ONS Local has been established by the Office for National Statistics (ONS) to support evidence-based decision-making at the local level. We aim to host insightful events that connect our users with exciting developments happening in subnational statistics and analysis at the ONS and across other organisations. The High Street Data Service is a partnership project between the Greater London Authority, London Boroughs and local organisations. Using a subscription model, it gives shared access to detailed footfall, spend, premises and context data to inform decision making, prioritisation and investment plans. In addition to central purchasing, processing and sharing of up to date data, it offers a package of support including workshops, self-service tools, data-surgeries and a professional network. Now entering its third year, the GLA team will talk about the different types of analysis, as well as how the programme has developed, what they’ve learned and future plans. If you have any questions, please contact ons.local@ons.gov.uk

1. HIGH STREETS
DATA SERVICE
ONS Local Presents
23 March 2023

2. What is it?
The High Streets Data Service (HSDS) is a collaborative
data sharing partnership between GLA, London boroughs,
and BIDs providing the insights on London’s 600+ High
Streets and Town Centres.
The GLA Good Growth & City Intelligence Unit enable:
― Direct access to raw data
― Custom-built data explorers and maps to provide quick
access
― Analytical support for your priority areas
― A network of public organisations using data to
evidence how High Streets are performing
How does it work?
A subscription model funds the collective purchase of data
and subsequent quality assurance and analysis.
200+ users from 19 LBCs are members of the service for the
2023 service.
2023 borough subscribers
Bromley • Camden • City of London • Ealing • Enfield • Greenwich • Hackney •
Hammersmith and Fulham • Haringey • Havering • Islington • Lambeth •
Lewisham • Merton • Newham • Redbridge • Richmond upon Thames •
Southwark • Tower Hamlets • Wandsworth • Westminster
HIGH STREETS DATA SERVICE
Overview

3. HIGH STREETS DATA SERVICE
Contents
Background (pre-Covid)
Discovery
Alpha
Beta
Live
Summary
2
1
3
4
5
6

4. HIGH STREETS DATA SERVICE
1 - Background (pre-Covid)
- Adaptive Strategies
- ‘Multifunctional public spaces’
- Network of Officers and experts
- Defined 600 High St Boundaries
- Report included ‘doing more with data’
- Town Centre Health Check
- Planning-led
- Retail Study
- Focussed on retail jobs
- In 2018, many High St had more jobs that 10
years before
- 24 hour London

5. HIGH STREETS DATA SERVICE
Contents
Background (pre-Covid)
Discovery
Alpha
Beta
Live
Summary
2
1
3
4
5
6

6. HIGH STREETS DATA SERVICE
2 – Discovery April 2020
- Survey of Borough Officers & BIDs
- Data currently used
- Data gaps
- Key questions
- Reviewing the market
- Lot’s of providers, making competing claims
- Some had very small samples (1-2%)
- Many had created a ‘product’ – often dashboard
with monthly subscription
- Issues with granularity
- Large variation in cost (including CSR offers)
- GLA pilot projects & TfL projects

7. HIGH STREETS DATA SERVICE
2 – Discovery April ‘20
- Survey of Borough Officers & BIDs
- Data currently used
- Data gaps
- Key questions
- Reviewing the market – honest broker / impartial
- Lot’s of providers, making competing claims
- Some had very small samples (1-2%)
- Many had created a ‘product’ – often dashboard
with monthly subscription
- Issues with granularity
- Large variation in cost (including CSR offers)
- GLA pilot projects & TfL projects

8. HIGH STREETS DATA SERVICE
Contents
Background (pre-Covid)
Discovery
Alpha
Beta
Live
Summary
2
1
3
4
5
6

9. HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21
- Made use of existing resources where possible
- Data team (up to 50% for some months)
- Data scientist
- Data visualisation developer
- GIS analyst
- Policy/Programme officers
- ‘Fixing the Plumbing’ resources
- Forum
- Data Sharing Agreement portal
- London DataStore
- GLA budgets repurposed to recovery missions
- Local specialist consultants

10. Key Audiences
• High St. / Town
Centre
Managers
• 24hr London
• BIDs
• Recovery Task
Force
• London-based
businesses
• Health planners
DATA FLOWS
HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21

