# Value Realization > Closes the loop that every other financial-case skill in this pack opens — checks realized results against the original business case, full-potential diagnostic, or synergy case line by line, and attributes the gap to assumption error, execution, or external shock. Use whenever the user wants a post-implementation review, wants to check if an initiative or deal actually delivered its promised val… - **Type:** Skill - **Install:** `agentstack add skill-natan-mohart-24-strategy-skills-for-claude-value-realization` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [Natan-Mohart](https://agentstack.voostack.com/s/natan-mohart) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Natan-Mohart](https://github.com/Natan-Mohart) - **Source:** https://github.com/Natan-Mohart/24-strategy-skills-for-claude/tree/main/skills/value-realization ## Install ```sh agentstack add skill-natan-mohart-24-strategy-skills-for-claude-value-realization ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Value Realization ## When to use Use 6-18 months after a business case, full-potential diagnostic, or synergy case was approved, to check whether it actually delivered. Every skill in this pack that produces a projection (business-case-builder, full-potential-diagnostic, synergy-case-builder) has no accountability loop without this step — a business case with no eventual value-realization check tends to get more optimistic over time, since no one ever pays for being wrong. ## What it does Compares the original projection's driver-level numbers against actuals at the same granularity, attributes material variances to a specific cause (assumption error, execution gap, or external shock), and states plainly whether the initiative is on track but delayed, or genuinely off track — then feeds the finding back into how future cases in this organization get built. ## Method 1. **Pull the original projection at driver level**, not just the headline number — the same granularity business-case-builder, full-potential-diagnostic, or synergy-case-builder produced. 2. **Gather actuals at the same driver-level granularity and time periods**, so the comparison is apples to apples. 3. **Compute variance per driver, not just the bottom line** — offsetting errors can make a headline number look fine while hiding that every underlying driver missed in a different direction. 4. **Attribute each material variance to one cause**: assumption error (the input was wrong from the start — check against any assumption-audit that exists), execution gap (the assumption was reasonable, delivery fell short), or external shock (outside anyone's reasonable forecast). 5. **State the verdict plainly**: on track but behind schedule (needs a revised timeline, not a new decision), or genuinely off track (needs a real decision about continuing, adjusting, or stopping). 6. **Feed the recurring cause back into practice.** If assumption error keeps showing up across past reviews, that's a signal the assumption-audit step is being skipped or done too lightly upstream — name it as a process fix. ## Inputs - The original projection (business case, full-potential diagnostic, or synergy case) at driver-level detail - Actual results at the same granularity and time periods - Any assumption-audit findings from the original case, if available ## Output format Driver-by-driver projected-vs-actual comparison with variance; cause attribution per material variance; an explicit on-track-but-delayed vs. off-track verdict; one process-level learning fed back into future case-building. ## Example An initiative projected at $3M NPV within 18 months is reviewed at month 12: revenue tracks 15% below plan (an overly optimistic conversion-rate assumption, an assumption error) while costs run 10% under plan (an execution win). The blended NPV still looks roughly on track, but the review flags the revenue-driver miss as the real signal worth revisiting, rather than declaring the case validated because the bottom line happens to still look fine. ## Common pitfalls - Checking only the bottom-line number, missing that offsetting driver errors can accidentally produce a healthy-looking total. - Treating every miss as an execution failure without checking whether the original assumption was ever realistic. - Skipping the review once a case has served its purpose of getting funding approved, breaking the accountability loop for every future case. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [Natan-Mohart](https://github.com/Natan-Mohart) - **Source:** [Natan-Mohart/24-strategy-skills-for-claude](https://github.com/Natan-Mohart/24-strategy-skills-for-claude) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-natan-mohart-24-strategy-skills-for-claude-value-realization - Seller: https://agentstack.voostack.com/s/natan-mohart - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.