# Compensation Modeling Engine

*/Opportunities/Compensation_Modeling_Engine*

## Opportunity Overview

**Wedge**: The beachhead is automating equity refresher grant modeling for pre-IPO technology companies. These companies face acute pain calculating dilution scenarios quarterly, allowing for fast proof of value with a motivated CFO or Head of Total Rewards. Once the system holds the cap table and HRIS integration, it expands into modeling annual cash bonuses and base salary band adjustments.
**Timing**: Language models map unstructured offer letter data and disparate HRIS field schemas into a standardized compensation ontology. Recent pay transparency laws across multiple US states force companies to formally codify and justify their compensation bands dynamically.
**Why This I C P**: Mid-market technology companies with 500 to 2,000 employees grant complex equity packages but lack the dedicated quantitative compensation teams found at large enterprises. They feel the pain of spreadsheet errors most acutely when scaling hiring across multiple geographies and rely on external consultants to fix broken models.
**Size Of Prize**: Approximately 45,000 mid-market and enterprise technology companies globally require active equity and variable compensation planning. At an average annual spend of $15,000 for compensation management tooling and external analyst labor, this yields a total addressable prize of $675M.
**Gap Narrative**: People Ops teams and compensation analysts build bespoke spreadsheet models to calculate equity refreshers, commission caps, and band adjustments. These static models break when ingesting live market data or reconciling edge cases like mid-year promotions. A compensation modeling engine connects HRIS, cap table, and market data sources to run live scenario analyses and calculate compensation bands.
**Defensibility**: The engine builds workflow lock-in by becoming the single system connecting HRIS, payroll, and the cap table. Companies configure custom approval routing and edge-case compensation rules into the system, creating high switching costs to rebuild these logic trees elsewhere. Aggregated, anonymized offer acceptance data across the customer base creates a proprietary real-time market benchmark that competitors cannot replicate.
**Why This Thesis**: A software approach allows People Ops leaders to own the workflow and retain control over sensitive payroll data. It structures the data ingestion while providing the deterministic, rules-based outputs required for legal compliance and payroll execution.

## Opportunity Linked Thesis

**Thesis**: [Software](/Theses/Software)

## Opportunity Linked I C P

**Icp**: [Human Resources Consultancy](/CompanyTypes/Human_Resources_Consultancy)

## Opportunity Market Sizing

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**S A M**: ~25k-30k specialized compensation and HR consultancies in North America and Europe × ~$10k-15k/yr ≈ ~$250M-450M
**S O M**: ~$15M-35M achievable within 3 years targeting mid-tier independent US consultancies
**T A M**: ~150k global HR consultancies and enterprise total rewards teams × ~$10k-15k/yr ≈ ~$1.5B-2.2B
**Growth Rate**: ~14-18%/yr, driven by expanding pay transparency mandates and dynamic remote geographic pay bands
**Paid Comparable Spend**: ~$30k-60k/yr spent on proprietary compensation survey datasets, generic spreadsheet macros, and junior analyst manual modeling labor

## Opportunity Incumbents

- [Workday Compensation](/Products/Workday_Compensation) — Tool
- [Pave Compensation](/Products/Pave_Compensation) — Tool
- [Microsoft Excel](/Products/Microsoft_Excel) — Spreadsheet
- [Google Sheets](/Products/Google_Sheets) — Spreadsheet
- [Aon Radford Consulting](/Products/Aon_Radford_Consulting) — Service
- [ChartHop Planning](/Products/ChartHop_Planning) — Tool
- [Compensia Advisory](/Products/Compensia_Advisory) — Service

## Opportunity Win Conditions

**Kill Thresholds**:
- Time to first mapped dataset exceeds 7 days for more than 40% of new accounts
- Less than 20% of users run multiple compensation scenarios within their first 30 days
- In-app presentation vs Excel export ratio falls below 1:3 indicating failure to replace the core workflow
- Customer Acquisition Cost exceeds $4,000 after 90 days of outbound testing
**Leading Metrics**:
- Time to first successfully mapped client dataset
- Percentage of internal roles automatically matched to geographic pay bands
- Number of compensation scenarios modeled per active analyst per week
- Export rate measuring frequency of users exporting back to Excel versus presenting in-app
- Survey data schema ingestion error rate
**What Proves Right**: Target customers migrate at least 50% of their client compensation models from Excel into the Compensation Modeling Engine within the first 60 days of deployment. Cohorts signing annual contracts at $12,000 maintain an active weekly usage rate above 70% across their analyst teams. Consultancies reduce time spent mapping internal roles to external survey data by at least 40%, validating the core efficiency hypothesis.
**What Proves Wrong**: Compensation analysts abandon the tool after initial setup and revert to legacy Excel macros for complex, client-specific bonus calculations. Trial users fail to upload or map proprietary salary survey datasets due to rigid schema requirements, causing onboarding times to exceed 14 days. The perceived value fails to justify the $10,000 price point because consultancies easily pass the cost of junior analyst labor directly to their clients.

## Opportunity Build Profile

**Hardest Part**: Building a deterministic rules engine capable of instantly recalculating thousands of interdependent compensation variables, such as prorated equity vesting and mid-cycle promotions, without performance degradation or calculation errors.
**Min Viable Scope**: Deliver a platform that models base salary and standard RSU equity refreshes for full-time corporate employees to run quarterly merit cycles. Explicitly leave out hourly wage tracking, variable commission plans, and multi-country tax compliance in the first release.
**Cold Start Problem**: External compensation benchmarks require a massive aggregated dataset to offer reliable insights. Overcome this by initially selling internal pay parity and budget projection tools that rely entirely on the customer's own HRIS and cap table data.
**Time To First Value**: 1-2 hours gated by the initial HRIS and cap table API data syncs
**Data Moat Available**: true
**Technical Difficulty**: Moderate

## Neighborhood

### Where the gap lives

- [Offer Acceptance Rate](/Metrics/Offer_Acceptance_Rate) — latent gap · Metrics

### Incumbent in

- [Aon Radford](/Products/Aon_Radford) — incumbent in · Products
- [Microsoft Excel](/Software/Microsoft_Excel) — incumbent in · Software
- [Workday Compensation](/Products/Workday_Compensation) — incumbent in · Products
- [Google Sheets](/Software/Google_Sheets) — incumbent in · Software
- [ChartHop Planning](/Products/ChartHop_Planning) — incumbent in · Products
- [Compensia Advisory](/Products/Compensia_Advisory) — incumbent in · Products
- [Pave Compensation](/Products/Pave_Compensation) — incumbent in · Products

### Applies thesis

- [Human Resources Consultancy](/CompanyTypes/Human_Resources_Consultancy) — applies thesis · CompanyTypes

### Embodies

- [Software](/Theses/Software) — embodies · Theses

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