A Report by Regeneris Consulting

www.regeneris.co.uk

Contents Page1. Introduction 1

2. Evaluation Objectives, Scope and Questions 3Evaluation Objectives 3Scope of the Evaluation and Key Research Questions 3

3. Design and Delivery of the Innovation Pilot 5

4. Approach, Methods and Tasks 10Formative Evaluation 10Mid-Term Evaluation 12Options for Impact Assessment 13

5. Monitoring 29Indicators 29Data collection methods and timeline 36

6. Implementation 38

Appendix A - Logic Chains

Appendix B - New appendix section

Appendix C - <Insert title here>

1. IntroductionAims of project

1.1 The Health and Care Sector Progression Academy (HCSPA) is a pilot project developed by the Cambridgeshire and Peterborough Combined Authority in partnership with the Department for Work and Pensions (DWP). The project is one of six pilots being supported by DWP, which will trial new approaches to helping disadvantaged people secure and retain high quality jobs.

1.2 The HCSPA pilot aims to reduce dependence on in-work and out-of-work benefits by recruiting unemployed or low skilled people in to the H&C sector and supporting existing employees to progress to higher skilled and better paid roles. The project was awarded £5m in funding from DWP in August 2017.

1.3 Project activities to date have included business case development, marketing, stakeholder engagement, a review of what has worked elsewhere, project team assembly, design of pathways (eg apprenticeships, care certificates) and setting up systems. The initial phase of delivery is currently planned for early 2018, with the precise date to be confirmed.

Evaluation Requirements1.1 DWP has not issued specific guidance on the monitoring and evaluation

requirements of the pilot projects. However, they are keen that the projects generate robust findings of what works in terms of supporting disadvantaged people in to employment and in-work progression. The project team have had discussions with DWP and evaluation specialists at the What Works Centre for Local Economic Growth (advisers to the Department for Work and Pensions). These discussions have explored the potential to undertake robust counterfactual impact evaluation using a treatment and control group and the pros and cons of this approach compared to alternatives.

1.2 The Combined Authority appointed Regeneris Consulting to produce this evaluation plan, which will guide the planning, management and conduct of the evaluation of the HCSPA. Specifically, the evaluation plan sets out: the scope of the evaluation and the key research questions that it needs

to address the logic chain for the project, which sets out how activities will

generate outputs, beneficiary outcomes and economic/social impacts, and the implications for the evaluation.

initial thoughts on information requirements and some of the potential challenges. This is intended to guide thinking but is not intended to be a detailed monitoring plan

an outline of the proposed approach to the evaluation, including consideration of options and identification of the preferred approach.

1.3 The plan has been developed through consultation with the project team and DWP and a review of methods adopted on similar labour market interventions.

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2. Evaluation Objectives, Scope and QuestionsEvaluation Objectives

2.1 The evaluation needs to: assess the extent to which the project has met its objectives which

include improved rates of progression in the H&C sector, increased recruitment into the sector and to address skill shortages experienced by employers.

understand which elements of project activities and processes have worked well and what challenges have been faced.

quantify the impact that HCSPA support has had on beneficiaries, which may include increased employment, earnings growth and a reduction in skill shortages.

assess the value for money of the project generate a set of lessons learned in delivering HCSPA that the CA and

DWP should reflect on in designing and delivering future programmes.

Scope of the Evaluation and Key Research Questions

2.1 The evaluation should include the following: A review of the consistency and relevance of the project: the

purpose of this is to understand the strategic fit of the project and whether it has been designed in a way which is fit for purpose. Key questions include: Are the project’s objectives consistent with local and sub-regional

strategies and policy documents? Is there clear evidence of the challenges that the project is

responding to? Is there a clear logic chain for the project, and are the outputs and

result indicators relevant to the project objectives and activities? A review of performance against financial, activity and output

related delivery targets: the aim will be to monitor progress towards the project’s goals using the metrics which are most relevant to project activities. This can be used to identify areas of over and under-performance and any challenges that have emerged. Key questions include: Are the financial, activity and output targets achievable but still

ambitious? Has the project been (or is it being) delivered within budget? If

not, why not?

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Has the project met or exceeded all of its targets for outputs? What explains any under or over-performance?

Process evaluation: this should explore how the project delivery model has worked in practice, including the structures and processes put in place, and how effectively these have been working. The full set of questions this would need to cover are described in Section 4 and covers governance and management, project design, project systems, marketing, stakeholder engagement, contractual relationships and the referrals process.

Impact evaluation: this is a key part of the evaluation which will establish what the impact of the project has been and help to answer whether the project has achieved its objectives. It needs to cover those outcomes which can be quantified (eg entry in to employment, increase in earnings) and softer outcomes (improved quality of life, increased confidence etc). This needs to establish: whether the project has achieved a change in outcomes and what are the causal effects of the project’s activities on the

different outcomes. Economic evaluation: the aim will be to compare the economic costs

and benefits of the project, so as to understand its value for money. Key questions include: Can the full range of costs and benefits be monetised so as to

compare with other projects? (this may be difficult for a project of this nature where many of the benefits will be qualitative in nature).

If so, what is the net present value of the project after accounting for costs and benefits?

What is the ratio of costs to benefits for the range of different outcomes (eg cost per job) and how does this compare to similar projects?

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3. Design and Delivery of the Innovation Pilot

3.1 This section describes the HCSPA pilot in detail, including the challenges that the pilot is responding to and how the project activities will respond to these challenges. It should be read in conjunction with the four logic chains included in the appendix. These provide a graphical depiction of the logical relationships between the resources, activities, outputs and outcomes of the project. We have produced four separate logic chains for different types of beneficiaries as the anticipated outcomes and impacts are different for each.

Project Concept3.1 The project aims to address two interlinked challenges facing the health and

care sector: A large number of vacancies and a shortage of skilled staff to fill these

vacancies A large number of people working in low-paid jobs, with limited

prospects for progression to higher skilled and better paid roles. 3.2 Research suggests that one of the main barriers to progression is that

employers are reluctant to train and promote staff for higher skilled roles because they cannot be certain of the pipeline of potential recruits to fill vacated positions. The pilot will address these challenges through a holistic approach which will help to develop this pipeline of employees, delivered in two parts: Helping people outside the sector gain work and a career pathway in

H&C Helping existing employees in the sector to progress in their careers

Beneficiaries3.1 There are a number of different potential beneficiaries for the project, which

the evaluation will need to consider. These include: People outside the sector: this could include unemployed people or

people working in low skilled and low paid work with limited prospects of progression. The project will only target people who receive in-work or out-of-work benefits

Existing H&C employees: this could include any staff with qualifications up to Level 4 who are receiving in-work benefits.

