1. Business Case
Summary Sheet
Title: Sudan Evidence Base Programme
Project Purpose: To realise more effective pro-poor development outcomes in Sudan by
generating more robust evidence base for decision-makers (especially for DFID, but also
other pro-poor development stakeholders- including civil society, academia, and, to an
extent, statisticians in the public sector).
Programme Value: £1,900,000 Country/Region: Sudan
Senior Responsible Owner: Martin Dyble
Project Code: 204021 Start Date:
13/07/2014
End Date: 13/07/2017
Quest Number: 4305597
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2. Intervention Summary
What support will the UK provide?
The UK will provide up to £4,500,000 over the next three years, only £1,900,000 of which requires
approval. The remaining £2,700,000 will be funded from other approved programmes in DFID Sudan
which will benefit from the availability of ‘services’ provided under this programme.
What are the main programme activities?
• The generation and analysis of new statistics- particularly the multi indicator cluster survey
(household health survey) and the DFID Sudan household survey.
• The independent monitoring of DFID Sudan funded programmes.
• Capacity building and engagement with civil society, universities, and public sector
statistics producers and consumers.
Why is UK support required?
At the broadest possible level there is a clear need for countries to have good quality data. This is
because it is impossible to make good decisions or evaluate outcomes without a solid evidence base. The
paucity of good quality data in Sudan, one of the least developed countries in the world, means that the
ability to undertake effective decision-making is severely curtailed.
The lack of reliable statistics and data also limits the ability of DFID to influence the government. DFID
does not work directly with the Government of Sudan. However, statistics, amongst other factors, does
play a role in decision-making. Therefore, by investing in statistics development and engaging with the
producers and consumers of data DFID can influence decision-making indirectly. As recent experience
has shown, when the Government of Sudan is confronted with data on poverty and depravation it cannot
completely ignore the plight of its own people.
What are the expected results?
• Increase the quality, availability, and access to evidence required to inform future
programming decisions,
• Identify lessons learned and opportunities for corrective action in current DFID Sudan
programmes,
• Collect and analyse data to facilitate pro-poor decision-making,
• Increase DFID ability to monitor programmes and verify results,
• Build partners’ capacity to monitor results and collect data,
• Generate better quality official statistics that will enable and possibly incentivize
stakeholders (civil society, private sector, and even government), to engage in more pro-
poor development decision-making.
How does the project fit with the country programme or department’s strategic objectives set out
in the Operational Plan?
The DFID Sudan Operational Plan commits us to address the poor evidence base in the country.
Specifically it stipulates that:
‘…the evidence base in Sudan itself is very poor. Data availability and quality is extremely low in some areas
of our work across Sudan. We intend to address this during the design of new programmes....”’
This programme aims to directly address these issues. In addition, by facilitating the development and
dissemination of statistics and data, the programme also aims to empower other pro-poor development
stakeholders with the facts they need to make better use of scare resources. This process should
facilitate the realization of the central strategic objective of DFID Sudan: ‘to reduce the levels of violence
and conflict; build economic stability; and allocate resources more equitably.i
’
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3. What are the key risks to the success of the programme?
The government revokes the right to commission the DFID household survey and/or access to parts of
the country in which DFID operates in.
There is a loss of momentum, amongst external actors (civil society, universities, and the statisticians in
the public sector) to engage with the capacity building elements of the programme.
Strategic Case
Context and need for a DFID intervention
1. At the broadest possible level there is a clear need for countries to have good quality data. As before
without an evidence base to make decisions or evaluate outcomes it becomes impossible to ascertain
the efficiency and effectiveness of policy-making. As the United Nations (2013) Report of the High-
Level Panel of Eminent Persons on the Post-2015 Development Agenda states (p.5)ii:
‘…We also call for a data revolution for sustainable development, with a new international
initiative to improve the quality of statistics and information…We should actively take advantage
of new technology, crowd sourcing, and improved connectivity to empower people with
information on the progress towards the targets.’
