Leverage Real World Data for Building Robust Inputs for a Successful Forecasting Model

Description

To make any successful forecasting model, the first step is to identify the key supporting metrics required to build an accurate forecast model. The conventional data sources (e.g. chart audit, survey data) present only a small part of the very big picture, where a lot of indirect factors affect the share of the drug, thus limiting the insights and scope of the analysis. Real-world data can be the supplementary evidence, if not the substitute for conventional data sources, in increasing the confidence of forecasting inputs.

In this webinar, we will be discussing how to efficiently merge information from both real-world data and secondary research data and build robust KPIs which can support development of an efficient forecasting model.

Presenters:

• Vishnu Prashanth, Principal Consultant, D Cube Analytics
• Ajitha Surendran, Consultant, D Cube Analytics