The Datavores of Local Government

Lambeth Insight Session6th September 2016

Contents

Overview of programme

Preliminary research and discussion paper

Case study research – preliminary findings

1. Explore how better use of data can help councils to cut costs, improve efficiency and drive better social, economic and environmental outcomes

2. To establish and articulate the critical success factors of better data use

3. To set out ways in which central government, Nesta and other organisations can help councils get more from their data

4. To create insight and tools which help councils to get more from the data they hold

The Local Datavores programme aims to improve the use of data in local government

The Local Datavores - programme overview

Preliminary research and reportLiterature review and interviews to sketch landscape of local gov data use

Case Study Research8 in-depth English local authority case studies + international case studies

Provocation Paper Series and Final ReportHow smart is too smart? What does devolution mean for data, and vice versa? And what does the data revolution mean for the study of ‘what works’?

March April May June July August Sept October

Nov Dec Spring 2017

Workshop 1 - Nesta, London

Workshop 2 - LGA, London

Workshop 3 - York

Final report launch

We published a discussion paper in July based on our preliminary research A taxonomy of local government

data Collation of different use cases for

data Trends in how councils are using

data 7 things councils can do to get

more from their data Framework and hypothesis for

second phase of work

Sources of data

● Administrative/Operational○ council processes○ personal○ business

● Service delivery information

● Web data● Sensors● Citizen-generated/crowd-

sourced● Partners (e.g. police,

schools, health, housing, charities etc)

● Commercial sources (e.g. Experian, Mosaic)

● Official statistics● Council assets● Survey (in-house or

external)○ official survey○ ad hoc survey

Tools of Analysis

● Descriptive statistics● Predictive Analytics

○ Classification○ Cluster analysis○ Regression○ Machine learning

● Data visualisation● Geo-spatial analysis

Use of Data

● Monitoring and measuring● Understanding of past events● Evaluation and testing ‘what

works’● Transparency and citizen

engagement● Prediction (individuals, services)● Case management e.g. social

care● Town planning● Optimisation of processes,

systems resources e.g. traffic management

● Detecting fraud and error● Better targeting of resources● Automation of decisions● Modelling impact of changes to

services● Risk-management

Making Data Usable

● Cleaning● Standardising● Integrating● Linking data● Using technology to access

in real-time

Feedback loop for monitoring and evaluation

A taxonomy of local government data use

Collation of use cases for local government dataUse Case Examples of Use Where? (selected examples)Evaluation and testing ‘what works’

 

Randomised control trialMatched control trialSurvey dataBig data analytics

Behavioural Insights Team methodologyGreater Manchester councils Troubled Families RCTEssex children’s social care Social Impact Bond

Transparency and citizen engagement

 

Open data portals and analytics hubs Multiple examples, such as Greater London Authority, Camden, Bristol, Leeds Data Mill, Cambridgeshire, Trafford

Prediction (individuals, services) 

Children’s social care front door risk assessments clientsFire risk, Illegal cooking oil disposal, Adverse birth events, Students most at risk of not completing their education 

Newcastle, Greater Manchester, Bristol, Westminster New York MODA Chicago ‘Data for Social Good’ programme

Case management 

Better management of client needs in children’s and adult social care

Newcastle ‘Family Insights’ programme

Optimisation of resources Smart Cities optimise the flow of traffic, public transport, street lighting etc. 

Multiple examples from around the world. Glasgow and Bristol considered world leading in the UK

Detecting fraud and error 

Analysis of procurement data to detect unusual patterns of buying activityPredicting households most likely to avoid paying council tax

Singapore uses AI to predict procurement fraudGravesham Borough Council

Trends in how councils are using data

Smart Places Open DataPredictive

AnalyticsGeo-spatial Analysis

Data Warehousing for integrated public services

Use of geo-spatial data to improve services, such as Optimising

waste collection routes

Reducing inefficiency and duplication in transactional services

Using data analytics to predict and prevent events such as: Children most

at risk of abuse likeliest

locations for house fires

children most at risk of not completing their education

Adverse birth events.

Combining data sets from across local government and the wider local public sector to Enable deeper

population level analysis

Provide frontline professionals with a much more comprehensive picture of people receiving services

The combination of sensors, Internet of Things technologies and data to improve the management of places e.g. traffic

management tracking air

pollution more efficient

use of infrastructure such as street lights.

