The Benefits of Self-Service Business Intelligence Tools
- Operational Efficiency
Empowering analytics users to find the answers they need without help from IT streamlines operations. Users don’t need to interrupt workflows to request analyses, and the analytics team can focus on strategic objectives rather than reporting for teams throughout the organization. The time savings can be significant—up to 60% less dependence on the IT team. As a result, the total cost of ownership of data analytics can decrease by 50%.
- Better Team Alignment
Life sciences companies gain an edge from a self-service business intelligence tool that integrates with an organization’s internal data and updates automatically. That means the information the field sales, marketing, and patient services teams receive aligns with insights that R&D and the executive teams access for better collaboration.
- Personalized Insights
Traditional dashboard solutions are time-consuming to build, so it’s common for IT teams to develop them to provide generalized insights to address as many users as possible. Those dashboards don’t provide granular insights based on the user’s role or geographic region. And they certainly don’t equip field sales to personalize engagements with specific physicians. Self-service analytics that leverages artificial intelligence provides users with the precise information they need on demand.
How to Choose a Self-Service Business Intelligence Tool
Life sciences companies evaluating self-service business intelligence tools should look for platforms with these features to ensure they receive the most significant ROI.
Large language model (LLM)
In a life sciences company, very few team members across business functions are IT and data science experts. Artificial intelligence (AI) that understands users when they ask questions conversationally and responds with insights in a way that’s easy for users to understand will enable them to use the platform without help from IT and data resources.
Ensure the platform allows users to configure their dashboards easily, giving them a quick view of the most critical information. A no-code environment enables them to track insights, review visualizations, and share information without coding.
AI business intelligence tools should be trained with life sciences data. It ensures fast implementation, often only a few weeks, and the tool will provide accurate, relevant insights immediately.
Life sciences datasets may contain protected health information. With more people accessing this information, selecting a tool that allows administrators to de-identify or restrict some information to comply with data privacy regulations and protect patient data is crucial.
AI and Self-Service Are the Future of Analytics
Traditionally, analytics user adoption has been low in life sciences, often only about 30-40%. Therefore, many decisions users have made across business functions didn’t consider that. This can result in missed opportunities, wasted time and resources, and a decline in brand performance. The future of business intelligence is giving users across the organization direct access to accurate, contextual information they can rely on to improve outcomes. And when team members see performance improve, user adoption increases. In fact, with WhizAI’s self-service business intelligence tool, adoption is as high as 100%.
WhizAI’s platform is designed to address life sciences companies’ business intelligence challenges and delivers fast, convenient user experiences. Contact WhizAI to learn more about how to give users direct access to the insights they need.
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