Commercial Operations in Pharma: Understanding how pharmaceutical companies operate commercially, including sales cycles, market access, contracting, and patient programs.
Gross-to-Net (G2N) in Pharma: This is critical. G2N analytics refers to the process of understanding and managing the difference between a pharmaceutical product's gross sales revenue and the net revenue actually received by the manufacturer after various deductions (rebates, chargebacks, discounts, returns, etc.). This is a complex area specific to the pharma industry due to its intricate pricing and rebate structures.
Revenue Leakage in Pharma: Identifying and quantifying areas where revenue is lost due to inefficiencies, incorrect pricing, contract non-compliance, or other factors unique to the pharmaceutical supply chain and commercial models.
Regulatory Landscape (US-specific): Familiarity with healthcare regulations, data privacy (HIPAA, CCPA if applicable), compliance requirements, and pharmaceutical pricing regulations in the US.
Data Analytics and Business Intelligence:
Advanced Analytics Methodologies: Strong understanding and experience with statistical analysis, predictive modeling, machine learning, and data visualization techniques relevant to business problems.
Data Warehousing and ETL: Knowledge of data extraction, transformation, and loading processes, and experience working with large datasets from various sources.
BI Tools and Dashboards: Proficiency in creating and maintaining interactive dashboards and reports using industry-standard BI tools (e.g., Tableau, Power BI, Qlik Sense) to present insights.
SAP Ecosystem Knowledge (Specifically Pharma-relevant):
SAP S/4HANA (or ECC): In-depth knowledge of SAP's enterprise resource planning (ERP) system, particularly modules related to sales and distribution (SD), finance (FI-CO), and potentially materials management (MM), as they relate to commercial data.
Vistex: Expertise in Vistex solutions, which are often used on top of SAP for managing pricing, incentives, chargebacks, and rebates in complex industries like pharma. This is explicitly mentioned and is a significant differentiator.
Ecosystem: Need for experience with centralized commercial data repositories and their architecture.