Elevate your Market Access Intelligence to identify targetable Payer and Provider Segments

Supported a mid-sized Biopharma Company with comprehensive insights onto the identification of Payers and Providers that control the therapeutic choice in the market

source of truth for 50+ stakeholders


through end-to-end automation

cost savings

“D Cube Analytics’ strong domain knowledge and pro-activeness in bringing new ideas to the table helped this project to evolve from a simple Payer-Provider list creation exercise to a predictive model framework development.

They have shown great attention to detail in not just meeting our requirements, but exceeding them.”


The customer had multiple assets across different therapeutic areas including Oncology.

Given the complex nature of the Oncology domain, the customer wanted to build a dynamic and predictive tool that provides rich insights onto Payer and Provider dynamics of the market to identify the leaders and device strategic decisions with them to increase their utilization of drugs.


D Cube Analytics leveraged DDS Terra to integrate multiple data sources (LAAD, MMIT, DDD) and applied in-house expertise to create robust and indigenous KPI’s such as – Payer and Provider Favourability Index to categorize Payers and Providers based on their control using Automated Tableau based solution with exhaustive and efficient data flow.


Using our in-house proprietary tools and frameworks, we created a robust solution which is summarised below –

  1. Quantifying Drug Favourability – Analysed various plan attributes namely formulary status, restrictions, and lives covered by each plan, and defined a composite score – Payer Favourability Index based on the above attributes
  2. Translating Drug Favourability to Payer Control – Defined restriction buckets such as – low, medium, and high based on payer favourability index and then defined Payer Control based on the restriction bucket and the spread of favourability index of drugs in the market
  3. Provider Control – Analysed various provider attributes such as – Prescription Pattern, Care Coordination, Sophistication, Size, etc and then defined a composite score – Provider Control Index based on the above attributes
  4. Geography Segmentation – Segmented the geography as Payer/Provider Controlled based on the calculated Payer and Provider indices


  • One-Stop solution for building robust pre-deal contract scenarios with data-driven assumption and access post-deal outcomes
  • Source of Truth for refining, optimizing, and prioritizing the physician and account target list for the field force
  • Helps in tracking the longitudinal behavior of Payer and Provider to analyzed the impact of formulary win and losses

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