Editable operational inputs
Weekly events, noise percentage, handling time, FTE cost, productive hours and reduction target.
7completed capabilities
4next improvements defined
3future roadmap items
v1.0current public release
Completed
7Capacity and cost model
Annual noisy events, hours consumed, equivalent FTE capacity and cost exposure.
Improvement opportunity model
Recoverable hours and value based on a realistic, user-selected noise-reduction target.
Exposure score
Transparent planning score combining noise rate, handling burden and equivalent capacity.
Leadership recommendations
Dynamic next actions based on the assumptions and result generated.
Scenario presets
Demonstration, smaller-operation and large-enterprise starting scenarios.
Printable executive output
Browser print support for saving an assessment as a PDF or sharing it in a review.
Next release
4Multi-team comparison
Compare event burden across services, platforms or resolver groups.
Currency selection
Support USD, GBP, EUR, AED and INR while preserving transparent assumptions.
Intervention comparison
Compare elimination, correlation, enrichment and automation scenarios.
Exportable assessment summary
Generate a concise executive brief with assumptions, result and recommended actions.
Future roadmap
3CSV data import
Allow anonymised event extracts to populate service-level volumes and handling patterns.
AI-assisted event clustering
Explore governed grouping of recurring event descriptions to identify rationalisation candidates.
Benefits tracking
Record baseline, intervention and post-change outcomes to demonstrate realised—not theoretical—value.
Current release definition
Version 1.0 is a working planning assessment intended for an initial executive conversation. It does not claim to replace service-level engineering analysis or automatically prove financial savings.
- Results are generated from user-entered assumptions.
- Default values are demonstration data, not a claim about a specific employer or service.
- Any investment case should be validated against event-platform exports, ticket data, workforce assumptions and actual cost structures.