2. The paucity of good quality data in Sudan, one of the least developed countries in the worldiii
, means
that the ability to undertake effective decision-making is severely curtailed. The causes of this lack of
data are due to a complex number of technical (lack of know-how) and non-technical factors (conflict
and political intervention). Even in the case of the Millennium Development Goals (MDGs), perhaps
some of the most widely tracked indicators globally, we currently lack timely and reliable data on 30 of
the 36 indicatorsiv
. Disaggregation of data by sex, or areas in which conflict is prevalent, remains very
erratic. This fact impedes the ability to assess the situation of women and girls and conflict-affected
persons effectivelyv.
3. The UK is one of the main donors in Sudan with a considerable portfolio of humanitarian and pro-poor
development programmes. The gap in the evidence base of Sudan has brought about some
challenges in decision making, prioritisation of resources, and in monitoring and evaluation for DFID,
other donors and development stakeholdersvi. Policies and programmes based on incomplete
information are less likely to deliver best value for money, or reach the most in need.
4. Statistics and the generation of official data remain one of the most neglected and under-invested
areas of government in Sudan. Most statistics are collated by the Central Bureau of Statistics (CBS)vii
but with important data also being collected by respective line ministries and other public sector bodies
(especially the Ministry of Financeviii
, the Central Bank, and the Ministry of Healthix
). A great deal of
actual data collection is undertaken by universities and other non-governmental entities. However, due
to a combination of factors, official statistics are reported erratically, sometimes altered for non-
technical reasons, and not always disseminated in a timely manner or a user friendly format. A set of
actions that severely limits the use of such data in decision-makingx
.
5. Some of our implementing partners and other development agencies have sought to mitigate the lack
of data by attempting to generate their own datasets and data gathering processes (see our
Monitoring & Evaluation Strategy for detailsxi). These strategies have had some notable but limited
success in addressing the data challenges faced by DFID Sudan, but have not been entirely effective
because: (1) amongst the few remaining bilateral donors very few have in-house expertise in statistics,
(2) non-governmental implementing partners (private sector and INGOs) face significant administrative
hurdles in order to undertake surveys, and (3) multilateral partners who also face fewer, but still
considerable, burdens in commissioning data gathering exercises, are usually our implementing
partners (generating a conflict of interest)xii
.
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4. 6. DFID Sudan has directly tried to mitigate the lack of data. Historically DFID played an active role in
technical assistance and capacity building in Sudanxiii
. Most attempts to gather data are now at the
programme level and sporadic in naturexiv
.
Gender Equality
7. Availability of data disaggregated by sex (and age) is poor in Sudan, due to infrequent data
collection, inconsistent use of categories in different surveys, and irregular and limited dissemination
of findings. This impedes the ability to assess both the situation and the differential effects of
programmes on women and girls, and men and boys. This is crucial to understanding how to design
and deliver programmes – particularly those that are targeted towards women and girls, such as
Sudan Free of FGC, but equally programmes related to water and environmental governance, where
women and girls are at risk of being marginalised.
8. By supporting robust collection of population data disaggregated by sex and age, the EBP will help
ensure that other DFID Sudan programmes have the data required to understand effects on different
groups. In addition, the implementation of the data collection and capacity building phases of the
programme will be conducted in a gender-sensitive manner. Specifically:
• Component 1 (data generation): The DFID household opinion poll will regularly collect gender-
and age-representative information from the Sudanese public. The subsequent analysis will
enable DFID programmes to include gender as a dimension in decision-making processes and
ensure their evidence reflects the views of both men and women, such as how gender affects
perceptions of service quality and access, trust in institutions and support for female genital
cutting.
• Components 1 and 2 (third party monitoring): Enumerators and interviewers for the household
opinion poll, MICS survey and third party monitoring will include an appropriate proportion of
women (e.g. for MICS which specifically samples female household members, interviewers will
be predominantly female). All data collected from the field will be disaggregated by sex and age,
thereby generating data to inform gender-sensitive decision making, and programming across
the DFID Sudan portfolio.