Employers in the H&C sector.

Approaches and Activities3.1 Both parts of the project will encompass three strands of activity but will use

different delivery methods. The three strands are:

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Skills training: the exact training provided will depend on the needs of the beneficiary, but will comprise of two main routes: Below level 2 route: this will provide sector specific induction

training resulting in a theory of care certificate. This route will apply to anyone from outside the sector or existing staff who do not hold a level 2 qualification or the care certificate. Beneficiaries could also receive basic skills training in IT, English, maths or ESOL depending on their need. This training would last for approximately 20 weeks.

Apprenticeship route: co-designed with employers from across the H&C sector. This route will be taken by existing staff who already hold a level 2 qualification. This would be for a minimum of a year.

Careers advice/coaching/post-employment support: this could include help finding vacancies, support with the application process or advice and support once beneficiaries have found employment. Support will be provided up to four months after the end of training.

Wrap-around support: this will help to remove or reduce the barriers to taking up training such as bursaries for child-care and transport costs.

3.2 Beneficiaries from outside the sector will also have the option of attending work experience visits at the end of their skills training, although this may not be convenient for all participants, particularly those who already have a job.

Phasing of delivery

3.1 The project will be delivered through a phased rollout. The project team is planning to have 16 rounds in total split over three years (six rounds in years one and two and four rounds in year three). The first round is scheduled to start in February 2018, with a new round starting every other month.

3.2 Each round will include multiple courses, which will be split between provision for people from outside the sector and people within the sector. There will be eight courses per round in year one, 16 courses per round in year two and 12 courses per round in year three. There will be a minimum of eight learners per course.

Table 3.1 Phasing of Delivery of the ProjectNumber of

roundsCourses per round Est number of

learners per round

Number of learners per

yearOut of sector

In sector

Year one 6 5 3 64 375Year two 6 11 5 128 750Year three 4 8 4 96 375

3.3 The first areas to receive the support will be Orton (Peterborough), March (Fenland) and Huntingdon (Huntingdonshire). It has not yet been determined which areas will be included in subsequent rounds. The project team have said they will work with the Combined Authority, district and unitary authorities to plan the future locations once the project is underway.

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Beneficiary OutcomesBeneficiaries from outside the sector

3.1 For those beneficiaries from outside the sector, the first outcomes we would expect to see are the submission of applications for jobs in the H&C sector and ‘soft’ outcomes such as increased confidence and social capital (for instance access to new networks or the formation of new relationships). These outcomes are likely to arise towards the end of the 20 week support period, when the participants have gained new skills and experience and are working with coaches to identify potential job opportunities.

3.2 In the months after the training has ended, beneficiaries are expected to have found employment in the H&C sector or made progress towards it. This could mean entry in to a volunteering role or a relevant training course (gaining the skills and experience which moves them closer to a role in the H&C sector). For those that find a job in the H&C sector, a large proportion are likely to be in entry-level positions. Therefore, while some beneficiaries may see an increase in earnings and a reduction in benefits (particularly those that have moved from unemployment), this may not be the case for many participants. The main benefit for beneficiaries that are already in employment is that they would have access to a career progression pathway, although this outcome is likely to be difficult to measure in practice because the question of whether a job has good prospects or not is a subjective one.

3.3 Once beneficiaries have found a job in the H&C sector, they could then make further progress in their career, which may include promotion to higher skilled roles and/or an increase in earnings. However, these outcomes may take a long time to emerge (a year or more after finding a job in the sector).

Beneficiaries within the sector

3.1 Beneficiaries within the sector may take one of two routes; the below level 2 route or the apprenticeship route. For those taking the below level 2 route, outcomes are likely to be similar to those from outside the sector. Most people taking this route are likely to be working in low skilled and low paid ancillary occupations in the healthcare sector where there are limited prospects for progression, such as cleaners. The main outcomes for these beneficiaries are likely to be entry in to a role with better career prospects in the long term. However, there may not be a significant change in earnings from their previous role.

3.2 For those taking the apprenticeship route, the longer duration of training means that outcomes will take a longer time to emerge (a year or more depending on the length of the apprenticeship). In the months following the apprenticeship, we would hope to see clearer evidence of career progression (eg a move in to higher skilled and/or higher paid employment) and reduced dependence on benefits. However, in practice it could take a longer time for these benefits to emerge, which it may not be possible to capture through the evaluation. Other possible outcomes could include progression to higher level apprenticeships or other relevant training.

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Employers

3.1 Outcomes for employers could be positive or negative and will vary depending on the nature of their engagement with the programme and whether they are in the H&C sector. The range of potential outcomes in the short term (in the six months following the end of the support) include: Employers outside the sector experience an increase in staff vacancies

as a result of employees participating in the programme and finding alternative work in the H&C sector. Recruiting staff to replace these positions would increase business costs and some may struggle to fill the vacancies.

Programme of training and other support means that employers within the H&C sector find it easier to recruit workers (for entry level and higher skilled roles).

Recruitment of workers for low skilled positions results in more employers being willing to promote existing employees to higher skilled positions.

Increased skill levels of employees participating in the programme helps to address skill gaps and skill shortage vacancies.

3.2 In the longer term (a year or more after support ends), outcomes could include Better matching of employees and employers results in reduced staff

turnover and absenteeism. Success of the progression/recruitment model results in employers

changing their approach to workforce development and progression.

Impacts3.1 The intended impacts which need to be assessed by the evaluation are:

Increased employment rate due to unemployed or inactive people finding employment as a result of the programme.

Fiscal benefits as a result of people paying more in tax and receiving less in in and out of work benefits.

A reduction in the number of vacancies, hard to fill vacancies, skill shortage vacancies and skill gaps in the H&C sector.

Improved quality of life and well-being.

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4. Approach, Methods and Tasks4.1 The evaluation will be undertaken in three stages:

a formative evaluation six months in to project delivery. The aim of this will be to improve the project’s design and performance in the early stages of delivery.

a mid-term evaluation, half way through the project delivery period. The main focus of this stage will be to review progress towards output and financial targets and to understand what is working well and what is not working well to inform the later stages of delivery.

