Bad Actors Analysis

Top 10 bad actors in minutes. Not weeks of pivot tables.

Plug into SAP PM, Maximo, Infor EAM, Oracle eAM or any CMMS. The agent ranks your worst-performing assets by downtime, cost, frequency, and criticality — so you stop firefighting and start fixing the real problems.

cost-of-failure · Q1 2026
Top 10 — cost impact

€882k across 10 assets

● 8 min run
412 assets analysed · 12 months · SAP PM
#1P-101A
€240k
#2C-202
€198k
#3V-300
€124k
#4HX-04
€88k
#5P-205
€62k
#6M-12
€54k
#7B-08
€42k
#8P-103
€31k
#9F-22
€24k
#10CV-15
€19k
Combined: top 10 = €882k · 686 h downtime — 61% of site maintenance burden.
The Pain Today

Your CMMS data is gold. It's just locked in pivot tables.

01

Three weeks per round.

Pulling 12 months of work orders, normalising failure codes, joining cost data, building pivots — by the time the list is ready, three new bad actors emerged.

02

One CMMS at a time.

Multi-site groups run SAP PM here, Maximo there, Infor in another plant. Each export has its own format. Combining them = manual nightmare.

03

Surface KPIs, no diagnosis.

You get a ranking but no "why". Engineers still spend a week investigating each top asset before any action lands.

Reliability Dashboard

The whole site. At one glance.

Not just a Top 10. The agent ships you a full reliability dashboard — KPIs, failure-mode breakdown, trend lines, recommended deep-dives. All from your CMMS, refreshed on demand.

PLANT NORTH · 412 assets · 12 months · SAP PM
12M YTD Q1
Bad-actor cost
€1.4M
▲ +18% vs prior 12M
Total downtime
1,124 h
▲ +9%
Top 10 share
61%
of total burden
Run time
8 min
vs 3-4 wks manual
Top 10 — cost impact

Where the money goes

Critical High Watch
P-101A
€240k
C-202
€198k
V-300
€124k
HX-04
€88k
P-205
€62k
M-12
€54k
B-08
€42k
P-103
€31k
F-22
€24k
CV-15
€19k
Failure mode split

By category

412
assets
Mechanical 48%
Process 22%
Electrical 18%
Operations 12%
Connected sources
SAP PM Maximo Infor EAM Oracle eAM Custom DB CSV / Excel
MTBF trend · top 3

Are they getting worse, or stabilising?

last 12 months
P-101A ▲ +40%
MTBF: 980h → 580h
C-202 ▲ +28%
MTBF: 1240h → 890h
V-300 → stable
MTBF: 1420h ≈ 1380h
R/
AI summary
4 assets ready for full RCA · 3 PM intervals to revisit · 2 alarms recommended.
See it on your data
The AI ranks. Your engineers validate. Top 10 reviewed in 1 hour, not 3 weeks. Your data stays in your environment — nothing trains a public model.
How our AI agent handles it

Connect → rank → act.

STEP 01

Connect to CMMS

SAP PM, Maximo, Infor EAM, Oracle eAM, custom DB.

STEP 02

Pull failure history

12-36 months of WOs, costs, downtime.

STEP 03

Normalise codes

ISO 14224 mapping · NLP fills missing fields.

STEP 04

Rank by impact

Cost × downtime × frequency × criticality.

STEP 05

Generate report

Top 10 PDF + Excel + KB entry · ready for next QBR.

What You Get

More than a list. A diagnosis.

Side by side

Manual way vs. Rob Reliability AI.

Manual way

  • Time to Top 103–4 weeks
  • CMMS coverageOne system at a time
  • Refresh cadenceAnnual at best
  • DepthSurface KPIs
  • FormatExcel pivot, hard to share

With Rob Reliability

  • Time to Top 108 minutes
  • CMMS coverageSAP, Maximo, Infor, custom
  • Refresh cadenceOn demand · monthly
  • DepthDiagnosis + RCA candidates
  • FormatPDF + Excel + KB ready
Rob — Founder, Senior Reliability Engineer
Built by a 20+ year reliability expert

Built bad-actor lists by hand. Now we automate it.

Rob has built bad-actor lists on 50+ sites — across LNG, power, mining, pharma. The agent automates exactly that workflow, and adds the diagnosis layer that used to take another two weeks of investigation.

Ready to see your
real Top 10?

30-minute discovery call. Bring an export from your CMMS — we'll show you what the agent would surface, on your data. No pitch. No obligation.

Book your call

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