• Component 3 (capacity building workshops): Gender equality will be ensured in workshop
participation, and at least 50% of selected participants will be female. The workshop
programme is to be developed in conjunction with a number of academic institutions, including
Afhad Women’s university. The curriculum support envisioned under this component will include
building up capacity amongst government and non-government participants and university
lecturers around the collection, analysis and use of sex-disaggregated statistics.
1. The programme logframe and annual review processes will capture gender progress in the above
areas..
2. The lack of reliable statistics and data also limits the ability of DFID to influence the Government of
Sudan. DFID does not work directly with the Government of Sudan. However, statistics, amongst
other factors, does play a role in decision-making. Therefore, by investing in statistics development
and engaging with the producers and consumers of data DFID can influence decision-making
indirectly. As recent experience has shown, when the Government of Sudan is confronted with data on
poverty and depravation it cannot completely ignore the plight of its own people. DFID recognizes that
its ability to alter decision-making in Sudan may be limited. However, engagement through statistics
capacity building is likely to be one of the most fruitful avenues for achieving any such change. This is
because technical engagement is likely to be less contentious than direct advocacy, and statisticians
work across government. Meaning that engagement of a large cross-section of decision-makers is
possible.
3. Box 1 briefly summarizes the overall effects of sub-optimal levels of information on DFID Sudan and
its partners.
Box 1: How the lack of data impacts on DFID Sudan & other development stakeholders
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5. Tracking impact/results monitoring: being able to target and assess the impact of DFID interventions
requires the ability to map the changing needs and perceptions of beneficiaries. Such activities occur
regularly in other countries, via such instruments as reliable opinion polls, but are not currently done, on
a regular basis, in Sudanxv
. Furthermore, the lack of data on what the Sudanese are thinking limits the
ability of local researchers and civil society to influence public policy more effectively.
Justification of resource allocation: Almost all DFID Sudan programmes make explicit use of official
statistics to allocate resources, yet we are not in a position to understand how these statistics are
compiled. Increasing our understanding of how this data is constructed could significantly impact on the
effectiveness of DFID programmes, and help mitigate implementation risks of our programmes.
Fraud and corruption: the inability to monitor DFID programmes means that there can be significant
risk of fraud and corruption. The lack of high quality data on overall levels of perceived and actual
corruption impedes the realization of our Anti-Corruption Strategy.
Poor quality & erratic data as an excuse for inaction: The lack of good quality and reliable data on
poverty may allow or make it easier for decision-makers in government to continue to use resources in a
manner that does not effectively mitigate poverty and or the humanitarian crisis.
Needs Assessment
Data uses in programmes
Table 1 below shows how, despite their very different sectoral foci and underlying activities, many of the
programmes in DFID Sudan have at least some common data requirements.
4. Given this commonality it makes sense to design a programme that can provide these services for the
whole office, thereby minimizing administrative costs.
Table 1: Indicative common data needs by a sub-set of DFID Sudan programmes
Programme Name
Use of opinion
polls/subjective data
for design/
baseline/
monitoring/
evaluation
Requirement for
systematic
monitoring
Use of official
statistics for
justification
evidence,
monitoring,
and/or
evaluation
Programme total
monitoring and
evaluation budgetxvi
Female Genital Mutilation Yes Yes Yes £600,000
Water in the East Yes Yes Yes £1,000,000
Democratization Yes Yes No £ 500,000
Economic Adjustment Yes Yes Yes £80,000
Environmental Governance and
Conflict Mitigation Programme
Yes Yes Yes £70,000
5. Specifically a large number of DFID programmes rely on the collection of survey data to generate
baselines and/or inform decision-making. However, in most cases, these surveys are conducted by
implementing partners (raising considerable issues regarding validity and conflict of interest) and using
questionable methodologies.