A final evaluation, conducted at least six months after the project activities have finished. The focus will be on assessing change in outcomes and impacts which can be attributed to the project.

4.2 We set out below the approach to the main strands of the evaluation described in Section 2 and at which stage of the evaluation.

Formative EvaluationReview of consistency and relevance

4.1 This will need to consider whether the project’s objectives are consistent with local and sub-regional strategies and policy documents and relevant to evidence of current challenges in Cambridgeshire and Peterborough. It should also review the proposed indicators proposed to measure outputs and results, and assess whether these are relevant to the project’s activities and objectives.

4.2 The task will require a policy review of relevant economic and labour market strategies and those related specifically to the H&C sector. It will also require analysis of relevant labour market datasets to assess the evidence for the challenges that this project is aiming to address. These could include datasets relating to employment, unemployment, vacancies, recruitment, training, skill shortages and gaps, particularly where there is a focus on the health and care sector. This should include publicly available datasets such as the Business Register and Employment Survey, the UK Employer Skills Survey and DWP benefits data, and research commissioned for the project such as employer surveys.

4.3 Based on this, the evaluation should reflect on whether the project is meeting an evidenced need and whether the project is designed around a clear logic chain for addressing these needs, or whether changes are required.

Process evaluation

4.1 The aim here will be to gain some early insights on which processes are working well and which are not working well. The research will be mainly qualitative, conducted through interviews with selected members of the project delivery team and some key project stakeholders, such as representatives from Jobcentre Plus and training providers. The themes that these interviews should cover are set out in Table 4.1 below.

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Table 4.1 Themes in the process review Governance and Management: what are the key decision making,

accountability and management structures and are they working effectively to guide delivery?

Project Design and Development: how did the approach develop and what was the rationale for this? Are services designed in a suitable manner to deliver the scale and type of outcomes and impacts expected? Are targets realistic and achievable in light of the value of the project and intensity of support being provided?

Project Systems: what are the key monitoring, reporting and financial control systems? Are these working effectively?

Marketing: what engagement and marketing approaches have been used? Are the right type of clients being targeted? What marketing and engagement activities have been more and less successful?

Stakeholder Engagement: has the project developed relationships with the right strategic stakeholders (e.g. with JCP for referrals)? Are these relationships working well in practice? Could more be done to strengthen these?

Contractual relationships: what processes have been put in places to develop and manage contractual relationships (eg with training providers)? Have any issues arisen with contractors and what lessons can be learned?

Needs assessment: how does the IAG stage work in practice? What tools and techniques are used to guide this?

Referrals: is the referral process working effectively? Are there particular client needs that are difficult to address?

Overall progress: Have there been any notable successes / challenges? Do any elements of the HCSPA approach or wider service offer need to be adjusted?

Scoping for impact assessment

4.1 The evaluation should carry out scoping work during the formative stage to assess whether the counterfactual approaches we suggest below are feasible in practice. By this stage of the project (six months after initiation), a number of rounds should have started receiving support so the evaluation should be able to review data on the number of participants and their characteristics. Based on this the evaluation should explore the potential to construct a control group using data from JCP or other sources (eg longitudinal Labour Force Survey). It should also be clearer whether sample sizes will be high enough to pursue methods which compare early and later participants.

Mid-Term EvaluationProcess Review

4.1 This will cover similar themes to the process review task described above, but will be able to go in to more detail for some themes as the project will have had more of a chance to gain momentum. It will also provide an opportunity to reflects on whether lessons have been learned from the formative evaluation.

4.2 Again the main methods should be consultations with key project stakeholders.

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Review of performance against financial activity and output related delivery targets

4.1 The evaluation will need to understand the costs of delivering the different elements of the project, and as far as possible link these to particular activities, outputs and outcomes. This is so that the evaluation can deliver insights around the costs, benefits and value for money of different activities. For this reason, the project monitoring data should provide as much detail as possible about different project activities and the role they played in generating outputs.

4.2 The evaluation will also need to provide a stocktake of performance against output targets for the project based on internal monitoring data (the full range of outputs are set out in the logic models, although the specific targets need to be determined). The evaluation will need to understand reasons for under or over performance through consultation with the project team.

Review of emerging impacts

4.1 While it would be too early to carry out a full assessment of impact at this stage (particularly using counterfactual methods), it should be possible to detect some emerging impacts from the longitudinal survey of participants and project monitoring data.

Options for Impact Assessment4.1 The assessment of impacts needs to establish (i) the achievement of a range

of outcomes or changes in these over time and (ii) the causal effects of the project activities on these different outcomes. As described above, these outcomes vary for different types of beneficiaries (those from outside the sector, those already working in the sector and employers). This section discusses the evaluation methods which are likely to be most suitable in determining the extent to which change in outcomes can be attributed to the project. We focus on each of the different beneficiaries in turn.

4.2 We discuss counterfactual approaches which aim to estimate the difference between the outcomes for individuals who participated in the project and the outcome they would have experienced without it. We also discuss some of the potential alternatives where counterfactual approaches may not be viable due to access to data or other methodological reasons.

4.3 Where we identify the potential for counterfactual approaches, we provide our assessment of where each approach would sit on the Maryland Scientific Methods Scale (SMS). The SMS ranks policy evaluations from 1 (least robust) to 5 (most robust) according to the robustness of the method used and the quality of its implementation. Robustness, as judged by the SMS is the extent to which the method deals with the selection biases and measurement issues inherent to policy evaluations. The What Works Centre for Local Economic Growth have identified level 3 as being the minimum level required for an evaluation to be considered robust1.

1 For a full explanation of the SMS and the criteria used to determine the levels, see the guide produced by the What Works Centre for Local Economic Growth (http://www.whatworksgrowth.org/public/files/Scoring-Guide.pdf)

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Beneficiaries from Outside the Sector4.1 The outcomes that will need to be assessed include:

Entry in to employment (for unemployed participants) Reduction in benefits Entry in to a H&C role with a good career pathway Improved skills Improvement in soft outcomes (eg confidence, social capital) Entry in to volunteering or relevant training course

Matched control group approach

4.1 Matched control group approaches compare outcomes between individuals who were subject to the intervention (‘the treatment group’) and similar individuals who did not participate (‘the control group’). These approaches are only feasible where the evaluator can access data on outcome indicators for both the treatment group and a suitable control group. Since most referrals will come from Jobcentre Plus, this approach would therefore be reliant on DWP sharing data on the characteristics of participants and non-participants. DWP has confirmed that a data sharing agreement is unlikely to be in place during delivery of the HCPA, and that the evaluation should plan on the basis that a matched control group approach would not be feasible. Although they did state that this approach could be done retrospectively if the data sharing agreement is approved at a later date.  For this reason, the project team should still ask participants to sign DWP consent forms to share their data.

