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Building a Data-Driven NHS: Lessons From the Health Sector


Data is now an omnipresent reality of modern life – and a skilled workforce that is able to manipulate, analyse and interpret data is essential for our modern healthcare system. However, there is no shortage of challenges in building a data-driven NHS.


Many organisations are struggling to keep up with the growing demand to become “data-driven” – and the NHS is no exception.

Currently, there are only 10,000 NHS data analysts. This may seem like a lot, but when you consider the scale of the NHS – 1.8 million employees and 1 million patients every 36 hours – and the amount of data that needs to be processed every day, this puts things into perspective. 

Furthermore, there is little formal data training. At a senior level, there is a poor representation of data skills. Data analysis is commonly done in silos, behind closed doors. As a result, current performance is variable, and often poor. 

So how can we address the challenges of the NHS? And what lessons from the health sector can be applied to our own organisations?

Challenge #1: Building demand for data analysis in the NHS

Why should the NHS care about data? First of all, companies who utilise data have a real competitive edge. Microsoft research revealed that companies that have started to use AI are already outperforming organisations that have not by 5%. Furthermore, McKinsey found that “a culture that brings data talent, tools, and decision making together” unleashed a competitive advantage.

The demand for data analysis is growing across industries and sectors. According to one survey, in 2018, a nearly unanimous 98.6% of executives indicated that their company aspires to a data-driven culture” – up from 85.5% in the 2017 survey. 

With rapid advancements of automation and AI, this brings with it the potential for new technology to automate tasks. And with the proper application, the power of data analysis could be transformative for the NHS. 

First of all, it could mean freeing up valuable time for health professionals, enabling them to focus on the high-value activities in which they have specialist skills and training. 

According to the NHS’ Interim Plan, scientific and technological developments including AI will “significantly influence how care is delivered in the NHS in the future”, creating “significant opportunities to help healthcare teams work more productively, releasing more time for care, helping provide fulfilling working lives and enabling every NHS pound to go further in improving access to – and quality of – care.”

However, the NHS will soon run into the problem that the rest of us are already facing: the data skills gap. Already, the European Commission has warned that 346,000 more data scientists are needed by 2020. The demand for data scientists is certainly there, but the pipeline can’t keep up. So how will the NHS overcome this challenge?

The Solution…

  • Stimulating demand from the top

We need to start by getting senior-level decision-makers to recognise the current deficiencies and the benefits of investing in data.

  • Creating analytical leaders 

We need more people at the top table who are fluent in data, in order to innovate. This could be the key to changing the mindset across healthcare.

  • Attracting young talent

We must attract young talent to data science in the NHS, and create an identifiable data analyst “profession” which carries status and potential. 

Challenge #2: Attracting data talent to the NHS

Perhaps most important, we need to integrate the right kind of talent in our organisations – including the NHS. And according to McKinsey, “that calls for striking the appropriate balance for your institution between injecting new employees and transforming existing ones.”

Younger people today have a greater tendency to move around every 2-3 years – and a big part of this is a desire to learn new skills. In fact, according to an analysis by Josh Bersin, among Millennials “career opportunities” is the #1 driver of employment brand.

According to Bersin, “education and skills are perhaps the biggest drivers of your own personal earnings potential, so organisations that offer training, lots of developmental assignments, and a coaching culture are now the premium places to work.” Perhaps this is why global investments in learning technology companies reached over $9.52 billion in 2017, up 30% from 2016.

In order to attract young people to data roles within the NHS, we need to mainstream the professionalisation of data analysts – providing opportunities for young people to grow, develop their careers, and see that they can have a data career in the NHS.

The Solution…

  • Building the profession of data analytics

We need to create an infrastructure that supports the development of the profession and show young people that they can have a career in data science in the NHS.

  • Creating leadership buy-in

We need to get leadership bought into the concept that the same set of expectations need to be applied across digital roles – nationally and locally.

  • Making a system for accreditation

We need to make a system for the accreditation of data analysts in the NHS and push leadership to demand accredited professionals.

Challenge #3: Cultural resistance to change

To succeed in creating a data-driven NHS, we don’t just need to change processes or create training programs. We need to address the cultural aspects that are holding back change.

Nearly 1/3 of executives cite “cultural resistance to change” as the primary factor in preventing success. When combined with challenges relating to organisational alignment and executive leadership, the results indicate that nearly 2/3 of the issues preventing the successful adoption of data initiatives can be attributed to cultural factors.

However, research from McKinsey suggests that, in order to create a competitive advantage, we have to stimulate demand for data capabilities from the roots up – and we need to develop a data mindset that moves “beyond specialists and skunkworks”.

As McKinsey argue, “You develop a culture by moving beyond specialists and skunkworks, with the goal of achieving deep business engagement, creating employee pull, and cultivating a sense of purpose so that data can support your operations instead of the other way around.”

So in order to achieve a data-driven culture, we need to start by eliminating silos, and uniting the whole organisation around data.

The Solution…

  • Eliminating silos and competition

Competition between health organisations creates a commercial blocker to better sharing. However, we need to find a way to shift that mindset and start learning from each other.

  • Standardising processes

We need to increase access to data across the organisation by standardising processes through collaborative, shared and transparent approaches. 

  • Creating a new data culture – across organisations

While senior leaders need to drive this shift in culture, it needs to be built from the ground up. We can start by introducing more sharing, collaborative learning, and new techniques early on in people’s careers.

AVADO helps build data-driven organisations

At AVADO, we are acutely aware of these challenges. And as a company, we help people and businesses achieve their potential by delivering inspiring digital-first learning. 

We work with a number of NHS Trusts and central organisations to transform capabilities and mindsets through joined-up programmes of leadership bootcamps, digital and data literacy programmes for all employees, intensive technical certificates for subject professionals, and levy-fundable apprenticeship programmes. And from working with major clients such as Google, CIPD, and Talktalk, we have a clear idea of the challenges that organisations are currently facing.

Want to know more about how AVADO can transform your organisation’s capabilities and mindset? Get in touch at solutions@avadolearning.com.

Caroline Koktvedgaard

Caroline Koktvedgaard

Caroline is a freelance writer and content strategist at AVADO and Arch. She researches and writes about data science, digital transformation, diversity and leadership.

Posted July 29, 2019