6. In addition the ability to undertake site visits in Sudan has historically been impacted by: (1) the
outbreak of conflict, which makes parts of the country inaccessible for enumerators and DFID staff,
and/or (2) the lengthy process for obtaining permission for international staff to travel outside of
Khartoum. Both of these factors make it difficult for DFID staff to monitor and/or to conduct spot
checks of programmes.
7. Finally, a large number of DFID programmes rely on official statistics, of which we have a poor
understanding of. Evidence from our partners suggests that a failure to engage statistical producers,
whether directly or through intermediaries (e.g. universities) can make the collection and dissemination
of data more problematic; as government obstructionism is more likely under these circumstances.
DFID’s own lesson learning from several evaluations suggests that, in the absence of engagement
with data producers, the risk that data collection will be impeded increases significantlyxvii.
8. In developing the activities of this programme the following key principles are adhered to:
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6. More effectively
targeted humanitarian
and development
interventions.
IMPACT
Better quality data used
for policy and
programme design.
OUTCOME
High quality data products
(Components 1-3).
OUTPUTS
• Emphasis on triangulation: data paucity means that reliance on one source/type of data
(analytical, programme level or official data) can present disproportionate risks as quality
assurance (of both validity and reliability) cannot be independently verified. Hence there is a
need to generate multiple data sources in order to ensure effective evidence based decision-
making.
• (Selective) engagement: given the political economy dynamics and lesson learning from past
experience, being able to build up support for data generation plays a significant role in
mitigating the future risk that data generation and field visits will be stopped due to non-
technical factors. Such an endeavour will also ensure that the programme builds the capacity
of local actors to engage in data collection and analysisxviii
. Furthermore, as noted above the
availability of data can, partially, incentivize elements of government to become more
responsive to the needs of its people.
• Do no harm: the programme will ensure that it does not create perverse incentives for DFID to
stop collecting data (via field visits and other activities). Therefore, the programme will focus on
generating high quality and systematic data that complements but does not substitute the
existing data gathering activities of DFID Sudan. By investing in local capacity building the
programme will also minimize the risk that any international expertise bought into the country to
implement the programme will ‘crowd out’ the nascent monitoring and evaluation capabilities
that exist in Sudanxix
.
• Documenting the needs of women, girls and marginalized groups: the programme will
ensure that all statistics (surveys) funded and developed by this programme will be
disaggregated by gender (if applicable). In addition capacity building workshops and other
activities that include participants from Sudanese civil society, government etc. will be required
to take gender balance into consideration when participation is being considered.
Appraisal Case
Impact and Outcome that we expect to achieve
1. As Diagram 1 below indicates, the outcome that is desired is the availability of reliable data that can be
used, primarily by DFID Sudan, but also other stakeholders (government, civil society etc.), for policy
and programme design, monitoring, lesson learning (via research), and decision-making.
2. The impact of this data will be more effective targeted humanitarian and development interventions.
Diagram 1: Outputs to Impact
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7. What are the planned results attributable to UK support?
3. More specifically, the programme will:
• Increase the availability and access to evidence to inform future decision-making,
• Identify lessons learned and opportunities for corrective action in current DFID Sudan
programmes and mitigate risk,
• Collect and analyse data to facilitate evidence based policy-making,
• Increase DFID ability to monitor programmes and verify results,
• Build partners’ capacity to monitor results and collect data,
• Make official statistics more reliable and effective- thereby making it more likely that the
government will have an incentive or can be challenged to pursue more pro-poor development
policies.
1. The outputs attributable to UK support will be:
• High quality analysis and research reports leading to a strengthening of the overall evidence
base,
• Monitoring field reports about the implementation of DFID Sudan programmes,
• A pool of more highly skilled Sudanese statisticians and M & E experts and knowledge
products (statistics and evaluation manual),
• Better quality official statistics and engagement with the producers (statisticians), and
consumers (civil society, journalists, and the private sector) of these.