11. commentary,
blogs, etc
data viz
High St. level
tools
APIs
Key Audiences
• High St. / Town
Centre
Managers
• 24hr London
• BIDs
• Recovery Task
Force
• London-based
businesses
• Health planners
Headline figures
Anonymised and
Aggregated data
by O2
CCTV feeds
Card spend
Pan-London
timeseries
Other sources
Funded
by
24hr
London
DATA FLOWS
open shared paid for
HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21

12. commentary,
blogs, etc
data viz
High St. level
tools
APIs
GLA and Turing internal systems Key Audiences
• High St. / Town
Centre
Managers
• 24hr London
• BIDs
• Recovery Task
Force
• London-based
businesses
• Health planners
Headline figures
Processing
(nightly)
Modelling
Storage
Footfall
Social distancing
Spend
High St. analysis
Anonymised and
Aggregated data
by O2
CCTV feeds
Card spend
Pan-London
timeseries
Other sources
Funded
by
24hr
London
DATA FLOWS
open shared paid for
HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21

13. HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA

14. HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
April ‘20 Aug ‘20
Oct ‘20 –
May ‘21
Are people leaving
their homes?
Effects of Tiered
lockdowns and
steps out
Are people
staying at home?

15. HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Home workers

16. HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Home workers
- Recovery at different times of the day

17. HIGH STREETS DATA SERVICE
3 – Alpha June ‘20 – June ‘21
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Home workers
- Recovery at different times of the day
- High St Signatures (National High Streets
Taskforce)

18. HIGH STREETS DATA SERVICE
3 – Alpha
- Anonymised and Aggregated data by Mastercard
- Weekday / weekend
- Index of spend & number transactions
- 2018 - present
- by 150m grid
- Analysis
- Spend over time
- By High Street
- By bespoke area
(e.g. Central London)
June ‘20 – June ‘21

19. HIGH STREETS DATA SERVICE
3 – Alpha
- Anonymised and Aggregated data by Mastercard
- Weekday / weekend
- Index of spend & number transactions
- 2018 - present
- by 150m grid
- Analysis
- Spend over time
- By High Street
- By bespoke area
(e.g. Central London)
June ‘20 – June ‘21

20. HIGH STREETS DATA SERVICE
Contents
Background (pre-Covid)
Discovery
Alpha
Beta
Live
Summary
2
1
3
4
5
6

21. HIGH STREETS DATA SERVICE
4 – Beta
- Pilot subscription model
- Flat-rate / Borough (22 members)
- 1 full-time data scientist
- Part-time programme manager
- Let’s Do London
- Service
- Summarised data
- Explorer tools
- Workshops
- Data Surgeries
- Lunchtime talks
- 1:1s
June ‘21 – June ‘22

22. HIGH STREETS DATA SERVICE
4 – Beta
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Dug deeper into the data
- New patterns
June ‘21 – June ‘22

23. HIGH STREETS DATA SERVICE
4 – Beta
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Dug deeper into the data
- New patterns
June ‘21 – June ‘22

24. HIGH STREETS DATA SERVICE
4 – Beta
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Dug deeper into the data
- New patterns
- Article 4 evidence
June ‘21 – June ‘22

25. +15°C
+20°C
+25°C
+30°C
+35°C
+40°C
HIGH STREETS DATA SERVICE
4 – Beta
- Anonymised and Aggregated data by O2
- Hourly counts
- worker / visitor / resident
- by MSOA
- Analysis
- Dug deeper into the data
- New patterns
- Article 4 evidence
- Responding to new events
- Plan B
- Strikes
- Lying in state
- Heatwave
June ‘21 – June ‘22
0
1
2
3
4
5
6
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
x
100000
Heatwave
-related
drop
Strike
-related
drop

26. HIGH STREETS DATA SERVICE
4 – Beta
- Anonymised and Aggregated data by Mastercard
- Weekday / weekend
- Index of spend & number transactions
- 2018 - present
- by 150m grid
- Analysis
- Dug deeper into the data
- Identified ‘cold spots’
June ‘21 – June ‘22

27. HIGH STREETS DATA SERVICE
4 – Beta
- Data Explorer
- How has High St ‘X’ changed over time?
- How does it compare to others?
- Web-based, longform, notebook-style tool
- Can focus on time period
- Bespoke areas
- Generate screen shots or small tables
June ‘21 – June ‘22

