Article | January 31, 2024

DataOps For Manufacturing: A 4-Stage Maturity Model

Source: HighByte
Pharma Manufacturing GettyImages-1135140594

The concept of Pharma 4.0 has led life sciences manufacturing leaders to envision a future where real-time data access transforms operational efficiency, agility, and compliance to produce high-quality drugs faster and at a lower cost. However, many manufacturers face challenges when early-stage successes give way to larger projects that struggle to scale due to limitations in their data infrastructure. This is where Industrial DataOps can make all the difference.

Data operations, or DataOps, involves orchestrating people, processes, and technology to securely deliver reliable, ready-to-use data to all the necessary systems and people. In life sciences manufacturing environments, DataOps solutions are crucial as data must be gathered from various assets and systems and subsequently leveraged by business users throughout the organization and its supply chain.

Explore a maturity model, created to help you better understand where you are on your DataOps journey and how to achieve the results you expect. This four-stage process encompasses data access, data contextualization, site visibility, and enterprise visibility.

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