The volume of digital information on patients, healthcare systems, research, clinical trials, manufacturing and supply chain processes, marketing activities, financial forecasts and social media is growing rapidly. The ability of Big Data analytics to detect patterns, generate predictions, assess risks and test hypothesis based on this enormous volume of data, is turning this technology into a key management decision tool for Life Sciences companies, both in the R&D and the commercial context.

Big Data can be used in a variety of ways to gain insights and support business decisions.

Product Traceability

Today’s industrial production lines are constantly monitored by computer controlled sensors while modern logistics systems ensure the real time traceability of products during distribution up to the point of sales. As digitization continues, both manufacturing and distribution processes, will generate increasingly large internal and external data sets. Given accessibility and adequate integration, these data sets can be used to trace each product component back to its source and date of production/purchase, thereby enabling maximum transparency and control in the case of product quality issues/recalls.

Third Party Risk Management

Third party due diligence analytics use external and internal data sources to generate and analyse indicators which allow a quantitative and qualitative assessment of third party risks. Such algorithm-based assessments enable staff to focus on those third parties that require individual in-depth reviews. This reduces the amount of time required for third party due diligence and improves the quality of outcomes.

Real-time Social Media Analysis

Social media data is generated by people whose circumstances, motives and objectives are unknown and might change suddenly and frequently. In this quagmire of social media data lies its value. Targeted systematic social media crawling is able to provide a continuous stream of information on new market trends, changes in consumer behaviour, consumer perception of products, marketing campaigns etc. This technology can provide unprecedented insights into business trends: for instance, the “sonar map” developed by the Bottlenose social media sentiment-analyser highlights connections that might not be obvious at first glance.

It is important to integrate the underlying tools into the wider IT and organizational set-up. From an organizational perspective, it is essential that these technologies are embedded into existing processes - who uses the tool, for what purpose and what are the information flows?

The possibilities are endless. The tools are available. It simply needs a coordinated approach to harness the power of Big Data in Life Sciences.

To request copies of the KPMG Publications „Deal Capsule“ or „What next for Pharma?“, please contact Katharina Ashauer, Chemicals and Pharmaceuticals, Tel.: +49 201 455-6826.