Generating Options
1. Given the cross-cutting data needs identified in Table 1 above the proposed programme has three
distinct components:
• Component 1: Analytical data - This component aims to generate new survey data in Sudan.
It has two sub-components: (a) DFID Sudan Household Survey: this bi-annual survey will
systematically capture the views and perceptions of a representative sample of the Sudanese
public (including vulnerable groups)xx. The results of this survey will be used to develop
research and knowledge products. These products will, in turn, facilitate a better evidence base
for DFID Sudan and other development stakeholders (there is already evidence that this
survey is useful for DFID Sudan programming needsxxi
). (b) Sudan Multiple Indicators
Cluster Survey (MICS): is an international household survey developed by UNICEF and
designed to fill data gaps in Sudan. The survey samples women aged 18-64 and covers
thematic areas very relevant to DFID, namely: child care, water and sanitation, reproductive
health, child development, literacy and education, and child protection. The data generated by
this survey is designed to be comparable across time and countriesxxii
.
• Component 2: Third Party Monitoring (TPM) - Based on experience from other countries this
component will provide an ‘on demand service’ to other programmes (who will pay directly for
it). At a minimum we would expect the provision of the following services: (1) Verification
Checks: spot checks that document the production of DFID outputs (e.g. photographs of
physical infrastructure with real time geographical coordinates, etc.); (2) Small Number
Qualitative Data Collection: focus groups of beneficiaries/non-beneficiaries of programmes- in
order to obtain detailed understanding of needs and/or programme impact; (3) Large Number
Qualitative Data Collection: small scale surveys of beneficiaries and/or non-beneficiaries to
obtain more representative information on perceptions of access and/or service quality; and (4)
Dataset Development: generation of detailed databases using the data gathered during field
visits, etc. (see QUEST 4552210 for an indicative ‘Terms of Reference’ based on DFID
Yemen’s experience).
Given that the objective of this Component is to provide a service across the office extensive consultation,
during the development of this service, will be carried out. In addition an ‘open access use’ principle will be
adopted. Meaning that evaluation partners and other development stakeholders may be allowed to make
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8. use of the services; as long as the priorities of DFID Sudan are met. The funding for this Component will
be through the use of resources of other programmes. Essentially, other programmes will be provided with
a menu of monitoring services that they can draw upon given their own budgets and priorities.
• Component 3: Capacity building - by providing a range of capacity building manuals,
workshops, and other engagement activities this component will: (1) provide DFID with a
mechanism for interacting with and understanding the quality behind the large number of
official statistics used in DFID programmes, and (2) by increasing the capacity of external
stakeholders to understand and analyse data it will generate a policy-making environment that
is more evidence based, and hence more conducive to pro-poor decision-making.
1. It is possible to use these components and the overall objective of meeting cross-cutting data needs
that they support to generate a coherent Theory of Change:
Diagram 2: Theory of Change
2. It is assumed that the DFID inputs (finance and staff time) will result in the production of key outputs
(different types of data - polling data, data from field visits, and better quality statistics). Each individual
component generates its own component specific outcome (usable data for decision-making).
However, the outcomes of all three components ultimately feed into one major/composite/general
outcome because what they all have in common is the generation of actionable data for decision-
making. This general outcome of the programme is, therefore, the increased availability and use of
multiple and complementary high quality data, by pro-poor development stakeholders (DFID, other
donors, and implementing partners) when they make decisions. The impact of this intervention is
more ‘evidence based policy making’ and lesson learning which will allow for the more effective use of
scarce resources by these stakeholders to design and change programmes, in order to more
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9. effectively: (1) foster development and (2) alleviate the humanitarian crisis. Thus, by improving the
effectiveness of other interventions the programme will impact on the overall development of Sudan.
This Theory of Change is based on the individual component assumptions as well as more general
assumptions about how data is used in decision-making.
