What is the difference between proprietary forecasting model and in market forecasting in pharmaceutical industry

In the pharmaceutical industry, proprietary forecasting models and in-market forecasting serve different purposes and are based on distinct methodologies. Here’s a detailed comparison:

Proprietary Forecasting Model

Definition of Proprietary Forecasting Model:

A customized, often company-specific model developed internally or by third-party consultants, tailored to predict sales, revenue, or market trends for a specific product, therapeutic area, or market segment. These models are unique intellectual property and rely on proprietary data and algorithms.

Key Characteristics of Proprietary Forecasting Model:

• Customization: Designed specifically to meet the company’s needs, considering product portfolio, pricing strategies, and market access.
• Data Inputs: Utilizes internal data (e.g., clinical trial results, patient population, market research) along with external data (e.g., epidemiology, competitive landscape, reimbursement trends).
• Sophistication: Can incorporate advanced techniques like machine learning, AI, or scenario modeling.
• Flexibility: Allows simulations, sensitivity analysis, and adjustments for new data inputs or market changes.
• Use Cases:
• Long-term strategic planning (e.g., lifecycle management, investment decisions).
• Business development (e.g., licensing and acquisition opportunities).
• Market entry forecasting for new drugs.

In-Market Forecasting

Definition of In-Market Forecasting

The ongoing process of forecasting based on real-time or near-term market data for products that are already launched and actively competing in the market.

Key Characteristics:

• Real-Time Focus: Based on actual sales data, market trends, and competitor activities.
• Data Inputs: Incorporates prescription data, sales performance, market share, inventory levels, and external factors like regulatory changes or seasonality.
• Short-Term Orientation: Often focuses on monthly, quarterly, or annual projections.
• Accuracy Over Flexibility: Relies heavily on historical trends and current market dynamics rather than complex predictive models.

Use Cases:

• Tracking and optimizing sales performance.
• Operational decisions like inventory management and supply chain optimization.
• Adjusting marketing strategies based on current trends.