The client aimed to optimize pricing for their generics portfolio in a highly competitive market. The goal was to react quickly to competitor pricing moves, improve profitability, and reduce the manual effort involved in pricing decisions, while aligning inventory and demand planning more accurately.

We implemented an AI-driven dynamic pricing solution that trained predictive models on historical sales, competitor pricing, and market demand to forecast price elasticity and profitability. The system generated real-time pricing recommendations integrated directly with the client’s ERP and finance systems. This enabled commercial and finance teams to adjust prices dynamically and autonomously, while maintaining governance and oversight.

We helped our client:​

• achieve faster reactions to competitor price changes, improving market competitiveness​.
• decrease manual pricing effort, freeing up teams to focus on other things​.
• improve financial forecasting accuracy, providing better visibility into revenue and margin outcomes. Pricing adjustments were aligned with inventory and demand patterns, reducing stock imbalances and lost sales opportunities.