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How to Set KPIs and Measure Success Post-CMMS Implementation

Introduction

A computerized maintenance management system (CMMS) only proves its worth when the numbers change for the better. Minutes saved, failures prevented, overtime avoidedโ€”these are the signals that convince leadership to keep investing. Yet many teams switch on the software, tick off the training sessions, and then stumble when asked, โ€œSo, what did we gain?โ€

This guide removes the guesswork.

Youโ€™ll learn which key performance indicators (KPIs) tell the real story, how to set meaningful targets, and where to find the data inside LLuminโ€™s reports. 

12 Core Maintenance KPIs Every Team Should Track

Below youโ€™ll find twelve metrics grouped by reliability, workload, cost, and compliance. Each entry includes a plainโ€‘language definition, why it matters, and guidance on targets. Use them as a starter pack, then tailor to your plant.

1. Mean Time to Repair (MTTR)

When an asset fails, the clock starts. Shortening MTTR is the fastest way to restore flow and protect throughput.

Formula: โ€‚ฮฃ repair duration รท number of repairs

Data Collection Tips

  • Use automatic timestamps. Pull โ€œfailure reportedโ€ and โ€œwork order closedโ€ directly from the CMMS to avoid manual entry errors.
  • Separate waiting vs. working. Tag each status change (awaiting parts, QA hold, etc.) so you can strip out non-productive time later.
  • Exclude planned work. MTTR measures unplanned or corrective repairs only; mixing in scheduled PM tasks hides real delays.

Track MTTR weekly, break it into waiting vs. wrench time, and attack the biggest delay buckets first. According to a research published on ResearchGate, plants that combine stocked spares, mobile workflows, and rapid fault diagnosis usually shave 15โ€“30 % off MTTR within the first year and unlock extra production hours without new capital spend.

Check out LLuminโ€™s Reporting Features.

2. Mean Time Between Failures (MTBF)

MTBF is the average running time between one unplanned stoppage and the next on the same asset.

Formula: MTBF = Number of Failures รท Total Operating Hours

What MTBF Reveals

PatternLikely InsightFirst Check
Steady climbPMs and condition monitoring are delaying faultsReview which maintenance tasks were added or improved
PlateauPreventive work is holding the line but not eliminating failure modesInspect backlog for recurring corrective jobs
DownturnHidden root causes or data entry gapsAudit failure codes and recent changes to work practices

Data Collection Tips

  • Automate runtime capture. Pull hours from PLCs or SCADA where possibleโ€”manual logs often miss changeovers and idling.
  • Use clear failure codes. Consistent coding lets you group faults by cause and attack the worst classes.
  • Exclude infant mortality. New-install teething issues skew MTBF downward; track them separately for warranty talks.

Aim for a 10 % lift in the first 12 months. Once achieved, break the figure down by asset class and set tighter goals on bottleneck machines. Consistent wins come from small, systematic changes: better lubrication, precise alignment, and data-driven PM tweaks.

For a deeper understanding, check out our guide on โ€˜MTBF and MTTR Explainedโ€™.

3. Planned Maintenance Percentage (PMP)

PMP is the share of total maintenance hours spent on scheduled, approved tasks.

Formula: PMP=  Planned Labor Hours รท Planned + Unplanned Labor Hours ร—100

Gathering Accurate Data

  • Split work orders at creation. Tag each job as planned, urgent, or emergency.
  • Capture labor automatically. Mobile tablets that timestamp start/stop give cleaner data than handwritten sheets.
  • Audit coding discipline monthly. A single โ€œmiscellaneousโ€ tag can hide half a day of reactive work.

Advanced Use

  • Segment by craft. Electrical and instrumentation teams often face more unplanned calls than mechanical.
  • Layer with overtime. A high PMP that relies on weekend OT hides real crew-capacity gaps.
  • Plot PMP against production schedule stability. Frequent product changeovers can knock even tight plans off course; adjust buffers accordingly.

High PMP means technicians spend most of their shift on scheduled work instead of emergency calls. Plants chasing worldโ€‘class reliability push above 85โ€ฏ%.

4. Schedule Compliance

Schedule compliance is a percentage of scheduled work orders that finish inside the time window the planner setโ€”start to finish, permits closed, notes entered.

