Analyse Work

Purpose

The Analyse Work phase is the intelligence engine of the Work Management Process. It receives data from Phase 5 and feeds insight back into Phases 1–5. Without systematic analysis, the organisation collects data but never converts it to knowledge — work orders accumulate, failure patterns stay hidden, and the same problems repeat.

Scope

Failure analysis, reliability analysis, cost analysis and work management performance
RCM reviews and maintenance strategy adjustment
Predictive analytics and condition monitoring trending
Reporting, dashboards and benchmarking

RCM Foundation

The seven RCM questions cannot be answered without failure data, condition data and maintenance history. Analysis is the bridge between raw data and RCM decision-making. Two improvement loops depend on this phase: the Sustained Maintenance Loop (Plan → Schedule → Execute → Follow-up) and the Continuous Improvement Loop (Work → Analyse → Modify strategy → Work).

Process Steps

01
KPI reporting
Intent
Publish a small set of trusted work-management KPIs at a fixed cadence so leadership discusses the same numbers every week and month.
Inputs
- CMMS transactional data from Phases 1–5
- Standard KPI definitions and formulas
- Prior-period trend
Actions
- Generate weekly KPIs: schedule compliance, break-in rate, PM compliance, backlog weeks, wrench time
- Generate monthly KPIs: reactive %, cost per RAV, reliability index, RCM review completion
- Publish to Maintenance and Operations leadership at a fixed time
- Include the trend line, not just the point value
People
Reliability Engineer / Planning Leader accountable. Maintenance Leader owns the response. Operations Leader receives.
Process
KPI definitions locked and versioned. Publication time fixed. Standard pack template.
Technology
CMMS or BI tool with automated KPI extracts — no manual spreadsheets.
What Good Looks Like
- Every crew member can point to where this step lives in the CMMS — no shadow spreadsheets.
- The opposite of: kPIs redefined every quarter
- The opposite of: kPI pack produced but never discussed
- The opposite of: point values without trend
What Bad Looks Like
- KPIs redefined every quarter — no trend possible
- KPI pack produced but never discussed — 'report theatre'
- Point values without trend — noise dominates signal
Outputs
- Weekly and monthly KPI packs published on schedule
02
Bad actor identification
Intent
Identify the small number of assets consuming a large share of maintenance effort and cost so investigation is focused, not scattered.
Inputs
- Failure history, cost history and downtime data
- Criticality register
Actions
- Pareto assets by cost, by frequency and by downtime — separately
- Take the top 5–10 from each Pareto
- Overlay criticality to prioritise investigation
- Assign named investigators for each bad actor
People
Reliability Engineer accountable. Maintenance Leader assigns investigators. Operations Leader consulted on production impact.
Process
Monthly bad-actor review at a fixed time. Named ownership; no orphan investigations.
Technology
CMMS or BI Pareto reports refreshed monthly. Investigation status tracked against the asset.
What Good Looks Like
- Every crew member can point to where this step lives in the CMMS — no shadow spreadsheets.
- The opposite of: bad-actor list produced but never assigned
- The opposite of: same asset on the list every month
- The opposite of: cost Pareto used alone
What Bad Looks Like
- Bad-actor list produced but never assigned — nothing happens
- Same asset on the list every month — no closure discipline
- Cost Pareto used alone — hidden safety-critical failures missed
Outputs
- Ranked bad-actor list with named owners
03
Failure mode analysis
Intent
For each bad actor, group failures by mode and take an evidence-based decision on how to change the strategy.
Inputs
- Failure history with coded damage, cause and object-part data
- Existing FMEA / RCM record
- Condition-monitoring and inspection data
Actions
- Group failures by failure mode; count and cost each
- Update the FMEA with the observed modes
- Decide per mode: RCM review, redesign, changed frequency, changed technique, run-to-failure
- Document the decision and the evidence behind it
People
Reliability Engineer accountable. Maintenance Leader and Engineering consulted. Operator input for observable modes.
Process
Standard investigation template. Decision categories fixed. Every investigation ends in a single named decision.
Technology
FMEA / RCM database linked to the CMMS asset record. Decision log attached to the asset.
What Good Looks Like
- Every crew member can point to where this step lives in the CMMS — no shadow spreadsheets.
- The opposite of: investigation ends with 'need more data' every time
- The opposite of: decision made but never fed to Planning
- The opposite of: fMEA updated but never revisited
What Bad Looks Like
- Investigation ends with 'need more data' every time — recording gap never closed
- Decision made but never fed to Planning — nothing changes on the floor
- FMEA updated but never revisited — becomes a shelf document
Outputs
- Updated FMEA and per-mode decision log
04
Strategy adjustment
Intent
Push analysis decisions into the live maintenance strategy — PM frequency, technique, spares, criticality — so the next cycle looks different.
Inputs
- Failure-mode decisions from 6.3
- Current PM strategy, Standard Job Plans, criticality register, spares holding
Actions
- Update PM frequencies and techniques in the CMMS
- Revise Standard Job Plans and job packs for changed methods
- Adjust spares holdings up or down against demand and criticality
- Revise criticality where consequence data has shifted
- Communicate changes to Planning, Scheduling and Execution
People
Reliability Engineer accountable. Planner implements. Maintenance Leader approves.
Process
Every strategy change is a controlled change — versioned, dated, communicated. Impact reviewed 6 months later.
Technology
CMMS maintenance-strategy module with version control. Change communication log.
What Good Looks Like
- Every crew member can point to where this step lives in the CMMS — no shadow spreadsheets.
- The opposite of: decisions made but never implemented
- The opposite of: changes made silently
- The opposite of: no 6-month impact review
What Bad Looks Like
- Decisions made but never implemented — same PM runs forever
- Changes made silently — crews run yesterday's Standard Job Plan for months
- No 6-month impact review — no proof the change worked
Outputs
- Live strategy changes visible in the CMMS and on the shop floor
05
Continuous improvement register
Intent
Every analysis produces named actions with owners and due dates — visible, tracked and escalated.
Inputs
- Analysis outputs from 6.2, 6.3, 6.4
- Audit findings, incident actions, KPI trend actions
Actions
- Log every action with owner, due date, expected outcome
- Review monthly with leadership
- Escalate actions overdue > 60 days to the Maintenance Leader
- Close only with evidence of outcome, not just completion
People
Reliability Engineer administers. Named owners accountable per action. Maintenance Leader chairs the review.
Process
Monthly CI review at a fixed time. Standard action template. Escalation rules documented.
Technology
CI register in the CMMS or dedicated tool — not a personal spreadsheet.
What Good Looks Like
- Every crew member can point to where this step lives in the CMMS — no shadow spreadsheets.
- The opposite of: actions logged but never reviewed
- The opposite of: closed on completion, not outcome
- The opposite of: escalations ignored
What Bad Looks Like
- Actions logged but never reviewed — register becomes a graveyard
- Closed on completion, not outcome — same issue returns next quarter
- Escalations ignored — the discipline collapses in a month
Outputs
- Live CI register with status, aging and outcome evidence
06
Benchmarking
Intent
Compare externally once a year to set the north star; act internally every month to move toward it.
Inputs
- Internal KPI history
- Industry benchmark datasets
- Peer-plant data where available
Actions
- Benchmark annually: wrench time, PM compliance, reactive %, cost as % of RAV, reliability index
- Identify the top three gaps to industry median or top quartile
- Set next-year targets from the gap — not last year plus 5%
- Communicate the targets and the reasoning across the organisation
People
Reliability Engineer accountable. Maintenance Leader owns the target commitment. Operations Leader endorses.
Process
Annual benchmark at a fixed time in the planning cycle. Same dataset year-on-year for comparability.
Technology
Industry benchmark subscription or peer network. Internal BI tool for the comparison.
What Good Looks Like
- Every crew member can point to where this step lives in the CMMS — no shadow spreadsheets.
- The opposite of: benchmark done but targets set from last year anyway
- The opposite of: different dataset each year
- The opposite of: targets set at the top and never communicated
What Bad Looks Like
- Benchmark done but targets set from last year anyway — the exercise is theatre
- Different dataset each year — no comparability
- Targets set at the top and never communicated — the floor never knows what it is chasing
Outputs
- Annual benchmark report with gap analysis and next-year targets

