From data to intelligence and improvement – what cutting edge councils are doing in the UK

Group of workers having a meeting

By Steven McGinty

Data has the potential to revolutionise the delivery of local services. Just like the private sector – where organisations such as Amazon and Facebook have leveraged user data – local councils have the opportunity to reap significant benefits from analysing their vast silos of data. Improving efficiencies, increasing levels of transparency, and providing services which better meet people’s needs, are just some of the potential benefits.

Although many councils are still at the early stages of utilising their data, some are innovating and introducing successful data initiatives.

Wise Councils

In November 2016, the charity NESTA published a report highlighting the most ‘pioneering’ uses of data in local government. The report emphasised that most local services would benefit from data analysis and that a ‘problem-oriented’ approach is required to generate insights that have an impact on services. The case studies included:

Kent County Council

Kent County Council (KCC), alongside Kent’s seven Clinical Commissioning Groups (CCGs), have created the Kent Integrated Dataset (KID) – one of the largest health and care databases in the UK, covering the records of 1.5 million people. The core requirement of the dataset was to link data from multiple sources to a particular individual, i.e. that information held about a person in hospital, should also be linked to records held by other public bodies such as GPs or the police.

This integrated dataset has enabled the council to run sophisticated data analysis, helping them to evaluate the effectiveness of services and to inform decisions on where to locate services. For example, Kent’s Public Health team investigated the impact of home safety visits by Kent Fire and Rescue Service (KFRS) on attendances at accident and emergency services (A&E). The data suggested that home safety visits did not have a significant impact on an individual’s attendance at A&E.

Leeds City Council

Leeds City Council have focused their efforts on supporting open innovation – the concept that good ideas may come from outside an organisation. This involved the initiatives:

  • Data Mill North (DMN) – this collaborative project between the city council and private sector is the city’s open data portal (growing from 50 datasets in 2014 to over 300 data sets, in over 40 different organisations). To encourage a culture change, Leeds City Council introduced an ‘open by default’ policy in November 2015, requiring all employees to make data available to the public. A number of products have been developed from data published on DMN, including StreetWise.life, which provides local information online, such as hospital locations, road accidents, and incidents of crime.
  • Innovation Labs – the city has introduced a series of events that bring together local developers and ‘civic enthusiasts’ to tackle public policy problems. Leeds City Council has also provided funding, allowing some ideas to be developed into prototypes. For example, the waste innovation lab created the app, Leeds Bins, which informs residents which days their bins should be put out for collection.

Newcastle City Council

Newcastle City Council have taken a data-led approach to the redesign of their children’s services. The Family Insights Programme (FIP) used data analysis to better understand the demand and expenditure patterns in the children’s social care system. Its aim was to use this insight to support the redesign of services and to reduce the city’s high re-referrals and the number of children becoming looked-after.

The FIP uses data in three different ways:

  • Grouping families by need – The council have undertaken cluster analysis to identify common grouping of concerning behaviours, such as a child’s challenging behaviour or risk of physical abuse. When a child is referred to long term social work, senior social workers analyse the concerning behaviours of the case, and then make a referral to a specialist social work unit. Since introducing this data-led approach, social work units have been organised based on needs and concerning behaviours. This has resulted in social workers becoming specialists in supporting particular needs and behaviours, providing greater expertise in the management of cases.
  • Embedding data analysts – Each social work unit has an embedded data analyst, who works alongside social workers. Their role is to test what works, as well as providing insights into common patterns for families.
  • Enabling intelligent case management – Social workers have access to ChildSat, a tool which social workers use to help manage their cases. It also has the capability to monitor the performance of individual social work units.

Investing in data

Tom Symons, principal researcher in government innovation at Nesta, has suggested that councils need support from central government if they are to accelerate their use of data. He’s suggested that £4 million – just £1% of the Government Digital Service (GDS) budget – is spent on pilot schemes to embed data specialists into councils.

Mr Symons has also proposed that all combined authorities should develop Offices of Data Analytics, to support data analysis across counties. Over the past few months, Nesta has been working on this idea with the Greater London Authority, and a number of London boroughs, to tackle the problem of unlicensed HMOs (Houses in Multiple Occupation). Early insights highlight that data analytics could be used to show that new services would provide value for money.

Final thoughts  

After successive years of cuts, there has never been a greater need for adopting a data-led approach. Although there are undoubtedly challenges in using council data – including changing a culture where data sharing is not the norm, and data protection – the above examples highlight that overcoming these challenges is achievable, and that data analysis can be used to bring benefits to local councils.


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New Idox research – Data Mining to inform public policy

By Susan Lomax, Data Scientist, Knowledge Transfer Partnership placement

The latest “new” thing in the world of data mining is using “Big Data” to inform public policy. Using data mining methods, we can aid evidence-based decision making by learning what the data can tell us and using this to write or implement policy. Idox are now exploring these methods to look at opportunities for our public policy and research members.

Investigation indicates that using data in this way is in its infancy, where data mining methods are in the process of being used, but so far, very little is completed. Published examples include, London Borough of Newham’s property data, which has been combined with numerous other datasets and mined to examine change in property tenure in order to support, amongst other things, their housing management services. The University College London mined Oyster Card data in order to minimize cost for travellers using public transport and to encourage public transport use. The first stage of the research will be exploring what can be done and what would be useful to members.

