Evolving regulatory environments, customer demands, pricing conundrums and blurred boundaries are changing the life sciences industry.
As noted in our report, Life Sciences 4.0: Securing value through data-driven platforms, life sciences companies must adopt agile, data-centric business models to create value now and in the future. They must build ― or participate in ― interoperable information systems that collect, combine and share streams of data. In this new era, where value creation is no longer just about the products, life sciences supply chains must transform to enable organizations to create and deliver shared value focused on personalized outcomes and fueled by unlocking the power of data.
To quickly attain this state, life sciences supply chains must first address the lack of planning, visibility and integration that result in high costs and skyrocketing inventory as well as shortages in other areas. End-to-end (E2E) supply chain transformation must now be undertaken to enable life sciences organizations to deliver on the new business models. However, this is not an easy or fast journey. It includes everything from suppliers to outsourcing providers to end customers ― the actual patients. It is a multiyear journey that requires considerable leadership support, cross-functional collaboration and a strong change management program to be successful.
The transformation journey
E2E supply chain transformation is a journey that integrates, synchronizes and builds trust among the supply chain and its partner functions, such as product groups, finance, commercial and marketing to deliver on the corporate supply chain strategy and to achieve business objectives. Deep-rooted functional silos in the industry have resulted in a fragmented model, where different functions own different processes of the supply chain. Often, a lack of coordination among the different functions and processes result in supply chain issues such as excess inventory, stockouts for in-demand inventory and obsolescence. Life sciences companies’ increased reliance on a global network of suppliers, logistics providers and contract development and manufacturing organizations (CDMOs) adds complexity. Therefore, it becomes crucial to first understand the current state of the end-to-end supply chain ― from the supplier to the patient.
A comprehensive, data-driven diagnostic exercise, such as one from EY SmartMaps, must then be undertaken to understand the root causes of supply chain issues. The diagnostic should be performed not only in functions related to the supply chain but also for functions peripheral to the supply chain, such as commercial, marketing, sales, finance and R&D. Such a comprehensive diagnostic can uncover underlying causes of supply chain issues. Using this methodology, many of the leading life sciences players can identify that a function-oriented approach and/or independent planning processes are potential causes of their supply chain problems.
Based on the assessment of the diagnostic, companies can then build an effective transformation road map, which should start with having a robust supply chain strategy and vision in place. Amid the need to fulfill their customers’ orders, quite often life sciences companies struggle to identify the right supply chain strategy for their business: one that is aligned with their overall corporate strategy and the business model. Many transformation efforts fail because companies try to improve multiple aspects simultaneously ― speed, reliability, flexibility, cost and return on assets ― or often choose the wrong attributes. Optimal value will come when companies segment and design their supply chains to match the demands of the different business models. The Life Sciences 4.0 report describes four broad business models for the industry: breakthrough innovator, disease manager, efficient producer and lifestyle manager (refer to the report for details). To successfully address changing customer needs, life sciences companies must design their supply chains to make the appropriate trade-offs among the five attributes, in alignment with the organization’s chosen business model.