Formula: Schedule Compliance = (Jobs Completed On-Time รท Total Jobs Scheduled) x 100

How to Capture Clean Data

  • Lock next weekโ€™s schedule by Thursday. No edits after the freeze unless the maintenance manager approves.
  • Time-stamp every status change. Tablets or bar-code scanners beat handwritten logs.
  • Tag break-in jobs. Anything added after the weekly freeze must carry a โ€œbreak-inโ€ flag so planners see the cost of last-minute changes.
  • Audit coding monthly. Mis-tagged work (e.g., โ€œcompletedโ€ but QA still open) drags the metric down unfairly.

Advanced Use

  • Layer with PMP and MTBF. High schedule compliance plus high Planned-Maintenance % typically precedes a rising MTBF.
  • Segment by craft. Electrical work often faces more interruptions than mechanical; track separately to see where to focus buffers.
  • Plot against backlog age. A high compliance number that sits on top of an ageing backlog means planners may be ignoring older jobs to stay on-timeโ€”false security.

If youโ€™re under 70 %, focus first on locking the weekly schedule and shielding it from break-ins. Most plants see a jump to 80 % within three months once freeze discipline, parts staging, and daily huddles are in place. The long-term aim is a steady 90 % while backlog stays currentโ€”proof that reliability work is driving the calendar, not the other way around.

5. Work Order Backlog Age

Work order backlog age exposes resource gaps and approvals stuck in limbo. Importantly, a backlog older than four weeks hides risk.

Formula: Backlog Age = โˆ‘ Days Open for All Active WOs รท Number of Active WOs

Why Backlog Age Matters

TrendWhat It SignalsFirst Check
Rising steadilyCrew capacity or spare-parts flow canโ€™t keep up.Compare labor hours worked vs. scheduled; review stores fill rate.
Sudden jumpApproval bottleneck or major outage diverted technicians.Pull the oldest ten jobs and see which department is holding sign-off.
Flat but highChronic under-resourcing feels โ€œnormal.โ€Audit overtime and contractor spendโ€”hidden workarounds often mask the gap.

Capturing Clean Data

  • Use status codes that match reality. โ€œAwaiting parts,โ€ โ€œawaiting window,โ€ and โ€œawaiting approvalโ€ tell you exactly where the aging sits.
  • Time-stamp every hand-off. If an approver signs in a different system, integrate or audit weekly so age isnโ€™t reset manually.
  • Exclude project work. Long-lead improvements skew the averageโ€”log them in a separate project module.

If your average sits above four weeks, focus first on clearing anything older than 30 days and on enforcing quick approvals. Most plants can reach a 14-day average inside six months once capacity, spares, and approval of SLAs line up. The long-term goal is a live backlog that rarely ages beyond a single production cycle, keeping surprises off the shop floor and labor hours focused on value-adding work.

6. First-Time Fix Rate (FTFR)

FTFR refers to the share of maintenance or service jobs that resolve the issue in one visitโ€”no return call, no extra parts run.

Formula: FTFR = (Jobs Closed on First Visit รท Total Jobs Closed) x 100

What FTFR Shows

PatternLikely CauseQuick Check
High and risingAccurate job scopes, right parts on hand, clear proceduresVerify work orders include feedback so planners keep learning
Flat at mid-rangeRepeat faults on a few assetsPull failure codes and parts pick lists for those items
FallingPoor diagnostics, missing spares, rushed estimatesCompare technician notes vs. planning estimates; audit parts substitutions

Capturing Reliable Data

  • Define a proof window. Agree on โ€œno call-back for 24 hโ€ (or one production run) before declaring a first-time fix.
  • Close the loop. Require a reason code if a tech returnsโ€”wrong part, new symptom, incomplete procedure.
  • Use barcode or NFC on parts. Mis-picks show up fast, cutting finger-pointing.
  • Audit 10 % of closed jobs weekly. Quick spot checks keep the metric honest.

If you sit under 70 %, start with better job scopes and full parts kits; many plants gain 10 points inside six months. Once above 85 %, drive smaller steps by tackling the stubborn repeat failures and using expert support tools. A steady 90 %+ FTFR cuts overtime call-outs, lifts schedule compliance, and boosts overall equipment uptime.

