--- name: benefits-benchmarking-analyzer description: "Compares a described employee benefits package against market norms for the employer's industry, size, and talent tier, then returns a structured gap-and-opportunity analysis across 8 benefit categories with competitiveness ratings, prioritized recommendations, and a cost-vs-impact matrix. Use when evaluating how a benefits package stacks up against competitors, preparing for an open enrollment redesign, building a case for new benefits, or diagnosing why offers are being declined for compensation-adjacent reasons." argument-hint: "[company-profile] [current-benefits]" allowed-tools: ["Read"] --- # Benefits Benchmarking Analyzer ## Purpose Compare a described benefits package against market norms for the company's industry, size, and talent tier — then return a category-by-category gap analysis with competitiveness ratings and a prioritized set of additions or upgrades. Replaces the slow, survey-stitching process of figuring out where a benefits offering is ahead, at par, or behind the market. ## When to Use Invoke this skill when the user asks to: - Benchmark their benefits package against competitors or market norms - Prepare for an open enrollment redesign or annual benefits review - Build the business case for adding or upgrading a specific benefit - Diagnose why candidates are declining offers for non-base-salary reasons - Identify the highest-impact gaps in their total rewards offering - Justify benefits spend to finance or leadership with market context ## Inputs Required Before starting, collect: - **Company profile**: Industry, headcount, growth stage (e.g., Series B SaaS, ~250 employees, scaling) - **Talent tier**: Who they compete against for talent (FAANG-tier, well-funded startups, regional employers, etc.) - **Geography**: Primary employee locations (US national, specific metros, remote-distributed, international) - **Current benefits**: The package as it stands — health, retirement, leave, equity, perks, anything offered - **Workforce composition**: Rough mix (e.g., mostly early-career engineers, dual-income parents, distributed senior ICs) - **Constraints**: Budget posture, fixed-cost limits, or benefits that are off the table - **Strategic goal**: What they want benefits to do — improve retention, win competitive offers, control cost, support a specific demographic If talent tier or geography is missing, default to the company's stated industry peers at the same headcount band and note the assumption. ## Instructions ### Step 1: Establish the Benchmark Cohort Before analyzing anything, define what "market" means for this employer. - Set the comparison cohort using industry + headcount band + talent tier — not a generic national average - Identify the two relevant benchmarks: **table stakes** (what's required to be considered) and **differentiators** (what wins competitive offers in this cohort) - State the cohort explicitly so every rating that follows is anchored to it (e.g., "Benchmarked against well-funded 100–500 person SaaS companies competing for senior engineering talent in major US metros") ### Step 2: Analyze Each of 8 Benefit Categories For every category below, do four things: (1) summarize what the employer currently offers, (2) state the cohort norm, (3) assign a competitiveness rating, (4) name the specific gap or strength. **Competitiveness rating scale** (use exactly): - **Below Market** — falls short of table stakes; actively costs offers or retention - **At Market** — meets table stakes; neither a draw nor a deterrent - **Above Market** — exceeds the norm; a genuine differentiator in the cohort - **Best in Cohort** — top decile; a recruiting and retention asset worth promoting **Category 1 — Health & Medical Coverage** Plan types offered, employee premium share, deductible/out-of-pocket exposure, dependent coverage cost, and HSA/FSA availability. Cohort norm centers on employer premium contribution % and dependent affordability. **Category 2 — Retirement & Long-Term Savings** 401(k) match structure, vesting schedule, auto-enrollment, and any profit-sharing. Benchmark on effective match value (% of salary) and vesting speed. **Category 3 — Equity & Long-Term Incentives** Grant size relative to level, refresh/evergreen policy, vesting schedule, early-exercise options, and extended post-termination exercise windows. Critical for startup and tech cohorts — often the single largest competitive lever. **Category 4 — Paid Time Off & Leave** Vacation policy (accrued vs. unlimited), sick leave, parental leave (primary and secondary caregiver weeks, pay %), sabbatical, and bereavement. Parental leave is frequently the most-scrutinized