Life science companies are seeking ways to make pharmaceutical business intelligence more user-centric. The easier it is for business users to consume data analytics insights, the more likely they will be to build data-driven decision-making into their workflows. Subsequently, a pharma company will improve key performance indicators (KPIs), including faster innovation and time to market. More importantly, it can deliver effective drugs and treatments to enhance patient outcomes. However, providing user-centric pharmaceutical business intelligence insights has persistently been a challenge in the industry.
One way to make it easier for business users to consume information is with data stories.
What Are Data Stories?
Data storytelling is communicating data analytics with insights and compelling visualizations. Data stories frame pharmaceutical business intelligence with context and personalization. They begin with a complete data analysis, using all available data sources to help create an accurate picture. Then, they deliver pharmaceutical business intelligence in an easily consumable and actionable way. Business users can refer to a chart, graph, or diagram and immediately understand relationships, values, and trends.
For example, a pharmaceutical sales team may want to know the performance of a particular drug last quarter. When the team sees a decline, it can turn to data analytics to understand what’s changed. Sales reps can turn to the analysis of prescription adherence, patient-level data, the number of new prescriptions, competitor activity, or other factors that could have impacted sales.
Getting to the Conclusion Faster
Creating a data story seems easy in theory, but it’s traditionally not been easy in practice. Legacy BI dashboard solutions take time to build and have limited scalability. Therefore, it often takes time to tell just a part of the story. Researchers, marketers and sales reps, market access teams, and other users who need pharmaceutical business intelligence for decision-making may receive a report or search through a cascade of screens to find answers to their questions.
Furthermore, a team may determine they need to dig deeper. For example, take a closer look at a specific geographic region or analyze prescriptions at the physician level. It may take another dashboard and more time to get the answer.
However, a pharmaceutical business intelligence platform that leverages forms of artificial intelligence (AI) can analyze data exponentially faster than legacy solutions. In fact, the WhizAI platform can analyze billions of data points in less than a second. AI platforms are also highly scalable, enabling pharmaceutical business intelligence based on unlimited data sources and volumes. Additionally, platforms that include natural language processing (NLP) capabilities allow users to ask questions in natural language and receive contextually; relevant insights presented optimally.
The Benefits of a Domain-Specific Pharmaceutical Business Intelligence Platform
To create a meaningful data story, however, a platform must be capable of understanding what users are asking. The best strategy is to train the platform’s machine learning model with life science data when this industry requires analytics and insights. Developers who take this approach provide platforms that can provide life science analytics insights out of the box and deploy in only a few weeks. AI platforms that aren’t life-science specific require months of training and testing to begin to provide value to a pharmaceutical company.
Moreover, domain-specific pre-training and a model with advanced linguistic and deep learning capabilities that understand users’ intent will generate data stories that resonate and help users build data-based decision-making into their day-to-day workflows.
The most relevant, actionable data stories come from intelligent platforms pre-trained for life sciences.
Life science teams must understand the story quickly to do their jobs effectively. Next-generation pharmaceutical business intelligence from WhizAI can provide actionable data stories to business users.