Thank you for your interest in the SAVVI case study of how the Rural Child Poverty project engaged with the SAVVI method to design how they will support vulnerable people.
Executive Summary
SAVVI, a Scalable Approach to Vulnerability via Interoperability, is a data project that aims to support early identification of vulnerable people and households, and to make smarter interventions and referrals. To do this, SAVVI proposes data standards for vulnerability for both technical interoperability and legal interoperability. SAVVI pulls together practical guidance, frameworks, standards, templates and resources in an to support every stage of implementing SAVVI standards. The Rural Child Poverty project is an initiative by three Scottish local authorities to develop a data driven approach that builds a picture of who is vulnerable, and which families may need support. The case study is therefore a deep-dive look at the activities undertaken by the project to establish the legal interoperability of reusing data to find cases of rural child poverty in Scotland.
In particular, this approach:
identifies the risk factors that are most useful in assessing the risk of child poverty proposes the sources of data from which these data items can be derived agrees upon identified legislation that enables lawful reuse of those data items. This case study shows how vital it is to establish a clear purpose for tackling the vulnerability, which provided structure for the information governance work in establishing legal interoperability, particularly when considering purpose compatibility and the need to find a lawful basis for the re-use of data.
Having a methodology to establish lawful, ethical and transparent data-use as part of the design process was foundational to facilitating agreement across project partners, validating the need for the SAVVI Playbook, and other practical IG tools that SAVVI has prototyped to support councils working on a vulnerability project. The participating Scottish councils now have a tested method for building data re-use propositions. This allows them to apply this method to other vulnerability projects.
The purpose of this document is to share the local authorities’ experience to enable other Local Authorities in Scotland to repeat this process and inspire other councils across the UK to adopt a similar SAVVI-style approach to finding and supporting families that are vulnerable to child poverty.
This case study will be of particular interest to:
project teams who want to find and support people in need; data and digital teams who want to handle and share data to a reusable standard; Information Governance teams who want to ensure that data is being shared legally, ethically, and transparently; performance and business improvement teams who want to evidence that a project is effective in reducing hardship. Introduction
This is a case study of how three Scottish Local Authorities, Angus Council, Argyll & Bute Council and Inverclyde Council, engaged with the SAVVI method during 2023 and 2024, to design how they will find and support vulnerable families in which children are at risk of poverty.
The project was run by the Remote, Rural and Island Child Poverty Peer Support Network for Local Authorities that the convenes, and supported by the SAVVI Engagement Team. The initiative was run as a feasibility project to test whether the SAVVI approach could be used to overcome the barriers to reusing personal data to find families, at risk of child poverty, previously unknown to the local authorities.
The purpose of this document is to share the local authorities’ experience and feedback what we learned. This is to enable other Local Authorities in Scotland to repeat this process and inspire other councils across the UK to adopt a similar SAVVI-style approach to finding and supporting families that are vulnerable to child poverty.
Why Child Poverty?
A combination of two drivers had increased the risk of child poverty in parts of Scotland. The cost of living crisis with increased household costs for all families, combined with the higher cost of living in a remote, rural or island location (e.g. through increased transport, delivery and food/retail costs) had meant rural and island child poverty had become a higher risk than in previous years.
One known cause of rural and island child poverty is low household income, which can be exacerbated by families being unaware of welfare benefits, or other entitlements such as a public transport passes, or, being unable to successfully claim these benefits without additional support. The three councils involved in the project, as well as many others in Scotland, had an intent to address the risk of child poverty in their rural and island localities through income maximisation advice and support.
Why Rural?
Whereas child poverty in urban areas can be focused in deprived geographies, that is not the case for rural, remote, and island localities. The Peer Support Network had found many instances where families in need were in rural localities which were not statistically identified as deprived. The Councils had found it difficult to identify and communicate with high-risk families in these locations because they were often surrounded by wealthier populations.
