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Decarbonization lever prioritization matrix builder

Scores and ranks a list of decarbonization initiatives across emissions reduction potential, marginal abatement cost ($/tCO2e), implementation complexity, time to impact, and co-benefits, then outputs a prioritized…

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Purpose

Turn a raw list of decarbonization initiatives into a scored, ranked action matrix using marginal abatement cost curve logic — so sustainability and operations leaders know exactly which levers to pull first, in what order, and why, without defaulting to whichever project has the loudest internal champion.

When to Use

Invoke this skill when the user asks to:

  • Prioritize or rank a list of decarbonization or emissions reduction projects
  • Build a marginal abatement cost curve (MACC) for their operations
  • Decide which sustainability initiatives to fund with a limited capital budget
  • Compare initiatives across cost, impact, and feasibility
  • Build a phased decarbonization roadmap or Scope 1/2/3 action plan
  • Justify a project sequence to a CFO, board, or steering committee

Inputs Required

Before starting, collect:

  • Initiative list: The decarbonization levers under consideration (name + 1-line description each)
  • Emissions baseline: Current annual emissions in tCO2e, ideally split by Scope 1 / 2 / 3
  • Estimated reduction per initiative: tCO2e/year each lever removes (or enough detail to estimate)
  • Cost data per initiative: Capex, opex change, and/or expected savings — whatever is available
  • Budget or capital constraint: Available spend, or "unconstrained" if none
  • Strategic priorities: What matters most — lowest cost, fastest impact, deepest reduction, or specific targets (e.g., SBTi, net-zero year)
  • Operational constraints: Anything that blocks or delays certain levers (leases, contracts, downtime tolerance)

If reduction or cost figures are missing for an initiative, estimate using standard abatement ranges and clearly flag each estimate as an assumption to be validated.

Instructions

Step 1: Normalize and Categorize the Initiatives

  • Restate each initiative with a consistent name and a one-line description.
  • Tag each by emissions scope addressed (Scope 1 / 2 / 3) and category (energy efficiency, electrification, fuel switch, renewable procurement, process change, supply chain, offsets).
  • Flag any initiative that is actually a bundle of sub-projects and split it if the sub-projects have materially different economics.

Step 2: Score Each Initiative Across Five Dimensions

For every initiative, assign a value on each dimension. Use the scales below.

1. Emissions reduction potential (absolute + relative)

  • Report tCO2e/year removed and as a % of the relevant baseline.
  • Band it: High (>5% of baseline), Medium (1–5%), Low (<1%).

2. Cost of abatement — $/tCO2e (the MACC axis)

  • Calculate: (annualized capex + annual opex change − annual savings) ÷ annual tCO2e reduced.
  • Negative $/tCO2e = the lever pays for itself (net savings). Flag these explicitly — they are the "no-regret" moves.
  • Band it: Net-negative (<$0), Low ($0–50), Medium ($50–150), High (>$150).

3. Implementation complexity (1–5, 5 = hardest)

  • Consider capital intensity, technical maturity, cross-functional dependencies, vendor availability, and disruption to operations.

4. Time to impact (months until emissions actually start dropping)

  • Band it: Fast (<6 mo), Medium (6–18 mo), Slow (>18 mo).

5. Co-benefits (1–5, 5 = strongest)

  • Score non-carbon upside: cost resilience, regulatory hedge, brand/customer value, employee safety, energy security, waste reduction. Name the specific co-benefit.

Step 3: Build the Marginal Abatement Cost Curve Logic

  • Sort all initiatives by $/tCO2e ascending (cheapest abatement first).
  • Present as MACC-style ordering: each lever's width = tCO2e reduced, height = $/tCO2e. Describe the curve in a table (a chart can't be rendered, so make the ordering and cumulative totals explicit).
  • Compute a cumulative abatement column: running total of tCO2e as you move up the cost curve, so the user can see how far a given budget gets them.
  • Explicitly separate the curve into: net-negative levers (do these regardless), low-cost levers, and high-cost levers requiring justification.

