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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
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