The Health Pulse: In life sciences, change is hard but worth it when it comes to digital transformation.
On this episode, Greg chats with SAS EMEA life sciences sales director Jonathan Riches about digital transformation in pharma. Jonathan argues that while buzzword technology like artificial intelligence (AI) and machine learning get a lot of attention, it’s really culture that determines an organization’s success with digital transformation. Why? The life sciences industry is highly regulated by necessity, and many pharmaceutical companies have been around for one hundred or more years. So, while change is challenging for any organization, it is especially challenging for pharma. According to Jonathan, life sciences organizations must back up their analytics evolution with ample training, empowerment around individual growth and C-level commitment to data-driven decision making. For 20 years or more, pharma has been using analytics and statistics to prove the efficacy and safety of drugs in order to obtain regulatory approval. There is now recognition that analytics can glean much deeper insights throughout the pharmaceutical life cycle. This kind of evolution requires significant change-management. Jonathan advises pharmaceutical companies to design data and analytics platforms for the business challenges they need to solve.
On this episode, Greg chats with SAS EMEA life sciences sales director Jonathan Riches about digital transformation in pharma. Jonathan argues that while buzzword technology like artificial intelligence (AI) and machine learning get a lot of attention, it’s really culture and change-management that determine an organization’s success with digital transformation. Why? The life sciences industry is highly regulated by necessity, and many pharmaceutical companies have been around for one hundred or more years. So, while change is challenging for any organization, it is especially challenging for pharma. According to Jonathan, life sciences organizations must back up their analytics evolution with ample training, empowerment around individual growth and C-level commitment to data-driven decision making. Greg points out that we see this in health care as well, where most medical providers don’t go to school to be data scientists, but they are evolving in their roles to use data and analytics more. And in pharma, Jonathan points out that we’re seeing more recruiting from other sectors such as retail, CPG and banking in order to leverage learned experiences from those industries. For the past decade or two, pharma has been using analytics and statistics to prove the efficacy and safety of drugs in order to obtain regulatory approval. There is now recognition that pharma can go much deeper by leveraging real world evidence in clinical development or forecasting analytics in demand planning. This kind of evolution requires changes and new skills to job roles within pharma. Greg and Jonathan also discuss the complexities of supply chains in pharma where specialty therapies often need to be produced near the patients they will treat. Jonathan offers his advice for pharmaceutical companies who want to accelerate digital transformation. The projects need to be led by the business and business challenge with collaboration and support from IT. Start slow and design data and analytics platforms to the business challenges they need to solve. Finally, Jonathan offers his predictions for the future of transformation in supply chain, digital engagement with health care providers and even patients, real world evidence, devices, personalized medicine, and collaboration and data sharing across the value chain.
All presentations represent the opinions of the presenter and do not represent the position or the opinion of SAS.
All presentations represent the opinions of the presenter and do not represent the position or the opinion of SAS.
