How is your organisation using data and analytics to support the corporate vision and purpose?
The NHS has since its inception relied on data and analytics to inform planning and decision-making - sometimes it has got it right and sometimes it has not. Over the years, we have seen that we have become data rich, but lacking in sophisticated insights that help us truly to transform the health and care service.
The long-term plan for the NHS has at its heart the promulgation of new models of care that achieve the quintuple aims of healthcare. In order to meet this ambition, we have had a huge focus on data and analytics in the last couple of years through the advent of reconfiguring teams, processes and moving towards data and analytics platforms and ecosystems.
2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?
We certainly noticed a pivot from our business-as-usual work to meeting the demand for data and analytics created by the Covid-19 pandemic. It has focused efforts and resources to deliver, at pace, beneficial changes that would have taken considerably longer without the focus on responding to a public health emergency.
In March 2020, we contracted Palantir to provide a single integrated data, modelling and analysis platform which cleans and harmonises data from the NHS Covid-19 data store to give a single version of truth that is needed to support decision-making. The NHS Covid-19 data store brings together multiple data sources from across the health and care system in England into a single, secure location (Microsoft Azure) which only NHS England and NHS Improvement have access to.
The Foundry platform enables the teams to create a data ontology from the NHS Covid-19 data store, allowing for a single source of analysis and streamlined information needed for accurate and rapid decision-making while protecting the privacy of patients. The results in the Foundry platform are displayed via dashboards that give a live view of the metrics needed to track and understand the current spread of Covid-19 and the capacity in the healthcare system to deal with it.
Looking forward to 2021, what are your expectations for data and analytics within your organisation?
We need to retain beneficial change and ensure that we take the learnings from Covid-19 to continue to improve the way that data is managed and used by the system while maintaining high standards of public trust and promoting transparency. As such, we can expect to:
Is data for good part of your personal or business agenda for 2021? If so, what form will it take?
Definitely part of both, which is a good thing. During the Covid-19 pandemic, a group of us across NHSEI, NHSX, PHE, HDR UK and techUK got together agnostic of organisational affiliation and set up what is now deemed to be one of the largest collaborative communities of practice for data and analytical teams (circa 14,000 individuals) built off the #futureNHS collaboration initiative. We will continue to harness the collective power of this collaborative to develop more end-to-end data initiatives and enable more cross-organisational working by breaking silos. We want to empower our data and analytical teams to lead transformation as opposed to simply support. We also want to use this community to improve data literacy across the non-analyst world.
What has been your path to power?
I trained as a pharmacist and over time have amassed over 20 years’ experience in managing and delivering large-scale change involving implementation of new operating models in complex and challenging environments. I joined the NHS in October 2009, initially leading commissioning support services in the West Midlands as the managing director for Healthcare Commissioning Services and then as the managing director for South Yorkshire and Bassetlaw Commissioning Support Unit.
Prior to joining the NHS, I was a partner with Accenture specialising in strategy and supply chain work. I have worked in Europe, North America, and South East Asia where I led the supply chain practice for three years. My experience spans global clients in consumer goods, retail, pharmaceutical, manufacturing and utility sectors.
I am currently the national director of data and analytics for NHS England and NHS Improvement responsible for delivery of national programmes to support commissioning of integrated care. In collaboration with NHSX, I am the senior responsible officer for the Covid-19 data store and the associated outputs that have formed the analytical backbone of decision-making through the pandemic.
What is the proudest achievement of your career to date?
I would list these under the umbrella of my current role. The essential ingredient for these achievements has been being able to hire and develop the right individuals, empowering them to fly and ensuring that they are outcome-driven - nothing jars more with me than fluffy, impractical ideation. In 2020, I can look back and say that we have a 300-strong team of data and analytical professionals working together under a new operating model. There is a strong move towards a data platform play as seen through the Covid-19 work and we have begun a journey of professionalising the role of the analyst.
Tell us about a career goal or a purpose for your organisation that you are pursuing?
I am a firm believer in augmentation, meaning that we need to do better today than we did yesterday. To do that we must embrace modern data and analytical approaches and tools and be willing to take our existing hard-working staff along with us on this transformation journey. This requires conviction at all levels of the organisation and the greatest enabler of any such change is people. My goal is to ensure that our current workforce moves into the new world of data and analytics as we go through a multi-year journey to develop data science capabilities at scale.
How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?
There is no doubt that the NHS (which is not really a homogenous, single organisation, but rather many different businesses) places a strong emphasis on data and analytics. Through learnings from Covid-19, NHS England and NHS Improvement seek to accelerate the delivery of data and analytics infrastructure by scaling the value of data, providing real-time, relevant data and analysis to decision-makers and operational teams across national, regional and local systems in order to unlock operational improvements and thereby patient outcomes.
The vision for data and analytics is to improve the way we capture, manage and deliver data and insights to the right person at the right time to support better decisions and enhance value through optimisation of health and care resources. Data should be treated as a product - data needs to be accessible, trustworthy, privacy-preserving, secure, inter-operable and audited. Analytics and modelling need to be reliable, available, understandable, reproducible, upgradable, audited and safe so as not to introduce bias.
The data and analytics infrastructure should be developed in a way that supports the different user groups: creators, users and consumers. We have embarked upon a journey of change as the NHS - in due course we will achieve alignment with industry best practices.
What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?
No-one argues with the importance of data and analytics, yet, as with most organisations embedding a data-driven culture, it needs to start at the top. We need to move away from the paradigm of policy being supported by data and analytics to a situation where insights drive policy-making. We need to see the introduction of new senior roles, such as chief data and analytical officers, at board level and career paths that help to build the pipeline of future leaders in this area.
Data science is the next frontier in advanced analytics and one that needs to be developed thoughtfully and together with business needs. Finally, we need to instil a culture that promotes open innovation and the fail-fast, learn-fast approach as we begin to develop and use sophisticated prediction models.