Generative AI in the Healthcare Sector

Unveiling New Opportunities

 

Western societies are aging. To maintain trust in a reliable healthcare system while keeping the rising costs of demographic shifts in check, manufacturers and service providers need more efficient structures and supply chains. Increasingly, companies in the pharmaceutical, medtech, and healthcare industries are turning to Generative AI (GenAI) for help.

GenAI is being used to secure the complex production and supply structures of the industry. For years, the global supply chains of medical technology and pharmaceutical companies were stable, but the COVID-19 pandemic and growing geopolitical tensions have exposed vulnerabilities. Companies now need solutions that allow them to negotiate fair prices and build resilient supply chains that can guarantee a steady flow of critical components and ingredients.

Initially, digital tools were introduced in procurement to streamline processes and automate routine tasks. However, GenAI’s capabilities go far beyond that. It enables a shift from reactive to proactive management: procurement teams can use AI to manage risks, precisely analyze and simulate costs, and develop long-term sourcing strategies. This gives businesses a critical advantage, allowing them to become drivers of transformation within the healthcare sector, as demonstrated by the following examples.

Companies now need solutions that allow them to negotiate fair prices and build resilient supply chains.

Example 1:Unlocking Synergies in Healthcare Services

The medical services market, including laboratories, radiology, and dentistry, is currently seeing increased consolidation, similar to the wave of mergers taking place in the pharmaceutical industry.

Companies pursuing mergers aim to realize synergy potential, with procurement playing a crucial role. However, the due diligence process that precedes mergers is subject to strict regulations. To prevent antitrust issues, companies are not allowed to share sensitive data, which often leads to incorrect estimates of synergy potential.

This is where tools like the Synergy Evaluator come into play. These tools consolidate and anonymize data from the merging companies in a legally compliant manner. Using qualitative and quantitative benchmarks, the tool analyzes spending across various categories, identifies opportunities for optimization, and creates transparency around future cost structures. The newly formed procurement team can then use this information to launch synergy projects as early as day one of the post-merger integration.

Example 2: Ensuring Supply Chain Security for APIs in Pharma

Since the supply chain disruptions of the COVID-19 pandemic, many pharmaceutical companies have significantly improved their risk management processes. Today, most have well-defined procedures and risk committees to address challenges swiftly and involve senior management when necessary.

However, these risk management systems often focus on broad market or category risks. For highly critical materials such as Active Pharmaceutical Ingredients (APIs), early detection of risks is rare, even though APIs face substantial risks. Due to regulatory constraints and lengthy approval processes, APIs are often subject to single-source dependencies. This creates a significant vulnerability if a supplier cannot deliver or uses their market power to impose excessive price increases.

Given these risks, it’s crucial to assess the specific risk for each API individually. A specialized GenAI tool can generate a unique risk profile for each API by evaluating the probability and potential impact of various risks. For instance, the tool assesses factors such as revenue, gross margin, and product strategy, including patent status and the availability of alternative medications.

To assess risk probability, the software analyzes factors such as quality, price, and supply risks. These include the potential for a supplier to become insolvent or for a country to impose export restrictions. The tool also evaluates the likelihood of delays or quality issues based on internal data, while external sources like ESG scores, commodity prices, and country reports inform price risk assessments. With this comprehensive risk profile, companies can take targeted measures to mitigate risks for each API and minimize disruption.

Many pharmaceutical companies have significantly improved their risk management processes.

Example 3: Creating Transparency with Should-Cost Models

Procurement professionals in the medtech and pharmaceutical industries often lack detailed insights into the actual cost structure of supplier products. Typically, they can only estimate costs based on materials, production, and overhead, making it difficult to counter supplier claims about rising material costs. In single-source situations, the lack of competition adds further complexity.

A GenAI-powered should-cost model offers a solution by calculating the cost dynamics of a product, allowing for fact-based negotiations. These models incorporate data such as raw material costs, energy prices, and labor expenses in the production country. Should-cost models are useful not only for negotiations but also for analyzing global sourcing options, such as when deciding between nearshoring or offshoring. They can also identify opportunities for material substitution or product redesign, creating additional value. 

 

CONCLUSION

Generative AI is already playing a vital role in making healthcare more cost-efficient, unlocking synergies, and ensuring supply chain security. By providing the ability to evaluate data, quantify risks, and analyze cost structures, GenAI is shedding light on previously opaque areas of the healthcare sector.

Companies in medtech, pharmaceuticals, and healthcare services should leverage this potential. The savings generated through these efficiencies can be reinvested into research and development, contributing to the ongoing advancement of public health.

Authors

Nicolas Willmann

Managing Director

is a Managing Director at Inverto in Cologne and responsible for our Healthcare business, advising clients on transformation projects, cost-down programs, and mergers & acquisitions.

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Sabrina Morton

Principal

is a Principal at Inverto in London, specializing in biopharma companies and complex transformation projects, including procurement model redesign.

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