You already have free benchmarking.
So why pay us?
Free tools already tell you where you rank. They cannot tell you why you stay there. Here is the honest comparison.
Free NHS benchmarking tools are good at what they were built for: tracking the operational metrics a trust already watches turnover, sickness, agency spend, fill rates, against peers. If your question is "where do we rank on the numbers we already monitor?", use them. They are free, and they work.
Our diagnostic answers the question those tools raise but cannot answer: which structural pressure is your position actually concentrated in, and is it a bad year or a standing condition? On our own panel a fragility flag persists rather than passes, rank persistence 0.72 across 429 observations. We do not claim to explain why any individual trust got there: the tests of a causal sequence between the mechanisms failed, and we publish that. Operational dashboards measure symptoms in silos. The structural conditions that produce those symptoms are only visible when five public NHS data sources are read together, against a named taxonomy, with pre-specified statistical gates.
| Capability | Model Health System | NHS Benchmarking Network | Internal dashboards | TLP Structural Review |
|---|---|---|---|---|
| Operational metric benchmarking (turnover, sickness, agency, productivity) | Yes | Yes (member programme) | Yes (own data) | Not the focus |
| Cross-silo structural constructs (Departure Lag, Pressure Displacement, Normalised Fragility) | No | No | No (each metric in its own silo) | Yes (core product) |
| Published record of what failed, including our own retracted findings | No | No | No | Yes (79 tests, 50 failures, all on the record) |
| Financial exposure range from the trust's own audited accounts | No | No | Rarely | Yes, board-paper ready |
| Pre-specified methodology with published failures | No | No | No | Yes (claims retracted and documented) |
| Testable hypothesis your analysts can validate in 30 days | No | No | n/a | Yes, in every report |
| Requires your internal data / IG gating | NHS access | Membership + data submission | Internal only | No (public data only) |
| Cost | Free | Membership fee | Analyst time | Scoped per engagement, quote on request |
What about your own analysts? A large trust's analytics team could, in principle, rebuild our public-data panel. Your analysts are allies in this work, not competitors: every report hands them a testable hypothesis to validate. What an internal build cannot supply is the 203-trust peer context and an external, pre-committed methodology, which is what makes findings usable in front of a board.
Use the free tools. Then, when they show you a number that won't move and can't tell you why, that is our conversation.
The same trust, through both lenses
"Your agency spend is above the peer average."
A ranking. You already suspected it, and it does not tell you what to change.
"In the years your agency spend fell, permanent-staff sickness absence rose, and your Departure Lag gap sits in the most exposed quarter of your peer group. The pressure appears to have moved, not disappeared."
A structural reading: which mechanism is active, and where it is concentrated.
The board leaves with a specific, testable hypothesis: examine the units where the displaced pressure landed, before setting the next cost-improvement target.
A decision, not a dashboard.
Illustrative example, not a client case study. The diagnostics named are validated structural diagnostics of the periods analysed, not forecasts.