Open data portals and analytics hubs to Provide

transparency Open

government Engage with

communities of developers, innovators and entrepreneurs

Drive economic growth

7 things councils can do to get more from their data

Take a problem oriented mindset to working with

data

Invest in the data science capacity

needed to perform analysis

and integrate large data sets

Integrate data into a data

warehouse to enable deeper

analysis and use

Take an agile approach to

working with data

Enable data sharing through

use case oriented information governance

protocols

Ensure that hard and soft

infrastructure enables

integration of data and analysis

Support the use of data at senior

leadership level

Case study research will look at these and other success factors in more granular detail

Overview of the case studies

ManchesterIntegrated data warehouse for frontline professionals and analysis to inform commissioning

NewcastleFamily Insights Programme and prevention support for people at risk of becoming NEET

Suffolk County Council – integrated approach to performance management and integrated frontline teams using data

Kent County CouncilKent Integrated Data set for strategic planning of integrated health and care services

Bristol City CouncilSmart city, citizen sensing and open data portal

Birmingham City CouncilSmart city and Digital Birmingham strategy

Leeds City CouncilData Mill North – building a community of partners to use open data to improve Leeds

London Borough of CamdenData integration of 16 business lines, data dashboards and open data

Children and Families

Adult Social Care and Health

Smart Cities and Economic Growth

Public Service Transformation and Open Data

Scope of case study research

What were the critical success factors for the project/programme?

What level of data maturity preceded the work?

What is the value case for the project/programme in terms of

internal productivity and external benefits?

How replicable is the project/programme for the wider

sector?

 

 

 

What were the key use cases for the data in the project/programme?

 

There are five key stages to the research methodology, which we are investigating using interviews, a survey and document review

• Open data portal and partnership approach to addressing Leeds’ challenges

• Data Mill North hosts data for range of organisations

• Innovation Labs to bring developers together with council staff to solve problems

• Data analysis to identify where council can strategically support growth of business

Leeds City Council

The case studies in more detail

Manchester

• Enables social workers to visualise data contained across case files in multiple agencies.

• Population-level analysis such as needs segmentation and regression analysis

• Increases staff productivity and informs commissioner decision making

Kent County Council

• Integrates health and care data for c1.5m people in Kent

• Data is pseudonymised and linked

• Enables matched-control trial evaluation of interventions and services

• Allows modelling the impact of changes in services on population health and care outcomes

Bristol City Council

• Smart city programme connects the city council with the needs and views of residents

• IoT mesh network to enable citizen generated data to flow towards government

• Open data portal to democratise information and increase transparency

• Operations centre to integrate data and optimise city management

The case studies in more detail

Newcastle

• Service transformation (Hackney Reclaiming social work model) informed by data

• Data-led segmentation of family by groupings of need

• Embedded data analysts within social work units

• “Institutionalising curiousity”

Suffolk

• Integration of health and social care services supported by data

• Moving to a performance culture based on outcome data

• Analysing services and population data to identify problems

• Integrated teams of frontline professionals supported by shared outcome frameworks

• Back office and service transformation led by data

• Camden Resident Index brings together 16 line of business systems

• Data dashboards to manage services following systems thinking reviews

• Open data portal to reduce FOI burden and engage with business

Camden Birmingham City Council

• Digital Birmingham is using data to inform the transformation of the council, and how it interacts with communities

• Smart city initiatives to improve city management, such as temperature sensors in roads so that gritting can be targeted when it snows

Barriers and Challenges Considered

Information governance Data integration – including standards, accessibility and data quality Hardware and software limitations Internal culture – including mindset for data use, and appetite for greater data

use Data skills availability Financial resources Organisational structure – location of data functions in an organisation Buy-in from senior leadership Data maturity

Preliminary research findings Leadership confirmed as the single most influential factor across the case

studies Data analysis is most useful when it has been seen as the enabler and not

been the end goal Information governance is hard, but is arguably as much a cultural issue as it

is legal Data quality is best addressed by starting to use the data, with the people

responsible for capturing it Data projects have demonstrated significant benefits, but harder to make the

case for financial savings New software offers advances, but benefits can be gained through basic

software such as Excel Creating a data-informed organisational culture best done through using data

to help people at all levels do their day to day work more easily