When you think about the future of healthcare, data and technology are at the heart of almost every discussion. But as Ming Tang, Chief Data and Analytics Officer at NHS England, reminds us, transformation is not just about the tech; it’s about people, mindset, and connection.
On a recent episode of Data & AI Mastery, hosted by Dr. Raoul-Gabriel Urma, Ming shared her lessons from leading one of the most ambitious digital transformations in the UK. The conversation explored how the NHS is using data and AI to improve patient care, connect siloed systems, and foster a culture of curiosity across one of the world’s largest public organisations.
Below are the key takeaways every data and AI leader can learn from Ming’s approach.
Ming’s first piece of advice for transformation leaders is simple but powerful: start by listening.
“Sixty to seventy percent of the problems we face aren’t technical,” she explains. “They’re about how people work together.”
In other words, technology alone can’t fix broken processes or misaligned incentives. The real work begins with curiosity, understanding the root cause of problems, the relationships that shape them, and the context in which people operate.
For Ming, this means spending time with frontline staff, clinicians, and administrators to see how systems impact their daily work. It means designing with people, not just for them.
Transformation, she notes, is a team sport, and success depends on orchestrating the right mix of people, data, and technology to tackle shared challenges.
One of Ming’s most compelling insights is how the NHS is shifting from a service-based to a person-based model.
Traditionally, healthcare systems have been designed around departments—primary care, secondary care, and emergency admissions—each with its own data and digital infrastructure. But patients don’t experience healthcare in silos.
To deliver a seamless experience, the NHS is building what Ming calls a longitudinal view of the patient, connecting data across services into a single journey.
“We want people to interact with the NHS like they do with their banking app,” she says. “A consistent experience where everything about you is part of that journey.”
This vision is being realised through the Federated Data Platform (FDP) and the Single Patient Record, core initiatives designed to break down silos and connect information securely across the system.
The goal is not one monolithic database but interoperable connection points that enable collaboration between pharmacists, GPs, hospitals, and patients themselves. For individuals with complex conditions, it means not having to repeat their story at every appointment. For staff, it means faster, more informed decision-making.
When it comes to measuring transformation, Ming warns against focusing on surface-level metrics like app downloads or technology adoption rates.
Instead, she emphasises outcomes that matter to people, reduced waiting lists, faster discharges, and improved patient experience.
“In the public sector, it’s easy to get caught up in process,” she says. “But the real question is: has technology helped change the business for the better?”
By treating transformation as a partnership between technology and business owners, the NHS can measure value in terms of real-world impact, from improved operations to tangible benefits for patients and staff.
This thinking guided the case for the Federated Data Platform. When presenting to the Treasury, Ming’s team identified five concrete use cases, from theatre utilisation to vaccination logistics and tracked value against each one.
It’s a lesson for all organisations: clarity of purpose drives meaningful ROI.
AI is already transforming how healthcare operates. Ming shared several examples of how NHS England is using AI to support clinicians and streamline operations:
Each example reflects Ming’s philosophy: technology should enhance human capability, not replace it.
Of course, implementing AI in healthcare requires careful regulation and oversight, from the MHRA to internal governance frameworks. But the goal remains clear: build systems that are both safe and transformative.
When asked what mindset leaders need to drive AI adoption, Ming doesn’t hesitate: curiosity.
“There’s no one-size-fits-all AI,” she says. “You have to understand your problems first, and then explore where AI can help.”
Curiosity means being open to experimentation, finding quick wins that inspire confidence, and using excitement, not fear, to bring people along the journey.
As she puts it, “Start small, be structured but free-flowing, and keep the focus on solving real problems.”
Perhaps the most important takeaway from Ming’s conversation is that data and AI transformation is ultimately about people.
Technology enables progress, but mindset, empathy, and shared purpose sustain it.
By listening deeply, designing around real-world experience, and using data responsibly, organisations of any kind, not just in healthcare, can deliver lasting, meaningful change.
At Cambridge Spark, we help organisations and leaders build the data and AI fluency needed to make that transformation possible. From executive education to workforce upskilling, our programmes are designed to bridge the gap between innovation and impact.