4.2 If a matched control group approach was applied retrospectively, it may face a high risk of selection bias. This is a common risk for matched control group approaches because it is difficult to account for the full range of variables which will influence whether a person participates in the project. It is a particular risk for this project because JCP advisors will be encouraged to refer people who display ‘caring qualities’ which are difficult to observe. These characteristics could potentially be established through proxy variables, such as a history of receiving a carers allowance2. However it will be difficult to account for differences in the character traits of individuals based on the subjective judgments of JCP advisors.

4.3 A further challenge which might undermine this approach is the size of the pool of people receiving in-work or out-of-work benefits, and whether this will be large enough to identify a suitable control group. Benefits data shows there were around 7,800 people claiming unemployment benefits across the CA area in November 20173. We do not have up to date data on the total number of people on benefits (either in-work or out-of-work) but we know there were around 70,000 in November 2016, although a large number of these will face significant barriers to work. The pool of unemployed and employed people with similar characteristics to participants may therefore be

2 There were 16,500 people claiming carers allowance in Greater Cambridge and Peterborough in May 2017

3 This includes people claiming JSA and people already on Universal Credit who are able and willing to work.

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quite small, in which case it may be difficult to identify a suitable control group. It should be noted that matched control group approaches tend to work better when matches are on a one to many basis rather than one to one. A small sample size for the control group could therefore impose a significant challenge for this type of approach.

4.4 Conclusion: the evaluation needs to plan on the basis that a matched control group approach will not be feasible because it will not be possible to access data from DWP. This approach could be applied retrospectively if a data sharing agreement is put in place at a later date. If this approach was applied retrospectively, there may be practical challenges in identifying a suitable control group and a high risk of selection bias which may compromise the robustness of the evaluation. It should therefore only be applied in combination with other approaches.

Comparing earlier and later participants

4.1 An alternative approach would be to take advantage of the phased roll-out of the HCSPA project by using participants on later rounds as a control group for the participants on earlier rounds. The advantage of this is that the selection bias described above is eliminated (because individuals in both the control group and the treatment group have been deemed suitable for support). Assuming that the individuals are relatively similar to each other on other criteria, the labour market performance of the two groups can be compared over the period that one was receiving support while the other was not.

4.2 The impact would then be estimated using a difference in difference regression which takes account of pre-treatment differences between the early and late participants and the changes post support. The key assumption in this approach is that changes in outcomes in the same period for later participants (those not yet in the project) are a good counterfactual for the change that would have occurred for earlier participants if they had not received treatment.

4.3 The approach to estimating impact is shown in the diagram in Figure 4.1. The net impact of the support for Group A at the point that Group B starts receiving support is equivalent to ‘a’, while the net impact for Group B at the point Group C starts receiving support is equivalent to ‘b’. Because the analysis might yield different impact estimates for different groups, this approach is suited to projects where there are multiple rollout periods which can generate multiple observations.

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Figure 4.1 Illustration of how impacts would be measured using the phased rollout approach

Source Regeneris Consulting

4.4 While this approach would be feasible for the HCSPA project, it would potentially be complicated because of the small numbers of beneficiaries in each round. For example in the first year, each round will deliver support to around 64 learners in total (assuming eight learners per course on eight courses). However only around 40 of these will be beneficiaries from outside the sector (the other 24 will be from within the sector), meaning there will only be 80 observations in the treatment group and control group. With sample sizes this small it would be difficult to detect statistically robust impacts.

4.5 A useful concept to analyse this issue is that of the ‘minimum detectable effect (MDE)’. In simple terms, an MDE is the smallest impact a sample size can detect at standard levels of statistical confidence. The smaller the sample size, the greater the impact would need to be for the evaluation to be able to say with confidence that it can be attributed to the intervention (see Figure 4.2). The evaluation would therefore need to consider the potential scale of the impact that they expect the project to generate for different outcomes and make a judgement about the sample size required to generate robust results. There are a number of studies which provide practical guidance on how to calculate the MDE for different approaches.

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Figure 4.1 Illustration of Minimum Detectable Effect Size for different sample sizes

Source European Commission (2012): Design and Commissioning of Counterfactual Impact Evaluations

4.6 In practice it is likely that the evaluation would need to group different cohorts together in order to detect statistically robust impacts. For instance, using the first three rounds in year one as the treatment group and the first three rounds in year two as a control group. This would mean there are individuals in the treatment group who receive support at different times (up to 4 months apart). This should not matter as long as impacts are likely to have occurred before the control group starts receiving support. This should be the case for beneficiaries from outside the sector where the main outcomes (eg entry in to employment) are expected to occur in the six months following the period of support.

4.7 This approach would mean that the evaluation would need to collect historic labour market data for each beneficiary going back to before the program started (eg employment status, sector/occupation of employment, engagement with training), in addition to data on demographic characteristics (age, gender, qualification levels). This is so that performance against outcome indicators between early and later participants can be compared over time, and to understand differences between cohorts which might influence outcomes. This could be collected at the point that beneficiaries are enrolled.

4.8 Conclusion: a counterfactual approach which compares performance between early and late participants would achieve an SMS score of 4 (above the minimum score of 3) and should therefore be explored by the evaluation. Low sample sizes are likely to mean it will be difficult to generate statistically robust results using individual cohorts, although this could be overcome by grouping a number of them together. The disadvantage of this is that it would only result in a small number of observations of differences between groups (a maximum of two or three) which may mean the results are unconvincing, particularly if there is a large difference between observations. For this reason, it should only be pursued in combination with other methods.

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Comparison with national, regional or local data

4.1 An alternative approach would be to compare certain outcome indicators with national or regional datasets to give an indication of whether the project has resulted in beneficiaries outperforming the average.

4.2 This option could focus on certain outcome indicators which compare: the proportion of unemployed participants who entered employment

with the proportion of jobseekers in Cambridgeshire and Peterborough who found a job over the same period, using DWP data.

the proportion of employed participants who entered employment in the H&C sector with the proportion of people who have changed their sector of employment over the same time period who went in to the H&C sector. This would need to use data from the Labour Force Survey or Annual Population Survey, which asks about changes in employment. The low sample sizes mean it would only be possible to carry out this analysis at the regional (East of England) or national level.

