Appendix
Social Return on Investment (SROI)
methodology and sensitivity analysisof the case studies

SROI Methodology
Social return on investment (SROI) is a methodologythat allows a deeper understanding of the social,health, environmental and economic values createdby a range of NGOs implementing projects undersocial contracting. It is a framework to measure
and account for the value created by a programmeor series of initiatives, beyond financial value. It
incorporates social, health, environmental andeconomic costs and benefits.1 SROI is a participatory,
beneficiary-led approach which uses financial values
defined by programme beneficiaries themselves torepresent outcomes, thus enabling a ratio of costs
to benefits to be calculated. For example, a project
ratio of 1:4 indicates that a donor investment of 1
USD delivers 4 USD of social value to the direct
beneficiaries of the programme.2
The usual stages of SROI analysis include: (i)establishing scope and identifying key stakeholders;(ii) mapping project outcomes with the stakeholders
using the theory of change; (iii) assigning a financial
value to the project outcomes; (iv) establishingproject impact from the project end line evaluation;(v) calculating inputs to the project; (vi) calculating
the SROI.3
Social contracting in the area of HIV can create
significant social returns, going beyond improving
the health status of PLHIV or reducing the incidence

in a particular country and in the region. In order tostudy the social returns created by social contracting,
we adapted and implemented the SROI methodology
to the context of HIV in the wider Eastern Europeand Central Asia (EECA) region.4 In this section weelaborate on the SROI methodology, while the next
section presents the sensitivity analysis around casestudies from three countries where we have conducted
a rapid implementation of the SROI methodology inthe context of HIV social contracting.
Stage 1: Establishing scope and identificationof stakeholder groups
The SROI analysis usually starts with establishmentof scope and identifying the key groups or
stakeholders that are to be included in the analysis.
In the context of HIV in the EECA region, there area few main beneficiaries: people living with HIV(PLHIV), caregivers of PLHIV, people who inject/
use drugs, sex workers, men who have sex withmen (MSM), transgender people, NGO workers thatprovide services to marginalized groups and othercommunity workers.
Stage 2: Mapping project outcomes withthe stakeholders using the theory of change
Following the identification of the beneficiaries,
the SROI methodology then maps the beneficiarydefined outcomes against relevant indicators,
which are usually available through the end of theproject evaluation or other repositories (e.g. health1The SROI Network, A Guide to Social Return on Investment, 2012, https://socialvalueuk.org/resource/a-guide-to-social-returnon-investment-2012/.
2 Banke-Thomas et al., Social Return on Investment (SROI) methodology to account for value for money of public health interventions: a systematic review, BMC Public Health, 2015, 15:582, https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889015-1935-7.
3 The SROI Network, A Guide to Social Return on Investment, 2012, https://socialvalueuk.org/resource/a-guide-to-social-returnon-investment-2012/.
4 https://www.eurasia.undp.org/content/rbec/en/home/about-us/about-the-region.html
1centres utilization data). Mapping the outcomes ofan activity done through social contracting can help
understand how increasing community action on HIV
prevention, care and impact mitigation can lead totangible changes in the lives of beneficiaries. Morespecifically, SROI analysis enables to measure thevalue of the impact of activities on beneficiaries’ lives,
and to see how a series of programmatic activities led
by community or implementing programme partners
have led to certain measurable outputs, which in turnhave led to measurable changes in beneficiaries’
lives. The relationship between the project activities,outputs, outcomes, and impact can be assessedusing the theory of change, and represented throughimpact maps.5
The graph below gives examples on the link between
the activities, outcomes, and ultimately impact ofprojects conducted under the auspices of social
contracting, with particular reference to HIV-related
projects in the EECA region. As the case studies
in the next section will reveal, in most cases, theprojects target either PLHIV or some (or all) of thekey populations via testing and counselling activities.