28. HIGH STREETS DATA SERVICE
4 – Beta
- Data Explorer
- How has High St ‘X’ changed over time?
- How does it compare to others?
- Web-based, longform, notebook-style tool
- Can focus on time period
- Bespoke areas
- Generate screen shots or small tables
- Map Explorer
- Brings together GIS layers from across the GLA
June ‘21 – June ‘22

29. HIGH STREETS DATA SERVICE
4 – Beta
- Year 1 Evaluation
- Survey of HSDS users
- Interviews with Borough officers
- Feedback from these sessions
- Direct Q & A sessions
June ‘21 – June ‘22
1
1
2
4
6
7
6
7
8
9
4
3
4
2
4
3
4
3
8
7
4
5
3
3
2
2
0% 20% 40% 60% 80% 100%
Reporting to senior executives
Reviewing recovery from Covid-19
and lockdowns
Monitoring for interventions or
funding requirements
Developing high street level plans
and strategies
Applying for grants/funding
Engagement with communities
Reporting to elected representatives
Developing nighttime
policy/strategy
Not important Unsure Somewhat important Very important

30. HIGH STREETS DATA SERVICE
Contents
Background (pre-Covid)
Discovery
Alpha
Beta
Live
Summary
2
1
3
4
5
6

31. HIGH STREETS DATA SERVICE
5 – Live
Operating model
- Governance
- Co-sponsors combines policy
expertise and data/digital
leadership
- Delivery
- 0.6 Programme Manager
- 1 FT Data Scientist
- Subscription model
- Boroughs - deepen engagement
- New users: Business
Improvement Districts
- Ability to share with consultants
Jan ‘23
GLA Co-sponsors
Data scientist
(FT)
CIU Sr
Manager (PT)
Programme
Manager (PT)
City
Intelligence
Night-time
economy
Economic
Development
Regen
Chief
Digital
Officer
Borough subscribers
LAMBETH
LEWISHAM
MERTON
NEWHAM
REDBRIDGE
RICHMOND
SOUTHWARK
SUTTON
WANDSWORTH
WESTMINSTER
BROMLEY
CAMDEN
CITY OF LONDON
CROYDON
EALING
ENFIELD
HACKNEY
H&F
HARINGEY
HAVERING
K&C
KINGSTON
BID subscribers
Administrator
(PT)
Governance
Delivery
Data users
Your
Action
BID
Aldgate
Partnersh
ip
Angel BID Argall BID
Baker
Street
Quarter
Beckenha
m
Together
BID
Beddingt
on for
Business
Central
District
Alliance
Better
Bankside
Bexleyhe
ath BID
Blue
Bermond
sey
Brixton
BID
Brompto
n Road
BID
Camden
Town
Unlimite
d
Cheapsid
e
Business
Alliance
Croydon
BID
EC
Partnersh
ip
Euston
(CTU)
Fulham
Broadwa
y
Fleet
Street
Quarter
Garratt
Business
Park
Hainault
Business
Park
Hammers
mith
Harrow
Town
Centre
BID (Ha1
BID)
Hatton
Garden
BID
Heart of
London
In Ilford
BID
In
Streatha
m BID
In West
Ealing
(West
Ealing)
Visit
Kensingt
on BID
Kingston
First
King's
RoadKipp
abid
London
Riverside
Love
Wimbled
on
Make it
Ealing
Marble
Arch
New
Addingto
n
New
West End
Company
(Business
)
Orpingto
n 1st
PaddingN
ow BID
(Paddingt
on
Watersid
e
Partnersh
ip)
Penge
SE20
Piccadilly
and St
James
Purley
BID
Positively
Putney
Richmon
d BID
Romford
BID
Sidcup
BID
South
Bank BID
South
Wimbled
on
Business
Area
(SWBA
Ltd)
Station
to
Station
Stratford
Original
Successfu
l Sutton
Team
London
Bridge
The
Fitzrovia
Partnersh
ip
The
Junction
BID
The
Northban
k
This is
Clapham
Try
Twickenh
am
Love
Uxbridge
Vauxhall
One
Victoria
BID
Victoria
Westmin
ster
Wandsw
orth BID
We Are
Waterloo
Whitehall
BID
Willow
Lane
Future
Wood
Green
BID
Your
Bromley
BID
BE
Richmon
d
GLA programmes
NTEZ
GG
Fund
eval
Econo
mics
Town
Centre
Health
Check
London &
co tourism
Markets