item. **Category 5 — Family & Caregiving Support** Fertility/IVF coverage, adoption/surrogacy assistance, childcare stipends or backup care, and dependent care FSA. Increasingly a table-stakes differentiator in competitive tech cohorts. **Category 6 — Mental Health & Wellbeing** EAP, therapy/coaching platforms (Lyra, Spring Health, etc.), wellness stipends, and covered visit counts. Benchmark on access and session caps, not just "we have an EAP." **Category 7 — Professional Development & Growth** Learning stipend, conference budget, tuition reimbursement, internal mobility, and coaching. Especially weighted by early-career and senior IC populations. **Category 8 — Flexibility & Lifestyle Perks** Remote/hybrid policy, home office stipend, flexible hours, commuter benefits, and meaningful perks (vs. perks-as-noise). Rate the policy substance, not the perk count. ### Step 3: Map Gaps Against Workforce Composition Re-read the category ratings through the lens of who actually works there. - Flag any Below Market rating in a category that matters disproportionately to this workforce (e.g., weak parental leave for a dual-income-parent-heavy team is a higher-severity gap than for an early-career team) - Identify "wasted spend" — Above Market or Best in Cohort benefits the current workforce underuses - Surface the one or two gaps most likely to be driving the stated strategic problem ### Step 4: Build the Cost-vs-Impact Matrix Place each recommended change into one of four quadrants: - **Quick Wins** — low cost, high impact (do first) - **Strategic Investments** — high cost, high impact (build the case) - **Fill-Ins** — low cost, low impact (bundle opportunistically) - **Reconsider** — high cost, low impact (likely deprioritize) Assign each recommendation a rough cost posture (Low / Moderate / Significant) relative to per-employee spend, and an impact rationale tied to retention, recruiting, or the stated goal. ### Step 5: Prioritized Recommendations Produce 5–8 recommendations ranked by expected impact on the stated strategic goal. For each: the specific change, where it moves the rating (e.g., "At Market → Above Market"), the rough cost posture, and a one-line rationale. Be opinionated about sequence. ## Output Format - **Structure**: Benchmark cohort statement → 8-category analysis table → workforce-fit gap flags → cost-vs-impact matrix → ranked recommendations - **Length**: 1,000–1,400 words - **Format**: Category analysis as a table (Category | Current Offering | Cohort Norm | Rating | Gap/Strength); recommendations as a ranked numbered list; cost-vs-impact as a labeled four-quadrant breakdown - **Sections**: Benchmark Cohort → Category-by-Category Analysis → Workforce-Fit Gaps → Cost vs. Impact Matrix → Prioritized Recommendations - **Tone**: Total rewards analyst — data-anchored, decisive, and budget-aware; reads like an internal brief leadership can act on, not a vendor pitch ## Quality Checklist Before delivering output, verify: - [ ] All 8 categories are analyzed with all four elements (current offering, cohort norm, rating, gap/strength) - [ ] Every rating uses one of the four defined labels — no improvised ratings - [ ] The benchmark cohort is stated explicitly and every rating is anchored to it (not a generic national average) - [ ] At least one gap is connected directly to the workforce composition and the stated strategic goal - [ ] Every recommendation includes a rating movement, a cost posture, and a one-line rationale - [ ] Recommendations are ranked by impact — not listed by category order ## Notes - The most common diagnostic error is benchmarking against a national average instead of the actual talent-competition cohort — a "generous" package can still be Below Market against FAANG-tier competitors. - Equity and parental leave are disproportionately scrutinized by candidates in tech cohorts; weight them accordingly even when other categories look strong. - When the user's strategic goal is retention vs. recruiting, the same gap can carry different priority — recruiting losses point to offer-stage benefits (equity, sign-on-adjacent perks), retention losses point to lived-experience benefits (leave, flexibility, caregiving). - If current benefits are described vaguely in a category, rate what's stated and flag the ambiguity rather than assuming a generous default. --- ## How to use this skill This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top. **Installing in Claude Code:** - `~/.claude/skills//SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects) - `/.claude/skills//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. 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