In some cases, councils had developed good processes for assessing needs and were finding some families through engagement via schools and other naturally occurring touch-points but this still did not help them to find those families that were in greatest need for support.
For rural localities, personal data is required to find families with Risk Factors that indicate Child Poverty.
For councils with urban areas, geographic campaigns had helped to raise awareness leading to increased welfare benefit claims in deprived localities, but this approach was ruled out as ineffective, disproportionate, and intrusive for rural communities.
What was the Problem?
In many cases, councils had sufficient aggregated data and intelligence about the local population to predict the number of families in rural and island locations who were likely to benefit from advice and support, but were unable to identify the individual families because of they had not established a lawful and ethical basis for the reuse of personal data.
The councils had evidence of what existing personal data could be indicators of Child Poverty, such as
This type of personal data, which was collected for a primary purpose, will need a lawful basis to allow it to be reused for a new purpose, in this case, finding families who may be at risk of Child Poverty.
Each council started with a different opinion on what personal data could be reused. They invited SAVVI to help them to work through the and IG Framework, to help them to agree some core definitions, and to articulate a shared understanding of how reusing personal data addresses the problem. The process was about getting agreement to these definitions across the participating councils so that they then had a common base to consider the legal, ethical, and transparent reuse of data
At SAVVI, we often find that councils wanting to reuse existing data in this way have a lack of clarity as to what is legally allowed and what isn’t. Councils have had to commission their own legal advice, which is costly and inefficient, which can lead to hundreds of Local Authorities making a slightly different request of many Departments or local public sector agencies, and potentially getting different answers.
What Kind of Support Could be Offered?
Common measures of income maximisation in Scotland include:
Crisis Grants, administered by Local Authorities as part of the Scottish Welfare Fund Council Tax Reduction, also administered by local authorities in Scotland as part of their Council Tax functions Universal Credit, administered by the Department for Work and Pensions (DWP) in the UK Government Scottish Child Payment, administered by Social Security Scotland (SSS), part of the Scottish Government. Finding Vulnerable Families - the Data Led Approach
The three local authorities created a new approach that
identified the data items that are most useful in assessing the risk of child poverty, the ‘Risk Factors’ defined a ‘Risk Policy’ to illustrate how Risk Factors can be combined to create a prioritised ‘Cohort’ of families at risk. developed a ‘Data Flow Map’ to show the sources of data from which these Risk Factors can be derived proposed the legislation that enables lawful reuse of the Risk Factors from their primary purpose to the new purpose of addressing child poverty The SAVVI Process is designed to be useful to any organisation who wishes to repeat the success, so, the definitions avoided the local context, and references to specific computer systems.
Ultimately, new access to reusing personal data can be negotiated once on behalf of all councils who adopt the same definitions.
How SAVVI enables organisations to find and support vulnerable people and households
About SAVVI
, standing for ‘a Scalable Approach to Vulnerability via Interoperability’, is a programme hosted by on behalf of the local public sector, and funded by the Department for Levelling Up, Housing and Communities’ (DLUHC)within the . SAVVI is proposing the , to promote how data can be used to improve early identification and smarter interventions, particularly where no single organisation has access to all the data and insight that can predict who may be struggling. Finding people or households who may be vulnerable requires that we are able to routinely bring existing data together, from many sources. The playbook includes
a to find, assess, and support vulnerable people and households; to support the common process, and promote interoperability; an to ensure that data is handled legally, ethically and transparently; The rationale for the SAVVI Playbook is that it can be applied to all vulnerability scenarios so that
investments in technologies and data sharing can be reused across initiatives; we are ready for the next emergency Phases of the SAVVI Process
The SAVVI Process is organised into five phases.
Working with SAVVI
Establishing the Project Team
SAVVI recommends a project team structure that includes
vulnerability or operational subject matter experts data analysis and integration expertise information governance professionals.
