An Effective Way to Provide Pharma Analytics Autonomy

Pharmaceutical companies have faced a monumental challenge: providing immediate access to insights from data analysis to people across their organizational charts. Traditional business intelligence (BI) dashboard solutions require training to use effectively. However, even with training, dashboards aren’t particularly user-friendly, and employees without comfort without data science still heavily rely on their IT or data teams for help with pharma analytics.

A strategy that will result in more users building data-driven decision making into their workflows is to deploy an augmented consumer platform. Augmented analytics not only analyze data.These platforms also use forms of artificial intelligence (AI) to make it easier for users to interact with them.

WhizAI’s augmented consumer platform for pharma analytics is built from the ground up to provide a user experience that makes data insights, not using technology, the focus.

How WhizAI Provides Easy Access to Pharma Analytics

  • Natural Language Processing Engine:
    WhizAI combines deep learning and linguistic techniques, such as natural language query (NLQ) that allows users to ask questions as if they were speaking to a colleague and natural language generation (NLG) that enables the platform to respond to users in ways they can easily understand. WhizAI is designed to deliver a conversational experience.
  • Automatic Visualizations:
    WhizAI uses cues from users’ questions and the data itself to determine the best way to create visualizations. If users prefer different visualizations, such as comparative line graphs instead of charts, they can easily update the visualization in WhizAI’s no-code environment.
  • Access from Devices and Business Applications:
    WhizAI integrates with the applications that pharma company employees typically use, such as Veeva, Salesforce, and Microsoft Teams. When employees need insights in the course of their day-to-day work, they can access WhizAI from the screens they’re already using. Additionally, users can access pharma analytics from a PC at their desks, on laptops when working remotely, or on mobile devices on the road or before onsite meetings with physicians.
  • Multilingual Capabilities:
    WhizAI gives employees in global organizations to interact with the platform in their native languages. WhizAI currently supports English and G5 languages.

How WhizAI Makes Data Analytics Processes Easier for Data Teams

When employees have pharma analytics autonomy, they need less assistance. Data and IT teams will reclaim time in their schedules to spend on higher-level tasks, such as building custom models for complex analyses that can help advance research and innovation that can improve the company’s competitive position.

However, WhizAI also benefits data teams in additional ways. They are leveraging WhizAI to eliminate writing SQL queries to determine which datasets to use in their analyses more quickly and easily.

Although WhizAI is designed for the augmented consumer, these power users are also finding that the platform is helping them perform their jobs more effectively.

Pharma Analytics Benefits, Courtesy of WhizAI


One of the biggest advantages of leveraging WhizAI for pharma analytics is the speed at which it delivers insights. WhizAI analyzes billions of data points to provide answers and insights in less than a second. Contrast this with the weeks it takes to build a new dashboard and run analyses; the competitive edge companies gain with WhizAI is apparent.

Additionally, WhizAI also makes insights instantly available to the C-suite. With the platform, it isn’t necessary to wait for an analyst to write a summary of findings, possibly interjecting bias into the report. Like all employees throughout the organization, business leaders can ask questions, drill down for information on the performance of specific brands or regions, and have the answers they need in minutes.

User Adoption

One of the biggest challenges life sciences companies face with dashboard analytics solutions is user adoption. Companies that have deployed WhizAI, providing employees with a platform that’s intuitive and fast, have increased analytics user adoption from 20% to 40% to as much as 100%.

Enterprise Readiness

WhizAI is designed for any size company and is capable of providing on-demand, contextual insights to global enterprises. WhizAI utilizes microservices architecture managed with Kubernetes for high reliability and scalability. It is also protected with enterprise-grade security and access control. It also integrates with pharma company business systems, enabling easy access and data flow.

Higher Data ROI and Lower TCO

WhizAI also enables pharmaceutical companies to finally see a return on their data and data analytics investments. Teams use data to enhance their performance and improve outcomes, and they accomplish those goals in less time with the support of fewer resources. Pharma analytics autonomy increases user adoption, enables data-driven decision making throughout the organization, and decreases the demand on IT and data teams.

Frequently Asked Questions

Is WhizAI capable of alerting users to changes proactively?
Yes. WhizAI learns users’ priorities and can provide alerts when numbers fall below or exceed set thresholds.
Does WhizAI have any limitations on the volume of data it can analyze?
WhizAI enables pharma companies to use an infinite number of data sources within one platform. It doesn’t require piecemealing analysis, even if a granular analysis is necessary.
What do companies have to do to update the platform when data sources update?
When a life science company gives WhizAI access to a data source, updates to that data are automatically reflected in WhizAI analyses.
How long does it take to learn how to use WhizAI?
WhizAI is designed to be simple for all life science users. It replaces the dashboard as the analytics unit of work with a question posed in natural language. Because it’s so easy to use, it only takes a few minutes for users to familiarize themselves with WhizAI, ask questions, and receive contextual insights.
How Does WhizAI use natural language understanding?
WhizAI is trained to understand how life science teams speak. However, it also is capable of determining intent. So, if a user asks a question in an unusual way, doesn’t complete a thought, or misspells a word when typing a question, WhizAI will fill in the gaps or ask for clarification.


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