By Katharine Purser

Consider this paradox: public sector leaders are recognising data as a strategic asset more than ever before, but many are becoming disillusioned with the concept of a data strategy as the way to unlock its value. Is it because data strategies are only really helpful in the private sector?

Public sector faith in data as the key to unlocking all our problems has been growing over the past decade, with increasing numbers of public sector leaders recognising the potential for better outcomes for communities, greater efficiency and lower costs. The current financial climate is putting even greater pressure on public sector organisations to squeeze every ounce of value from all their assets: people, buildings, finances, technology AND data.

Over this period many public sector organisations have developed a data strategy, which articulates how they will develop the technology, processes, people, and rules required to manage and make the most of their data. A search for the term on gov.uk reveals 381 results.

And yet, many public sector leaders we speak to feel frustrated, confused, and disillusioned when it comes to data. The grand promises have failed to materialise; it can seem that even after years of having a data strategy, not much has really changed. This is often despite the best of intentions and planning, approval (or even pressure) from the authorising environment, and investment of time and money.

So what is a leader to do? Our experience shows there is benefit in a data strategy. But strategies that assume large-scale investment or wish away legacy systems are bound to disappoint. Unfortunately, no matter how glossy your data strategy is or how many buzzwords it contains, a document alone is not enough to make real change.

Instead, public sector leaders need to develop data strategies that are fit for purpose and realistic for the circumstances. This means paying attention to context: all the things going on in an organisation that can determine whether a data strategy actually drives the intended results.

Data strategies have four success factors

At Nous we love thinking about problems like these, and we have identified four key success factors for developing useful data strategies in the public sector:

1. Acknowledge the process is the important thing, not the strategy. There is no single approach to writing an effective data strategy and there is no model template. It is an iterative process and it takes time to land. Engaging with leaders across your organisation about what they are trying to achieve and identifying those who can champion your move toward becoming data-led are vital parts of the process. Gaining their buy-in and engaging them to build the buy-in of others is more effective than spending time writing a strategy document. Agreeing on your organisation’s stance on how to manage and leverage data is a key part of this process. It’s most useful when this process takes place over months, rather than weeks.
2. Align the data strategy with the business strategy. It is helpful for a data strategy to set out the skills and technologies your organisation is seeking to acquire to manage and make the most of your data. But without connecting it back to the bigger picture of what the organisation is trying to achieve, it won’t get you very far. Start with your business strategy and work out what data you need to achieve it. Are you a service delivery agency that needs to understand better the whole person coming to you for help? Are you an operational organisation that needs get better value from your increasing scarce assets – buildings, people, money, data? Is your primary goal to make or implement policy that drives social change, where data will help you understand your context and your impact? Each will lead to very different data strategies. By grounding your data activities to the areas that will advance the business strategy, you can make mutually reinforcing decisions about how you will use data to maximise impact. If ministerial priorities change, the business and data strategies can be adapted.
3. Work towards building data foundations. Beware of the trap of thinking you can build advanced data capabilities, which may flow from your data strategy, without devoting time and energy to building the fundamentals. These fundamentals include developing a skilled and capable workforce; creating a supportive culture that enables effective feedback; investing in appropriate analytic tools, technologies and services; and instituting streamlined processes, protocols and guidelines. Resource constraints may mean you need to build these up over time, or piecemeal as you connect investment in these with business outcomes, but shortcutting here will get in the way of progress. When it comes to developing capabilities, we have previously identified five steps you can take to improve the data skills of your staff.
4. Articulate who your data strategy is intended to influence, and how. The most effective strategies are tailored to the context of the organisation. Do you need it to align senior stakeholders behind a vision? Is it to convince budget-holders to invest? Is it to reassure the public about what you are doing with their data? Is it to energise the data experts in the organisation and give them something to orient their work around? The answers to these questions will shape your process to develop your data strategy as well as scope of the strategy itself.

It is not all about the written strategy

The data strategy that emerges from this process can vary greatly – and sometimes a written document is not the end game. For some organisations, the process is enough. Indeed, Gartner describe a data strategy as a “dynamic process”[1] and the Data Management Association (DAMA) describes it as a “set of choices and decisions”.[2]

One department we spoke to had tried three times to write a formal strategy, but in the end found the process it went through was enough to enable it to get going. For others, a simple one-page set of principles, like one from the Office for National Statistics,[3] is enough to start making progress with their agenda. And some need a much longer document and a much longer process, which includes public consultation – for example the Department of Health and Social Care data strategy,[4] a key objective of which is to build public confidence.

We remain big fans of data strategy at Nous, but we know success depends on it being the right fit for the organisation at a particular time. Ultimately, organisations set themselves up for success with their data strategy by putting in place key elements beyond the written document itself: being clear on what they are trying to achieve, working to build the senior buy-in, and securing investment in data that matches their ambition.

Get in touch to discuss how we can help your public sector organisation to develop or evolve its data strategy, including through using our data strategy health check.

Connect with Katharine Purser on LinkedIn.

Prepared with input from Peter Horne, Veevek Doolabh and David Diviny.

Published on 28 November 2022.

[1] Gartner Glossary, Data Strategy

[2] DAMA International, Data Management Body of Knowledge, 2017

[3] Office for National Statistics, Our Data Strategy

[4] Department of Health and Social Care, Data saves lives: reshaping health and social care with data