Life Science Intelligence that Keeps Up with a Changing Industry
The healthcare landscape is growing more complex, necessitating a new approach to life science intelligence. Mergers and acquisitions (M&A) and physicians choosing to work independently continually change who decision makers are. At the same time, life science commercial teams represent a wider range of products, from drugs that address ailments that affect people throughout the population to personalized medication meant to treat only a few thousand people.
WhizAI enables companies to overcome the hurdles they face with business intelligence (BI) dashboard solutions and gives employees throughout the organization easy access to the insights that help them enhance their performance.
The WhizAI Life Science Intelligence Solution
WhizAI solves life science intelligence business problems, including:
Building dashboards, analyzing data, and digging deeper for additional insights can take weeks or months from the time a company acquires data until employees can get the actionable answers they need.
WhizAI analyzes billions of data points from multiple data sources in less than a second to enhance workflows and processes, not slow them down.
Legacy life science intelligence dashboards don’t scale very well, resulting in teams using multiple screens to try to piecemeal analyses for the insights they need.
WhizAI’s platform easily scales to add new data sources and analyze larger data volumes, removing limitations that data teams face with their legacy systems. Furthermore, they can access those insights from the applications they routinely use, such as Salesforce, Microsoft Teams, or Veeva.
Although there are several business intelligence solutions on the market, even a variety that leverages artificial intelligence (AI), there is only one choice designed specifically for life sciences by a team with industry expertise: WhizAI.
WhizAI’s platform is pretrained for life sciences data so that it deploys quickly and provides contextual insights out of the box. Additionally, the workflow within WhizAI closely aligns with how life science teams organize and share data insights.
Many employees throughout life science companies have limited data science expertise, and they must spend hours in training sessions – but may still not be able to use legacy life science intelligence solutions comfortably and proficiently.
WhizAI is designed for the augmented analytics consumer. Natural language query (NLQ) allows users to ask questions conversationally, and the platform understands them and responds with contextual answers in a near instant. WhizAI’s hybrid natural language processing (NLP) engine also understands users’ intent, even if they misspell words or phrase a question in an unusual way. Additionally, WhizAI continues to learn with us, tailoring responses to user preferences and behaviors.
Case Study: Uncovering Root Causes with WhizAI
One life science company wanted to get to the root cause of why sales of a particular brand were slowing. A WhizAI user asked the question in natural language: “Why are our sales down?” The platform understood that the user was referring to TRx. Then, using patient data claims data, and other data sources, the platform confirmed that sales were slowing by presenting historical data over time.
Next, the user asked the platform to show the 13x13 change for claim counts for the brand and its key competitor. The user only had to ask – no coding or phrasing queries in a certain way were required.
The platform showed that rejected claims for the brand had increased by 17% over the specified period, but that metric was steady for the competitor. Additionally, the platform revealed that the rejected claims originated at the intermediary level, providing the company with direction to correct the issue.
Also note, WhizAI was able to provide these insights in just minutes rather than the weeks it would have taken to run analyses and build new dashboards to uncover the root cause.
What Companies Can Achieve with a WhizAI Life Science Intelligence Solution
WhizAI enables companies to achieve their goals for life science intelligence, including:
Dynamic, Omnichannel Engagement
WhizAI allows users to access data insights and share them at any time and from within the systems and applications they typically use.
With instant life science intelligence, commercial teams can pinpoint top opportunities and target their efforts with personalized, targeted marketing.
Improved Data Analytics TCO
WhizAI decreases dependence on life science data and IT teams, lowering data analytics total cost of ownership (TCO) by 60% or more.
WhizAI makes data insights available to everyone within a life science organization, enabling all teams to use current data in analyses and supporting greater team alignment.
A life science intelligence platform can only provide value if a company’s teams use it. Companies that deploy WhizAI see adoption as high as 100% due to the platform’s ease of use, accurate insights, and responsiveness.
To learn more about WhizAI’s life science intelligence platform, join WhizAI for a live demo.
Frequently Asked Questions
WhizAI Webinar Series: Part 3 - Payer & Market Access Analytics
WhizAI Webinar Series: Part 1 - Life Sciences Field Analytics
Test Automation of Augmented Analytics Systems that Employ a Conversational- AI Interface like ChatGPT
Gartner Reports Augmented Consumerization Will Drive Analytics Adoption by 2025
Life science companies considering which augmented analytics platform is the optimal choice for their organization will find a list of Augmented Analytics Tool Vendors and Products at the end of the Gartner Market Guide for Augmented Analytics.
WhizAI Deployed as a New Field Reporting System at a Top 3 Global Pharma
Better, Faster, Smarter Decisions at Lower Cost for a Top 3 Global Pharma. A top 3 global pharmaceutical faced the following challenges with their legacy field reporting system:
WhizAI Puts Sales Reps at the Center of the Analytics Process for a Leading Specialty Pharmaceutical Company
Sales reps use WhizAI data exploration to answer questions like 'Sales trends this year by region, brand (or by city, territory, GPO, COT, IDN)?' in seconds.