Ming Tang is Interim Chief Digital and Information Officer and Chief Data and Analytics Officer at NHS England, where she is responsible for setting the strategic direction for digital, data, and analytics across the health and care system.
She joined the NHS in 2009, initially leading commissioning support services in the West Midlands before becoming Managing Director of South Yorkshire and Bassetlaw Commissioning Support Unit. These roles gave her first-hand experience of how fragmented data and legacy systems affect frontline staff and patient care, shaping a long-standing focus on strengthening data foundations as a prerequisite for meaningful transformation.
As the NHS’s senior leader for data and analytics, Ming is accountable for building the national capabilities that underpin system transformation, policy development and predictive insight. Her remit spans strategic information assets, digital tools and analytical services designed to support better decision-making across the NHS. She has played a central role in initiatives such as the Federated Data Platform, the NHS App and the Single Patient Record vision, creating the conditions for AI to be safely and effectively embedded into everyday clinical and operational workflows.
Before joining the NHS, Ming was a Partner at Accenture, specialising in strategy and supply chain transformation. Her consulting career followed a start as a pharmacist at GSK, after which she completed an MBA and moved into strategy consulting. She has more than 20 years’ experience delivering large-scale change and new operating models across global organisations in consumer goods, retail, pharmaceuticals, manufacturing and utilities.
Ming’s leadership is guided by a simple test: whether digital, data and AI initiatives give time back to staff and make care simpler, fairer and better for patients, with technology acting as a trusted partner rather than an additional burden.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“For me, three traits matter most in data and AI leadership: the ability to see around corners, an obsession with plumbing not products, and the courage to say ‘no’ early.
“First, you need to hold a long, slightly uncomfortable view of where systems are heading: platforms, digital twins, agentic workforces and then work backwards into today’s choices. That thinking sat behind the NHS App, the Single Patient Record and the Federated Data Platform, all conceived as pieces of the same ecosystem and architecture rather than separate projects.
“Second, you must care more about the core foundations than shiny tools. In my organisation, I insisted on shared infrastructure, standards and skills, even when it slowed us down at first, the trick is to test with real use cases in parallel as this builds momentum. These basic building blocks are what now allows trusts use data in real time, making reusable products quickly and start to adopt AI safely across pathways. Forming strategic alliances intra- and extra-industry are key to solving our huge challenges.
“Third, you must protect focus. Saying ‘no’ to dozens of tempting pilots allowed us to concentrate on a small number of national products with real reach and measurable impact for patients and staff. Those three behaviours have done more for our data and AI journey than any single technology decision.
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“Keep learning and treat your career like a series of controlled experiments on yourself, not a ladder.
“The non‑traditional advice I give is deliberately collect and build on ‘misfit’ experiences that make no sense on a linear CV but force you to see systems from very different seats. The jump from pharmacy to consulting, from commercial supply chains to NHS commissioning, then into national digital roles, made me comfortable walking into rooms where I was never the obvious expert, but could connect dots others could not.
“For an aspiring C‑suite data or AI leader, that means saying ‘yes’ to roles that feel sideways or even backwards: a stint in operations, a spell in finance, time on the frontline, a policy role. Each one teaches you a different language and set of incentives. Later, when you are trying to redesign a whole system, those languages matter more than any algorithm.
“In short: optimise less for neat progression, more for range, discomfort and stories you can draw on when the room gets difficult.”