Graph 1. Theory of change map for an SROI analysis (Applied to selected HIV-related projects in the EECA region)
Inputs

Outputs

Outcomes

ImpactINPUTS

ACTIVITIESOUTPUTSOUTCOMES

Training on self-care,health, and exercise;Hygiene awareness;
Referrals for ART,
Care and support• No. of PLHIV
who received careand support

Better healthand nutritional statusamong PLHIV

Project budget

Community volunteers’
time inputs• No. of PLHIV who
received ART
through facilitationand support of homecare teams• No. of PLHIV trainedin ART adherenceCounselling provided
to key populations
on safe sex practices• No. of membersof key populations
receiving counselling
support;Potential HIV infections
among key populations
averted• No. of condoms
distributed

Stage 3: Assigning a financial value to the project
outcomes
The theory of change allows to identify some of theproject outcomes going beyond simple outputs.
The next stage in the SROI analysis is to identify
the outcomes of a social contracting project/activity
and to attach an appropriate financial proxy to them.
For example, if an activity involved counselling of
key populations at higher risk of HIV on safe sex
practices, the project outcomes could include thenumber of HIV infections that could be averted asa result of the counselling. By the same token, thefinancial proxy for this outcome could be the priceof ART (which should be administered in case theinfections were not averted) (Graph 1).
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Stage 4: Establishing project impact from the project end line evaluation
Another important aspect of the SROI approach isthat it allows researchers to isolate the impact of aparticular activity on the project outcomes. To look at
this in more depth, there is a need to adjust financial
value of the outcomes by measuring and applying:(i) attribution; (ii) deadweight; and (iii) drop-off.
Attribution estimate
i. Attribution—an assessment of how much of
the outcome was caused by the contributionof others (organizations or people): “who elsecontributed and what is their claim in achieving
the outcome?”

Ibid.

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Accounting for attribution is an important step in theestimation of the impact of a project, and failing to doso would result in an overestimation of the benefits
attributable to an HIV-related project, as we would
effectively be claiming 100 percent of the credit for
any changes that have taken place. This is a key
difference between an SROI approach and manyother evaluation techniques. Usually the estimationof attribution is done by consulting with thebeneficiaries about who else was carrying out similar
activities in the target areas (government agencies,
other NGOs, individuals, community groups etc.),
and who may have influenced or contributed to theoutcomes or changes experienced.6Given the nature of the HIV-related projects inthe EECA region as well as the concentrated
nature of the epidemic, we expect that most of theimprovement in beneficiaries’ lives to come throughthe project itself. In other words, the NGOs working
in the area are fairly focused, with limited mandate,catering to key populations (e.g. people who injectdrugs, sex workers, MSM and transgender persons)and which would have not been otherwise includedin activities by other projects.
Deadweight estimate
ii. Deadweight—the percentage of the outcomethat would have happened even if the project
activity had not taken place.
As in the case above, given the nature of the HIV
epidemic and response in the region, it is expectedthat some of the activities and outcomes would have
not happened without the existence of the project.
Drop-off estimateiii. Drop-off—this measures the reduction of
the outcome after the intervention has beenimplemented, i.e. the value by which the effectis decreasing over time. For example, after
an intervention has been implemented, it isexpected that some of its effects will continue.
For example, if a project provides employment
opportunities for people from marginalizedgroups, it is expected that some of them willcontinue to have their employment after thework is finished. However, with time more
beneficiaries may be losing their jobs; thedrop-off rate reflects the percentage of such
beneficiaries.
Even when the contribution of the project to a given outcome has dropped off completely, this does
not necessarily mean that the beneficiaries are nolonger benefiting from the project activity. It simply
means that the relative importance or influence of67Ibid.
Ibid.

the project activity on that outcome has diminished.
For example, as we mention above, if a project has
counselled some of the key populations on safe
sex practices, it is expected that the knowledge obtained through the counselling would be retained
for a few years after the activity has ended.
Stage 5: Calculating inputs to the project
The next step in the SROI analysis is identifying theproject inputs. These are fairly easy to obtain andusually include the standard set of costs that havebeen incurred in running the project. For example,
this could include: (i) staff costs; (ii) equipment andsupplies; (iii) administrative costs; (iv) travel, training;and (v) implementing partner’s own contribution. In
addition, there are some other, ‘hidden’ costs that
could be associated with the implementation of an
HIV-related project. This could, for example, include
the caregiver’s time spent on caring for PLHIV or
co-infected beneficiaries of a project.7
Stage 6: Calculating the SROI
After all of the steps above are done, the final part
includes taking the monetary value of the activityoutcomes, dividing it by the activity inputs and expressing the SROI in terms of the ratio mentioned in
the beginning of the section.

