Sample Diagnostic Report
An illustrative management example showing how Aigenrix separates economic exposure from the expected recoverable range, and connects financial symptoms, likely operating causes, intervention priorities and payback assumptions. All company details, figures and findings below are hypothetical and say nothing about average client results.
Illustrative company profile
- €10M annual revenue
- ~150 employees
- Service / operationally complex business
- Several departments, recurring processes
- CRM, finance and operational data available
Modelled annual economic exposure: €620K
In this modelled scenario, seven hypotheses survive the evidence test and account for €620K in annual economic exposure across four areas. Exposure is not recoverable value, and neither is realized value — see the expected recoverable range below.
Annual economic exposure by category — not recoverable value
Where the illustrative exposure sits
Seven findings make up the €620K figure above. Each is stated with its modelled annual exposure, confidence level and the intervention that would address it.
| Finding | Annual exposure (modelled) | Confidence | Intervention | Estimated cost | Est. payback |
|---|---|---|---|---|---|
| Reception/admin capacity spent on manual scheduling and rebooking | €95K | High | AI-assisted scheduling & intake automation | €18K | 3 months |
| Field/delivery team idle time between jobs due to routing inefficiency | €115K | Medium | Route & capacity planning redesign | €35K | 5 months |
| Underpriced service tier relative to delivery cost | €100K | High | Pricing model redesign | €8K | 1 month |
| Vendor and subcontractor cost overrun on three recurring service lines | €80K | Medium | Vendor renegotiation & workflow standardization | €12K | 2 months |
| Extended receivables cycle with top 10 clients | €140K | Medium | Invoicing & collections process redesign | €15K | 2 months |
| Inbound leads not followed up within 24 hours | €55K | Medium | Lead-response automation & CRM workflow | €14K | 4 months |
| Inconsistent upsell and cross-sell at renewal | €35K | Low | Renewal playbook & CRM prompts | €6K | 3 months |
Candidate mechanisms — and how well the evidence supports them
Operational inefficiency
Supported: scheduling and routing decisions are made ad hoc by individual staff, with no shared capacity model across teams.
Margin
Supported for pricing, still a candidate for vendors: pricing was set at launch and never revisited against delivery cost; vendor contracts appear to renew without cost review, which needs confirming.
Working capital
Supported: no standardized invoicing trigger is tied to project milestones, and collections are handled reactively.
Revenue
Candidate: lead routing depends on manual CRM checks and there is no first-response SLA; CRM completeness must be validated before the revenue effect is relied on.
Now / Next / Later
- →Pricing model redesign
- →Invoicing & collections process redesign
- →AI-assisted scheduling & intake automation
- →Lead-response automation & CRM workflow
- →Route & capacity planning redesign
- →Vendor renegotiation & workflow standardization
- →Renewal playbook & CRM prompts
What it would illustratively cost to fix
Exposure ≠ Recoverable value
The recoverable range is narrower than total exposure because it is confidence-weighted — low- and medium-confidence findings are discounted until validated against real data. The €620K figure is not automatically recovered cash; it is the starting exposure this model is built from.
An illustrative sequence, not a fixed template
Validate & quick wins
Validate findings against real data; implement pricing and invoicing/collections changes — the two lowest-cost, fastest-payback items.
Build the automation
Build and pilot scheduling/intake automation and lead-response workflows for the highest-confidence capacity and revenue findings.
Measure & decide
Measure realized value against the baseline; decide whether the ‘Later' bucket (routing, vendor renegotiation, renewal playbook) is worth pursuing.
How confidence is assigned
- →High confidence findings are based on directly observable data — time logs, pricing tables, invoicing records.
- →Medium confidence findings require additional validation, such as routing data or CRM completeness.
- →Low confidence findings are directional and need a short follow-up analysis before committing budget.
- →Every figure on this page is illustrative and calculated from simplified, hypothetical assumptions — it does not represent any real client engagement, current or past.
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