Objectives To share the ambition and work of The Essex Data Programme To bring to life with a working model – predicting school readiness in Basildon What we are doing The results To highlight future opportunities and learning to date Q&A and group discussion

2. Objectives of the session
1. To share the ambition and work of The Essex Data
Programme
2. To bring to life with a working model – predicting
school readiness in Basildon
3. To highlight future opportunities and learning to date
4. Q&A and group discussion

3. Rethinking commissioning – 8 common features
1. Engaging with citizens and communities in a profoundly different and
immersive way
2. Creating (or collaborating to create) a transformative vision focused on
outcomes
3. Discerning about what is simple and what is complex
4. Being comfortable with complexity and uncertainty, and helping others to
be comfortable with it
5. Investing in and managing relationships across a system to reach common
goals
6. Designing solutions, drawing on good data, expertise, methods and
approaches
7. Making a clear and compelling case for different and better
8. Always thinking long-term

4. They have tried to mobilise very different types of teams

5. Theory of
change for
Co-produced
solutions
Risk
Stratification
Data Outputs
Local
Insight
Community
Assets
The ambition…

6. The Essex Data Programme
A partnership programme of work led by ECC
A pilot programme with PredictX – testing, learning and
building whole-system capability
Using data to shift from I think to I know this is a problem
Using data to improve outcomes and reduce demand and
cost
A programme that seeks to provide the capability and capacity to safely share and match data
across Essex partners so that it can be used to provide insight and to predict risk to inform
where and how to direct resources.

7. Essex Data is made up of….
A programme team
The Predict X safe data
sharing platform
A series of predictive
risk prototypes

8. Essex Data is nationally innovative….
Focus on predictive
analytics, not just
operational flows across a
system
Using whole-system data not
just data from one
organisation or one sector
The

9. Predictive Analytics in a nutshell
Forecasting
Customer
Segmentation
and
behavioural
insights
Risk
Stratification
Pathway
modelling,
Simulation &
Scenario
models
Predictive analytics is about using data about the past to plan for current and
future needs, demands and behaviours. Working with PredictX to create
models and generate insight about the future

10. Predictive Analytics in a nutshell
Predictive analytics is about using data about the past to plan for current
and future needs, demands and behaviours. Creating models and
generating insight about the future
Risk
Stratification
• Creates risk scores and/or pathways
• Risk = Probability that an outcome is
achieved
• Used for targeting resources where they
are most needed
• Creates risk and resilience profiles and
pathways
What we know
about people
now
What might
happen in the
future

11. Can we use insight from ED to
triangulate with other insight to
commission differently to increase the
number of children who are school
ready?
Can we predict which
children will not be school
ready on starting school in
reception?
Predicting communities in Basildon who are most at risk of not being school
ready.
School Readiness….The Ask
https://www.youtube.com/watch?v=3J2S82vjb
8U&feature=youtu.be

12. School Readiness….what we did
• Data from ECC, Basildon BC and Essex Police which is pseudonymised at
source and matched at household level.
• Results are displayed at output area level and will enable targeted
intervention at a community level which was considered the right level for
this work.
• Using predictive risk models to triangulate with other insight to agree a suite
of changes and or interventions that will enable ‘best start in life’.
Theory of
change for
Co-produced
solutions
Risk
Stratification
Data Outputs
Local
Insight
Community
Assets

13. School Readiness…. Ethics
Cabinet Office Data Science Ethical Framework – 6 Key Principles

14. School Readiness….The Results
• In Basildon those who are known to services are 1.5 times more likely to
not be ready for school
• This leaves a sizeable cohort (1,539 over the four year period of the data)
of school starters that are not known to services and that were ‘not school
ready’.
• The risk model would have correctly identified half of these at ‘risk of
being not ready’ – which is 2 times better than random.
• The model is 75% accurate enabling resource to be targeted to those
communities that would benefit from it the most.
• Financial stability & presence of anti-social behaviour are the most
significant social and environmental factors.

15. School Readiness….The Results
Highest Risk Areas

16. Using the Insight
Combining
insight
sources
June/July
2017
Agree co-
production
plan
September
Co-deliver
changes
October
onwards
First
potentially
impacted
children enter
school
Sept 2018
School
readiness
data
available
March
2019
Next steps
• Local families engaged and asked to share their views on key factors – insight
collected by TONIC
• TONIC insight + assets register + data profile used to inform a process of co-
production with the community.
• The recommendations will enable more effective shaping and focus of existing
resource and capacity that will lead to more children getting the best start in life
by being ready for school, improving their longer term outcomes and reducing
service demand later on.

17. Developing future prototypes
1. Agreement of the problem to
be tackled & assessment of
ethics
2. Identification of data
required and ISPs
3. Load data, create risk
model, generate insight 4. Application of ED insight, along
with other information to inform
service reform activity
5. Delivery of reformed services to improve outcomes for local
people, reduce cost and/or demand
Informationgovernance
Culturechange
Finding the right problem

18. Future prototypes concepts
Theme
Domestic Abuse
What are we
seeking to
understand?
Can we predict
earlier those who
are likely to
experience
domestic abuse?
To enable change
Earlier
intervention and
preventionHealth and Social
Care
Can we predict
earlier those who
have preventable
reasons for hospital
admission such as
first time falls?

19. Some key lessons so far…
Need to specify the predictive problem and the relevant data
sets – is a data solution right for this problem?
Enabling cross partner data share is as much about the culture,
politics and organisational capacity as the enabling technology
Ethical consideration needs to be integral within project design
and delivery – how to balance the duty to protect with the duty
to prevent?
Communities want to be involved in designing and delivering
change.

20. Group discussion…
How can we help communities understand the benefits of
sharing and using their data?
How can we measure and understand the public benefit of
using data?
What are the risks associated with using data and of not
using data?
Julia Ross
Chief Strategist Care and Health
PredictX
julia.ross@predictx.com
07725653654
Dave Hill
Executive Director, Social Care & Education
Essex County Council
Dave.Hill@essex.gov.uk