The pharmaceuticals and lifesciences industry is undergoing transformation at an unprecedented scale mainly due to the regulatory, diminishing margins, growing amount of data and push for AI. One way to keep up with this pace of change is to create a robust analytics infrastructure that will help sponsors organizations to share information more efficiently and engage everyone involved to maximize value.

Most players in our industry are still laggards when it comes to leveraging the potential benefits of analytics due to lack of appropriate technology, processes, and required expertise. To make timely strategic decisions, decision-makers need easy access to actionable information. Success lies in overcoming the challenge of legacy systems and archaic processes.

A novel approach, which will enable users to access data faster without compromising on the security, is very much needed. To that end, modern self-service analytics can help users derive actionable insights by giving them an easier and timely access to data. Read on to know-how.

What is self-service analytics?

Self Service analytics (SSA) is vastly different from traditional business intelligence (BI). While tradition BI tools require background and expertise in statistical analysis and data mining, SSA helps clinical and business professionals to access data independently. It does so by automating data access, preparation, consumption, and analysis. In a self-service analytics environment, users can create and access specific datasets and reports on demand without the help of an IT resource.

An ideal self-service analytics platform should be able to

• Ingest data (structured & unstructured) across multiple sources in real-time.
• Store, prepare and provision large volumes of data to service analytical requirements.
• Serve data to the business in a consumable format through an easy-to-use interface.
• Manage the quality, integrity, and availability of the data through robust governance.

Gartner predicted that by 2020 self-service analytics will make up 80% of all enterprise reporting. While the prediction is accurate, it is disheartening to see that our pharmaceutical industry contributes to a large chunk of the 20% population who are still to adopt. Pharmaceutical companies need to restructure their analytics models to become more agile and successful. The ones who make the transition early are sure to reap the benefits.

By leveraging a modern analytics architecture and a platform for self-service analytics that can be scaled across the enterprise, these organizations would transcend from traditional reporting and business intelligence tools to automate data preparation and advanced analytics capabilities.