Efficient coordination between Supply Planning and Demand Planning is essential for optimizing operations, mitigating risks, and maximizing customer satisfaction in the S&OP process. By integrating these two functions within the framework of Integrated Business Planning (IBP), organizations can achieve a holistic view of their operations, balance supply and demand effectively, and drive sustainable growth. This good practice has a significant impact on service levels, lost sales, optimal stock levels, equilibrium in S&OP KPIs, and collaboration in the Demand Planning process, ultimately enabling organizations to achieve their strategic objectives and gain a competitive edge in the marketplace.

AI and Machine Learning are transforming FP&A by providing advanced insights, improving efficiency, and driving better business outcomes. By harnessing the power of integrated platforms like Pyplan, organizations can leverage AI-driven analytics to detect anomalies, automate reporting, facilitate real-time close processes, streamline collections, and drive more accurate revenue recognition. This evolution in FP&A enables organizations to achieve greater agility, accuracy, and competitiveness in today’s dynamic business environment.

In this blog we summarize some of the best practices for demand planning in pharmaceuticals, highlighting the importance of data-driven forecasting, collaboration with stakeholders, inventory optimization, and flexibility in response to market dynamics.