Digital acceleration in industrial R&D

Data and AI are transforming R&D, leading to new innovations, improved processes, less waste, and faster time to market. But successfully building a portfolio of data science and AI projects is challenging, with too many projects still falling short of expectations.

Our new white paper shows how to get this right. It draws on a wide range of data and AI projects – across CPG, chemicals, agri-business and manufacturing industries – to explore the factors that deliver success.

Its lessons include:

• How to decide which data projects to take forward
• How to ensure the right data is generated, prepared, controlled and made accessible
• How to select the tools to get the answers you need
• How to deliver applications that withstand real-world use
• How to bring it all together for rapid results