Empowering Data-Driven Decision-Making for a Healthcare Benefits Platform

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Healthcare

Empowering Data-Driven Decision-Making for a Healthcare Benefits Platform

Healthcare benefits administrators reviewing analytical insights to guide plan adjustments and strategic decisions.

Focus Areas

Data Analytics

Business Intelligence

Healthcare Benefits Optimization

Data-Driven Decision Engine for Benefits Management

Business Problem

A rapidly growing healthcare benefits platform serving employers and members was facing limitations in delivering insights to internal stakeholders and enterprise clients. Despite collecting vast amounts of claims, enrollment, and engagement data, decision-making remained reactive due to fragmented systems and manual reporting. Leaders lacked real-time visibility into cost drivers, member behavior, and benefit utilization, limiting the platform’s ability to guide clients on optimizing health plan value and outcomes.

Key challenges:

  • Data Silos Across Systems: Claims, enrollment, wellness engagement, and employer data were stored across isolated systems with no centralized view.

  • Delayed Reporting:  Manual extraction and ad hoc reporting led to delays in surfacing key trends and responding to client needs.

  • Limited Client-Facing Insights: Employers using the platform lacked actionable data to manage healthcare costs or guide employee engagement.

  • Inconsistent KPIs: Teams relied on inconsistent metrics and lacked a single source of truth for performance and utilization reporting.

The Approach

Curate partnered with the healthcare benefits platform to implement a robust analytics and reporting infrastructure that unified data sources, automated insights delivery, and empowered both internal and client stakeholders to make informed decisions. The initiative focused on modernizing the data stack, enabling scalable business intelligence, and embedding analytics into client-facing experiences.

Key components of the solution:

  • Discovery and Requirements Gathering: Through workshops with data, product, sales, and client success teams, Curate defined critical analytics use cases, including:

    • Real-time visibility into plan utilization and costs

    • Employer-facing dashboards for health and wellness program insights

    • Claims trend analysis for proactive benefit design recommendations

    • Executive reporting on platform growth, client health, and member engagement

  • Data Analytics Solution Implementation:

    • Data Consolidation: Integrated data from claims processors, eligibility systems, CRM, and engagement platforms into a centralized cloud data warehouse (Snowflake).

    • Unified Data Model: Created a standardized data model to align metrics across finance, product, and client-facing teams.

    • BI Dashboards: Developed interactive dashboards using Tableau and Looker for claims trends, ROI reporting, and member activity tracking.

    • Embedded Analytics for Clients: Created white-labeled dashboards accessible within the employer portal, enabling on-demand insight into benefit performance.

    • Automated Data Pipelines: Deployed Airflow and dbt to automate data ingestion, transformation, and validation processes.

  • Process Optimization and Enablement:

    • KPI Standardization: Defined core business metrics (e.g., cost per member, engagement rate, top claim categories) for consistent tracking.

    • Self-Service Analytics: Enabled business users with guided analysis paths, data dictionaries, and user training to explore data independently.

    • Alerts & Anomaly Detection: Implemented automated alerts for spikes in claims costs, enrollment drops, or disengaged members.

    • Data-Driven Client Success: Equipped account managers with client scorecards and benchmark data to drive proactive conversations.

  • Stakeholder Engagement & Change Management:

    • Cross-Team Collaboration: Established a data governance committee to ensure alignment on data usage and definitions.

    • Training and Documentation: Created training content and conducted sessions for internal teams and client users on dashboards and KPIs.

    • Iterative Development: Piloted analytics tools with select clients and refined functionality based on real-world usage and feedback.

Business Outcomes

Faster and Smarter Decision-Making Across the Organization


Leaders gained access to real-time insights, enabling agile responses to market and client needs.

Stronger Client Retention Through Transparent Reporting


Clients appreciated visibility into their benefit performance, strengthening trust and partnership value.

Proactive Optimization of Benefit Strategies


Data-driven insights enabled tailored recommendations for plan design improvements and targeted engagement.

Operational Efficiency and Scale


Automated reporting and self-service analytics reduced manual workload and supported scalable growth.

Sample KPIs

Here’s a quick summary of the kinds of KPI’s and goals teams were working towards**:

Metric Before After Improvement
Time to generate client reports 5–7 days 24 hours 80% faster reporting
Client dashboard adoption rate 40% 90% High engagement
Claims trend identification Monthly lag Real-time dashboards Proactive cost management
Member engagement visibility Aggregated, delayed Real-time by segment Improved personalization
Internal analytics usage rate Low (analyst-driven) 3x increase Empowered business teams
**Disclaimer: The set of KPI’s are for illustration only and do not reference any specific client data or actual results – they have been modified and anonymized to protect confidentiality and avoid disclosing client data.

Customer Value

Insightful Client Partnerships


Employers gained tools to better understand, manage, and optimize their healthcare investments.

Strategic Internal Decisions


Leadership had access to timely data to guide product innovation, pricing, and service delivery.

Sample Skills of Resources

  • Data Engineers: Built and maintained ETL pipelines and managed Snowflake architecture.

  • BI Developers: Designed and deployed scalable dashboards and embedded analytics.

  • Product Analysts: Defined metrics, user stories, and insights tied to platform objectives.

  • Client Success Analysts: Applied data insights to support client relationships and ROI delivery.

  • Project Managers: Oversaw implementation timelines and ensured stakeholder alignment.

Tools & Technologies

  • Data Warehouse: Snowflake

  • ETL & Orchestration: dbt, Apache Airflow

  • Visualization & BI: Tableau, Looker

  • CRM & Engagement Platforms: Salesforce, HubSpot

  • Workflow Tools: Confluence, Jira, Slack

Conclusion

Curate’s data transformation initiative enabled the healthcare benefits platform to elevate its decision-making capabilities and offer real-time insights to both internal stakeholders and employer clients. By centralizing data, automating reporting, and embedding intelligence into the user experience, the company unlocked strategic value across operations, client success, and product development. The platform now operates as a data-first organization with the tools to grow smarter, faster, and with greater impact.

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