4.3 Conclusion: This is not a counterfactual approach and therefore the results would not be as robust as either of the methods described above. Nevertheless it would represent a simple and low-cost option which provides useful contextual data and should therefore be carried out alongside other methods.

Theory-of-change approach

4.1 It may only be possible to assess the impact of the project on certain outcome indicators through a more qualitative approach which assesses beneficiary journeys during and following the project delivery period. This is particularly relevant for those outcomes for people who have moved from a job with limited prospects of progression to a H&C role with better prospects. Assessing the impact on these outcomes would be complex using a counterfactual approach because it is difficult in practice to define which jobs have no prospects of progression. For participants, this will be based on a subjective judgement by the individual or a JCP advisor about that individual’s current work situation and prospects.

4.2 Counterfactual approaches also do not lend themselves to assessing the impact on ‘soft’ outcomes such as improved confidence, job satisfaction, improved quality of life and increased social capital which are all aims of this project but are difficult to quantity.

4.3 A theory-of-change approach would be more suitable for assessing these outcomes because they would allow the evaluation to capture and reflect the perceptions and insights of beneficiaries as well as other stakeholders such as JCP advisors, employers and mentors. This approach could also be used to assess quantitative change in harder outcomes such as entry in to employment. This would be less robust than the counterfactual methods described above but the findings could be triangulated with other approaches, thereby building a stronger evidence base.

4.4 We would expect the theory of change approach to include the following: Analysis of the longitudinal survey of beneficiaries, which will be carried

out at four different points in time. This will include questions which could be used to measure changes in soft outcomes (confidence, access

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to networks, quality of life) and their perceptions about future progression opportunities in their current role, as well as hard outcomes such as employment status, earnings, benefits and occupation.

Analysis of information recorded in the Individualised Learning Plan for beneficiaries. This will be a ‘live log’ of individuals progress towards their goals which can be added to by the beneficiary, their mentor or coach or learning provider.

More in-depth qualitative interviews with beneficiaries, employers, mentors and JCP advisors, which can be used to produce case studies. The aim of these case studies should be to assess the extent to which positive outcomes can be attributed to the project. Case studies should be produced for a reasonably representative group of beneficiaries so that there is some degree of confidence in the findings.

4.5 Conclusion: Theory of change approaches would not compare change in beneficiary outcomes with a control group and therefore do not meet the minimum level of robustness on the SMS scale. However this offers the only means of assessing the impact on the project on a number of soft outcomes and helps to explain why outcomes have occurred. It should therefore be included as part of a mixed methods approach.

Beneficiaries from within the Sector4.1 The outcomes that will need to be assessed vary for those taking the ‘below

level 2’ route and the apprenticeship route. For the former, outcomes will include: Entry in to a role with an improved career pathway Improved skills Entry on to further training Improvement in soft outcomes (eg confidence, social capital)

4.2 For those taking the apprenticeship route, outcomes could include the last three of these but could also include a number of outcomes relevant to career progression including: Entry in to a higher skilled job in the H&C sector Increased earnings Reduced dependence on benefits

4.3 Assessing these impacts will call for different methods.

Matched control group approach

4.1 A matched control group approach which compares changes in the earnings, benefits or occupational level of beneficiaries with a group of non-participants with similar characteristics should be possible for those taking the apprenticeship route. Although there may be some challenges.

4.2 The key challenge is identifying a control group which displays similar characteristics to the treatment group, including unobserved characteristics related to the decision to participate (eg motivation). Differences in these characteristics would be more difficult to control for than for beneficiaries from

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outside the sector because referrals will not come from JCP, but directly from employers (as well as self-referrals). The control group would therefore need to reflect differences between employers and their approaches to workforce development and not just differences between individuals.

4.3 Ideally the control group would need to come from non-participating staff from the same employers or from very similar employers, who would have to be willing to share sensitive information on their staff (eg earnings), including those who are not participating in the project. We believe this would be unrealistic, especially given that it would require the cooperation of multiple employers.

4.4 An alternative would be to construct a control group from the Longitudinal Labour Force Survey (LFS) – a national survey undertaken by the Office for National Statistics that interviews around 80,000 people each quarter. Survey respondents are interviewed about their earnings at two time points, one year apart. This approach would use data on observed personal characteristics that are both available for the HCSPA participants and from the LFS (including age, gender, disability, location, ethnicity, qualification level, current occupation and sector of employment and initial salary level). This could be used to identify a matched group using a Propensity Score Matching approach. This calculates the probability of an individual participating in the project (the propensity score) based on their observed characteristics using a regression model. The control group can then be established by matching participants with non-participants with a similar score.

4.5 A recent evaluation of the West London Alliance Skills Escalator pilot took a similar approach using data from the LFS longitudinal survey which suggests it is feasible. However, it is not clear how they accessed the raw data or selected the control group in practical terms. This would need to be explored by the evaluators at the formative evaluation stage.

4.6 Data on earnings or occupational level would need to be collected from employers or via self-declaration from participants one year after receiving support and compared to the matched group from the LFS. Impacts would then be estimated using a difference in difference approach.

4.7 The limitation of this approach is that the LFS does not contain variables or proxy variables which would allow the evaluation to account for unobserved differences between the treatment and control group. For this reason it would not be possible to state with confidence that changes in outcome indicators can be attributed to the project. However this approach should still meet the minimum SMS level 3 robustness criteria.

4.8 The main practical challenge would be collecting sufficient, robust data on progression indicators (earnings, occupational level etc) for participants at different points in time. The data should be provided by the employers themselves and should only be collected from a self-declaration from the beneficiary as a last resort since it may be less accurate4. It is likely that attrition will increase over time as employers and beneficiaries will be less likely to respond to surveys after support has ended. The delivery team should therefore ensure that they have robust systems in place for maximising the number of employer and beneficiary responses.

4 In some cases, reliance on self-declarations will be unavoidable eg where beneficiaries have found employment with a different employer who is not willing to provide this information

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4.9 Conclusion: We believe a matched control group approach using data from the longitudinal LFS would be feasible as long as there is a sufficiently high response rate to requests for data on progression indicators, and there are no issues accessing the raw data from the LFS and constructing a control group. This would not account for unobserved differences but should still meet the minimum SMS Level 3 criteria and should therefore be pursued alongside other methods.

