EMY inspects an organisation's operating and financial data, diagnoses where value is leaking against sector benchmarks, suggests ranked interventions, and stays in the loop through implementation.
Each stage feeds the next, and the loop restarts every reporting cycle so the diagnosis never goes stale.
EMY ingests financials, operational logs, and sector data through the same pipeline that feeds ATLAS's public indicators.
Every metric is benchmarked against sector medians so underperformance is visible immediately, not buried in a spreadsheet.
Interventions are scored on expected impact versus implementation effort, so the highest-leverage move is always first.
EMY watches the exact metric that triggered the diagnosis, so you know within weeks whether the fix worked.
WORKING CAPITAL CYCLE
GROSS MARGIN
CUSTOMER CONCENTRATION
| Rank | Intervention | Expected impact | Effort | Status |
|---|---|---|---|---|
| 1 | Renegotiate top-3 customer contracts to reduce concentration risk | High | Medium | In progress |
| 2 | Shorten receivables cycle via early-payment incentive | High | Low | Suggested |
| 3 | Re-price bottom-quartile SKUs against sector benchmark | Medium | Low | Suggested |
| 4 | Consolidate supplier base to unlock volume pricing | Medium | High | Backlog |
Because EMY sits on the same PostgreSQL warehouse as the public ATLAS indicators, your organisation's diagnosis is always compared against real, current sector medians — not a static template.
Same sourcing and validation as the public ATLAS dataset.
EMY ships the diagnostic view — you bring the data feed.
Comparisons adjust automatically to your domain sector.
Every suggestion is tied to a metric that proves it worked.