In the complex and fast-evolving landscape of global markets, the strategic importance of pricing can hardly be overstated. It’s the linchpin that not only affects revenue and margins but also determines market competitiveness.

This is where Artificial Intelligence (AI) steps in, revolutionising the way industries approach pricing strategies. In particular, the implementation of AI in tender and RFP (Request for Proposal) pricing across Italy, Spain, France, the Nordics, and other EU & ME markets has been nothing short of transformative.

The AI-Driven Pricing Revolution

AI technology has opened new avenues for analysing historical data, recognising patterns of wins and losses, and applying these insights to future tenders and RFPs. This analytical prowess has empowered businesses with predictions and scenarios rooted in real-life outcomes, leading to substantial revenue growth — ranging from 12% to 25% — and enhanced margins by 17% to 25% across diverse markets and assets.

Our Three-Phased Approach to Pricing

Our journey towards pricing is meticulously structured into three phases, each designed to build upon the insights and foundations laid in the preceding steps.

Phase 1: Data Discovery, Cleansing, and Enrichment

The first step in the process is to meticulously curate and enhance the dataset, ensuring its integrity and richness. This involves a thorough examination of the data to identify any inconsistencies, errors, or missing information that could potentially undermine the accuracy of the predictive models. Once these issues are detected, the data undergoes a rigorous cleansing process to correct the invalid entries and ensure the dataset’s overall quality.

However, the preparation phase goes beyond mere data cleaning. To truly unlock the potential of the predictive models, it is essential to enrich the dataset with valuable market insights. This enrichment process involves integrating relevant external data sources, such as industry trends, competitive intelligence, and regulatory information, to provide a more comprehensive and contextual understanding of the market dynamics.

By combining the internal data with these external insights, the dataset becomes a powerful asset that can drive more accurate and actionable predictions. This solid foundation of clean, enriched data sets the stage for the development of robust and reliable predictive models in the subsequent phases of the project.

Phase 2: Model Building

In this phase, the focus is on developing sophisticated predictive models that incorporate a vast array of variables. These models are designed to tackle complex challenges, such as forecasting prices at the molecular level and identifying the most likely winning bids for individual stock-keeping units (SKUs).

The algorithms take into account a wide range of factors that influence the pricing of drugs or medical products throughout their entire lifecycle, from initial launch to post-patent expiry scenarios. By considering the impact of various market dynamics, regulatory changes, and competitive landscapes, these models provide valuable insights into pricing strategies and help organisations navigate the complexities of the pharmaceutical and healthcare industries. The ultimate goal is to empower local teams with data-driven recommendations that optimise revenue, maximise profitability, and ensure sustainable growth in an increasingly competitive market.

Phase 2: Model Building

In this phase, the focus is on developing sophisticated predictive models that incorporate a vast array of variables. These models are designed to tackle complex challenges, such as forecasting prices at the molecular level and identifying the most likely winning bids for individual stock-keeping units (SKUs).

The algorithms take into account a wide range of factors that influence the pricing of drugs or medical products throughout their entire lifecycle, from initial launch to post-patent expiry scenarios. By considering the impact of various market dynamics, regulatory changes, and competitive landscapes, these models provide valuable insights into pricing strategies and help organisations navigate the complexities of the pharmaceutical and healthcare industries. The ultimate goal is to empower local teams with data-driven recommendations that optimise revenue, maximise profitability, and ensure sustainable growth in an increasingly competitive market.

The Vamstar Difference

The drive for greater commercial efficiency has become increasingly urgent against a backdrop of inflation, shortages, and the shift towards value-based healthcare. Vamstar distinguishes itself by leveraging AI to orchestrate, analyse, and provide intelligence on MedTech and Pharmaceutical data. This approach not only enhances market visibility but also optimises pricing strategies, thereby simplifying and automating commercial workflows to achieve sales excellence.

The Impact

Adopting AI in pricing does more than just improve financial metrics; it represents a paradigm shift in how businesses approach the market. By providing a granular view of demand and supply dynamics, and facilitating informed decision-making, AI technologies like those offered by Pricing Co-Pilot are setting new standards for efficiency and competitiveness in the healthcare sector.

Conclusion

The integration of AI into pricing strategies marks a significant leap forward for industries striving to navigate the complexities of modern markets. With its proven track record of enhancing revenues and margins, AI offers a promising path to not just survive but thrive in the competitive landscape. As we continue to explore and refine these technologies, the possibilities for innovation and improvement in pricing strategies are boundless.

Leading pharmaceutical companies are increasingly focusing on global health initiatives, which has led to a rise in procurement through tenders and long-term agreements (LTAs) by Intergovernmental Organizations (IGOs) and Non-Governmental Organizations (NGOs).

In 2023, the total value of pharmaceuticals and medical supplies distributed by these entities is estimated at US$ 21.3 billion, with a significant portion allocated to vaccines, medical supplies, and diagnostics. Pharmaceuticals alone account for about US$ 4.7 billion of this total.

The Covid-19 pandemic caused a noticeable surge in healthcare spending by NGOs and IGOs in 2021, particularly in diagnostics and vaccines. Although the pharmaceutical sector experienced a decline during this period, it has been witnessing a notable upward trend since 2022, with an average year-over-year growth of over 11%.

This trend underscores the growing significance of global health teams within pharmaceutical companies.

These teams are becoming increasingly important due to various factors:

1. Shifting Disease Landscape: There’s a growing prevalence of neglected tropical diseases and infectious diseases in low- and middle-income countries (LMICs), requiring innovative approaches and partnerships for drug development.

2. Equity and Access: Heightened awareness of healthcare inequities in LMICs is pressuring pharmaceutical companies to improve access to essential medicines. Global health teams are pivotal in addressing these challenges by developing sustainable distribution models and navigating complex healthcare systems.

3. Emerging Markets: LMICs are emerging as significant markets for pharmaceuticals. Global health teams are key in helping companies understand and penetrate these markets.

4. Pandemic Preparedness: The COVID-19 pandemic highlighted the need for improved outbreak preparedness. Teams with expertise in public health and vaccine development are valuable for future pandemic response strategies.

5. Regulatory Landscape: As governments and international bodies implement policies to enhance medicine accessibility in LMICs, global health teams are crucial for ensuring compliance and navigating these regulations.

Companies are recognising that strong global health programs not only fulfill social responsibilities but also attract consumers and investors. These programs are focused on making medicines more affordable and accessible in LMICs through various initiatives.

Industry Response Includes:

• Establishing dedicated global health units.
• Engaging in public-private partnerships.
• Exploring innovative financing models.
• Investing in local capacity building.
• Developing medicines for neglected tropical diseases (NTDs).

Challenges and Opportunities:

Despite their importance, global health teams face challenges such as limited resources and the need to balance commercial objectives with social impact. However, the opportunities for significant social impact, market access, and long-term value creation are substantial. These teams play a crucial role in strengthening healthcare systems, advocating for policy change, and demonstrating the value of global health initiatives.

One major challenge is the lack of transparency and market intelligence in the sector, where a large portion of the market remains non-tender based and procurement is often local and in partnership with governments. Vamstar is addressing this challenge by combining AI-based data scraping with subject matter expertise to provide ATC class-level market insights, which are vital for shaping global health strategies in the pharmaceutical industry.