NEON Conference
13 October 2011
NOMS Co-Financing Programme:
Overview and emerging findings
Bill Spiby
NOMS CFO Lead Manager (Corporate)
Delivery Model
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Split into two phases
Phase 1: Jan 2010 – Dec 2011
Phase 2: Jan 2011 – Dec 2014
2011 transition year
Case management model
Delivered through CATS
Link to Offender Management arrangements
70:30 community/custody split
Support mechanisms to include mentoring,
social enterprise and Discretionary Access Fund
• Ex-service personnel to make up 4% of cohort
• Focus on the ‘hardest-to-help’
Offender Target Group
DWP…
Unqualified,
unskilled
Skilled,
qualified but
unemployed
and unemployed
SFA…
Unskilled, unqualified,
de-motivated, drugs /
alcohol issues,
behavioural issues,
debt problems,
accommodation
problems.
NOMS CFO
Hard to help group who are currently
not able to access mainstream
provision, and are therefore unable
to return to the labour market
Hard-to-Help Groups
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North East – Lifers
North West/Merseyside - Women with low-level mental health needs
Yorkshire & Humber - Islamist extremists/sex offenders
South Yorkshire - Sex offenders
East Midlands - Dual Diagnosis Offenders/female sex workers
West Midlands - Travellers/show people
East of England - Female sex workers
South East - Offenders with dependent families (particularly 18-24s)
London – Veterans/young people involved in gang activity/prisoners
released following sentences served abroad
• South West - Young offenders transitioning into the adult justice
system
• Cornwall – link to SW sub-group participants
NOMS CFO
in numbers
project overview
demographics
40,896 participants started so far
4434 employment outcomes claimed
223 of which were for NEETs
8356 hard education/training outcomes
224,526 soft outcomes achieved
1 in 4 participants are non white-British
30 years old on average at time of starting
1 in 8 female participants
1742 veterans
1818 aged 50 or over on starting
assessed needs
59% have used illegal drugs
16,806 did not complete their formal school education
1 in 3 have outstanding debts or fines
1 in 3 would consider self employment
1269 are carers for a friend or relative
72% do not have a valid, current driving licence
1 in 9 have mental health problems
3061 have problems using numbers
Insights So Far…
• Two topics covered today:
• What support makes a difference to participant’s
likelihood of gaining employment?
• Assessing a participant’s journey while on the
project
• All data has been collected from the CATS database.
• All analysis is based on participants who have had their
record closed - 25,691 individuals to date, unless
otherwise stated.
• Where appropriate, statistical adjustments have been
made to control for regional variation between providers.
Likelihood of Gaining Employment
less likely
more likely
men
women
odds the participant will gain employment
odds the participant will gain employment
8 to 1
12 to 1
female participants were
40%
less likely to gain employment
than male participants
white-British
non white-British
odds the participant will gain employment
odds the participant will gain employment
8 to 1
9 to 1
non white-British participants were
18%
less likely to gain employment
than white-British participants
remained in region
moved from region
odds the participant will gain employment
odds the participant will gain employment
8 to 1
22 to 1
participants who moved
area were
2.6 x
less likely to gain employment
than those who remained in one region
Do Soft Outcomes Increase the Likelihood of
Gaining Employment?
just as likely to
gain employment
much more likely to
gain employment
1x
number of participants
gaining outcome:
25
100
2x
5x
mentoring
not contracted
motivational training self presentation
interview
motivation
achieved by 2856 participants
achieved by 251 participants
secured
4.8X more likely to later
5.4X
gain
more
employment
likely to later gain employment
DAF
hard ETE
ed/train
other
qualifications non-accredited
courses
500
1000
5000
work placement or taster
achieved
448 participants
signposting
to I.T.bytraining
6.3X
more
likely
to
later gaintransport
employment
advice
achieved by 44 participants
achieved
by
339
participants
3.3X more likely to later gain employment
4.8X more likely to later gain employment
access counselling
services
interview
skills
achievedachieved
by 181 participants
by 1091 participants
employability
NO more3.5X
likelymore
to later
gain
employment
childcare/dependent
guidance
likely
to later
gain employment
signposting
advice
achieved by 1749 participants
(referrals)
NO more likely
to later gain employment
Does ethnicity have an effect with regard to
gaining benefit from a soft outcome?
Comparing non white-British (NWB) participants
to the rest of the cohort (white- British (WB))
NWB more likely to
achieve than WB
less beneficial
more likely to
achieve
more beneficial
more likely to
achieve
awareness of
community based
services
mock interviews
more beneficial for
WB than NWB,
towards gaining
employment
people skills
more beneficial for
NWB than WB,
towards gaining
employment
motivation training
health awareness
debt management
less beneficial
less likely to
achieve
WB more likely to
achieve than NWB
more beneficial
less likely to
achieve
How Does the Positive ‘Effect’ of a
Soft Outcome Vary between Genders?
Comparing female participants
to the rest of the cohort (male participants)
less beneficial
more likely to
achieve
women more likely to
achieve than men
more beneficial
more likely to
achieve
application
process
self presentation
access counselling
service
access community
based services
signposting to benefit
advice
mentoring
more beneficial for
men than women,
towards gaining
employment
disclosure advice
more beneficial for
women than men,
towards gaining
employment
DAF
less beneficial
less likely to
achieve
men more likely to
achieve than women
more beneficial
less likely to
achieve
Quick Recap
• Evidence shows that soft outcomes are clearly beneficial
towards aiding a participant to gain employment.
• Some outcomes are more beneficial than others.
• Some outcomes are more beneficial for specific groups.
• More analysis needs to be done:
• How do outcomes interact with each other?
• How effective is the assessment process?
• To what extent do individual barriers prevent soft outcomes
from being beneficial?
• Which soft outcomes should we be contracting for?
Assessing the Participant’s Journey
What Happens When?
action plan created
%
motivation changed
%
start
end
end
%
start
end
%
end
outcome - signposting
end
start
education or training
%
end
end
%
start
outcome - qualification
start
start
outcome – interview secured
end
%
start
end
%
start
outcome - mentoring
%
start
outcome - employability
%
outcome - advice
%
start
outcome - DAF
note added
end
employment
%
start
end
start
end
Social Enterprise – provider comments from
Interim Reports:
•“Partner referring agencies need to improve internal
communications and systems and engage properly”
•“Poor risk assessment / risk sharing limits commercial activity”
•“Poor offender selection / matching to project leads to
unreliable work force to detriment of business”
•“Projects that are part of wider organisation benefit from scale
economies”
Positive messages from interim reports:
• Social Enterprise based interventions have a positive effect
on offenders
• Compliance increases and attitude improves
• Engagement, confidence and employability improve
• Real work environment and mixed peer groups have positive
effect
• A number of projects (including Paint It in Nottingham) report
offenders returning as volunteers post order
• Early indications of positive ETE outcomes for participants as
a result of engagement with social enterprises
In summary
•Early evidence indicates that social enterprises can achieve
positive, cost effective results
•Can be sustainable, but funding/subsidy in some cases may
need to taper over more than 1 year
•Strong on social aims, less so in terms of commercial
enterprise
•Need a strong and effective relationship with referring agencies
- mutually supportive partnership
•Commercial settings have positive impact on offenders