Comparing earlier and later participants

4.1 Some of the challenges described above could be addressed by comparing earlier and later participants from within the sector. This would avoid the need to collect data on employees who are not participating in the project because the control group would all be participants from later rounds. However it would be complicated because earlier and later participants may be working for different employers with different characteristics and different approaches to workforce development and progression. This could be partially controlled for by asking participating employers for information on number of employees, whether they have a training plan etc, but it would be difficult to entirely control for differences between workplaces.

4.2 A greater challenge is likely to be the small sample sizes involved in this part of the programme. The delivery team are anticipating smaller numbers of participants from within the sector than from outside the sector. In the first year of delivery there is expected to be around 24 beneficiaries in each round, however most of these are likely to be people taking the ‘below level 2’ route where there is not likely to be any impact on progression in the short term.

4.3 The number of people taking the apprenticeship route (where there is a greater chance of impacts emerging in the short term) is likely to be very low. Even if multiple cohorts were grouped together it may be difficult to reach the sample sizes required to generate statistically significant results. Furthermore, there may be a lag in the time it takes progression impacts to emerge, which would mean there is insufficient time between the first group of cohorts receiving support and the second group for impacts to be observed.

4.4 Conclusion: This option could be explored in tandem with a matched control group approach, with the results compared against each other. However the small sample sizes and potential time-lag for impacts to emerge mean it may not be feasible

Theory-of-change approach

4.1 For participants taking the ‘below level 2’ route, we do not expect there to be an impact on progression in the short term. The main outcome is likely to be the same as employed participants from outside the sector ie a move in to a job with better prospects of progression. As described in paragraphs 4.1, these outcomes, as well as soft outcomes such as improved confidence, will be difficult to assess through counterfactual methods. Therefore a theory-of-change approach which uses analysis of longitudinal survey data alongside qualitative interviews and case studies will be more appropriate (see 4.4).

4.2 Conclusion: Theory of change approaches would not compare change in beneficiary outcomes with a control group and therefore do not meet the minimum level of robustness on the SMS scale. However this offers the only means of assessing the impact on the project on a number of beneficiary

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outcomes and should therefore be included as part of a mixed methods approach.

Employers4.1 The main employer outcomes which would need to be measured relate to the

ability of employers to recruit and retain workers and address skill shortages.

Matched control group approach

4.1 A matched control group approach would involve matching participating employers with those with similar characteristics that have not participated. Observed variables could include size of workplace, sub-sector, existence of skill gaps and skill shortages, whether the organisation has a training plan. This information will be collected from participating employers and be recorded on the project’s employer database. Obtaining this data for non-participating employers would be difficult. The only public dataset which records this information is the UK Employers Skills Survey. However this is not a longitudinal dataset meaning it would not be possible to construct a control group and monitor change over time. The alternative would be to carry out a longitudinal survey of non-participating employers, however this would be expensive and difficult to implement as employers would have no incentive to participate in the survey.

4.2 Conclusion: a matched control group is the most feasible counterfactual approach but would be very difficult and expensive to implement in practice and therefore should not be pursued.

Theory-of-change approach using a business survey

4.1 A simpler way of assessing change in outcomes for employers would be through a survey of participating employers, which collects information on recruitment, vacancies, skill shortages and progression of staff and investment in training at the end of the project and compares this to the baseline data collected at the start of the project.

4.2 The survey would ask businesses about their perceptions as to the role of the project in assisting them to recruit workers, address skill shortages and promote staff. This should include questions on other factors which have influenced levels of recruitment, vacancies, skill shortages and investment in training since the project started and the relative importance of these. This would allow the evaluation to control for these other factors and form a view on the specific contribution of the project to the change in outcomes.

4.3 Conclusion: this approach would not consider a counterfactual and therefore does not meet the minimum level of robustness on the SMS scale. However in the absence of any viable counterfactual approaches, this would provide a pragmatic way of understanding the project’s impacts on employers.

Summary and Conclusions on Approach to Impact Assessment

4.1 Based on the above, we recommend that the evaluation uses a mixed-methods approach which triangulates between different methods, both

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counterfactual and non-counterfactual, in order to examine the extent to which the evidence from each corroborates each other.

4.2 The greatest potential to use counterfactual approaches is in the assessment of: Entry in to employment for those from outside the sector: by comparing

change in outcomes between participants in earlier and later rounds. This could achieve an SMS score of 4.

Changes in earnings and other progression indicators for participants already working in the sector: using a matched control group approach. This could achieve an SMS score of 3.

4.3 For a number of other outcomes, there is little scope to use counterfactual methods and the best approach is likely to be a theory-of-change method which makes use of the longitudinal survey (for individual participants) and employer survey (for employers). These methods could also be used to assess hard outcomes such as increased earnings and entry in to employment, so that the results can be compared with the findings from counterfactual approaches.

Table 4.1 Summary of recommended methods for assessing outcomesOutcomes Beneficiaries from

outside the sectorBeneficiaries from inside the sector

Employers

Entry in to employment (for unemployed/inactive)

Entry in to H&C job

Comparison of early/late rounds

Theory of change using longitudinal survey

Entry in to jobs with greater chance of progression

Entry in to volunteering roles or training

Improvement in soft outcomes (job satisfaction, confidence etc)

Theory of change using longitudinal survey

Theory of change using longitudinal survey

Increase in earnings

Reduction in benefits

Promotion to higher occupations

Matched control group

Theory of change using longitudinal survey

Change in vacancies

Change in skill shortages

Change in recruitment

Theory of change using employer survey

Economic Evaluation4.1 There are a couple of different approaches to assessing the value for money of

the project:

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Cost-effectiveness analysis (CEA): this expresses the ratio between the costs of the project and the quantity of outcome generated to produce a cost per unit of outcome generated (eg cost per job)

Cost-benefit analysis (CBA): this goes further by placing a monetary value on the changes in outcomes as well. This means CBA can examine the overall justification for the project (ie do the benefits outweigh the costs) as well as comparing the value for money between different types of projects. CBAs monetise as many of the costs and benefits as possible, including social and environmental impacts.

4.2 Given that one of the aims of the project is to deliver fiscal savings to the public sector, it should be possible to carry out a fairly simple fiscal CBA which takes in to account the net impact of the programme on savings from benefits and increases in tax revenues, and compares this to the cost of the project. This may need to make some assumptions on increases in tax revenues based on the project’s impact on entry in to employment and increased earnings.

