A Checklist of Essential Features of the Best Business Intelligence Reporting Tools for Life Science Companies
When evaluating platforms, life science companies must ensure it has these features that will provide the most value and ROI. Businesses should choose solutions that are:
- Trained with life science data:
One of the biggest differentiators when evaluating the best business intelligence reporting tools for life science companies is domain-specificity. An AI model trained with life science data can deliver relevant, accurate insights to business users from day one. Additionally, life science organizations can implement the solution more quickly in their own environments, typically 4-6 weeks rather than the months it would take to implement a horizontal solution developed with no specific life science domain expertise.
The best analytics platforms for life science companies are enterprise-ready. They should integrate with the business systems and applications that employees use, such as Veeva, Microsoft Teams, and Salesforce. The platform should also be highly secure, allowing companies to require multi-factor authentication (MFA) to ensure that only authorized people are logging in. Global companies should also use a platform that supports multiple languages to provide the best user experiences.
- Designed for the augmented analytics consumer:
Analytics platforms for life science companies also need to facilitate analytics self-service. Staff throughout life science organizations need data insights, whether it’s to find sales opportunities, understand payer activities, or reduce the time it takes to set up and manage a clinical trial. However, many professionals throughout the organization aren’t data experts. Therefore, they rely heavily on the company’s data or IT team to create dashboards and generate visualizations and reports. The best platform for life sciences is designed for “augmented consumers,” which Gartner describes as people of all IT skill levels who leverage technology to access data insights. A platform based on a large language model (LLM) understands users when they ask questions conversationally and provides contextual answers. An augmented consumer platform gives users autonomy and frees the data or IT team to focus on other responsibilities.
What is the Future of Analytics?
Another consideration is how a platform will serve the business in the future. WhizAI’s webinar, “The Future of Analytics – Domain-Specific and Augmented,” answers questions such as:
- What are use cases ready for an augmented analytics future?
- How can companies overcome challenges to adoption?
- What data management techniques will help organizations take advantage of insights within data?
- What is the role of artificial intelligence, machine learning, and natural language processing in increasing the value of an analytics platform?
Watch the webinar on demand to learn more about the future of analytics and how to take advantage of innovative solutions today.
The Benefits of Using Business Intelligence Platforms Designed for Life Sciences
Life science teams often wait weeks or months for the data analytics insights they need. An augmented consumer platform leveraging a large language model and deep learning enables users to reduce that time to seconds. Furthermore, if users need deeper insights, they can simply ask them instead of requesting an additional dashboard.
Legacy analytics tools have limits to the data volumes and the number of data sources they can use. A platform that can analyze billions of data points in less than a second and scale without a negative impact on performance will deliver the greatest value and ROI.
Because traditional analytics platforms are slow, complex, and not user-friendly, adoption is usually low, often between 20-40%. An intuitive platform that provides accurate, reliable insight on-demand can increase user adoption to 100%.
Higher Data ROI and Lower TCO
A platform suited to life sciences workflows will result in a return on the company’s data and data analytics investment. Additionally, total cost of ownership can decrease by 50% as dependence on the data or IT team decreases, often by up to 40%.
Companies will find a variety of the best business intelligence reporting tools on the market, but only one checks all the boxes for the life science industry. Contact WhizAI to learn more about how making access to data analytics insights will benefit all pharma teams.
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