7. Labor Utilization

Labor utilization is defined as productive wrench time divided by total paid hours. Include travel, meetings, waiting, and cleanup in the denominator so the figure shows the share of each shift spent with tools on the asset.

Formula = Labor Utilization (%) = (Hands-on time รท Paid hours) ร— 100

How to Measure

  • Random time studies: Observers shadow technicians for short intervals and log activity codes.
  • Digital permits and work-order clocks: Time stamps on travel, waiting, and sign-offs feed utilization dashboards automatically.
  • Self-report cards: Quick end-of-job surveys fill gaps where automation is not in place, though they rely on honesty and clear definitions.

Proven Ways to Lift Utilization

  • Job kitting: Stage parts, consumables, and special tools before the shift; one missing gasket can drain an hour.
  • Pre-shift briefings : Five-minute huddles hand out permits, radio channels, and priorities so crews walk straight to the first job.
  • Point-of-use storage: Small parts bins and tool boards at the asset cut long walks to the main crib.
  • Mobile approvals: Supervisors sign permits or scope changes on a tablet instead of making technicians wait by the phone.
  • Route sequencing: Bundle nearby work orders so technicians repair multiple assets in one pass rather than shuttling across the site.
  • Cross-training: Multi-skilled crews reduce idle pockets that form when single-trade workers wait for their portion of the job.

Sustained gains come from relentless removal of small delays, not heroic sprints. Track utilization weekly, review blockers in the planning meeting, and celebrate every percentage-point riseโ€”the compounding effect over a year is substantial.

8. Inventory Turnover

Annual cost of spare parts and consumables issued from the storeroom divided by the average inventory value held on the shelves for the same period is called inventory turnover. 

Formula: Inventory Turnover = Cost of goods issued in year รท Average inventory investment

How to Measure

  • Pull issue costs from the CMMS or ERP each month. Ensure returns and warranty credits are netted out.
  • Calculate average inventory value with a 12-month rolling window to smooth seasonal buys.
  • Segment by fast-moving vs. slow-moving SKUs; an overall figure can hide pockets of excess.

Ways to Lift Healthy Turnover

  • ABC-XYZ analysis: Rank parts by annual spend (ABC) and demand variability (XYZ). Carry higher safety stock only for A-critical items with unpredictable usage.
  • Min-max planning in LLumin: Set dynamic reorder points that rise for peak-season consumption and fall when demand eases. The engine also blocks replenishment of dormant SKUs, cutting dead stock.
  • Kitting and just-in-time pulls: Build maintenance kits so only needed parts leave the shelf, reducing safety stock paddings added โ€œjust in case.โ€
  • Vendor-managed inventory (VMI): For fasteners and consumables, let suppliers restock bins based on real usage.
  • Obsolescence reviews each quarter: Flag items with zero issues in 24 months; sell, scrap, or transfer to sister plants before they expire.

9. Stockout Frequency

Stockout frequency is the number of times a requested critical part is not in stock when needed.

Formula: Stockout Frequency = Count of Stockout Events per Period

Data Collection Tips

  • Tag each pick as critical vs. non-critical in the CMMS or inventory system.
  • Record stockout events automatically when a pick fails; avoid manual tallying.
  • Log lead times alongside stockouts to spot suppliers causing delays versus planning issues.

Advanced Use

  • Correlate stockouts with MTTR: Each stockout adds minutes or hours to repair timeโ€”quantify cost impact.
  • Segment by supplier: Track which vendors lead in on-time fills versus late deliveries.
  • Overlay with work order backlog age: Parts shortages that coincide with aging backlog point to systemic planning gaps.

A low stockout frequency keeps spares ready, cuts emergency orders, and shrinks overall downtime costs.

10. Downtime Cost Avoided

The difference between what you used to lose in downtime and what youโ€™re losing now, expressed in dollars (or your local currency) is called downtime cost avoided. 

