Tag Archives: data science

Plantech and the Singapore experience

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The publication in early August of the government consultation on reforming the planning system in England was accompanied by plenty of soundbites on the need for more efficiency and faster decision-making.

Technology, and digital services, were highlighted (once again) as an area which needs improvement: “Reform should be accompanied by a significant enhancement in digital and geospatial capability and capacity across the planning sector to support high-quality new digital Local Plans and digitally enabled decision-making.”

The consultation report goes on to say that “we think the English planning profession has the potential to become an international world-leader in digital planning, capable of exporting world class planning services around the world.”

Running to catch up

Many countries around the world have already made significant investment in digital planning, both technology and skills, and of these, Singapore is often mentioned as a world leader. While the city state’s administrative set-up gives it some advantages over countries with devolved and fragmented systems of regulation and planning powers, there are still lessons to be learned.

A webinar hosted by the Connected Places Catapult last month allowed staff from Singapore’s Urban Redevelopment Authority (URA) to share its work on plantech, and in particular how data science is embedded in planning processes and long-term strategic planning. The journey they have been on over the last decade suggests that the UK has a long way to go.

The Singapore approach

The URA’s Digital Planning Lab was set up in 2013 to bring together planners and data specialists to use digital tools to improve planning processes and outcomes. The approach is holistic, with different professions working together to combine insights. This contrasts with the UK, where local authority budget cuts have led to an erosion of the skills base.

The mission of the Digital Planning Lab is to act as a catalyst – to incubate skills and ideas, to accelerate insights and transformation, and to inspire, through innovation and partnerships. There is a strong focus on building skills and capabilities within government, with the Lab running a data analytics immersion programme twice a year, to train cohorts of government staff on how data can be used in their work.

One output of the Lab has been their digital planning tool, ePlanner, which applies data science to urban planning processes. The one-stop inhouse geospatial tool is accessible to staff in over 50 government agencies and brings together information and analytics on population and demographics, land use, mobility, housing types, planning approvals, enforcement action, parking and public consultations and feedback. Data and maps are layered to allow deeper analysis of individual topics while protecting individual data. The tool also visualises existing site approvals and restrictions which may exist based on strategic planning documents.

The ePlanner aims to identify information and workflow gaps, and improve interagency working. The data analysis also enables a more flexible approach to strategic planning. While in most countries the evidence used in long-term planning is drawn from sources such as 10-year censuses, and uses surveys to gather people’s preferences, the Singapore tools allow for much more nuanced and responsive policymaking based on actual behaviour. It also recognises the complex factors which shape how communities use their infrastructure.

Plantech creates better places

The goal of plantech in Singapore is explicitly to facilitate data-informed, people-centric planning outcomes. A goal which planning reforms in the UK can only currently aspire to achieve.

While the challenges are recognised (such as the protection of individual and health-related data), the Urban Planning Lab approaches their work from the perspective of asking ‘how can we unlock the value of data’ – providing evidence-based insight on trends without exposing raw data. By mitigating risk, Singapore has been able to unlock the possibilities that modelling and simulation, and artificial intelligence, can bring to urban planning.

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How AI is transforming local government

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By Steven McGinty

Last year, Scottish Local Government Chief Digital Officer Martyn Wallace spoke to the CIO UK podcast and highlighted that in 2019 local government must take advantage of artificial intelligence (AI) to deliver better outcomes for citizens. He explained:

“I think in the public sector we have to see AI as a way to deliver better outcomes and what I mean by that is giving the bots the grunt work – as one coworker called it, ‘shuffling spreadsheets’ – and then we can release staff to do the more complex, human-touch things.”

To date, very few councils have felt brave enough to invest in AI. However, the mood is slowly starting to change and there are several examples in the UK and abroad that show artificial intelligence is not just a buzzword, but a genuine enabler of change.

In December, Local Government Minister Rishi Sunak announced the first round of winners from a £7.5million digital innovation fund. The 16 winning projects, from 57 councils working in collaborative teams, were awarded grants of up to £100,000 to explore the use of a variety of digital technologies, from Amazon Alexa style virtual assistants to support people living in care, to the use of data analytics to improve education plans for children with special needs.

These projects are still in their infancy, but there are councils who are further along with artificial intelligence, and have already learned lessons and had measurable successes. For instance, Milton Keynes Council have developed a virtual assistant (or chatbot) to help respond to planning-related queries. Although still at the ‘beta’ stage, trials have shown that the virtual assistant is better able to validate major applications, as these are often based on industry standards, rather than household applications, which tend to be more wide-ranging.

Chief planner, Brett Leahy, suggests that introducing AI will help planners focus more on substantive planning issues, such as community engagement, and let AI “take care of the constant flow of queries and questions”.

In Hackney, the local council has been using AI to identify families that might benefit from additional support. The ‘Early Help Predictive System’ analyses data related to (among others) debt, domestic violence, anti-social behaviour, and school attendance, to build a profile of need for families. By taking this approach, the council believes they can intervene early and prevent the need for high cost support services. Steve Liddicott, head of service for children and young people at Hackney council, reports that the new system is identifying 10 or 20 families a month that might be of future concern. As a result, early intervention measures have already been introduced.

