Introduction
With the goal of introducing new medical drugs, boosting sales, and expanding market share, the company faced the challenge of navigating unfamiliar territories. Our role was to provide advanced pharmaceutical analytics and tailored Business Intelligence solutions. These tools enabled the company to gain deeper insights into new markets, identify growth opportunities, and make data-driven decisions in their global expansion efforts.
Challenge
These points highlight the multifaceted challenges faced by the pharmaceutical company in its global expansion efforts, emphasising the need for robust data management and analytics solutions to navigate complex market dynamics and organisational structures.
- Global Market Expansion Challenge Launching a new drug in unfamiliar global markets requires accurate insights into regional demand patterns.
- Complex Disease Target The drug addresses a condition interlinked with other medical issues, complicating demand prediction and market analysis.
- Data Inconsistency Across Departments Lack of uniformity in data between various business units (Marketing, Finance, Operations, etc.) hinders cohesive analysis.
- Dual Reporting Platforms Separate data visualisation tools (MSTR for field representatives, Tableau for leadership) create potential for information discrepancies.
- Granular Patient Data Management Handling extensive patient-level data presents both opportunities for precise insights and challenges in data processing and privacy.
Solution
This BI solution leverages a robust technology stack to collect, process, and analyse diverse pharmaceutical data sets. By combining cloud storage, powerful analytics tools, and custom development capabilities, the system provides tailored insights for both field operations and strategic decision-making at the headquarters level.
- Diverse Data Sources Integration of external (Veeva, Symphony Health, AHA) and internal company data for comprehensive market insights.
- Analytics and Visualization Tools Utilisation of Google Analytics, Tableau (HQ), and MSTR (field) for data analysis and reporting.
- Data Processing and Storage Implementation of SQL for data manipulation and Amazon S3 and Redshift for cloud-based data storage and warehousing.
- Custom Development Use of Python for tailored data processing and potential custom solution development.
- Tailored Reporting Strategy Dual reporting approach with Tableau for headquarters and MSTR for field representatives, addressing specific user needs.
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