4.3 Carrying out a full economic CBA would be more challenging, particularly given the range of outcomes that would be difficult to monetise, including: soft outcomes such as improved confidence, access to networks etc. outcomes related to moving closer to employment (eg volunteering,

further training) moving in to roles with better career pathways and prospects for

progression.4.4 Although some benchmark values exist for these types of impacts, in reality

the value is highly context specific. In addition, there may be other social benefits from people moving in to employment or better jobs which are not being assessed here eg improved health. Finally, given the nature of the evaluation evidence available, it may be difficult to quantify the savings to employers from reductions in recruitment costs or improvements in efficiency as a result of reduced skill shortages.

4.5 The evaluation should therefore carry out a CBA but acknowledge some of these limitations. This should be carried out alongside cost effectiveness analysis for selected measures of impact, in particular ‘cost per person moved in to employment’ which is a commonly used performance indicator for labour market projects.

4.6 The evaluation should look to benchmark the CBA and CEA estimates against other similar intervention types, providing the evaluation evidence meets similar minimum quality standards (especially in terms of the counterfactual). However this needs to take in to account the novel and innovative nature of the project which means it may be difficult to identify comparable projects where good evidence exists.

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5. Monitoring5.1 The monitoring plan has been developed in line with the intervention logic

models provided in Appendix A.

IndicatorsBaseline data

5.1 This section sets out a proposed set of baseline indicators and data against which impacts can be measured. These are all from publicly available data sources, with the exception of Burning Glass which could be accessed via the Combined Authority or LEP if they have a subscription.

Table 5.1 Baseline Indicators from Secondary Data SourcesIndicator Source Latest date and frequency

of collectionEmployment rate Annual Population Survey Sep 2017 - quarterlyNumber/percentage of people claiming in-work benefits

DWP Jan 2018 - monthly

Number/percentage of people claiming out-of-work benefits

DWP Jan 2018 - monthly

Percentage of population with Level 2/3 qualification

Annual Population Survey Sep 2017 - quarterly

Vacancies per 100 employees in health and social care sector

Burning Glass, Labour Market Insight and Business Register and Employment Survey (BRES)

Burning Glass: real timeBRES: 2016

Number of hard to fill vacancies in health and social care

UK Employers Skills Survey 2015 (data for 2017 to be published in summer 2018) - bi

Number of skill shortage vacancies in health and social care

UK Employers Skills Survey 2015 (data for 2017 to be published in summer 2018)

Number of staff with skill gaps in health and social care

UK Employers Skills Survey 2015 (data for 2017 to be published in summer 2018)

Participant dataAdministrative data collected from participants

5.1 The administrative information in Table 5.1 will need to be collected from participants at the point of enrolment. The project team will also need to ask the participant to sign a consent form for their data to be shared with the evaluators. This should use the DWP consent form template so that their data could also be used at a later date if a data sharing agreement is put in place.

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Table 5.1 Characteristics of participantsVariable Type Values

Gender Categorical Male; FemaleAge Numerical Integer valuesDisability Categorical Not disabled; DisabledEthnicity Categorical White; Black; Asian; Mixed; Chinese; OtherMarital status Categorical Single; Married; Widowed; Divorced;

Separated; CohabitingSought occupation

Categorical 26 broad categories based on SOC codes eg “Administrative”; “Health Professional”

Postcode Categorical Full Unit Postcode eg PE1 1HGLone Parent Categorical Lone Parent; Couple; Not a ParentAge of youngest child (if a parent)

Numerical Integer value

Highest Level of Qualification

Categorical Entry level; Level 1; Level 2; Level 3; Level 4; Level 5; Level 6; Level 7; Level 8 (based on National Qualifications Framework)

Economic status Categorical Employed; Self-employed; Unemployed; Economically inactive

Current Occupation

Categorical 26 broad categories based on SOC codes eg “Administrative”; “Health Professional”

Gross annual salary

Numerical Pounds sterling

Benefits received List of those categories that apply

Bereavement benefits; Carers Allowance; Child Benefit; Disability Living Allowance; Disablement Benefit; Employment and Support Allowance; Housing Benefit; Incapacity Benefit; Income Support; Jobseekers Allowance; Universal Credit; Working and Child Tax Credits; Other (please specify)

Total monthly value of benefits

Numerical Pounds sterling

Date first started claiming benefits

Categorical Month and year of first claim

Length of time not in work

Numerical Number of weeks

Baseline longitudinal survey

5.1 The longitudinal survey will be used to collect data on hard and soft outcomes which are not available from other sources. The survey will be undertaken at four points in time: Baseline: at enrolment Interim: at the end of the period of training support Final: six months after the end of training Destination: one year after the end of training

5.2 The baseline questionnaire should collect the following information: Employment status (employed, unemployed, economically inactive) Current occupation (one of 26 broad categories based on SOC codes) Gross annual earnings (£) Total value of monthly benefits (£)

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Baseline measures of soft outcomes, including questions on the following categories: Confidence and aspirations Social capital Job satisfaction (if relevant) Quality of life/wellbeing

5.3 There are a number of documents which provide guidance on measuring wellbeing and other soft indicators. These discuss a number of different methods which the project team should review when designing the longitudinal survey. One method is to ask participants about the extent to which they agree with certain statements. We have provided some illustrative examples below, however the project team should agree on the most appropriate indicators to include.

Table 5.1 Example questions for measuring wellbeing (to what extent do you agree with the following, where 1 = strongly disagree and 5 = strongly agree)

1 2 3 4 5Confidence/aspirations

I have a clear sense of the future direction of my careerI feel confident about my future careerI cope well in new situationsWhen I apply myself I can develop new skills

Social capital

I have family and friends who I feel close toI have made new relationships in the last two monthsI am actively involved in my local communityI believe most people can be trusted

Job satisfaction

I am happy in my jobThere are good opportunities for me to learn new skills at workThere are good opportunities for me to get promoted at workI believe the work I do is meaningful

Wellbeing/ quality of life

I feel optimistic about the futureI feel I have a number of good qualitiesI am very satisfied with my life

Data collected following IAG session

5.1 The following data should be collected following the initial IAG session and stored on a central database by the project team.

