By Aparna Seksaria, Global Practice Lead R&D Solutions – Life Sciences, SAP
The keys to leaving behind the competition and promoting organizational growth are changing significantly in the pharmaceutical industry – even to the extent where data and technology investments are emerging as pivotal factors in differentiation. Among midsize life sciences companies surveyed by IDC, 51% cited enabling digital transformation initiatives as their top business objective.
From attracting the attention of larger pharmaceutical enterprises for acquisitions to providing superior customer experiences and increasing customer loyalty, these companies have recognized the inherent value of having a robust IT infrastructure.
They’re not only unearthing new growth opportunities and enhancing services and product personalization, but also fortifying their supply chains and carving a path toward ongoing success in an increasingly diverse and competitive landscape.
Now, artificial intelligence (AI) presents new opportunities to advance into the next phase of their digital transformation journey. However, this latest development is more than just adopting recent technology or improving current practices. It’s forging a future where new ideas and higher success rates lead to a better understanding of innovative personalized medications and quicker, smoother launches of new life-saving therapies.
Adding a new cornerstone to the value paradigm
Midsize life sciences businesses wield a distinct advantage in their ability to adapt quickly, pivot deeply, and implement operational changes swiftly, compared to their larger competitors. Integrating AI into their processes, workflows, and business systems can enable more-efficient operations that yield faster and more-strategic outcomes.
For example, the synergy between AI adoption and the life sciences value chain will help scale R&D and production capabilities with real-time impact on demand and supply changes. Over time, firms can streamline operations and enhance decision-making through data-driven insights – both are pivotal for a competitive edge in promoting growth and efficiency.
Discover how digitalizing processes, products, services, and business models can be crucial to the growth of your midsize life science business. Read the IDC info snapshot, “Midsize Life Sciences Businesses Look to Supercharge Growth
No matter how critical, such changes often emerge through incremental steps of AI adoption rather than a singular transformative leap. By concentrating on smaller components and measuring results in manageable pieces, firms can realize quick wins in critical areas including planning, transportation management, sourcing, and procurement and build on them to offer uniquely differentiating value.
Cheerland Biotechnology Investment Co. Ltd. is a prime illustration of how AI amplifies the value of growing life sciences businesses. The company tightly integrated its operations by adopting a cloud ERP solution that offers AI, machine learning, robotic process automation, and support for integrated finance, supply chain, manufacturing, and sales and distribution processes. This includes removing internal barriers, applying rigid data protection and security practices, and enabling data-driven decision-making through access to rich data and analytics.
All these changes enabled Cheerland Biotechnology to achieve critical improvements, including 30% higher supply chain efficiency and 50% fewer current good manufacturing practices (cGMP) tickets.
Refocusing traditional ROI metrics toward value centricity
The full realization of AI’s potential relies on developing and adopting ROI metrics for digital investments that are unique to the business’s ecosystem. By steering away from traditional quantitative metrics such as cost reduction, product capacity, time to market, and revenue margins, businesses can deepen their understanding of value creation over a much longer time horizon.
This value-based mindset is particularly critical because AI impacts diverse business areas with smaller, tangible outcomes rippling throughout the business. These outcomes require nuanced evaluation that breaks down each contribution into measurable components – such as improving productivity, enhancing customer experience, and refining operational efficiency.
Interestingly, the case for value-based analysis isn’t entirely novel. It resonates deeply with existing industry methodologies for R&D, clinical trials, and other research-related activities managed with complex operational frameworks, stringent regulatory governance, and diverse ecosystem dependencies.
By applying this value-based approach to AI investments, companies can further transform their operations. They can better understand how to drive efficiency, speed, precision, and advantages where every moment and investment counts – especially in supply chain planning, scheduling, production processes, vendor selection, and delivering patient care.
Redefining an industry with real-time intelligence
As midsize life sciences companies continue to harness AI’s transformative potential, a nuanced focus on tangible outcomes amplifies their role in reshaping the industry’s competitive landscape. This evolution not only underscores the significance of technology but also heralds a future where AI-led innovations redefine the boundaries of possibility in advancing healthcare and scientific endeavors.
Discover how digitalizing processes, products, services, and business models can be crucial to the growth of your midsize life science business. Read the IDC info snapshot, “Midsize Life Sciences Businesses Look to Supercharge Growth,” sponsored by SAP (IDC #US50427323, March 2023).
