Strategy decision reversibility index

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will executive operations chiefs use it to solve "teams apply the same approval burden to reversible and irreversible choices"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree the acceptance criteria, input limits and reviewer responsibilities before starting.
4. Measure, then decide. Track review cycle time and classification corrections. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Costed pilot: Qualitative categories with no invented precision score. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: extract commitments; identify switching costs. Support the third task through an assisted review queue: flag external dependencies. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of decision reversibility register. Authentication, account isolation, deletion controls and basic operational logging are included. Specialized production certification, live write integrations and broader rollout are not included unless explicitly stated.

After the MVP. After paying customers repeatedly accept decision reversibility register, automate draft reversal steps; record executive judgment; export routing rationale. Add one tested read integration, reusable customer configuration and scheduled repeat delivery. Increase supported formats or teams only when evaluation cases and reviewer capacity cover the new scope. Qualitative categories with no invented precision score.

What the build depends on. Stable identifiers, consistent metric definitions, deterministic calculations, source lineage and representative review samples. Poor coverage must remain visible. Obtain representative authorized inputs, an agreed review rubric and a buyer-side owner. Specific scope: Qualitative categories with no invented precision score.

Pricing to test

Test USD 500-2,000 for an initial analysis of one bounded dataset. Offer USD 250-1,000 monthly for repeat reporting at agreed volume. Data cleanup and specialist analysis are separately priced. These are test ranges. For this buyer, package the first sale around classify twenty historical decisions and the defined decision reversibility register. Record actual review effort before offering a recurring allowance. The commercial pilot fee is distinct from the platform development budget.

Message to test

Match decision process to documented reversal costs. Demonstrate the result with classify twenty historical decisions for executive operations chiefs. Use a concrete before-and-after example without promising unmeasured savings.

Where to find buyers

Chief-of-staff communities and executive coaches

Lead magnet

Classify twenty historical decisions

The first 30 days

1. Week 1: interview five prospective buyers from executive operations chiefs and inspect how they handle teams apply the same approval burden to reversible and irreversible choices.
2. Week 2: prepare classify twenty historical decisions using authorized or synthetic material.
3. Week 3: share the demonstration through chief-of-staff communities and executive coaches and seek one bounded paid pilot.
4. Week 4: measure review cycle time and classification corrections, review delivery effort and ask for a repeat purchase. This is a validation schedule, not a promise that the full product can be built in thirty days.

Paid pilot

Agree the acceptance criteria, input limits and reviewer responsibilities before starting. Run classify twenty historical decisions and deliver decision reversibility register. Compare review cycle time and classification corrections with the buyer's current process on comparable cases; include corrections, missed issues and reviewer time. Seek payment and repeat use. Stop or revise the scope if data access, accuracy or unit economics fail.

Success metrics

Review cycle time and classification corrections

Retention and expansion

Build repeat use around decision reversibility register. Save approved configurations and review decisions with permission, revisit unresolved exceptions and show progress on review cycle time and classification corrections. Offer a recurring volume allowance after repeat demand; expand to adjacent tasks only when the buyer asks and delivery quality remains acceptable.

Why clients would pick it

Domain-specific definitions, trusted source mappings and a history connecting findings to actions and observed results. For this concept, accumulate permissioned examples and reviewer corrections around match decision process to documented reversal costs. The durable asset is reliable task-specific execution and trusted customer configuration, not access to a general-purpose AI model.

Alternatives and positioning

Analysts, business intelligence dashboards, spreadsheets and general text summarization tools. Position this concept around match decision process to documented reversal costs. Compare it against the customer's current process on the same representative task. This is proposed differentiation; no exhaustive competitor study or uniqueness claim has been established.

Main delivery costs

Data preparation, reconciliation, classification, expert interpretation, customer-specific definitions and recurring reporting support. Initial validation additionally budgets for executive interviews. Track model usage, storage, reviewer minutes, exception handling and customer support per accepted deliverable.