Table 5.1 Data to be collected following IAG session

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Variable ValuesTraining route Below Level 2; ApprenticeshipTypes of training to be undertaken English; Maths; ESOL; Specific

apprenticeship frameworkWrap-around support Childcare bursary; Travel bursariesBeneficiary goals Goals of beneficiaries by category (eg

Qualifications; Employment; Soft outcomes; Others)

Data collected from participating employers

5.1 The following information should be collected from employers that the project has direct contact with, particularly those employers that refer their staff for training. This should be stored on the employer database. The data collected here will be used to establish the baseline for measuring changes in outcomes for employers.

Table 5.1 Data to be collected from employersVariable Type Values

Size of workplace Numerical Number of employeesType of organisation Categorical Private care home; NHS care

home; NHS hospital; OtherVacancies by occupation in last 12 months

Categorical/ Numerical

Number of vacancies by broad occupation group (26 categories)

Skill shortage vacancies (SSVs) by occupation in last 12 months

Categorical/ Numerical

Number of SSVs by broad occupation group (26 categories)

Skill gaps by occupation in last 12 months

Categorical/ Numerical

Number of staff nut fully proficient by broad occupation group (26 categories)

Recruitment in last 12 months by occupation

Categorical/ Numerical

Number of recruits by broad occupation group (26 categories)

Number of staff undertaking apprenticeships in last 12 months

Numerical Number of apprentices

Number of staff promoted to more senior role in past 12 months

Numerical Number of staff promoted

Input indicatorsIncome

5.1 The project should monitor the value (£) and source of any income for the project. This should distinguish between: DWP grant Apprenticeship funding Contributions from local authority or LEP Other sources (please state)

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Expenditure

5.1 The following data on expenditure should be monitored

Table 5.1 Project expenditure data (£)Type Out of

sectorIn-sector

pre-level 2In-sector

apprenticeship

Total

Delivery costs

IAG adviceWrap around support bursariesSector specific trainingEnglish and MathsCareers coachingEmployer engagement

Programme management costs

PremisesStaff salariesOverheadsMarketingMonitoring & evaluation

Output indicators5.1 The output indicators in Table 5.1 should be collected by the programme

management team. In addition, the project team should collect data on: the total number of referrals to the project (including all of those that

did not progress to the IAG stage) the total number of participants who dropped out of the project.

Table 5.1 Output indicatorsOutput indicator Out of

sectorIn-sector pre-level

2

In-sector apprentic

eship

Total

Participants

Number of people engaged for IAGNumber starting trainingCourse/apprenticeship completionsQualifications/certificates gained

Employers Number of employers engagedNumber of employers referring staff for trainingNumber of employers co-designing training coursesNumber of employers interviewing candidatesNumber of employers offering apprenticeships

Outcome indicators

Table 5.1 Outcome indicatorsOutput indicator Out of

sectorIn-sector pre-level

2

In-sector apprentic

eship

Total

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Participants

Number of job applications submittedNumber of job interviews attendedNumber of participants entering employmentNumber of participants entering different job in H&C sectorNumber of participants entering higher skilled job in H&C sectorChange in earnings of participantsChange in receipt of benefits Number of participants entering volunteering rolesNumber of participants entering further studyNumber of participants reporting improved confidence or self-beliefNumber of participants reporting increased social capitalNumber of participants reporting improved job satisfactionNumber of participants reporting improved quality of life

Employers Change in number of employees recruitedChange in number of vacancies Change in number of skill shortage vacanciesChange in investment in trainingChange in staff retention

Data collection methods and timeline5.1 The monitoring and evaluation will need to draw upon a range of different

data sources and data collection methods. Table 5.1 sets out the key roles and responsibilities of different parties and the point at which data will need to be collected.

Table 5.1 Data collection responsibilities, methods and timelinesIndicators Collected

byMethod When?

Baseline Administrative data on participants (see Table 5.1)

Project team

Enrolment form

Enrolment

Indicators collected at IAG session (see Table 5.1)

IAG advisor

IAG interview, recorded in ILP

IAG session

Baseline info on Project Employer At point of

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participating employers (see Table 5.1)

team interview, recorded in employer database

referral or contact

Baseline data on confidence, social capital and quality of life

Project team

Longitudinal survey

Enrolment

Outputs Number of people engaged for IAG

Project team

Internal monitoring

Enrolment

Number of course starts Number of course

completions Number of qualifications

gained

Learning providers

Monitoring and recording in ILP

During delivery

Employer engagement outputs (see Table 5.1)

Project team

Internal monitoring

During delivery

Outcomes

Number of job applications submitted

Number of job interviews attended

Number taking up volunteering opportunities

Number entering employment

Mentors/ coaches

Recording in ILP

Four month period after support

Reduced dependence on benefits

Number entering employment

Number entering higher skilled occupation

Increased earnings Change in soft outcomes

Project team

Longitudinal survey

Six months after support and one year after support

Employer outcomes (see Table 5.1)

Evaluators

Business survey

Project evaluation

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6. ImplementationAssessment Route

6.1 The evaluation should be undertaken by independent specialists with experience of undertaking large and complex evaluations, including counterfactual methods. The invitation to tender should be advertised on a competitive basis, either through an open tender or directly to a number of different specialists.

Timescales6.1 The project launch is scheduled for early 2018, although this may be revised.

Based on a February 2018 start date, we have identified the following indicative timescales: Procurement of evaluator: July 2018 Formative evaluation: August-September 2018 Mid-term evaluation: May-June 2019 Final evaluation: October-December 2020

Managing the assessment and ensuring quality6.1 The assessment should be carried out in line with a project management plan

which should be developed by the evaluators once appointed and be agreed with and signed off by the project delivery team. This should also identify the nominated project manager who will be the main point of contact between the project delivery team and the evaluators.

6.2 The project management plan should set out: The project methodology Agreed outputs and deliverables and the timescales for delivery The key project risks and how these will be managed Reporting arrangements and the frequency of progress meetings

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Appendix A - Logic Chains

Appendix C - 1

Appendix C - 1

Appendix C - 2

Appendix C - 3

Appendix C - 4

Appendix B - New appendix sectionB.1

Appendix C - 1

B.2

Appendix C - 1

Appendix C - <Insert title here>C.1 <Use Appendix Heading 5>

C.2 <Use Appendix Heading 5>

Appendix C - 1

www.regeneris.co.ukLondon: 0207 336 6188 Manchester: 0161 234 9910

www.regeneris.co.ukLondon: 0207 336 6188 Manchester: 0161 234 9910