Augmented Analytics Debuts on Gartner’s Hype Cycle for Life Sciences Commercial Operations, 2022
Augmented analytics for life sciences appeared on Gartner’s Hype Cycle for Life Sciences Commercial Operations for the first time in 2022. By giving employees, regardless of their data science expertise, easy access to insights, augmented analytics shows promise as a valuable addition to life science tech stacks.
This technology addresses the challenge that organizations face from increasing numbers of data sources and volumes measured in petabytes. Augmented analytics platforms provide life companies with scalable, centralized repositories for data for all analyses. Furthermore, platforms that leverage machine learning can analyze data in a sub-second, decreasing the time from data acquisition to insight.
Rohit Vashisht, CEO and Co-Founder of WhizAI, explains, “Innovation is vital to life sciences. They need to advance research, discovery, and development of drugs and treatments. But they need practical ways to manage operations. Augmented analytics can help them do it.”
Building a New Relationship with Data Analytics
Business intelligence solutions have created challenges for life sciences companies for over a decade. Using legacy processes, users interact with insights through static dashboards or Excel reports that provide limited insights. Additionally, dashboard solutions require a data team’s time and expertise to uncover insights, making analytics consumers dependent on them for the information they need.
With augmented analytics for life sciences, on the other hand, users have autonomy. They can build data-driven decision-making into workflows with easy access to insights from their PCs, laptops, or mobile devices.
Vashisht points out that although many of the augmented analytics platforms listed in Gartner’s Hype Cycle report leverage AI, “The type of AI matters.” For example, when augmented analytics platforms include natural language query (NLQ) and natural language generation (NLG) models, users can ask questions naturally rather than using keywords or phrases. Additionally, when models are pre-trained for life sciences and built by a team that understands the industry, the platform responds with relevant, contextual insights. Life sciences users interact with the platform conversationally and can focus on the answers it provides, not the technology that makes them possible.
It's worth noting that the augmented analytics platforms Gartner lists in its Hype Cycle report take different approaches to how analytics consumers interact with data. For example, WhizAI enables users to build Pinboards within the platform’s no-code environment, allowing them to query, analyze, and share insights without switching between different systems.
Vashist explains, "WhizAI married natural language query and sharable which aligns best with the way life science users work.”
“Emerging,” Yet Proven, Technology
The life sciences industry is known for being risk-averse, which has led Gartner to question how long it would take to adopt this new technology. However, in WhizAI’s experience, it doesn’t take long.
When companies deploy WhizAI, users experience first-hand how easy it is to use, the accuracy and relevance of insights, and enhanced job performance from on-demand data insights.
“Life science user communities may not all be well-versed in data science and technology, but they know their business very well,” Vashist says. After only a few minutes of training and a few days of use, WhizAI users see it’s an analytics platform they can trust.
As a result, WhizAI has already built a user base of thousands, employed by some of the largest pharmaceutical companies in the world. Moreover, companies see as much as 100% adoption of the platform.
Life sciences companies reviewing Gartner’s 2022 Hype Cycle for Life Sciences Commercial Operations might interpret augmented analytics solutions for the space as the newest innovation years away from mainstream adoption. The reality is, however, that this technology is helping analytics consumers in life sciences make decisions every day – and giving their organizations a competitive edge.
“We want to encourage life sciences companies to try augmented analytics,” Vashist says. “Don’t wait.”
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