Formula: Downtime Cost Avoided = (Baseline Downtime Hours ร— Cost per Hour) โˆ’ (Current Downtime Hours ร— Cost per Hour)

What It Reveals

TrendInsightFirst Step
Growing cost-avoidedYour reliability actions are paying off in real moneyCheck which asset improvements drove the biggest drop in hours
Flat resultYouโ€™ve stopped getting incremental gainsRe-examine your baseline period and ensure youโ€™re comparing apples to apples
Falling cost-avoidedDowntime is creeping back, eroding prior winsAudit recent failure modes and repair delays for fresh problems

Use your historical downtime cost as the baseline. Aim for a 10 % avoidance in the first 6โ€“12 months, then push for 20 % by year two. Tracking the dollar impact keeps teams focused on improvements that move the financial needle.

Measure Success Post-CMMS Implementation

After go-live, success hinges on three steps: establish a baseline, monitor progress, then course-correct. Begin by capturing three months of pre-CMMS data for each KPI. Use LLuminโ€™s dashboards to compare current MTTR, MTBF, PMP and Schedule Compliance against those starting points.

Display key metrics on a one-page summary that updates automatically. Glance at MTTR trends, spot rising backlog age, and check stockout counts. When a number falls short, dig into the root causeโ€”whether parts shortages, approval delays or planning gaps.

Set a monthly review with maintenance, planning and operations. Highlight one metric that improved and one that needs attention. Agree on a single actionโ€”pre-kitting a spares kit, locking the next weekโ€™s schedule or rolling out mobile approvalsโ€”and record its impact in the next report.

This steady cycle of data capture, review and targeted fixes drives real gains. Within six months youโ€™ll see double-digit cuts in downtime, stronger first-time fix rates and higher plannedโ€work percentages. That proof builds confidence and secures ongoing CMMS support.

About LLumin

LLumin is a CMMS designed to keep teams active and data flowing. It offers role-specific dashboards, flexible workflows, and mobile approvals that match each userโ€™s tasks. Automated alerts and reminder prompts encourage timely updates, while clear performance reports show progress at a glance. This steady feedback loop helps technicians and planners see the impact of their work, driving ongoing engagement and reliable trend insights.

Ready to maximize your CMMS investment? Request a demo and learn how LLumin helps you track and optimize maintenance KPIs!

Conclusion

Tracking maintenance performance with clear KPIs turns data into action. Start by setting your baseline, then watch MTTR, MTBF, PMP and the rest of your core metrics each week. When a trend dips, drill into root causesโ€”whether parts, processes or planningโ€”and run a focused fix. A monthly review brings teams together around one win and one challenge, keeping everyone aligned on the next step.

Those improvements cut emergency calls, smooth production and open conversations about new tools or training. As each KPI moves in the right direction, LLumin proves its value and your maintenance program builds its own momentum. Continuous measurement, targeted fixes and visible wins make ongoing CMMS success inevitable. Book a demo today!

FAQs

What KPIs should you track after CMMS implementation?

Focus on reliability (MTTR, MTBF), workload (Planned Maintenance Percentage, Labor Utilization), cost (Downtime Cost Avoided, Stockout Frequency) and compliance (Schedule Compliance, Work Order Backlog Age, First-Time Fix Rate). Together they show how fast you repair, how often failures occur, how proactive your team is, and whether you stick to your plan.

How do you measure CMMS ROI?

Compare baseline and current downtime costs, subtract CMMS expenses, then divide net savings by the total investment to get your return.

How soon should you start tracking KPIs after go-live?

Begin as soon as the system is liveโ€”ideally on day oneโ€”using three months of pre-go-live data as your benchmark. Early and consistent tracking lets you validate quick wins, spot issues fast, and build momentum within the first month.

Director of Business Development at LLumin CMMS+

Chris Palumbo brings over 13 years of expertise in B2B sales across diverse sectors including Manufacturing, Food and Beverage, Packaging, and Pharmaceuticals. Leveraging 6 years of leadership experience, Chris has successfully guided sales teams within Manufacturing and Distribution to achieve success, particularly in large capital expenditure projects. As Director of Business Development for LLumin, Chris oversees the identification of business opportunities, pushing the development and implementation of a robust business development strategy aimed at accelerating revenue growth. With a proven track record of excellence, Chris has established himself as a respected industry leader and invaluable asset to the LLumin team.

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