As a new member of the Idox staff, I am on a scheme known as Knowledge Transfer Partnership (KTP), which helps companies engage in this type of research and development. The scheme is celebrating its 40th Anniversary this year, having first been formed in 1975 as the Teaching Company Scheme. The KTP program is funded by 17 public sector organisations and led by Innovate UK, formally the Technology Strategy Board. The aim is to support UK businesses wanting to improve their competitiveness, productivity and performance by accessing the knowledge and expertise available within UK Universities and Colleges.

Traditionally taking place in engineering and manufacturing industries, they have now branched out into ICT, looking at data analysis, and creative industries such as design, fashion, music and video games businesses. There are currently 800 partnerships across the UK.

Our research partnership includes an academic institution and The University of Salford, is on hand to provide support and guidance. It has an outstanding record with regard to innovation, enterprise and skills. The Informatics Research Centre builds on history, success and achievements of research in Computer Science and Information Systems over the last 30 years.

Data mining is a process to discover patterns in large datasets. Its roots are in disciplines such as artificial intelligence, machine learning, statistics and database systems. Its overall goal is to extract information from data and make this understandable, so that it can be used to make decisions. A popular book “Data mining: Practical machine learning tools and techniques with Java” has information about the most common data mining methods.

The three main data mining methods we will be trying are association rules, classification and clustering and we will be exploring these in the research.

  • Association rule learning searches for relationships between variables (or attributes) in the dataset. A most popular example is a supermarket finding out which products their customers buy together and use this information for marketing purposes. This is also known as market basket analysis.
  • Classification is when a dataset has examples grouped into known classes; the task is to assign a new example to one of these known classes. A well-known algorithm performing this task is the Decision Tree algorithm C4.5.
  • Clustering performs a similar task to classification but with clustering we don’t have an assigned ‘class’. A technique known as k-nearest Neighbour is a popular method. Other main tasks are regression, summarization and anomaly detection.

Although the research is explorative at the moment, I hope to keep you updated with our progress throughout the project. If you have any thoughts or want to find out more, please get in touch.


The Idox Information Service can give you access to a wealth of further information on data and knowledge management. To find out more on how to become a member, contact us.

Further recent reading*

Classification

Association rule

Measuring transit use variability with smart-card data

Digital councils

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

How can the government unlock the potential of big data?

By Steven McGinty

Last May, the Open Rights Group announced that they were in discussions with the UK Government over their proposals to remove the barriers to data sharing and link up government databases. This would mean that thousands of government databases, containing information such as criminal records and even energy use, could be accessed by local councils, schools, the civil service and the police. It’s hoped that the sharing of data will allow the government to capitalise on big data techniques and provide better and more tailored public services.

However, several issues have been identified that may make widespread government data sharing challenging. These include:

  • a lack of prioritisation by local council and government leaders;
  • concerns over protecting the privacy of citizens;
  • a mistrust of government data handling;
  • the use of different systems and different standards by government bodies.

The Information Commissioner’s Office (ICO) reports that from April 2013 to March 2014 there were just over 1500 breaches of the Data Protection Act. Local authorities accounted for 234 of these breaches, coming second only to health organisations, who committed 551 breaches. In the last quarter of the year, the most common offences were disclosing personal information in error (175 incidents) and lost or stolen paperwork (74 incidents).

The ICO has also handed out several high profile fines to organisations in the public sector. For example, North East Lincolnshire Council was fined £80,000 for losing an unencrypted USB stick which held the personal and sensitive data of children. Similarly, Aberdeen City Council were fined £100,000 after a member of their staff accidently uploaded documents onto the internet, including personal information about social care cases.

The Improvement and Development Agency (I&DeA) released a report in 2010 on the role of data sharing in tackling worklessness. The report findings, still relevant today, highlighted the importance of developing data sharing systems that:

  • build in the need for data sharing into the design;
  • adopt clear and consistent definitions;
  • respect the privacy of individuals;
  • ensure data integrity.

Further, the report explained how anonymised personal data can be used to share data legally. For example, anonymised data (data which has had its identifiable information removed), has been used increasingly to provide local analysis across a number of areas, including health, crime and employment. Some examples include Eastleigh Ambition, which uses data to target and support vulnerable families, and Newham Council, who use a range of data, including Disability Living Allowance information to improve their understanding of changing populations and needs.

Working in partnership and using technological innovations has also provided solutions for data sharing issues. For instance, the Tyne and Wear City Strategy Partnership was established to purchase a shared customer tracking system to facilitate data sharing. The system has been rolled out in a variety of ways across the North East of England, with partners helping to make the system more user friendly. The system has been designed to ensure that consent is built in whenever data is shared. Users also have different levels of access depending on their organisation and on what they ‘need to know’, to ensure compliance with the Data Protection Act.

Although there have been some high profile cases of government data mishandling, it’s clear that data sharing will continue to increase, particularly as all levels of government look for more targeted services. Government and society will have to come to an agreement on how this should be done.


 

Further reading: