Stakeholder Analysis & RACI

Purpose

Maps stakeholders on a power/interest matrix and assigns responsibilities with RACI.

Anchored in research

• BABOK — stakeholder analysis
• 45ck — raci-matrix / power-interest-grid

Method

1. List every stakeholder or stakeholder group touched by the initiative — BABOK's categories are a useful checklist: sponsor, domain SME, end user, operational support, supplier, regulator. Don't stop at the obvious names already in the room.
2. Score each stakeholder on power (ability to affect the outcome) and interest (how much the outcome affects them), and place them on the resulting 2×2 grid (Mendelow's power/interest matrix): manage closely (high power/high interest), keep satisfied (high power/low interest), keep informed (low power/high interest), monitor (low power/low interest). The quadrant — not a general impression — determines how much engagement effort each stakeholder gets.
3. For each in-scope activity or deliverable, assign RACI roles — exactly one Accountable per item (never zero, never more than one), any number of Responsible, Consulted, and Informed. A RACI with two Accountables, or an item with none, is a design flaw to fix before publishing, not a detail to gloss over.
4. Cross-check the RACI against the power/interest grid: a "manage closely" stakeholder who isn't Accountable or Consulted for anything is a signal that something's missing.
5. Flag any stakeholder position that's inferred rather than confirmed ([assumption — verify]) — stakeholder maps built on the analyst's guess about who actually holds power are a common source of failed buy-in.
6. Revisit the map at key milestones — power and interest shift as a project moves from planning to delivery, and a map validated once at kickoff goes stale.

What this skill does NOT do

• Doesn't make the final decision for you — it produces a structured draft to support a human decision.
• Doesn't confirm figures, market data, or competitor data from memory — it uses the inputs you provide, or marks an assumption clearly ([assumption — verify]).
• Doesn't identify an organization's stakeholders for you without you naming the real actors involved.

Refinement notes

Areas to keep deepening with real practice:

• your own rules of thumb and heuristics for this technique
• concrete templates (into ../../references/)
• reference cases / your own examples
• what this skill deliberately does not do (guardrails, common mistakes) — add to the list above

This is an internal working note, not a claim about the skill's current usability. Track depth privately via the maturity field in skills_index.json (see ../../../meta/maturity_levels.md). Don't add new fields to the frontmatter — name and description are the only ones allowed (see ../../../meta/frontmatter_schema.md).

Continue from here

• Next in this pack: ../assumption-and-evidence-audit/SKILL.md — Tests assumptions and identifies evidence gaps before a recommendation is locked in.
• For a public-sector, municipal, or non-profit client: extend this method with ../../../specialisation-packs/public-sector-ai-service-design/skills/ps-stakeholder-and-political-landscape-mapping/SKILL.md — public-sector stakeholders split across distinct actor types (elected officials, civil servants, unions, oversight bodies) with different veto points that a generic power/interest grid doesn't distinguish on its own.
• A ready-made skill chain for this situation: see ../../../playbooks/
• This pack's shared guardrails: ../../CLAUDE.md

References

• ../../references/ — the pack's shared background material
• ../../CLAUDE.md — the pack's shared guardrails