1. NEON Conference 13 October 2011 NOMS Co-Financing Programme: Overview and emerging findings Bill Spiby NOMS CFO Lead Manager (Corporate)

2. Delivery Model 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’

3. Offender Target Group Skilled, qualified but unemployed Unqualified, unskilled and unemployed Unskilled, unqualified, de-motivated, drugs / alcohol issues, behavioural issues, debt problems, accommodation problems. DWP… SFA… 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

4. Hard-to-Help Groups 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

5. NOMS CFO in numbers 40,896 participants started so far 4434 employment outcomes claimed 8356 hard education/training outcomes 1 in 3 would consider self employment 59% have used illegal drugs 72% do not have a valid, current driving licence 16,806 did not complete their formal school education 1 in 9 have mental health problems 1 in 3 have outstanding debts or fines 1269 are carers for a friend or relative 224,526 soft outcomes achieved 3061 have problems using numbers project overview assessed needs 1 in 4 participants are non white-British 30 years old on average at time of starting 1742 veterans 1818 aged 50 or over on starting demographics 1 in 8 female participants 223 of which were for NEETs

6. 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.

7. Likelihood of Gaining Employment men 8 to 1 odds the participant will gain employment women 12 to 1 white-British 8 to 1 non white-British 9 to 1 remained in region 8 to 1 moved from region 22 to 1 more likelyless likely odds the participant will gain employment less likely to gain employment than male participants less likely to gain employment than white-British participants less likely to gain employment than those who remained in one region female participants were 40% non white-British participants were 18% participants who moved area were 2.6 x

8. Do Soft Outcomes Increase the Likelihood of Gaining Employment? just as likely to gain employment much more likely to gain employment 1x 2x 5x number of participants gaining outcome: 25 100 500 1000 5000 motivation employability mentoring not contracted other signposting (referrals) advice qualifications non-accredited courses interview secured DAF hard ETE ed/train motivational training achieved by 2856 participants 4.8X more likely to later gain employment self presentation achieved by 251 participants 5.4X more likely to later gain employment work placement or taster achieved by 448 participants 6.3X more likely to later gain employment interview skills achieved by 1091 participants 3.5X more likely to later gain employment signposting to I.T. training achieved by 44 participants 3.3X more likely to later gain employment transport advice achieved by 339 participants 4.8X more likely to later gain employment access counselling services achieved by 181 participants NO more likely to later gain employment childcare/dependent guidance achieved by 1749 participants NO more likely to later gain employment

9. Does ethnicity have an effect with regard to gaining benefit from a soft outcome? more beneficial for NWB than WB, towards gaining employment more beneficial for WB than NWB, towards gaining employment NWB more likely to achieve than WB WB more likely to achieve than NWB Comparing non white-British (NWB) participants to the rest of the cohort (white- British (WB)) mock interviews people skills awareness of community based services debt management motivation training health awareness less beneficial more likely to achieve more beneficial more likely to achieve more beneficial less likely to achieve less beneficial less likely to achieve

10. How Does the Positive ‘Effect’ of a Soft Outcome Vary between Genders? more beneficial for women than men, towards gaining employment more beneficial for men than women, towards gaining employment men more likely to achieve than women Comparing female participants to the rest of the cohort (male participants) application process self presentation mentoring access community based services access counselling service signposting to benefit advice less beneficial more likely to achieve more beneficial more likely to achieve more beneficial less likely to achieve less beneficial less likely to achieve DAF disclosure advice women more likely to achieve than men

11. 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?

12. action plan created start end motivation changednote addedoutcome - advice outcome - DAFoutcome - employabilityoutcome – interview securedoutcome - signposting outcome - mentoringoutcome - qualificationeducation or trainingemployment %% % %% %% Assessing the Participant’s Journey What Happens When?

13. 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”

14. 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

15. 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