Five fundamentals to deliver data's promise in the public sector

04 September 2023 8 min. read

For years, researchers have hyped the ‘transformative’ qualities of data to organisations in the private and public sphere – with public sector entities in particular promised opportunities to improve outcomes for citizens, manage risks, and cut costs. These results still seem out-of-grasp for many though, leading Nous Group to examine what fundamentals leaders need to change to actually get the most from their data.

According to Nous Group - an international management consultancy with over 700 people working across Australia, New Zealand, the United Kingdom, Ireland and Canada – the firm has heard from many public sector leaders who have been through a painful learning curve relating to data. Among Nous’ specialisms are public policy, data and analytics, and digital and design services, so organisations often come to the consultancy for support with problems relating to public sector data use.

These problems range from clients being unsure of where to start with a new data strategy, to trying to understand why they are not getting what they need from their data at present. In many cases the organisations have “some form of data strategy” in place, or at least an intention and direction at leadership level – but even so, “progress can remain elusive”.

These experiences inspired Nous to take a closer look at how the UK’s public sector is using its data to develop and deliver data strategies that unlock value for its organisations. To do so, Nous ran a series of structured interviews with senior leaders at 12 public sector entities in the UK, drawing from its experience with data strategy, data maturity and analytics in the UK and internationally – exploring why progress for public organisations with data can remain elusive, despite all the talk and investment and the many data strategies in the sector.

Five fundamentals to deliver data's promise in the public sector

“Data strategies’ failure to deliver results is often more about how those strategies are developed, rather than their content,” Nous Principal Katharine Purser said of the firm’s findings. “ChatGPT could write a generic data strategy, but would miss the fundamental foundations of success: identifying and coalescing around shared goals, understanding what is required, and agreeing on necessary trade-offs. These foundations are built through structured, intentional internal and external dialogue during the strategy development process. They provide a supportive context for delivery: without them, a data strategy will languish and organisations’ ability and commitment to make better use of data will wane.”

To help bridge the strategy to delivery gap, Nous has identified five critical elements of successful data strategies in the public sector. Together the following principles provide a framework for the structured dialogue essential to success.

Strategic alignment

Nous’ study found that the public organisations which were best at using data for their work intertwined their business strategy with their data strategy – making it so that each strategy enabled the delivery of the other. But achieving this first requires detailed articulation of what an organisation actually hopes to achieve.

Leaders in the field offer wide-ranging communications – including all-day workshops with staff to explore how a new data strategy would impact every role at an organisation – while looking to add necessary skills to their team via recruitment and training. But organisations also need to walk before they run: not all groups Nous spoke to had even written a strategy down. The researchers suggest that this is the bare minimum to take care of first, with firms with a written strategy scoring higher on alignment for their alignment, setting themselves up for a greater chance of data strategy success.

Data stance

With data privacy and security in the public sector considered paramount, a key barrier entities face in their execution of data strategies is the tension between data protection and data exploitation. Risk-averse leaders can hold the group back from realising a data set’s potential. Meanwhile, Nous found that organisations making the most progress in their data strategies address tensions between data exploitation and data protection head on.

Broadly speaking, the majority of firms were performing well in this regard. However, a few lagged behind. The researchers suggest that communication is once again the key to shifting the organisation’s mindset. Repeated discussions in particular can help, as half of all respondents told Nous that once leaders took the time to understand more advanced uses of data, they could agree on a data stance. Then, they can build clear boundaries for what can and can’t be done with data, and bring in partners to help manage its uses.

Leadership education

According to Nous, an organisation is more likely to fail in its ability to maximise the value of its data if the chair, board, and executive leaders are not aligned in recognising the importance of data for its objectives. This may be due to leaders not understanding what is really needed to uplift data capability. So, education to build data-informed leadership, aligned on the way forward, will help drive forward improvements.

The findings on this front were some of the most positive in the whole study. Nous discovered in its research that a growing number of leaders recognised the value of data to public organisations – and some were even excelling. However, in some entities, progress has been slowed by conflicting priorities from leaders of different functions. This highlights a greater need for public sector organisations to educate leaders on the risks of data silos, and how they can hold back opportunities for both the wider organisation and their department in the process.

Data culture

Public bodies in particular are frequently not the primary collectors of the data they use, so data quality issues cross organisational boundaries. Fostering a sense of data curiosity in an organisation can help change that. Nous’ researchers assert that “the more curious and interested your staff are in how data can help them do their jobs, the greater the quality of your data”. But how can the public sector alter its culture to help usher in that improvement?

Nous suggests making it easier to collect quality data is the simplest way to kick-start things. Data collection is often seen by staff as incurring unnecessary paperwork, or an administrative burden – but a successful data strategy can tackle these issues for busy employees, opening opportunities for them to collect and analyse data. At the same time, opening up projects like an insight hub – giving employees from across the organisation the chance to look at data in their areas of specialism and ask questions – can help provoke more engagement, with employees now telling an organisation what they want the data to do for them.


At the end of the day, changes of any kind – even those which will boost efficiency in the long-term – cost time and money in the hear-and-now. In the public sector, funding can be hard to come by, and that seems to be holding back a lot of data progress – with Nous finding that investment was the lowest scoring of its five categories in terms of present performance. But successful organisations can still find clever and creative ways to get results from constrained funding. To that end, Nous recommends using low-hanging fruit to help build a case for further investment.

Pointing to one example, Nous cited an organisation which had identified an area where it felt investment in data quality could drive savings in its operations quickly. Securing investment in that smaller successful project enabled the organisation to show value of investing in data, and grow its confidence in investing more in data capability development. At the same time, organisations need to find ways to articulate the value these projects are realising to help build a case for wider funding. For example, Nous found one organisation had adopted a valuation approach which enabled its leaders to view data assets in a new light, and recognise the return they would get from investment in data capability.

Purser concluded, “Data is transforming society and public services across the world. Excellence in data now goes beyond understanding numbers and systems. It requires a diverse mix of creativity, capability and communication to build a shared understanding of data’s potential and deliver on it.”