Meta operates at global scale with tens of thousands of employees, managers, HR partners, and finance stakeholders relying on internal tools to make compensation decisions during planning cycles. The company is redesigning an internal compensation analytics experience used across People Analytics, HRBP, and leadership workflows.
Today, compensation data is spread across a high-level dashboard and several detailed reports in Meta's internal analytics stack. Users complain that the dashboard is cluttered, slow to interpret, and mixes executive monitoring metrics with diagnostic metrics that only matter during investigation. At the same time, some drill-down reports are underused because critical signals are buried too deep.
Meta wants to decide which KPIs should appear on the primary compensation dashboard versus which should live in a drill-down report. The goal is to help different users answer the right questions quickly without overwhelming them or increasing the risk of misinterpretation of sensitive compensation data.
Assume the product supports these example KPI types: compa-ratio, pay range penetration, promotion-adjusted pay changes, gender pay gap, ethnicity pay gap, offer acceptance rate, attrition of top performers after comp cycles, budget utilization, out-of-band adjustments, manager exception rate, and compensation review completion rate.