The pharmaceutical industry is witnessing a significant shift in strategies for outpacing competitors and fostering organizational growth. Increasingly, data and technology investments are being seen as key differentiators. A survey revealed that 51% of midsize life sciences companies identified digital transformation initiatives as their primary business goal.
These companies are using robust IT infrastructure to attract larger pharmaceutical corporations for acquisitions, enhance customer experiences, and boost customer loyalty. They are exploring new avenues for growth, improving product and service personalization, strengthening their supply chains, and charting a course for sustained success in a diverse and competitive environment.
Artificial intelligence (AI) is now offering fresh possibilities for these companies to progress to the next stage of their digital transformation journey. This development is not just about adopting the latest technology or refining existing practices. It is paving the way for a future where innovative ideas and higher success rates lead to a deeper understanding of personalized medications and expedite the launch of new life-saving therapies.
Midsize life sciences businesses have a unique advantage in their ability to adapt quickly, pivot profoundly, and implement operational changes swiftly, compared to their larger counterparts. By integrating AI into their processes, workflows, and business systems, they can achieve more efficient operations that deliver faster and more strategic results.
The integration of AI into the life sciences value chain can enhance R&D and production capabilities, with real-time responses to changes in demand and supply. Over time, companies can streamline operations and improve decision-making through data-driven insights, both of which are crucial for gaining a competitive edge and promoting growth and efficiency.
However, such critical changes often occur through incremental steps of AI adoption rather than a single transformative leap. By focusing on smaller components and measuring results in manageable segments, companies can achieve quick wins in key areas such as planning, transportation management, sourcing, and procurement, and build on these successes to offer unique value.
Cheerland Biotechnology Investment Co. Ltd. is a prime example of how AI can enhance the value of growing life sciences businesses. The company integrated its operations by adopting a cloud ERP solution that incorporates AI, machine learning, robotic process automation, and support for integrated finance, supply chain, manufacturing, and sales and distribution processes. This includes eliminating internal barriers, implementing stringent data protection and security practices, and facilitating data-driven decision-making through access to rich data and analytics.
These changes allowed the company to achieve significant improvements, including a 30% increase in supply chain efficiency and a 50% reduction in current good manufacturing practices (cGMP) tickets.
The full potential of AI depends on the development and adoption of ROI metrics for digital investments that are tailored to the business’s ecosystem. By moving away from traditional quantitative metrics such as cost reduction, product capacity, time to market, and revenue margins, businesses can gain a deeper understanding of value creation over a longer time frame.
This value-based mindset is particularly important because AI affects various business areas, with smaller, tangible outcomes rippling throughout the business. These outcomes require a nuanced evaluation that breaks down each contribution into measurable components, such as improving productivity, enhancing customer experience, and refining operational efficiency.
Interestingly, this value-based analysis is not entirely new. It aligns closely with existing industry methodologies for R&D, clinical trials, and other research-related activities, which are managed with complex operational frameworks, strict regulatory governance, and diverse ecosystem dependencies.
By applying this value-based approach to AI investments, companies can further transform their operations. They can gain a better understanding of how to drive efficiency, speed, precision, and advantages in areas where every moment and investment is crucial, such as supply chain planning, scheduling, production processes, vendor selection, and patient care delivery.
As midsize life sciences companies continue to harness the transformative potential of AI, a nuanced focus on tangible outcomes enhances their role in reshaping the industry’s competitive landscape. This evolution not only highlights the importance of technology but also signals a future where AI-led innovations push the boundaries of what is possible in advancing healthcare and scientific pursuits.
For more information on how digitalizing processes, products, services, and business models can be crucial to the growth of your midsize life science business, consider reading the info snapshot, “Midsize Life Sciences Businesses Look to Supercharge Growth,” sponsored by SAP.
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