How AI Solves Pharma’s Data Disconnect

By Rohit Vashisht

Competition in the pharmaceutical industry is driving a race to collect the most data and build the most comprehensive analytics. Theoretically, the more data available for analysis, the more meaningful insights for sales reps and commercial teams – and the best shot at increasing market share. 

Pharma companies’ healthy appetite for data is great news for data brokers. These businesses have built billion-dollar revenue streams from data collected from hubs, pharmacies, and payers and now even going to healthcare-related software, wearables, and Internet of Things (IoT) applications. The pharmaceutical industry has discovered, however, that even after purchasing data, cleaning and mapping it, and implementing business intelligence (BI) tools, the return they get falls short of expectations. 

The millions of dollars that a pharmaceutical company invests in people, processes, and technology with the goal of actionable insights for its commercial team is, in many cases, still not enough to move the needle. Most analytics applications typically have low adoption rates among sales users. They’re time-consuming and require using multiple, complex dashboards — no technology investment produces ROI if no one uses it. 

Moreover, current solutions fail to scale. I spoke with leadership at one company that has access to billions of records for one therapeutic area alone. With current analytics technology, their team must perform piecemeal analysis, using multiple applications and counting on people to extract insights from hundreds of dashboards and reports. 

These issues, among others, contribute to what Gartner research has found to be a $48 billion loss annually as companies chase illusive data analytics ROI. 

Adding insult to injury, while companies are struggling with legacy BI, other pharmaceutical companies are beating their sales team to the field. While their teams are using analytics processes that take weeks to return actionable insights, a competitor is somewhere already talking with a physician who will prove to be the top opportunity in market. 

Businesses that solve the data-to-insights disconnect for their teams are poised for a big return. 

What AI Does for Pharmaceutical Companies

Artificial intelligence (AI) bridges the gap that currently exists between massive data stores and actionable insights that pharma commercial teams can – and will — use. First, business intelligence via AI-powered cognitive insight tools are fast. AI can find the proverbial needle in the haystack in seconds, using billions of records to find opportunities, show a sales rep the best way to engage a prospect, or identify the signs that an account is at risk. What is humanly impossible to accomplish, e.g., instantaneously determining which healthcare providers are leading in new or total prescriptions at ZIP code level, is routine for AI. 

Additionally, everyone throughout the pharma company’s organization, from executives and sales to operations and brand managers, can access those insights from a single source of truth. As such, AI improves alignment across the organization, facilitating the flow of information and enabling different teams to work in concert. Home office gets real time insights into sales needs, and can adjust or prioritize projects that would make the biggest impact in the field.

Pharmaceutical commercial teams also benefit from the inherent features of AI. AI works in real time, not in legacy BI tools’ realm of using aged data and taking weeks to analyze it. In fact, AI can use a business’ internal sales or customer data in real time to provide the most up-to-date analysis. AI technology is advanced enough to learn each user’s behaviors and the types of information that they need so that it can provide insights proactively. In addition, it can send alerts when pivotal changes occur in the market that the user may not even be aware of.

Also, AI systems are built to scale. There’s no limit to the data sources or number of records you can use. This fact takes the pressure off pharmaceutical companies’ data teams wondering how they’ll meet their sales team’s current demands and how they’ll possibly keep up as new data, such as from healthcare wearables, IoT, and other sources, continually become available.  

The Sales Team of the Future

With AI specifically trained for life sciences, commercial teams can adopt completely new processes. Teams don’t have to undergo extensive training on how to use legacy BI dashboards and rely heavily on their IT or data teams for help. Everyone in the organization, from sales, marketing, and market access to managers and executives, can make data-based decisions and use cognitive insights from AI in only seconds. 

Furthermore, a next-gen BI tool powered by AI adapts to the sales rep, learning their market, customers, goals, and hot-button issues and serves up the insights they need instantaneously. AI frees sales reps to work the way they want to, rather than chaining them to dashboards for hours they’d rather spend face-to-face with accounts. And because AI expedites the time from data acquisition to actionable insights from weeks to seconds, they’ll also find much more time to spend with those accounts.   

By providing insights that lead to timely access to opportunities, pharmaceutical companies can develop sales teams that are well-informed, agile, and effective. They’ll also see a return, not a loss, on their BI tool investment as well as the ability to scale data analysis easily as new data sources are available. Their teams will have the ability to be first to move on an opportunity, close deals and win market share. 

Moving forward with AI, more data truly can be a benefit, not a burden, for pharma’s commercial teams. 

About the Author
Rohit Vashisht is the co-founder and CEO of WhizAI, the first and only purpose-built cognitive insights platform for life sciences. He has over 20 years of experience in enterprise software sales, product management, development, and strategy. As a serial tech entrepreneur, Rohit has built successful businesses and was CEO and co-founder of Sverve – an influencer marketplace that was acquired by Bloglovin and rebranded as Activate. At Sverve, he led the revenue growth and development of a self-serve platform connecting brands and influencers for marketing campaigns. At Activate he spearheaded product, sales, and marketing strategy to grow the influencer marketing business. A seasoned tech entrepreneur, he founded a fintech startup, held leadership roles at an enterprise software startup that grew to a $30M business, and executed profitable strategies at Vista Equity Partners product management group. Rohit holds an M.B.A from the NYU Stern School of Business and an engineering degree from I.I.T, Delhi. When Rohit is not in front of his laptop, he can be seen reading non-fiction, playing cricket and golf, or speaking at industry events.