Opportunities to leverage big data analytics and machine learning within Product Supply. Topic could be broad to identify and evaluate multiple opportunities or could focus on 1 or 2 specific areas (e.g. Supply Chain).
“Big Data Analytics” which incorporates new approaches to managing integrating and analysing data offers tremendous potential to the pharmaceutical industry and Novo Nordisk specifically. By leveraging data more effectively opportunities exist to enhance operational excellence improve risk management and increase customer engagement. In Pharmaceutical product supply the first two areas are particularly relevant. Possibilities include implementing mechanisms to capture consolidate and evaluate production data to improve product quality and manufacturing yields. At a more advanced level we could leverage real-time sensor data and machine learning techniques to pin-point quality issues before they become critical.
How are other companies using big data analytics in manufacturing and supply chain? What is the value proposition of leveraging big data analytic within production (e.g. impact on QMS leading to better product quality less waste better utilisation of equipment less consumption of materials giving better output reduced costs)? How does Novo Nordisk’s maturity compare? What are the best opportunities for Novo Nordisk in this area? What would be a realistic roadmap to pursue? What are the barriers to achieving the roadmap?
Your particular profile and expertise as well as your area of interest will dictate the focus area for your thesis. As a possible candidate we expect you to meet the following criteria:
Please send your applications via online form by providing up to 150 words proposal to the case and by attaching the CV of yours (and your partner). Applications are being screened on an ongoing basis where the latest date to apply is 30th of October 2016. We are looking forward to start a collaboration with you!