Leadership lessons from a grand endeavor: Finding answers to complex scientific questions in Healthcare R&D thanks to the innovative use of data
Back in May 2019, I was offered the incredible opportunity to dive into my current adventure: Head of data42, Novartis’ ambitious initiative to change the paradigm of healthcare data in Research & Development (R&D). My journey so far has been eventful — full of learnings and full of surprises.
We started off with the big moonshot goal of changing the way we develop medicines, the buy in of some senior leaders at Novartis and a small group of visionaries. On the backdrop vision of using digital tools such as artificial intelligence (AI) to find new ways to treat disease and improve the experience of customers and patients, we set out to create a unique platform for Novartis scientific researchers and drug developers. But more importantly: we didn’t want to just run another corporate initiative — we wanted to become a group of intrapreneurs who change the paradigm of Healthcare R&D.
If data42 lives up to its vision, its future potential is enormous. Over the past two years, we have created the first FAIR-ified, consolidated, interconnected R&D dataset, along with analytics that are powering new discovery. Our breakthrough moment came end of last year when we first went live with our platform of 2 million patient-years of interconnected clinical and omics data that was finally searchable and analyzable. Accessible, searchable R&D data in one single location open to analysis using advanced data science techniques! We had done it! Our platform was live — taking us a step closer to achieving our grand endeavor — using data to transform medicine. Our Head of Science, Sam Khalil, has summarized our journey very well in his article here, and our Head of Technology, Pascal Bouquet, looked at our agile story in his great article here
Two years into the journey, when reflecting on this venture into new territory, I have wondered what the key ingredients were that enabled this breakthrough. What were the behaviors and attitudes which have helped bring our innovative vision into being? Six key learnings have come to mind:
Too many Red Oceans distract from the Blue Ocean
In their book “The Blue Ocean Strategy”, the two authors Kim & Mauborgne argue that instead of focusing on Red Oceans — the known marketplaces — we should conquer the Blue Ocean — uncontested market space — thereby making the competition irrelevant. Hence, in my first year at data42, we spent a lot of time on articulating that Blue Ocean for us, which resulted in multiple iterations of vision, mission and purpose statements, and a drill down into relevant products and customer groups.
The Blue Ocean will lead us into the future and will be game changing.
When ambiguity becomes the norm
data42 is entering unchartered territory. There is no cookbook for transforming Healthcare R&D into a data driven organization. How to live in a world where there is no reference from the past, where there are no stable processes to rely on and where there is no clear target? What helped me was: Getting input and advice from multiple sources and diverse points of views (including many thought leaders outside of Novartis), articulating the end goal and constant communication in all directions, with full transparency on what was clear and what wasn’t.
Too much stability slows down. Use ambiguity as a driver and motivator for personal change.
I had no idea how important this lesson is. I invested a lot of time in intense stakeholder management. One day we made the effort and counted more than 300! individuals who we would have to connect with on a personal and regular basis. Managing stakeholders was like paying into a savings account and not knowing when you will need the money back. There were moments in the first year when I needed to “withdraw” from a few of those investments and it paid off.
Personal relationships matter — a lot, especially in complex setups with no clear decision rules.
Less is more — focus, focus, focus
In a space like data42, the amount of opportunities is vast. And the wish list of topics to take into scope was getting longer and longer. Examples were data governance, R&D data landscape, agile methodologies, approaches to shift from project to product organizations, etc. All of them great topics, but all of them not really helping us with our end goal. Hence one of my biggest learnings is: Be clear on what you want and can do, and then say no to everything that is not part of that plan. It sounds simple but is hard to do.
Focus on the things that matter. Stay the course and always keep the end goal in mind.
Leaders need to adjust their decision-making to the context they operate in, which can be anything from simple, to complicated, complex and chaotic. (“A Leader’s Framework for Decision Making”, D. Snowden and M. Boone, 2007) Although at data42, it felt chaotic at times, in many cases I actually faced a complex context — which called for interactive communication, clarity on what is allowed and what not, encouragement of dissent and diversity, and a culture of letting small ideas grow. These principles have since formed the basis of my decision-making.
Be clear on the context of decision-making. Complex environments require different decision-making.
Startup or Corporate? Or can we get the best of both?
We wanted to run this program as an internal startup — fully flexible, with non-corporate talent and breaking up with the traditions of the past. The reality, though, looked different: The corporate umbrella is strong. Many stakeholders, many presentations to committees, lots of paperwork and processes for even the simplest task. Then again, the corporate umbrella is a great advantage. Seed funding can be done “easily” and does not need several rounds of investor herding. Back office functions like Finance, HR, IT are available and can be leveraged. And most importantly: The corporate umbrella comes with a reputation. The entity “data42 powered by Novartis” gave us access to the who is who in the Healthcare sector.
Changing the corporate culture through a small internal startup takes time. But it’s worth it.
I truly hope that by 2025, these and other non-corporate behaviors and attitudes will foster the creation of a data-empowered, global R&D community who will be innovating at scale on our platform to answer complex scientific questions and solve business challenges through the innovative use of our own data, as well as from industry-wide datasets, which have matured to common standards. Ultimately, we want to get better medicines and new indications to more patients, faster.
And where are we going next? As we are embedding data42 deeper and deeper into our Novartis R&D landscape, we are curiously investigating whether our learnings and approaches could benefit the world outside of Novartis. We are asking ourselves questions like:
- What if there are other data42s out there? Why don’t we combine our efforts across the Healthcare sector?
- What if data-sharing will become the norm in our industry — as we have successfully seen during the Pandemic? Can we break down the barriers of data-sharing while preserving data privacy and regulatory legislation?
- What if there was a marketplace where data assets, AI models. expert knowledge, and cross-industry connections could be enabled in an easy, seamless way?
We would like to engage in a dialogue about these kinds of questions with like-minded people by sharing our thinking and experience in this medium channel.
Unlike the supercomputer Deep Thought in Douglas Adam’s novel “The Hitchhiker’s Guide to The Galaxy”, it won’t take us 7.5 million years to find the answer to the Great Question. And we assume that the answer will not be 42.
data42 is Novartis’ transformational program to leverage our resource of patient, clinical and research data — one of the largest and most diverse datasets in the pharma industry — with the ultimate moonshot goal of changing the way we develop medicines.
Contact us at firstname.lastname@example.org
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