Key Performance Indicators

KPI	Why It Matters	How To Measure	World Class	Benchmark	Typical
Bad actors reviewed monthly	The Pareto principle rules maintenance — the top 10 assets consume most of the cost and downtime, so if they aren't reviewed monthly, improvement stalls.	Standing monthly meeting: pull top 10 assets by 12-month rolling cost and by work-order frequency, minute the actions, track to closure.	Top 10 reviewed and 80% with an active action	Top 10 by cost and by frequency	Reviewed ad-hoc or never
RCM reviews completed on plan	RCM only pays back if the review cadence holds — reviews slipping is the first sign the improvement loop has broken.	RCM reviews completed on their scheduled month ÷ RCM reviews planned for the period from the master strategy calendar.	≥ 95%	≥ 90%	20–40%
Continuous improvement actions closed within 60 days	Actions that age past 60 days rarely close — the improvement register becomes a graveyard and the analysis loop loses credibility.	Actions with closed_date − raised_date ≤ 60 days ÷ total actions raised in the period.	≥ 90%	≥ 80%	30–50%
Reactive work trend	The direction of the reactive line is more important than the absolute number — a declining trend proves the whole process is working.	12-month rolling reactive-work % (breakdown WO hours ÷ total WO hours) plotted month-on-month.	Reactive < 15% and still trending down	Declining year-on-year	Flat or rising
Maintenance cost / Replacement Asset Value	Maintenance cost normalised to Replacement Asset Value is the industry benchmark that survives currency, size and complexity differences.	Total maintenance spend (labour + materials + contractors) for 12 months ÷ current Replacement Asset Value of the site.	< 2%	< 2.5%	3.5–6%
Reliability Index	The Reliability Index rolls compliance, schedule, wrench time and cost into one composite — a single trend line the whole leadership team can react to.	Composite scoring model per site standard (typically weighted average of PM compliance, schedule compliance, wrench time and cost/RAV).	> 70	> 50	20–35

Best Practices

Analysis is a discipline, not a report — weekly cadence, standard agenda, named actions
Every bad actor investigation produces a single decision: continue, modify, or eliminate
Data quality issues raised in analysis feed straight back into Phase 5 recording standards
Dashboards for leadership are lagging KPIs; team-level dashboards are leading KPIs
Benchmark once a year, act monthly — external comparison sets the north star