Optimize the second-largest line item on your P&L
Model plan design trade-offs, optimize HSA/FSA strategies, provide personalized enrollment decision support, and monitor benefits compliance — turning total rewards from cost center to retention lever.
Common pain points that structured decision models eliminate.
Plan costs rise 6-8% annually with little visibility into drivers. Model plan design trade-offs, identify cost optimization levers, and forecast utilization by segment.
Employees pick the wrong plans and leave value on the table. Decision support models recommend optimal plan-benefit combinations based on individual needs.
ACA affordability, COBRA administration, ERISA fiduciary duties — regulatory requirements multiply. Automated compliance scanning with remediation workflows.
Competitive total rewards data is stale by the time you act. Benchmark packages against real-time market data and model the retention impact of benefit changes.
How teams use DecisionLedger to make better decisions.
Models plan design trade-offs across medical, dental, and HSA options before renewal season — comparing cost impact, employee satisfaction, and utilization projections side by side.
Saved $1.2M annually by optimizing plan design before renewal lock-in
Uses the open enrollment decision support model to provide personalized plan recommendations for each employee based on family size, expected utilization, and tax advantages.
Employee plan satisfaction scores increased 28% after guided enrollment
Runs the total rewards retention model to benchmark compensation and benefits packages against market data, identifying where the company is losing talent to competitors on total rewards.
Identified that dental and HSA gaps were driving 15% of voluntary turnover
Based on platform benchmarks across early adopters.
Plan Design Cycle
Broker-driven renewals
Model-backed optimization
Benefits Cost
6-8% annual increases
Targeted optimization levers
Enrollment Quality
Employees guess wrong
AI-recommended plans
Compliance Monitoring
Annual ACA review
Continuous scanning
Connects With
Pre-built decision models ready to run with your data.
Scans benefits program for compliance risks across ACA, ERISA, HIPAA, COBRA, and state mandates, scoring each area and recommending remediation.
Scores benefits data quality across enrollment, claims, and eligibility feeds, detecting anomalies and estimating cost of poor data quality.
Scores equity of employer subsidy structures across income tiers, identifies regressive subsidy patterns, and recommends progressive alternatives.
Optimizes HSA/FSA contribution strategies based on employee demographics, expected utilization, and tax advantages.
Predicts best-fit plan per employee household using utilization, risk tolerance, and budget preferences; outputs plan comparisons and OOP ranges.
Models plan design changes and estimates premium and member OOP impact.
Connects benefits richness to retention and offer acceptance risk by job family.
Scores and ranks voluntary benefit offerings (pet insurance, legal, identity theft, etc.) using multi-criteria decision analysis based on employee demographics and market benchmarking.
Three steps to structured, auditable decisions.
Benchmark compensation and benefits against market data. Model the total cost of rewards packages across employee segments and geographies.
Run plan design trade-off models, optimize HSA/FSA strategies, and score voluntary benefit adoption scenarios against cost and retention impact.
Provide personalized enrollment decision support, track utilization trends, and monitor compliance with automated ACA and ERISA scanning.
Broker-driven renewals
Accepting rate increases because your broker says 'that's the market' — without counter-models
Benefits admin platforms
Enrollment systems that process elections but can't analyze whether plans are optimal
Spreadsheet plan comparisons
Side-by-side cost tables that miss utilization patterns and retention impact
Annual benchmarking surveys
Stale compensation data from 12 months ago that doesn't reflect current market