32. HIGH STREETS DATA SERVICE
5 – Live
Collective data procurement
- User needs: Responsive to user needs that came
up in alpha & beta
- Re-Procured data
- Increased granularity
- Time periods for spend data
- Smaller areas for footfall
- Dwell time, repeat visits
- Catchments
- Business Premises data
- Pushing the market
- Experimenting with geographic granularity
and temporal detail to maximise granularity
without compromising quality
- Delivery cadence with suppliers
Jan ‘23
Mobility
Spend
Business premises Experian new!
BT new!
Mastercard
Procured data

33. HIGH STREETS DATA SERVICE
5 – Live
Analysis
- Improve core service
- Review outputs & tools
- New analysis & outputs
- Broaden use cases
- Street Markets
- Daytime population for crime data
- Support 24hr Economy Plans
- Cost of Living analysis
- Special Event evaluation
- Less emphasis on lockdown
Jan ‘23

34. ARTICLE 4 DIR.
EVIDENCE
MEMBER
REPORTS
ESTIMATING
HOME WORKING
LICENCING
MONITORING
SPECIAL EVENT
EVALUATION
FOOTFALL
PROFILING
NIGHT TIME
STRATEGIES
INTERNAL
DASHBOARDS
ESTIMATING
WORKER RETURN
ACADMIC
RESEARCH
BIDS
BENCHMARKING
PREDICTIVE
MODELING
Current Future
HIGH STREETS DATA SERVICE
5 – Live
ROUTINE
MONITORING
POLICY
ANALAYSIS
DECISION
SUPPORT

35. HIGH STREETS DATA SERVICE
Contents
Background (pre-Covid)
Discovery
Alpha
Beta
Live
Summary
2
1
3
4
5
6

36. Collect
Anony-
mise
Procure QA Curate Convene
Analyse Act
The coordination problem
Existing data assets are hard to
find and high streets practitioners
lack a common analytical agenda
HIGH STREETS DATA SERVICE
6 – Key Findings
The cost problem
High cost of privately collected
data and administrative overheads
prohibits its use
The evidence problem
High streets policy and
investment are made from
anecdotal, out-of-date, or
imprecise evidence
Data suppliers
Data users (boroughs,
BIDs)
HSDS Programme
The commercial data market was not serving local organisations
Disaggregating the ‘data value chain’ focuses each party’s effort on what they are good at

37. HIGH STREETS DATA SERVICE
6 – Key Findings
Strategic policy goals
User needs (technical and non-technical)
Following the completion of its pilot in
June 2022, the High Street Data
Service requires continuous
improvement to its data assets and a
continued high standard of service to
partners to achieve lasting and scalable
engagement.
It also requires ongoing pivots to
impactful and flagship analytical use
cases to evidence value and drive the
case for investment.
Flexible
and unique
data assets
Responsive
research
and analysis
Scalable
operating
model

38. HIGH STREETS DATA SERVICE
6 – Key Findings
Practical learning for setting up your own service:
March ‘23
Raw data
allows you to address a wider range of
questions
Detail &
frequency Think carefully about what you need
Comparator
data
Doesn’t have to be identical, for us it was
TfL oyster & high-level economic analysis
Impartial
assessor
If you don’t have this internally maybe
partner with an organisation?
Resourcing
You don’t need a huge team, but will need
data science capability
User focus
Engage your users often and draw your
‘super users’ in close

39. For more information, please contact
Paul Hodgson | Senior Manager – City Data
Craig Campbell | HSDS Programme Manager
HighStreetsDataService@london.gov.uk
HOW CAN I GET INVOLVED?
2023 borough subscribers
Bromley • Camden • City of London • Ealing • Enfield • Greenwich •
Hackney • Hammersmith and Fulham • Haringey • Havering •
Islington • Lambeth • Lewisham • Merton • Newham • Redbridge •
Richmond upon Thames • Southwark • Tower Hamlets •
Wandsworth • Westminster