Five Ways to Scale Up “Cottage Industry Analytics”
If you think about modern, enterprise-scale data culture, the term “cottage industry analytics” is unlikely to come to mind. Yet this system of analysts and data professionals working in small, isolated teams, each team siloed off from the others, was until recently the norm in many parts of the National Health Service (NHS) in the UK. This is gradually changing, thankfully. But this change runs deep, and requires rethinking how we do tackle many parts of the process.
Historically this model worked, but as we’ve begun to invert it towards enterprise-level processes, it made no sense for one person to do the data extraction, manipulation, analysis, and so on. It’s expensive, quality varies widely, and it’s grossly inefficient because you don’t build specific expertise and assets aren’t reused and shared.
Here are five mantras we’ve used to scale up what we do toward enterprise-level data science and analytics:
- Stop repeating tasks. Resilience is built on a variety of challenges, not rote repetition.
- Encourage data sharing beyond silos. Data shared within a silo benefits the silo. Shared beyond, it can benefit the entire organization.
- Use technology tools that scale. Evaluate your technology tools based on this idea and you’ll quickly separate the wheat from the chaff.
- Define a new operation model that includes the right processes. Consistent processes are not the same thing as repetition.
- Win hearts and minds to inspire people to go on the journey. Even the best technology can’t sell itself. As a data leader, you’ve got to evangelize.
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 in 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 deployment of 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.