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Novo Nordisk
Novo Nordisk

Novo Nordisk Streamlines Market Access with a Custom CRM Solution

2000+ Internal Users Supported
2000+ Internal Users Supported
Enabled efficient operations for Novo Nordisk’s nationwide sales team.
1 CRM System
1 CRM System
A coherent platform for account strategy & analytics.
Machine Learning with Built-In NLP
Machine Learning with Built-In NLP
Turned unstructured data into actionable insights.
Novo Nordisk Streamlines Market Access with a Custom CRM Solution
Industry
Life Sciences / Pharmaceuticals
Provided Services
Custom Product Development
CRM Development
Machine Learning / NLP Model Development
Data Engineering
Tech Stack
Python / Objective-C / MongoDB / NLTK (Natural Language Toolkit)
Team Size
15+ people

[ client & product overview/ ]

Novo Nordisk is a global pharmaceutical leader based in Denmark with over a century of experience in treating chronic conditions such as diabetes, obesity, hemophilia, and growth disorders.

As one of the largest insulin producers globally, the company relies on accurate market access strategies to support its mission. Novo Nordisk partnered with MEV to streamline market access operations and maximize data utility through a custom CRM platform.

Executive Summary
MEV built a custom CRM platform for Novo Nordisk that transformed complex, unstructured insurance data into actionable insights for 2,000+ sales and market access team members. By combining data engineering with NLP, the solution enabled faster planning, improved data transparency, and maximized the value of high-cost data feeds.

[ challenges/ ]

The Challenge

Novo Nordisk’s U.S. Market Access team had access to a large number of costly insurance data feeds but the data was disorganized and hard to use. Sales and account managers couldn’t easily find the specific insights they needed for their regions, making it difficult to support national and regional healthcare exchange initiatives.
Key challenges included:
  • Disorganized and overwhelming volumes of payer and insurance data
  • Difficulty tailoring data to specific accounts, regions, or sales goals
  • Lack of a unified system to plan and track account-level strategy
  • Missed opportunities to draw insights from expensive data sources
They needed a scalable, strategic solution that would both ingest unstructured data and surface relevant insights for business planning—without overwhelming account teams.

[ what we did/ ]

Scope & Approach

The business goal was to help account managers quickly navigate complex healthcare exchanges by organizing vast insurance data into clear, actionable insights tailored to their regions.

MEV began with a collaborative discovery process with the Market Access Group, aligning on key challenges and goals across national and regional accounts.
Custom CRM Development: MEDIX
MEV designed and developed a proprietary market access CRM platform called MEDIX. It enables:
  • Strategic and tactical account planning
  • Ingestion of unstructured insurance and healthcare data
  • NLP-driven contextual analysis for geography- and payer-specific insights
  • Real-time filtering by geography, account, and payer type
  • Leadership transparency into national and regional account plans.
They needed a scalable, strategic solution that would both ingest unstructured data and surface relevant insights for business planning—without overwhelming account teams.
Continued Partnership
After delivering MEDIX, Novo Nordisk continued working with MEV on additional commercial technology projects, including:
  • Building Interactive Visual Aids (IVAs) to strengthen field engagement
  • Developing a custom analytics layer for payer data

[ results/ ]

This unified ecosystem helped Novo Nordisk increase efficiency, reduce data waste, and align regional actions with national business goals.
R1:
Supported ~2000 internal sales and account management users
R2:
Created one process, one tool, and one unified data view
R3:
Enabled transparency and strategic alignment across the Market Access Group
R4:
Maximized the value of costly insurance data through contextual filtering and NLP
R5:
Established a scalable foundation for future data-driven initiatives

[ portfolio/ ]

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