A leading Healthcare and Life Sciences company planned a BI migration to scale decision-making. The company needed a modern analytics foundation to support growing data demand and reduce operational risk tied to legacy analytics tools. However, the initiative surfaced fragmented dashboards, duplicated metrics, and business rules trapped in a proprietary BI platform. This meant low trust, risk, and a high migration cost. 

Indicium’s Data & AI Product Discovery went beyond defining migration scope and cutting redundant assets; we reimagined the client’s entire data consumption strategy. After mapping pain points, dashboard redundancy, and demand patterns, we designed a Hub-and-Spoke dashboard architecture. This was validated via a PoC and supported by a roadmap of 40+ initiatives and 27 data products to scale self-service BI.

The projected impact: $175K reduction in migration costs and $116K in annual infrastructure and headcount savings, driven by reclaiming 8,896 hours/year of analyst capacity for higher-value work, alongside a clear roadmap for asset consolidation.

BI Fragmentation Drove Rework, Mistrust, and Migration Risk

The company had too many dashboards, and many repeated the same metrics. Numbers did not always match, which reduced trust in reporting. Users opened multiple dashboards and exported data to spreadsheets to rebuild the same indicators manually. Across ~600 requests to the data team over 15 months, the work was reactive: 54% were routine indicator pulls for management close.  

The Indicium Data & AI Product Discovery showed the main blockers were not only technical. A maturity survey across the organization with 200+ responses highlighted gaps in skills and alignment:

• 64.5% said they lacked the technical skills to work with data
• 66% said the company did not reward or encourage data growth
• 55% of leaders said they had low visibility into the data strategy 

On the data side, only 11% of mapped sources fed the Data Warehouse, and most ingestion focused on billing. Some use cases required many refreshes per day, which raised the bar for scheduling and reliability. The legacy BI tool stored business rules inside proprietary formats, which made them hard to extract and document. That increased effort and delivery risk.

A Discovery to Define Scope, Cost, and Priorities

Indicium ran a discovery across five tracks to align business needs, technical constraints, and the cost drivers that shaped not only the client’s data strategy, but also the migration scope. Business interviews identified pain points and optimization opportunities. An analytics maturity survey assessed gaps across People, Organization, and Data. 

Demand analysis of recurring requests clarified what belongs in self-service versus what still requires ongoing support. A technical source assessment mapped golden systems, ingestion coverage, and feasibility for new ingestion. Finally, a dashboard inventory review measured usage, redundancy, and leadership engagement.

Hub-and-Spoke Architecture

Based on the findings, we proposed a Hub-and-Spoke dashboard architecture to reduce overlap and standardize business logic at scale: 

• Consolidate isolated dashboards into a single structure
• Build four strategic Hubs for executive-level views
• Keep operational depth without recreating logic across teams
• Unify business logic to support traceability and consistent reporting

Proof of Concept Validation

We validated the model inside one business unit. The PoC consolidated redundant assets into four Hubs, with direct impact on migration scope and exposure to legacy black-box maintenance. 

Roadmap to Shift the Operating Model

Architecture alone would not solve the root causes surfaced by the maturity and demand analyses. Indicium delivered a roadmap with 40+ initiatives across governance, data product management, enablement, automation, and data foundations. The roadmap proposed 27 data products to reduce recurring manual work, expand self-service BI, and align business areas around shared definitions and reusable assets. 

Lower Migration Cost, Higher BI Capacity

This discovery produced a quantified business case that fundamentally reimagined the client’s data strategy and consumption framework, alongside the migration itself.

1) Migration Scope Optimization and Savings

• Proof of concept identified ~15% redundant dashboards in the assessed unit. This confirmed that the company can deliver more insight with fewer assets
• Extrapolated impact projected $175K reduction in migration cost
• Estimated $4K in recurring annual infrastructure savings on the new platform under the same storage and processing conditions

2) Productization and Operational Performance

• Manual routines consumed 8,896 hours between 2024 and 2025, equivalent to six full-time data analysts dedicated to extraction and support work
• This represented ~$112K per year in cost
• The roadmap targets this demand through self-service BI and intelligently architected data products, ensuring technical teams can shift from repetitive data extraction to higher-value analysis.

Instead of migrating duplicated dashboards and scattered logic, the company now has a clear cutline for consolidation. Beyond the migration itself, this strategy also replaces low-complexity ad-hoc requests with true stakeholder empowerment, providing the autonomy needed to scale BI without burdening the data team with repetitive tasks.

A Roadmap Built for Scale

The client needed a partner to transform a complex BI migration into a clear, evidence-based strategic roadmap. Indicium provided the execution path by auditing actual usage patterns to identify what was truly valuable versus what was redundant. We mapped the recurring ad-hoc requests and skill gaps that were hindering adoption, ensuring the new strategy addressed business needs, not just technical debt.

By validating consolidation through a POC and removing hidden logic from legacy tools, we optimized the migration scope while modernizing the consumption model. We delivered a roadmap of 40+ initiatives to strengthen governance, automation, and enablement. This ensures the new platform isn’t just a replica of the old one, but a scalable self-service ecosystem designed to outlast the migration itself.