• No planner training beyond on-the-job absorption. The tell: planners never attended a seminar and have no written program — the rubric scores this at 1 point or 0.
• Confusing scheduling with planning by issuing daily assignments. The tell: no visible backlog by craft, no weekly scheduling meeting, and constant reactive re-sequencing driving overtime nearly three times what it should be.
• Planning and scheduling outside the CMMS or with a CMMS not integrated to production scheduling. The tell: fewer than 90% of activities planned in the system and no connection between maintenance and production schedules.

• ▸Planner assigned (name): confirm a dedicated planner owns this work order, not a supervisor or technician
• ▸Craft required: list craft type and number of technicians
• ▸Materials required: list parts and confirm each is staged/available before release
• ▸Tools required: list special tools and confirm on hand
• ▸Job instructions/plan attached: yes/no — do not release if no
• ▸% non-emergency WOs completed within 4 weeks: record this week's figure, target 90%+
• ▸% planned WOs delayed by incomplete plans: record, target under 10%
• ▸Backlog by craft (hours) vs. available capacity (hours): enter both and commit only up to capacity
• ▸Schedule issue frequency & scheduling meeting held: confirm weekly for both

1. 1Take control of what gets stocked. In half of organizations, someone outside maintenance dictates what to stock, how many, and how many to issue — reclaim this so maintenance (the customer) owns the stocking decisions rather than a support function running your business.
2. 2Build a complete stores catalog with both alphabetic and numeric listings, aiming for 90%+ of inventory items appearing in it. A catalog that is alphabetic-only, numeric-only, or incomplete scores half credit or zero on the benchmark.
3. 3Specify aisle/bin location for more than 95% of stores items so craftsmen can physically find parts — this directly attacks the wrench-time problem where craftsmen average under 4 hours (as low as 2) of hands-on work per day due to missing resources.
4. 4Set maximum and minimum levels for more than 95% of inventory items, then update inventory levels daily upon receipt of materials. Min/max levels keep stock low enough to control carrying cost while high enough to avoid stockouts.
5. 5Require that every item is issued to a work order or account number on leaving the store (target 95%+). This ties material cost back to the job and account, feeding the labor-plus-material repair cost calculation.
6. 6Measure your service level: what percent of the time are materials in stores when the maintenance organization requires them? Above 95% is best practice; below 50% is failing.
7. 7Run an activity check — verify that each item has had at least one issue every six months (target 90%+). Items with no issues are dead stock inflating carrying cost.
8. 8Stock critical maintenance material (95%+ of it) in the warehouse or a readily accessible location so downtime on critical assets is not extended waiting for parts.

Consider a storeroom overstocked to 'remedy' materials problems. The company holds a $1 million maintenance inventory believing more stock means fewer stockouts. But inventory carrying cost runs over 30% of item price per year, so that $1 million inventory costs over $300,000 annually just to hold. Meanwhile, materials already account for 40% to 60% of the maintenance budget — second only to labor. The correct move is to drive inventory down while protecting service level: set min/max on 95%+ of items, keep critical parts readily accessible, and confirm materials are actually in stores 95%+ of the time when needed. Done right, the company cuts the $300,000 carrying burden without introducing stockouts.

• If materials are in stores less than 50% of the time when required, then service level is failing — fix availability before touching carrying cost.
• If someone outside maintenance controls what is stocked, then transfer stocking authority to maintenance; a support function should not dictate to its customer.
• If an item has had no issue in the last six months, then flag it for review as potential dead stock inflating the 30%+ carrying cost.
• If a part supports a critical asset, then stock it (95%+ target) in the warehouse or a readily accessible location so lost production — often 4x the repair cost — is not extended.
• If the stores catalog is incomplete or listed only one way, then rebuild it as combined alphabetic and numeric listings covering 90%+ of items.

• Overstocking to solve shortages — the tell: rising inventory valuation with no drop in stockouts, ignoring that carrying cost exceeds 30% of item price per year ($300,000 on a $1M inventory).
• Letting a non-maintenance group set stock levels and issue quantities — the tell: maintenance responsible for its own inventory in only about half of organizations, with the support function telling customers how to run their business.
• Issuing materials without charging them to a work order or account number — the tell: repair costs cannot be reconciled and material-as-percent-of-cost reporting breaks down.
• No specified aisle/bin locations — the tell: craftsmen hunting for parts, contributing to hands-on wrench time dropping to as low as 2 hours per day.
• Missing or stale min/max levels — the tell: simultaneous stockouts on some items and dead stock on others, since replenishment has no defined trigger and inventory is not updated daily on receipt.

• ▸Service level %: percent of time materials are in stores when required (>95% = best)
• ▸Catalog coverage %: percent of inventory items appearing in the stores catalog (target 90%+)
• ▸Catalog format: alphabetic AND numeric / one only / incomplete
• ▸Stocking authority: maintenance controls stock decisions? (yes/no)
• ▸Bin location coverage %: percent of stores items with specified aisle/bin (>95%)
• ▸Min/max coverage %: percent of inventory with max and min levels set (>95%)
• ▸Issue-to-order %: percent of items issued to a work order or account number (>95%)
• ▸Critical-part accessibility %: percent of critical material stocked and readily accessible (>95%)
• ▸Activity check %: percent of items with at least one issue every six months (90%+); note carrying cost = 30%+ of inventory value/yr