In the US, the University of Chicago’s initiative ‘Data Science for Social Good’ has been using machine learning (a form of AI) to help a variety of social-purpose organisations. This has included helping the City of Rotterdam to understand their rooftop usage – a key step in their goal to address challenges with water storage, green spaces and energy generation. In addition, they’ve also helped the City of Memphis to map properties in need of repair, enabling the city to create more effective economic development initiatives.

Yet, like most new technologies, there has been some resistance to AI. In December 2017, plans by Ofsted to use machine learning tools to identify poorly performing schools were heavily criticised by the National Association of Head Teachers. In their view, Ofsted should move away from a data-led approach to inspection and argued that it was important that the “whole process is transparent and that schools can understand and learn from any assessment.”

Further, hyperbole-filled media reports have led to a general unease that introducing AI could lead to a reduction in the workforce. For example, PwC’s 2018 ‘UK Economic Outlook’ suggests that 18% of public administration jobs could be lost over the next two decades. Although its likely many jobs will be automated, no one really knows how the job market will respond to greater AI, and whether the creation of new jobs will outnumber those lost.

Should local government investment in AI?

In the next few years, it’s important that local government not only considers the clear benefits of AI, but also addresses the public concerns. Many citizens will be in favour of seeing their taxes go further and improvements in local services – but not if this infringes on their privacy or reduces transparency. Pilot projects, therefore, which provide the opportunity to test the latest technologies, work through common concerns, and raise awareness among the public, are the best starting point for local councils looking to move forward with this potentially transformative technology.

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Rise of the Datavores … showing no fear of data, it takes skills

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Datavores infographicPrevious work by NESTA highlighted companies with apparently no fear of data. They called them ‘datavores’. When making decisions about how to grow their sales, they rely on data and analysis over experience and intuition.

Does being data active have an impact?

According to a new NESTA report published this week Skills of the datavores: talent and the data revolution, those organisations which are more ‘data-active’ perform better than those that are not, as the infographic above illustrates:

  • Datavores are 10% more productive
  • But, only 18% of companies are datavores
  • If all “dataphobes” became “datavores” it would add a 3% uplift in productivity
  • Data-driven firms are 40% more likely to launch new products and services.

What does a skilled data workforce look like?

The research suggests that the biggest issue facing the industry is the lack of skilled data analysts/scientists, where demand has grown 41%. Businesses are using a combination of actions to solve this lack of supply of skilled people, including off-shoring the roles, recruiting best fit and using a combination of inhouse, on the job and external training to grow their own.

Many organisations are also developing inter-disciplinary teams to create a data literate workforce because the skills needed within a data scientist are so rare; as the report says, as rare as “unicorns”. Our own experience of recruiting a data scientist would support this.

The workforce which is emerging is one focussed on adaption and flexibility, based on data sciences across the board, such as qualitative researchers, mathematicians, statisticians, developers and business analysts. Within this mix of skills, the new workforce also needs to have a creative flair and business knowledge that enables them to use the data in the organisation’s best interest and to add value.

What does it mean for skills suppliers?

As an emerging profession, it is difficult to pin down the exact skills an employer needs which in turn makes it difficult for schools, colleges and universities to supply the right type of education. The accompanying policy briefing from NESTA and Universities UK, Analytic Britain: securing the right skills for the data-driven economy, makes a number of recommendations, highlighted in the infographic above, many of which focus on the skills suppliers.

Universities are both a supplier and user of these skills and have a unique opportunity to really enage with the market. The focus on metrics in both the proposed Teaching Excellence Framework and Research Excellence Framework means that universities themselves are in need of the same skills and have an opportunity to supply based on experience.

For universities these recommendations have a number of impacts, and data issues are increasingly at the forefront of policy thinking. Universities UK has reviewed how data analytics are taught across disciplines and reflects on the shortage of academic staff who are confident in teaching data analytics in this way and the varying skills of students entering higher education.

The pervasive nature of the data revolution explains why a variety of disciplines and skills are being brought together. No one can argue against the need for more and better data to improve policy making and business planning. Plenty of data is now being captured but not used, and in the words of John Lennon “you say you want a revolution” and “we all want to change the world” … data is changing our world significantly but are you equipped for it?

The Idox Information Service can help you access further information on the use of data science, and the skills needed. To find out more on how to become a member, contact us.

Download the Datavores Infographic.

Further reading on the topics covered in this blog and infographic*:

Skills of the datavores: talent and the data revolution

Are you a Datavore? Insights on the use of online customer data in decision-making

UK data capability strategy: seizing the data opportunity

Information economy strategy

Inside the Datavores: how data and online analytics affect business performance

Employer insights: skills survey 2015

Big data analytics: assessment of demand for labour and skills 2013–2020

UK corporate perspectives: new technologies – where next?

*Some resources may only be available to members of the Idox Information Service

We’re hiring! Data Scientist vacancy at The Knowledge Exchange

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Alex Thomas

The Knowledge Exchange is advertising for a Data Scientist as part of a Knowledge Transfer Partnership with the School of Computer Science and Engineering at the University of Salford. The role will examine the applicability of data mining techniques to big data held within Knowledge Exchange and Idox products including The Information Service.

The Information Service holds a unique collection of over 40 years of UK public sector research, strategy and policy. Such a collection offers rich and unique potential for sentiment analysis of the shifts and trends in public sector research since the 1970s. Anonymised user log-data from the Information Service could also be analysed to provide an unparalleled view of how the public sector uses and accesses research. This has far-reaching implications for academic research impact and funding. Continue reading →