Rethinking Data Analytics in the Pharmaceutical Industry: Turning Information Into Action

Data analytics in the pharmaceutical industry is evolving from being a compliance and reporting tool to playing a strategic role in helping take informed decisions. When used correctly, data analysis can play a big role in taking operational decisions, preventing time overruns, reducing quality related issues and unlocking Overall Equipment Efficiency (OEE) in the pharma industry.

In the recently conducted Insights Forum 6.0, David Zouggagh of Sanofi shared how the company has redefined what data can do and how they use it. By careful collection of SmartSkin data over a period of time, Sanofi has built tools that help interpret the data and solve production line problems as they occur without causing unplanned downtimes and reducing costly maintenance.

Sanofi’s novel approach to data analytics in pharmaceutical industry is transformative in the way that it focuses on interpreting and comparing data that makes root cause analysis simpler and the problem easier to solve.

Why Interpretation Is the Future of Data Analytics in Pharma

SmartSkin plays a vital role in this novel approach to pharmaceutical production optimization. The data collected by the system highlights the problem area and helps make accurate changes to equipment. A quick look at what data is being used for:

• Mapping stress patterns on the production line: The system charts the precise distribution and intensity of stress across individual pieces of equipment, revealing potential points of weakness or excessive strain.
• Identifying pressure points on the container: By correlating stress data with observations of product integrity, Sanofi can visualize specific areas where pressure is contributing to undesirable outcomes such as deformation in syringes or vials.
• Pinpointing source of glass breakage and bubble formation: The data set and analytics allows for the precise identification of mechanical stressors that directly lead to defects like glass breakage or formation of air bubbles within the product, thereby enabling timely corrective actions.
• Using visual data to drive operational decisions: The complex stress data is translated into visual representations, empowering technical and operational teams to make informed, data-driven decisions that enhance efficiency, reduce waste, and improve product quality.

Mindset Shift for Pharmaceutical Manufacturers

Whether you’re leading operations excellence or working in quality control, the Insights Forum 6.0 will change how you view data analytics.

It shows how interpreting production data can cut wastage due to defects and reduce line stoppages. More importantly, it showcases how implementing a new approach to data analytics can impact bottom lines.

Discover how Sanofi is pioneering a smarter, more actionable approach to analytics. The full webinar includes a walkthrough of their data dashboard, case studies, and a look at how they built a decision-ready analytics platform.