Revolutionising Tender Bidding Strategies with AI

The company struggled to manage the competitive pressures of the generics market, relying on traditional market knowledge and manual data collection and analysis for tender bidding.

Despite attempts to use Excel-based models for pricing estimates, they concluded that accurately modelling tender bidding scenarios and accounting for the myriad variables influencing bidding outcomes was an insurmountable task.

The leadership recognised the need for a more sophisticated approach to drive growth and profitability in the face of intense competition.

Vamstar collaborated closely with the company to deploy the AI-based Pricing Co-Pilot in Italy.

This entailed collecting and organising tender data, analysing influential factors in tender outcomes, and developing predictive models using advanced machine learning and deep learning techniques.

Vamstar’s solution enabled A/B testing and reinforcement learning, allowing continuous refinement of the algorithms based on actual tender outcomes, effectively transforming the tool into a dynamic decision support system.

The implementation of the Pricing Co-Pilot marked a dramatic turnaround in the company’s tender strategy. With the AI-driven tool, the company not only generated an additional $1.5 million in revenue but also improved its tender win rates by 76% and margins by 32%. 

The success of the project created a buzz across the company’s European operations, with various teams eager to adopt this new technology. The Pricing Co-Pilot not only facilitated better decision-making but also democratised access to sophisticated analytics, enabling team members of varying technical expertise to leverage data for strategic advantage.

Vamstar’s AI-powered Pricing Co-Pilot has profoundly transformed how pharmaceutical companies approach competitive tender bidding in the generics market. By utilising historical data, advanced analytics, and machine learning, the solution has enabled the company to optimise margins and make informed, data-driven decisions.

This case study underscores the significant potential of AI in enhancing profitability and growth in challenging market conditions, setting the stage for the company to fortify its market leadership and continue its trajectory of success.