Sensitivity analysis
Bosnia and Herzegovina
In order to see how stable results are to various
changes in the assumptions, a few sensitivity analysis tests should be conducted. In the case of BiH,first, we increased the attribution rate to 20 percent.
When doing this, we obtain a ratio of 1:3.1, whichcorresponds to the lower bound of the sensitivity
analysis (see Table 3 in the Policy Brief) and is fairly comparable to our main finding. Second, we applied a more gradual drop-off (25 percent in year 2,50 percent in year 3, 75 percent in year 4, and 90
percent in year 5). The result that we obtain in thiscase (1:4.1) corresponds to the upper bound of thesensitivity analysis (Table 3 in the Policy Brief) andis still comparable to our main findings. Third, wereduced the financial proxy for the outcome of theapplied intervention relevant for PLHIV. Rather thantaking the value of the total annual wage, we haveapplied 50 percent (as the health of PLHIV is unpredictable, even with continuous subsistence support,
applying a full financial proxy to the outcome relevant to PLHIV may lead to over-estimation). In thiscase, the ratio obtained is 1:3.1, which corresponds
to the lower bound of the sensitivity analysis (seeTable 3 in the Policy Brief). This is again comparable
to the main findings.

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North Macedonia
In the case of North Macedonia to see how stable
results are to various changes in the assumptions,
we also increased the attribution rate to 20 percent.
The final ratio obtained in this case is 1:1.4, which
represents the lower bound of the sensitivity
analysis (see Table 3 of the Policy brief) and isfairly comparable to our main findings. Second,
we applied a more gradual drop-off (25 percent inyear 2, 50 percent in year 3, 75 percent in year 4,
and 90 percent in year 5). The ratio in this case is
1:2.0 and it corresponds to the upper bound in thesensitivity analysis (see Table 3 in the Policy Brief).
It is, however, still comparable to the main findings.
Belarus—Red CrossSimilarly, for Belarus—Red Cross, to see how
stable our results are to various changes in theassumptions, we increased the same attribution
rate to 20 percent. The final ratio obtained in thiscase is 1:1.4, which corresponds to the lower boundof the sensitivity analysis (see Table 3 in the Policy
Brief) and is comparable to our main findings.
Second, we applied a more gradual drop-off (25percent in year 2, 50 percent in year 3, 75 percent
in year 4, and 90 percent in year 5). The ratio in
this case is 1:1.9 and it corresponds to the upperbound in the sensitivity analysis (see Table 3 in
the Policy Brief). Even then it is still comparable tothe main findings. Third, we reduced the financial

proxy for the outcome of the applied intervention
relevant for PLHIV. Rather than taking the value ofthe total annual wage, we have applied 50 percent(as the health of PLHIV is unpredictable, even with
continuous subsistence support, applying a full
financial proxy to the outcome relevant to PLHIV
may lead to over-estimation). In this case, the ratio
obtained is 1:1.4, which corresponds to the lower
bound of the sensitivity analysis (see Table 3 in thePolicy Brief). This is again comparable to the mainfindings.
Belarus—Pozitivnoe Dvizhenie
As with the other three cases above, for Belarus
Positive Dvizhenie, the sensitivity analysis tests
conducted were also included. First, increasing theattribution rate to 20 percent changed the ratio to1:2.3, which is the upper bound of the sensitivity
analysis (see Table 3 in the Policy Brief). Second,
we reduced the financial proxy for the outcome of
the applied intervention relevant for PLHIV. Rather
than taking the value of the total annual wage, wehave applied 50 percent (as the health of PLHIV isunpredictable, even with continuous subsistence
support, applying a full financial proxy to the outcome
relevant to PLHIV may lead to over-estimation). In thiscase, the ratio obtained is 1:1.3, which corresponds tothe lower bound of the sensitivity analysis (see Table
3 in the Policy Brief). This is again comparable to themain findings.

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