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The healthcare industry is responsible for generating 30% of the world’s data volume. But harnessing that data to create the greatest possible value rests on having the optimal data and analytics operating model. Without these, companies will struggle to unlock data’s full potential and gain the insights they need to power future performance and growth.
«Unlocking the full potential of data and analytics in pharma» sets out a phased approach that can help companies understand the data and analytics capabilities they need, gauge their current level of sophistication, and identify best practices for developing their future model.
Operating model design process
Download the report to read about two example case studies that demonstrate best practice approaches within the pharmaceutical industry for conducting diagnostics and defining target future states for data and analytics operating models.
- Case study 1 shows a diagnostics approach for digital and analytics capabilities within the market access function of a mid-sized biotech.
A robust diagnostics framework based around key data and analytics capabilities is paramount. This can enable organisations to develop a solid baseline understanding of itself within the industry, as well as provide clear guidance on where the main focus areas should be for the future operating model and governance design.
- Case study 2 shows the target future state design approach for the development and scaling of digital and analytics use cases in a mid-size pharma company.
Any successful data solution needs to be viable, desirable and feasible. To ensure this, there needs to be a simple but adaptable operating model and governance supporting the development and realisation of use cases for their respective areas. When designing a use-case development operating model within the data and analytics space in the pharmaceutical industry, four core elements need to be taken into account.
Download the report
https://pages.pwc.ch/core-asset-page?asset_id=7014L00000053KhQAI&embed=true&lang=en
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