Additionally, SAVVI recommends a governing group to sign-off key decisions and definitions that are set out in the SAVVI Playbook. The key decisions were:
the Vulnerabilities that are in scope the power(s) or duty(ies) that define the Purpose the target population segments the risk factors that identify and prioritise the Cohort adopting an ethical assessment the lawful basis for the new data processing the legal gateway that gives authority to reuse data from its original purpose to the initiative’s purpose
The group formed a single project team to collaborate and agree definitions across the participating councils. The three councils nominated the following personnel into roles to be part of the joint team:
data analysts who were familiar with the sources of data that were likely to be reused service delivery practitioners who were familiar with services for at-risk families data protection officers, or those with Information Governance or related legal knowledge, able to assess and advise their council about the lawful basis on which data could be reused Project Workshops
SAVVI delivered a series of workshops for the project team to take them through the SAVVI process as a way of making the required decisions about which data to use, where it could be sourced from, and the lawful basis on which any new data processing activities would be relied on. The tables below show the topics of these workshops.
Workshop 1: Purpose and Outcomes Framework
The outputs of the workshop are set out in detail in the following sections below:
Workshops 2 & 3: Risk Model, Data Ethics and Data Flow Map
The outputs of the workshop are set out in detail in the following sections below:
Workshops 4 & 5: Data Reuse Propositions and Asks
The outputs of the workshop are set out in detail in the following sections below:
Applying SAVVI to the Rural Child Poverty Project
This section provides the outputs of the workshops using SAVVI templates and definitions.
Defining the Vulnerabilities
The SAVVI Concept Model defines ‘Vulnerability’ as
The Local Authorities defined the following Vulnerability.
Defining the Purpose
An organisation needs to demonstrate that it has a remit to address vulnerabilities. This becomes important when data that was collected for an original purpose, is to be re-used for this new purpose. This is best expressed as powers and/or duties that define the Purpose.
The SAVVI Concept Model defines ‘Purpose’ as
The Local Authorities defined their Purpose as
The Risk Model
Defining Risk Factors
The SAVVI Concept Model defines ‘Risk Factor’ as
11 Risk Factors were considered
Risk Factor Combinations
Risk Factors can be combined into categories
Applying Risk Factors to the Risk Policy
The SAVVI Concept Model defines ‘Risk Policy’ as
The purpose of the Child Poverty Risk Policy was to build a Cohort of families for whom child poverty is a risk and prioritise where an intervention to maximise their household income may help.
To be selected for inclusion in the Cohort, each of the Risk Factor Categories
Claiming a welfare benefit Not claimed a welfare benefit … are to be present.
The priority levels of risk within the Cohort can be indicated from Risk Factor Categories
Family Make Up Increased Risk
Evidence for the Risk Policy
The SAVVI process highlights that the choice of Risk Factors needs to be supported by some evidence that demonstrates that they are effective in finding people at risk. This becomes important when arranging for data sharing so that the data controller can be assured that their data is necessary to make the Risk Policy work.
The Local Authorities set their evidence as
Finding Sources of Risk Factors
SAVVI sets out a Data Flow Map, to show where Risk Factor data can be drawn from.
Rather than refer to specific computer systems, or suppliers, SAVVI uses a more generic ‘Information Type’ so that other organisations can re-use parts of the map.
The SAVVI Concept Model defines ‘Information Type’ as
The Local Authorities defined their Data Flow Map as
Several other risk factors and data sources were considered as part of the process, but the local authorities agreed on risk factors derived from the above sources as an initial minimum risk model that would effectively prioritise families for an income maximisation needs assessment.
The data flow map demonstrates that three of the Information Types are controlled by Local Authorities, and two are from external organisations; however, the SAVVI Process to undertake lawful, ethical and transparent processing of each of these data sources is the same.
Using Data Lawfully, Ethically and Transparently
The SAVVI Playbook includes an with steps to ensure that data is used, and reused, legally, ethically, and transparently. The SAVVI IG Framework refers to existing codes and guidance including ...
The framework defines the key steps and assessments to take, which are then ultimately referred to in a Data Protection Impact Assessment (DPIA).