Novartis came to us with a strategic challenge: “What should our commercial organization look like in the future?”
Having the best foundational insights for building a future organization that is competitive in the Nordic markets, attracts the right talents, and enables a culture that will successfully execute commercial operations is key for any data-driven pharma company.
With a clear picture of the insights they needed to shape their strategy – from headcounts to the composition of the workforce, Novartis also wanted to uncover opportunities for partnering with HelthTech companies as well as how their company structure fit into the new young workforce.
In a project like this we felt it necessary to think out of the box. And luckily, we have a lot of masterminds at DLIMI who do this every day, and we joined some skewed competencies – so what happens when a PhD in Food Sociology collaborates with a computer scientist?
The project consisted of a qualitative and a quantitative analysis. To explore development in capabilities, we conducted interviews with commercial roles in leading pharma companies in the Nordics as well as explored how partnerships within HealthTech. In the quantitative analysis we mapped headcounts as well as job descriptions in pharma companies across the Nordics by scraping unstructured online data on commercial job titles, job postings which provided us with insights to competencies required for various commercial positions within affiliates in the Nordics.
Using data science we could transfer the combination of qualitative and a quantitative data, and a network of main competencies for all commercial functions was unlocked. Looking at how job functions developed over time we could – in detail – paint a picture of how job functions are likely to develop in the future. For example, how the role of Market Access has evolved over the past 10 years, and which competencies are in now play for this role.
Another key finding is the trend towards more open teams in a network-based organization. Novartis used the results of the analysis as part of to confirm / disprove their own hypotheses, as well as an eyeopener to how to work more holistically in the future