Digital infrastructureSmart CitiesThe six barriers to urban data optimisation

The six barriers to urban data optimisation

What are the six major barriers to city data optimisation and how do local authorities overcome them?

There’s no getting away from the fact that data is valuable. It’s the great enabler of digital self-service, as well as the foundation behind validation, planning, operational management and decision-making when it comes to our urban areas. It’s also a given that even more effective technologies of the future, such as AI, will be grounded in data.

There’s a wealth of data available through smart city technology – covering everything from city energy use to high street footfall and traffic management. These can help tackle urban challenges through the development and adoption of new data-rich technologies and services.

However, as the Future Cities Catapult points out in its Quick Start Guide to City Data, there’s so much room for improvement as we move along the data lifecycle. For example, we’re poor at innovating in services that span between two or more organisations when we know that data capability and data sharing are the key barriers, like health and social care.

To help local authorities improve their city data usage, the Quick Start Guide to City Data takes a look at the six major barriers to data optimisation and how to overcome them – information we share here.

  1. Mindset

Those who don’t see data and digital capability as an eff­ective investment of resources, will fall behind competition. Local authorities need to adopt a mindset that embraces data, encourages understanding and values experimentation.

Embedding data-enabled solutions throughout public institutions relies heavily on a mindset that values data, encourages its use and views investment in data and digital as worthwhile. We must equip our experts with investment to grow data capability within our organisations. A shift in the mindset of our leaders is also required to appreciate that data is useful and not just an exercise. Public sector leadership must develop a greater understanding of the transformative journey ahead.

  1. Resources

Local authorities are challenged by shrinking budgets, resource constraints and competing priorities. In looking for ways to solve these challenges, there are big opportunities for more collaboration on data initiatives between public sector organisations in close proximity.

Regional government has a role to play in helping local organisations shape their strategy and policy around data. It can also help coordinate engagement and strategic procurements with private sector and third sector organisations.

Collaboration between local authorities can lead to shared resources, knowledge and advice – alongside shared risk when it comes to investing in the new. The good news is that this is already happening in some cases. For example, in 2017, West Berkshire and Oxfordshire County Councils signed a Digital Collaboration Agreement, which enables them to meet bi-monthly, share code and other digital developments. This agreement also allows the two councils to provide support and advice around different specialisms. It has the potential to save the councils time and money.

  1. Skills

Cities are facing a gap between data expertise and aspiration. At the same time, there is a pool of bright and raw talent graduating from universities within UK cities outside of London. This talent is currently being drawn to more developed and lucrative sectors in larger cities. In order to stem the flow, public bodies and city authorities must start focusing on stimulating demand for data capability across their region, working with private sector businesses and academic institutions to create attractive opportunities for skilled individuals.

There are a number of organisations offering local authorities the ability to try data science by hosting a PhD graduate for short project in London. Trying out new skills before making a larger investment can help your organisation to develop a stronger case. An applied use case can also help begin to change mindsets of leadership. A more ambitious initiative would be for regions to establish their own feeder schemes with local universities and businesses.

  1. Technology

New technology can make working with data easier and more effective in organisations. They can enable secure data sharing, easy reproduction of data, better data storytelling and more informed decision-making. But it takes time for an organisation to decide which tools to use and how to apply them to their organisation. Market analysis can help make these decisions easier.

Organisations are tackling similar problems. New data tools that combine datasets and allow for those methods to be shared can help organisations save time and effort. In 2018, Future Cities Catapult released the Urban Data Explorer and Digital Connector, two tools designed to help cities share geospatial data modelling and visualisation.

Decisions based on data and their associated methodologies are often best made openly. This enables an opportunity for feedback and potentially the improvement of the methodologies used in the decision-making process. Data technologies should be designed to be transparent and accessible.

  1. Operations

To achieve effectiveness in data analytics, organisations should ensure they can scale its application internally and collaborate on common challenges with others. The emergence of cross-government organisations to provide advanced data services on behalf of others across regions should be encouraged. After all, there are multiple public sector providers with similar missions and challenges. Shared offices of data analytics should help speed up data innovation.

Barking and Dagenham, for example, has recruited a real data science team within the council. Since 2015, a dedicated team has worked exclusively on data projects. Operating like an internal consultancy, the team’s expansion depends on its ability to deliver benefits to the organisation. The team works collaboratively with the business and has so far tacked licensing and community solutions. It’s a good model that can be replicated by other local authorities looking to transform services through data analytics.

  1. Legal

Connecting siloed data, or connecting skilled people to data, is becoming increasingly important for service delivery innovation. Data sharing is the key enabler. But resolving legal concerns, governance headaches, management confusion and stakeholder worries is a resource intensive process that adds lengthy delays to any engagement. This is hindering experimentation and stopping innovation from getting off­ the ground. A mixture of standards, frameworks, governance and software solutions are needed to reduce the legal burden.

The Information Sharing Gateway is a great example of public sector innovation rising up to solve a commonly shared challenge. It takes the pain out of information sharing agreements allowing users to create, manage, sign and store them easily, online. It enables GDPR compliance and is a step toward standardising the information governance around data sharing. And it’s already been adopted by over 1,700 organisations.

The full Quick Guide to City Data expands on the above in detail, providing some great detail. Click here to read the guide in full.

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