Step 4: Apply a Weighted Priority Score

When strategic priorities are provided, compute a composite score so ranking reflects more than cost alone:

  • Default weighting (adjust to stated priorities): Abatement cost 35%, reduction potential 30%, time to impact 15%, complexity 10% (inverse), co-benefits 10%.
  • Normalize each dimension to a 0–100 scale before weighting.
  • Produce a final priority rank and note where the weighted rank diverges from the pure MACC rank — that divergence is where strategy overrides economics.

Step 5: Place Initiatives on the Action Matrix

Map every lever into one of four quadrants (impact vs. effort):

  • Quick Wins — high reduction, low complexity/cost → do now.
  • Big Bets — high reduction, high complexity/cost → plan and fund deliberately.
  • Fill-Ins — low reduction, low complexity → do when capacity allows.
  • Reconsider — low reduction, high complexity → defer, redesign, or drop.

Step 6: Sequence into a Phased Roadmap

  • Phase 1 (0–12 mo): Net-negative and quick-win levers — self-funding momentum.
  • Phase 2 (12–36 mo): Low-cost levers and the first big bets that require Phase 1 savings or capital planning.
  • Phase 3 (36 mo+): Deep-decarbonization big bets and residual/harder abatement.
  • Note funding logic: which Phase 1 savings can bankroll Phase 2, and which levers unlock others (dependencies).

Step 7: Constraint Check and Recommendation

  • Test the ranked plan against the stated budget or constraint; show cumulative abatement achievable within budget.
  • Deliver a clear recommendation: the top 3–5 levers to start immediately and one sentence each on why.
  • Flag every estimated input that must be validated before capital commitment.

Output Format

  • Structure: Scoring table → MACC-ordered table with cumulative abatement → weighted priority ranking → 2x2 action matrix → phased roadmap → recommendation
  • Length: 1,000–1,400 words plus tables
  • Format: Tables for scoring and MACC ordering; quadrant list for the matrix; numbered phases for the roadmap; prose for the recommendation
  • Sections: Initiative summary → Five-dimension scoring table → Marginal abatement cost curve → Weighted priority ranking → Action matrix (4 quadrants) → Phased roadmap → Recommendation & assumptions to validate
  • Tone: Analytical operations leader — decisive, numbers-first, no hedging on the final sequence

Quality Checklist

Before delivering output, verify:

  • [ ] Every initiative is scored on all five dimensions (reduction potential, $/tCO2e, complexity, time to impact, co-benefits) — no blanks
  • [ ] The $/tCO2e calculation is shown or explainable for each lever, and net-negative levers are flagged separately
  • [ ] Initiatives are ordered on the MACC by ascending abatement cost with a cumulative tCO2e column
  • [ ] Every initiative is placed in exactly one of the four action-matrix quadrants
  • [ ] The roadmap sequences levers into 3 phases with explicit funding/dependency logic
  • [ ] Every estimated (non-provided) input is flagged as an assumption to validate

Notes

  • Net-negative abatement levers should almost always lead the roadmap — they fund everything downstream and build organizational momentum for the harder bets.
  • Pure MACC ordering optimizes for cost efficiency, not speed or strategy; the weighted score exists precisely to surface where a slightly costlier lever should still go first (e.g., to hit a near-term SBTi milestone).
  • Where Scope 3 dominates the baseline, most internal levers will look small — say so plainly and steer part of the roadmap toward supplier engagement rather than over-optimizing minor Scope 1/2 wins.
  • Offsets should be scored like any other lever but explicitly labeled as residual-emissions handling, not abatement, so they never crowd out real reductions in the ranking.

How to use this skill

This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.

Installing in Claude Code:

  • ~/.claude/skills/<folder-name>/SKILL.md — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
  • <your-project>/.claude/skills/<folder-name>/SKILL.md — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

Using in Claude.ai, ChatGPT, Gemini, or other AI tools:

  1. Drag this file into a new chat, or copy and paste its contents
  2. Send your task or request as your next message — the AI will apply the skill where it fits

For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills