Compensation Analytics

Use AI to optimize compensation planning with real-time benchmarking and equity insights

Business impact

• Employee retention — Improved compensation competitiveness increases employee loyalty and reduces turnover rates
• Compensation competitiveness — Real-time benchmarking ensures pay aligns with market standards to attract top talent
• Compensation planning efficiency — AI automates data analysis and workflows, reducing time spent on compensation planning
• Employee satisfaction — Transparent and fair compensation plans enhance morale and job satisfaction

Data requirements

• Internal payroll and compensation data (Structured) — Used to analyze current pay structures and employee compensation details
• Market salary and equity benchmarks (Numeric) — Provides external competitive pay data for benchmarking and strategy alignment
• Employee performance and engagement data (Structured) — Informs compensation adjustments linked to performance and satisfaction
• Compensation plan documents and policies (Text) — Used to automate and validate compensation rules and workflows

AI methods and techniques

• Predictive AI — Forecasts compensation trends and employee turnover risks based on historical data
• Generative AI — Generates optimized compensation plans and communication content for stakeholders

AI models and model families

Google Gemini, Vertex AI, GPT-4, Claude

Industries

Real-world evidence

1 documented case study on record.

Companies using this: Pave.