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Digital acceleration in industrial r&d

How to rapidly and safely deliver value from data science and AI projects

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 report 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