Three Ways to Encourage Collaboration Across Your Data Ecosystem
What kind of collaboration can help a data leader be more successful? The answer is - all collaboration is good. But how do you think about enabling collaboration with data, across groups, departments and even outside an organization? This is a question you need to approach at three levels.
Level One: Encourage internal collaboration one step at a time
At The National Health Service (NHS) in England, we have a central, data and analytics teams as well as data teams scattered across the system in various organizations. Every organization looks different, and this structure may be similar to your data organization, but even if it isn’t, enabling collaboration all starts with making people feel good about sharing their data. That doesn’t always happen naturally, so leaders need to seek out those opportunities and make it happen.
For example, convince individuals to save their data in the cloud or in tools like Github instead of keeping their work on their hard drive. That way it’s more broadly available to all. Sounds like a small change, but enabling a change in mindset around collaborating with analytics and data takes many baby steps. As it happens, it's taken us about three years to get to the point we’re at today, where data-sharing is starting to feel more the norm than the exception.
Level Two: Plan for external collaboration with a focus on big impact wins
Even though we refer to the NHS with an emphasis on the N, for national, it's actually lots of different businesses. Lots of small NHSs, in other words. In this arrangement, every group has their own vested interests, their own goal that they want to achieve.
To encourage collaboration more broadly across organizations, we’re starting by focusing on some big wins. For example, we have 42 Integrated Care Systems (ICSs) around the country. How do we work with these 42 health systems to show them the power of data, such as achieving population health management (PHM)? By making this target enticing – narrowing in on how they could reduce their costs, generate more value for patients, and result in higher-quality care – we offer to move beyond communicating in slide decks and working with their data to show what’s possible. Piloting even small successes toward a larger goal can generate a surprising amount of traction. We have been able to show the power of collaboration through the AnalystX initiative which brings together 15,000 data professionals and analysts together on the award-winning futureNHS platform.
Level Three: Develop Centers of Excellence to build and support the growth in collaboration
Especially in Population Health Management (PHM), a key question right now is how do we start developing more centers of excellence? These Centers of Excellence can be tremendously valuable in setting the right guardrails that will accelerate and facilitate broad data collaboration.
That’s critical, because PHM requires a different skill set than most data analysts are used to. We’re focusing here on training and creating consistent standards and guidance for all 42 ICSs. By doing so we’re leading these data practitioners down a new path that is helping them to align better and to build a stronger understanding with non-data analysts and other users. That means they need to bring their managers into that mix.
What happens when you bring internal collaboration, external collaboration and centers of excellence together? In practice, it means we’re far more likely these days to be able to scale something once and then push it out, versus doing it dozens of times. In terms of overall impact, it means we’re creating a learning and collaboration system. And learning systems built on valid, vetted data are vital to the future of healthcare.
The views here represent those of the author and are not necessarily those of NHS England and NHS Improvement.
Sukhmeet Panesar (Suki) trained as a doctor in emergency medicine and public health and is skilled management consultancy, health policy and academia. At EY and Accenture, his work has focused on the national program for designing new care models. He has also been the chief clinical safety officer for deploying national solutions such as NHS Mail. In his current role, he leads digital transformation, strategy and development across 270+ individuals aggregated together from NHS England and NHS Improvement into one of the largest Data, Analysis and Intelligence Service (DAIS) teams, whose purpose is to help integrated care systems deliver population health management initiatives.