2021-06-24-埃森哲-Six_building_blocks_for_digital_R_D_in_chemicals_17页_2mb

Evolution of Digital R&D in Chemicals Industry

Digitalization is transforming the chemical industry's research and development (R&D) by enabling more efficient, cost-effective, and innovative processes. Advances in technology have made it feasible for chemical companies to adopt digital tools that were previously impractical, helping them accelerate innovation, reduce costs, and improve competitiveness in an innovation-driven market.

The key building blocks identified for future digital R&D include:

• Search and content analytics for deeper insights, such as automated patent and trend analysis to support innovation decisions.
• Lab automation to enhance productivity, data consistency, and efficiency in experiments.
• Artificial intelligence (AI) to speed up ideation, product development, and market expansion.
• Quantum computing for rapid, cost-effective molecule analysis and simulation.
• Intelligent knowledge management to optimize the use of innovation-related information.
• Co-creation platforms to foster cross-functional collaboration and integration.

These building blocks can be applied to the end-to-end R&D process, from concept to commercialization, potentially reducing costs, increasing margins, improving services, and accelerating innovation. Benefits include faster time-to-market, better resource allocation, and higher success rates in development.

The business case for digital R&D is substantial; for instance, a €10 billion revenue chemical company could increase EBIT by €40-70 million through top-line growth and cost savings. However, challenges include the need for a systematic, multidimensional approach to digital transformation, addressing issues like fragmented technology use and lack of integration.

To move from physical to fully digital R&D, companies should evolve along paths of ideation, connectivity, process, analytics, and skills. Initial steps involve creating a vision and roadmap, building a state-of-the-art data platform, and executing with agility, supported by external partnerships. This evolution requires moving beyond isolated projects to integrated, AI-enabled, and highly automated R&D functions that drive competitiveness.

Digital R&D represents a shift from isolated practices to a cohesive strategy, offering the potential for significant economic value but demanding comprehensive planning and execution for success.