A Journey into insight

Barnet Council & LOTI

Opportunities and strategic case for change

• Largest population in London – 400,000 residents, projected to increase by 10% in next decade
• The Borough has a higher percentage of over 85 year olds compared to rest of London
• Number of people aged over 65 is projected to increase by 29% in the next decade
• Barnet is forecast to have the largest number of children of any London borough by 2020
• There is an increasingly diverse population therefore more complex resident needs

Strategic case for change – linked to three themes, which should be embedded in all our wider strategic programmes

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Our proposed model – Insight & Intelligence Hub

• Responsible for scoping and overseeing cross-cutting data/insight initiatives
• Performance and statutory reporting to remain within service areas
• Strong links to corporate strategy teams to shape wider council transformation programmes
• In the immediate term ‘driving insights to support wider recovery programme’
• Embed data-enabled culture and insight capabilities across Barnet
• Delivering the long-list of opportunities identified through our data maturity assessment

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We were very ambitious…

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How we work

Based on the principles set out in our Borough Plan and our commitment as signatory to the Local Digital Declaration . This informs how we work as a team and with our partners.

Practical

Open & Collaborative

Developing our people

Sustainable

Outcomes focussed

We will have a clear framework and measurable outcomes in developing our service. Our projects and initiatives will be centred on user and resident needs.

We are a small team, operating based on a “hub & spoke” model. This means an emphasis on collaboration, joint-delivery and a culture of openness to shape our direction, share lessons learnt and toolkits.

We are clear on and from the outset that being insight driven goes beyond data and technology – it requires investing in development of our talent pipeline, providing opportunities to join projects and learn together.

Our projects will balance strategic and operational aspects and needs so we deliver practical insights to user groups. We will also “learn by doing”, recognising not everything is perfect the first time round!

Our approach will consider the longer term view so any investment into projects and systems will align with our Digital Roadmap and wider strategic initiatives.

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So what have we been doing...

Nov ‘19

Work initiated to explore developing insight capability and enable Barnet to be �“Fit for the Future”

Discovery phase

Engaged over 50 Barnet stakeholders and 13 local authorities

Voice of the customer interviews

Insight Network engagements

Local Authority interviews

June ‘20

Recommendations and Options Paper discussed at Council Management Team, commitment to proceed

Barnet Insight & Intelligence Hub established

Aug ‘20

CMT Sponsor, Head of I&I, Service Engagement Officer

Registered as members of London Office of Technology and Innovation

I&I Technical Lead in post

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Set of pilot insight projects commenced with service sponsors identified

Sep ‘20

Oct – Nov ‘20

I&I Hub welcomes:

• Public Health Intelligence Analysts
• GIS team Leads
• Prevention Workstream Project Manager
• Graduate Project Officer

Oct - Nov ‘20

Series of outputs for pilot insight projects delivered at pace

Some Project highlights…

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Drawn on 8 Revenues & Benefits, Housing data sources to better understand picture of debt and financial needs in the borough, with a place-based lens

Debt & Financial Vulnerability

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Analyses and insight indicators development to support Barnet’s response to Covid-19 impact and local economies monitoring

Employment and Jobs Dashboard

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Developing our network…

Led Data and Innovation Funding applications to MHCLG and Social Care Analytics Funding bid to Health Foundation (successful in latter to final round interview)

Nov - Dec ‘20

Launched Data Academy course in collaboration with WhiteHat for 24 Barnet staff

Developing data & insight culture…

First and second Prevention & Insight Think Tank with c.13 AD representative across services

Public Health Intelligence and CMT insight dashboard development to understand spread of cases in local communities

Covid-19 Dashboard

And the journey continues...

Jan ‘21

• Launch of the L4 Data Fellowship (25 students across Barnet)
• 2^nd wave of Pandemic – response to Covid-19
• Support for Local Contact Tracing

Feb-March 2021

1

Working with colleagues to develop a prioritisation tool kit for IDP and CIL

IDP Prioritisation Tool Kit

2

Taking the FV/Debt work started in Q3, overlaying with ASC debt data.

FV and Debt (ASC Pilot)

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Census 2021 – supporting engagement with the Census 2021

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Barnet Plan 2021-25

Development of dashboard’s/needs assessment to support priorities across the borough plan:

• Employment and Labour Market
• Poverty/Long-term impact of COVID
• Food Security
• EDI Dashboard

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April ‘21

• Launch of London BI Data Leads Group (co-chair with Camden)

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• Development of EDI Dashboard
• Prevention mapping and validation across Workstreams
• Introduction of Local Insight Tool and development of Ward Profiles

Successful bid LOTI Innovation Fund – Digital Mapping across London, collaboration with 5 other LA’s

May ’21 (so far..)

