Reductions in budgets, soaring demand for certain services, austerity, and rising citizen expectations are all current challenges that require public sector organisations to rethink how they deliver their services, deploy their assets and make the best use of their staff.

Business as usual is not an option.

At Nesta we believe that some of these challenges can be tackled, or at least assisted, by the good use of data analytics (for example, Nesta’s Datavores of Local Government discussion paper explores how data can help councils provide more personalised, effective and efficient services).4 Done well, it can help save lives, prevent major incidents, enable organisations to make more efficient and impactful decisions and improve the lives of those living and working in the communities they serve.

Nesta has championed the model of Offices of Data Analytics (ODA) as an effective means for achieving this aim. Taking inspiration from New York City’s Mayor’s Office of Data Analytics, established during the administration of Mayor Michael Bloomberg, we and others have worked to adapt the ODA model for a UK setting, while keeping true to its original aim of enabling better services and decision making through data analytics.

Happily, the model is now gaining serious traction in the UK.

Through our research, however, we’ve come to realise that there is no ‘one-size-fits-all’ model and there’s generally a lack of consensus on what an Office of Data Analytics even is.

Offices of Data Analytics are not your ‘run of the mill’ analytical business functions, nor the usual performance analysis department measuring in-house statistics and activity, nor intelligence teams that only inform internal activities.

Our definition of Office of Data Analytics is:

• A model for multiple organisations to join up, analyse and act upon data sourced from multiple public sector bodies to improve services and make better decisions.
• ODAs always adopt a shared vision and objectives, sometimes have shared capabilities and resource, often have a range of collaborative working practises, and definitely have a commitment to data analytics.
• Ultimately, an ODA creates multi-organisational, actionable insight from otherwise siloed information.

Overall, an ODA has at least two essential functions:

• Conducting data initiatives: conducting practical data sharing and data analytics projects (see Nesta’s six stage process described later in this guide).
• Templatising: creating reusable codes of ethics, data standards, legal documents, process guides and open source tools to make future data sharing and analytics projects quicker and easier to deploy.

If resources are available, two additional functions are desirable:

• Convening and coordinating: acting as a hub for a city or region’s data science and policy community; supporting and nurturing the ecosystem of data practitioners.
• Training: running data and methodology workshops catered for the specific needs of public sector leaders and data science practitioners.

Although not all Offices of Data Analytics are structured and run in the same way, they do have a number of principles in common that differentiate them from other approaches.

An ODA is a multi-agency approach. An ODA may have originated from one organisation, but it should involve multiple partners. This requires an overarching strategic vision that all are signed up to.
An ODA is not a data analytics function sitting within one organisation. It is not an existing performance analysis or business insight team that exists to meet one organisation’s own requirements.

An Office of Data Analytics is run by and for the public sector.
An ODA is not a data analytics function sitting within one organisation. It is not an existing performance analysis or business insight team that exists to meet one organisation’s own requirements.

ODAs bring together datasets from a range of different sources (for example: public sector, commercial and open data) through an effective and secure data sharing process. They create a place-based view of a problem by complementing an otherwise siloed picture with information from other areas.
ODAs do not only focus on one single source of information, or a single organisation. They do not solely self serve data from inhouse systems.

ODAs focus on producing actionable insights from information, making sure that actions will be taken following the delivery of analytical outputs. This requires a clearly defined problem that needs to be solved, or question that needs to be answered, in order to ensure that the output is usable and impactful.
ODA isn’t another word for a “data lake”. It’s not about pulling together a number of ‘potentially’ useful datasets into one place, in case they are needed. An ODA doesn’t produce insight because it’s interesting, without it being useful.

Different organisations have gone about designing and shaping their Offices of Data Analytics in different ways.

Nesta has developed a four-step process for helping public sector organisations understand what types of problems and questions they can resolve with data.

Full details can be found in Nesta’s Guide to Public Sector Data Analytics.

What are the benefits of having an Office of Data Analytics? This is a common question, even for those organisations that are well into the process of setting up an ODA. It’s important that the benefits are well defined and articulated, as they are essential for designing business cases, applying for grants or funding, and gaining senior leadership support for the approach.

Below we summarise some of the most common and important benefits of the ODA approach:

Finance

• There is no need for a big investment up front;
• It clearly provides returns on investment, efficiency savings through reducing duplication of effort and possible solutions to mitigate / counterbalance devolution cuts.

Policy

• It is policy agnostic, overcoming siloed political interests and drivers;
• It is not a superficial bolt-on to city governance, but is rather fully integrated into the way the city is run, informing policy, city strategy and public service delivery.

Collaboration

• It better targets intervention services through partnerships with different agencies;
• It improves multi-agency working relationships and organisational culture;
• It cuts across borders of single boroughs, districts and agency jurisdictions, with a possibly modular application.

Insight

• It provides a more informed picture of challenges within a locality which organisations would not otherwise have access to;
• It provides greater information to inform better decision making. Profiling and predictive modelling, for instance, can be used to better understand demand and tackle vulnerability.

Innovation

• It encourages new and innovative ways of working;
• The use of new technology and techniques ensures that public sector bodies are in line with the rapidly developing national digital agenda;
• It grows and develops skills set of those working with and using data.

Although there is often a desire for sharing data amongst services, it can be challenging in reality. Some of the challenges will be deeply rooted in a particular service, its culture and staff, and will take time to change.

Other barriers, such as information governance, technology or finance can be more quickly overcome by being well informed and learning from others.

In the report we break down the different types of barriers associated with setting up an ODA, exploring the problem under each theme (organisational culture, people, data, technology, funding, and legal) and suggesting ways each problem can be overcome.