Supply chain performance review · for supply chain and operations consultants
From raw shipment data to a clear operational story.
The ledger has ten thousand rows and the client wants to know where the money leaks. Nexlyr AI pivots the data in code, benchmarks every lane and site against the average and builds the readout while you work the recommendations.
What you hand it
What Nexlyr AI does with it
It digests the whole ledger
Dense operational data is summarised exactly in code, so a file with thousands of rows is computed, not sampled.
It benchmarks by default
Spend per unit by route, site or supplier is indexed against the average, concentrations are measured and outliers surfaced, the comparisons an analyst would run first.
It compares periods when you give it both
Hand it this year and last year and the movement is computed exactly, by whatever dimensions the data carries.
It frames the story for the room
The findings are structured with recognised operational frameworks where they fit, and every figure on every slide traces back to the ledger.
What comes back
Cost breakdown by lane, site or supplier
Unit economics indexed against the average
The outliers worth investigating
A clear direction grounded in the computed figures
Every deck arrives as a real, fully editable PowerPoint with each figure traced to your source. See everything Nexlyr AI does.
Built for this work
Real computation
Pivots, concentrations and unit costs calculated on the actual rows.
Benchmark charts
Native editable charts that show who is above and below the line.
Recognised lenses
Operational frameworks applied where the material supports them.
A second opinion
Think further challenges the read and runs what-ifs on the figures.
Questions, answered.
Can it really handle a dense ledger?+
Yes. Large tabular files are pivoted and summarised exactly in code before the analysis, so the figures come from every row, not a sample.
Does it benchmark sites against each other?+
Yes, by default. Spend per record by group is indexed to the average so the expensive lanes and sites stand out immediately, computed from your data.
I run several client engagements. Do they stay separate?+
Each client lives in its own workspace. What Nexlyr AI learns from one engagement never crosses into another.
What if the data is messy?+
Header rows are detected even on awkward exports, identifier columns are never summed as if they were money and anything the data cannot support is left out rather than invented.
You set the direction. It carries the analysis.
Start free and bring Nexlyr AI alongside you on the next piece of work.