• Launch of a new L3 Data Literacy Programme and second cohort of the L4 Data Fellowship
• Homelessness Needs Assessment
• Support for Town Centres work and needs assessment for Local Plan
• Further development of EDI Workstream
• PH Intelligence streamlining of datasets
• Scoping of Disproportionality work

Projects in the pipeline:

• Further development of Local Insight Tool to inc. partners
• Data Literacy Training Programme
• Further development of data to support Barnet Plan
• Deep-dive of Barnet to support Place-Based Needs Assessment
• JSNA … and much more

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We’ve started the journey and made huge progress… but there’s more still do do!

Lessons Learnt & 360 Feedback

• The team’s technicality is amazing alongside the culture and collaboration built
• The creation of the team has been a massive benefit and we’re only really at the beginnings of the potential
• Already feels more like an organisation that uses insight

What’s gone well

• How can we use insight for service transformation?
• Can we improve data sharing and quality across the org.?
• Can we further embed a culture of curiosity?
• How can we develop an Insight Hub for wider Barnet including VCFS etc.?

What we could develop

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How insights are shaping our recovery from COVID – Spotlight Project

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Mapping Digital Exclusion in London

Spotlight Project

A multi-borough collaboration

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Project Overview

The challenge

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• The impact of digital exclusion on health wellbeing and participation has become exacerbated by the pandemic

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• Digital Exclusion is multifaceted and different people experiencing digital exclusion will have different needs.

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• We need to understand the where people are digitally excluded and what their specific digital exclusion needs are to help effectively

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Solution: Digital Exclusion Mapping Project

The Project set out to tackle digital exclusion (DE) by using data enabled insights to understand the spatial distribution of digital exclusion and the nuance of the needs experienced by individuals.

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Insights from the Map

Purpose: To understand the extent of DE across London and provide a visual tool for London Boroughs and their partners to use to quickly identify digital exclusion at ward level

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• Mapped using national and local datasets e.g. ONS
• Key groups identified through initial WCC research
• Validated against additional local data sets

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Key Groups

• Older People
• Low-Income Families
• Unemployed
• Those with a disability
• Small and Micro Businesses

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Access the Map:

• Link to map here

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Identify Key Groups

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Identify Key Groups

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Digital Exclusion User Personas

Personas are a tool for designing services based on user needs. The bank of 24 personas enables you to understand the needs, experiences and factors leading to digital exclusion from a person-centred perspective

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Methodology:

• Reviewed national, regional and local data to capture and identify the demographics, attitudes and behaviors of DE residents against the prevalence of the groups in the borough
• Created persona analysis and validation for pan-London applicability
• Conducted interviews with internal service representatives and stakeholders to refine persona list
• Taking insights to inform and tailor interventions for these groups
• Conducted interviews with across key groups in 3 additional boroughs to understand how individuals interact with services

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Key Insights/ Output:

• Residents often have multiple barriers to becoming digitally included
• Pan-London Digital Inclusion Personas

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Augment open data with local data sets for deeper insights

Use the Mapping Digital Exclusion Toolkit as a guide to producing richer and more granular insights using local data

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• How to access and download the data
• Suggested data sets to combine with
• Validation principles
• Data ethics

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Access the toolkit

Mapping Digital Exclusion Toolkit

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Insights from Quantitative and Qualitative Research

Qualitative Research

To understand the impact and experience of digital inclusion support service on residents lives

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• Barnet, Brent, Southwark conducted research with EY Seren -One-hour one-to-one interviews

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Key Groups

• Residents with learning disabilities.
• Residents experiencing unemployment or low skills.
• Residents who experience home learning.

Quantitative

Face to face surveys with 800 digital excluded residents to better understand the specifics of their digital exclusion needs

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• RBKC and westminster with Lake Research

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Key Groups

• Residents over 60
• Disabled residents or residents caring for someone with a disability
• Unemployed residents
• Low-income households

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To gain a better understanding of the specific impact of digital exclusion on individuals we conducted qualitative and quantitative research

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Key Qualitative Insights

Digital Inclusion: Learning Disabilities

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• Digital support allowed participants to stay in touch with peers, significantly improving behaviour, mental wellbeing, confidence and comfortability with digital activities.
• It can be challenging to learn how to use a new device especially keyboards with lots of letters and symbols which can confuse and distract participants.

