10-Day Throughput Reliability Assessment
Start with one line. Ten business days. One decision-ready report.
Who this is for
You run a plant, a group of plants, or an operations function. You have MES data. Your OEE numbers aren’t terrible — but you suspect they’re hiding something. Schedule fragility, chronic overtime, CI projects that don’t hold, the same problems cycling through the same Pareto chart quarter after quarter.
You don’t need another dashboard. You need someone to tell you which line is actually reliable, which one is quietly deteriorating, and where to put your first dollar for maximum return.
What we need from you
- MES/OEE export (90 days, shift-level or hourly)
- Downtime log with reason codes
- Production schedule
- Product/SKU history by line
- Changeover history
- Target rates by product
- Maintenance events (if available)
No new sensors. No new software installation. No disruption to operations.
The 10-day process
A 30-minute fit call to understand your lines, your data, and your situation. Then you send the data. We deliver the report. That’s it.
What you get
Which lines are dependable, which are unstable, which are improving, which are deteriorating. Reliability-weighted, direction-aware operating states — not just averages.
Where variance actually lives — within-shift (equipment/material), between-crew (training/standard work), or schedule-induced (changeover/product mix). This ends the blame argument with data.
The dollar cost of throughput instability: lost throughput, excess labor, service risk, emergency maintenance, quality events, safety stock, and expediting. Connected to the P&L, not just percentages.
Interventions ranked by economic return, not severity. Each identifies the driver, estimated cost to fix, and projected annual recovery. Your first CI dollar goes where the return is highest.
Week-by-week progression showing where reliability improved, where it declined, and when events occurred that the OEE average concealed.
What this looks like in practice
In a recent four-line assessment, the analysis revealed two lines with nearly identical OEE (~31%) that were 27% apart in reliability. A line in crisis (output essentially random noise) that appeared “about the same as usual” in standard reporting. $1.4M in annualized exposure that no existing report surfaced. And a single highest-return intervention that OEE-based prioritization would have missed entirely.
Investment
Throughput Reliability Assessment
TRI baselines, variance decomposition, EVAR by line, and a prioritized intervention plan with dollar figures attached.
Full Deployment
- TRI live on your lines
- Incident-to-action system with named owners
- Recurrence tracking at 30/60/90 days
- 90-day capability roadmap
- Team training for independent operation
Ongoing Partnership
- Monthly trending and recurrence monitoring
- Quarterly operating review with executive summary
- Kaizen pipeline management
- Remote support for incident analysis
If the assessment doesn’t surface at least one decision your current reporting missed, you pay nothing.
From bad OEE to governed recovery
A plant does not deploy formulas. It deploys routines.
Stabilize the truth
Validate rates, planned downtime rules, reason codes, and data quality. You can’t diagnose a plant you can’t measure.
Establish the TRI baseline
Classify lines by reliability, momentum, variance, and economic exposure. Now you know what you have.
Attack the right constraint
Choose TPM, SMED, standard work, schedule changes, material review, or process fixes — based on the actual instability pattern.
Prove the fix held
Track recurrence at 30/60/90 days. Document before/after behavior. If the fix didn’t hold, you know it before the P&L does.
Questions
What MES platforms do you work with?
Any system that can export shift-level OEE or production data. I’ve worked directly with Traksys, Ignition, and Vorne, but the assessment only requires an export — CSV, Excel, or database extract.
Do we need to install anything?
No. No sensors. No software. No agents running on your network. You send a data export. I send back the analysis.
What if our data quality is poor?
That’s diagnostic information too. The data trust audit is part of the deliverable — it shows where reason codes are unreliable, where planned/unplanned classifications are inconsistent, and what that means for any analysis built on top of them. You can’t fix what you don’t see.
How is this different from our existing OEE reports?
OEE reports tell you what happened. The assessment tells you whether you can trust what happened, whether it’s getting better or worse, where the variance lives (and who owns it), and what the instability costs in dollars. Your OEE report says “72%.” The assessment says “72% average with $380K in hidden exposure driven by crew-level variance on second shift.”
What industries do you serve?
Food processing, baked goods, confectionery, protein, powder blending, meal kit, and consumer packaged goods. If your plant has production lines, an MES, and OEE data, the framework applies.
What happens after the assessment?
If the assessment identifies a credible recovery opportunity, we can move to full deployment ($10K–$20K over 4–8 weeks) and then ongoing partnership ($2K–$4K/month). If it doesn’t identify a credible opportunity, we don’t move forward. The assessment is designed to be valuable on its own.
Send one line. Get the truth.
If you have one underperforming line and at least four weeks of MES/OEE data, start there. The first call is 30 minutes. No sales deck.
Book a 30-Minute Fit Call →Throughput Reliability Index is proprietary methodology of Crusoe Advisory LLC.