Accelerating Decision-Making with AI-Powered Analytics in Life Sciences to Drive Commercial Success
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Description
Legacy self-service analytics require extensive data model training and deep technical knowledge to be used effectively. The alternative is developer-driven dashboards that have too broad a scope and are not unique to each user request, territory, or country. Every new data insight requires the creation of a unique dashboard, custom-built to address the specific needs of each request. These dashboards have long development cycles and can only answer the specific analytics questions for which they are built. With existing solutions it is difficult for business teams — especially non-technical users in sales and management positions — to use reporting and analytics to its full capacity.
These problems hurt an enterprise pharma’s competitive advantage in the industry.
Join us in this interactive presentation session to hear from industry stalwarts how life sciences-trained, AI-powered analytics enables accelerated decision-making to drive commercial success.
Key Discussion Points:
- The historical role of commercial insights and the exponential evolution of data and insights and what it means for commercial operations
- Key capabilities to look for when reimagining commercial insights and the role of AI, ML, and NLQ
- The business impact of democratizing access to insights to help business users make smarter, faster decisions at significantly lower cost