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Digital Inclusion: Unemployed / Low Skills

• Most participants discovered digital support via a support worker or teacher and did not always recognise what “digital support” means.
• There wasn’t a full understanding of what digital skills training could lead to e.g. what career progression after an Excel course could look like.

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Digital Inclusion: Home Learning

• Not having suitable device for schooling (e.g. using a smartphone screen, old devices, one device for multiple children) was very challenging and stressful so digital support enabled confidence in learning and social skills for both parents and children.
• The learning resource gap was minimised between disadvantaged and advantaged children as they could access courses outside of school (e.g. coding, singing, language) alongside meeting additional needs such as therapy.

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Key Quantitative Insights

• The most significant barriers identified included: lack of interest, confidence and skills. 64% of non-internet users said they have no interest in using the internet, and that nothing would persuade them.
• Just 1 in 10 non-internet users said a free device would most likely encourage them to use the internet in the future.
• Across the top four key groups, social activities were the most important perceived benefit of accessing the internet.
• Unemployed respondents were more likely than average to access the internet in a library, community centre or public place.
• 40% of respondents said they’d prefer to receive help from friends and family to improve their confidence and skills, but more than 9 in 10 (91%) had no children living in their household.

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Digital inclusion segments

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Segments Identified

Segment 1 - Not for me

The key barrier is lack of interest.

Defining characteristics

• Consisted predominantly of older residents; 86% were over 65 years old, and almost half (46%) were over 75 years old.
• The majority (94%) said they weren’t planning to access the internet in the next 12 months, and more than 4 in 5 (84%) felt they didn’t need to learn any skills in the future.
• Over half (59%) said they saw no benefits to accessing the internet.

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Segment 2 - Reliant on others

The key barriers are impairments, getting someone else to do what they need and over complexity.

Defining characteristics

• More than a third of members in this segment said that impairments make it difficult for them to use the internet, and that they get someone else to use the internet on their behalf.
• Members of this segment were less likely to face barriers associated with cost or lack of equipment (<5%).
• Almost 1 in 5 (18%) had children living in their household.
• Almost half (49%) said they would just like to develop basic skills, such as sending and receiving emails, but not more advanced skills (e.g. internet banking or staying safe online).

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Segments Identified

Segment 3 - Unconfident

The key barriers are a lack of confidence, uncertainty and lack of trust.

Defining characteristics

• All members of this segment said they were not confident using devices or the internet.
• Over a quarter (26%) didn’t know where to start with it and almost 2 in 5 (19%) were worried about making mistakes or being taken advantage of.
• Almost a third (31%) said that getting more support from someone to help them get online would encourage them to use the internet in the future.
• Lack of confidence transcended demography - few demographics were over or under-represented in this segment.
• Approximately 2 in 5 (19%) said they were non-registered unemployed seeking work.

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Segment 4 - Low income and confidence

The key barriers are a lack of equipment, a lack of confidence, over-complexity and the high cost of devices.

Defining characteristics

• Members of this segment were more likely to face multiple barriers to digital inclusion; all said they lacked the right equipment, three quarters lacked confidence, and more than half cited the high cost of devices as a barrier.
• Approximately 4 in 5 (81%) had a yearly household income of 10k or less.
• The majority (86%) were in NRS social grade E (non-working) and approximately 2 in 5 (19%) said they were non-registered unemployed seeking work.
• Almost a quarter (24%) would like help from a council service, such as Adult Education or other learning provider.

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Segments Identified

Segment 5 - Financially constrained

The key barriers are the high costs of wi-fi data and the high cost of devices.

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Defining characteristics

• This was the smallest segment of non-internet users. High costs were the main barrier for members of this segment, rather than other factors such as lack of confidence or interest.
• Almost 1 in 10 (9%) also said English as a second language was a barrier to accessing the internet.
• Almost half (48%) said that free or low cost internet access would encourage them to use the internet in the future.
• Over half (52%) said they would just like to develop basic skills, such as sending and receiving emails, but not more advanced skills (e.g. internet banking or staying safe online).

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Triage Questions

Types of Digital Inclusion Intervention

List of local digital inclusion provision

(Open Referral Standard)

Can need be met?

Refer Resident

Collect evidence on service gap to inform future investment

Yes

No

Create and test list(s) of triage questions, building on persona profiles

Triaging Digital Exclusion Needs

Yogita Popat - yogita.popat@barnet.gov.uk

Jay Saggar – jay.saggar@loti.london