3. The development of a coherent theory of change allows us to develop a set of criteria for evaluating
feasible options for delivering the desired outcome:
Available delivery routes and implications for generating feasible options
The “Do Nothing” Counterfactual
• Option 0: Given the paucity of data, not developing an evidence base for DFID Sudan poses
significant risks: DFID Sudan continues to use unreliable data to take decisions. It is possible
that other donors may intervene to improve data for their programmes, and that some
implementing partners will increase their own capacity to determine results. DFID would stand
to benefit from these efforts, but only for a portion of its programmes. As noted above the lack
of better quality official statistics is likely to mean that the government has less of an incentive
to engage in pro-poor decision-making.
1. Given the undesirability of Option 0 we completed a set of soft market tests to identify possible options
for delivery. From this exercise we were able to significantly narrow down the delivery options to a
decision about how to distribute the completion of tasks amongst DFID and other implementing
partners.
2. Specifically, the objective was to select the delivery option which provides technically sound outcomes
while minimizing (the total of) administrative and oversight costs.
3. The following viable options were identified:
• Option 1: DFID could independently commission every activity, apart from MICS (administered
by UNICEF) and TPM (commission via an open tender processxxiii
). While this would ensure
that the quality of the work met DFID standards it would place a very high burden and
transaction costs on staff and result in a very large number of contracts.
• Option 2: DFID could directly commission the collection of the DFID Sudan household survey
and could commissions, via DFID’s Professional Evidence and Applied Knowledge Services
(PEAKS), some small scale quality assurance research and technical data dissemination. The
bulk of analysis, capacity building, and more general data dissemination would be undertaken
by the World Bank. This option would yield the advantage that DFID could directly monitor and
evaluate the technical quality of the outputs produced while minimizing the transaction costs for
staff. As above MICS is administered by UNICEF and the TPM by a successful candidate from
the open tender process.
• Option 3: Virtually all activities, except MICS (UNICEF) and TPM, could be delegated to the
World Bank. This option would radically reduce transaction costs. However, this option would
also severely limit DFID’s ability to independently verify the quality of data collection and
ensure the development of the most effective knowledge products.
B. Evidence base for each feasible option
1. It is important to note that the evidence base for the use of data by DFID (generally), and other partners,
remains quite weak. This is partly due to the fact that many elements of the programme (especially
TPM) have not been extensively used by DFID before or have only recently been developed.
However, anecdotal and programme information from DFID Sudan (see Table 1 above and QUEST
4552200), as well as detailed information on costs, and the potential use of survey data and official
statistics by DFID Sudan, means that in practice, there is sufficient evidence to discriminate between
the options available.
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10. Table 2: Evidence for Each Option
Option Evidence Rating Source of Evidence
Do Nothing
(Option 0)
Strong Continued inability to access large parts of the
country. Lack of consistent and high quality
data and minimum influence.
DFID Commissioning
(Option 1)
Strong/medium Evidence from market test, UNICEF experience
with previous rounds of MICS in Sudan,
conducting of pilot polling by DFID, PEAKS
research, and experience from DFID Yemen.
Hybrid World Bank/DFID
(Option 2)
Medium/strong As above but World Bank inputs based on a
soft market test and quality assurance from the
centre.
World Bank Focused
(Option 3)
Medium/strong World Bank inputs based on soft market test
and quality assurance from the centre.
C. Assessment and strengthening of local capacity
2. All of the options (other than the counterfactual), will necessarily involve Sudanese partners and
Sudanese staff involvement. As it would not be possible to perform the work required with an entirely
foreign staff. Therefore, all options will lead to employment, experience, and opportunities for
Sudanese. In particular Options 2 and 3, which rely more heavily on non-DFID staff, are likely to
generate the most opportunities for local capacity building.
3. Given the scope of the work and the limited technical staff resources available in DFID Sudan
Option 1 (administrative costs) would be challenging to implement. Given the World Bank’s much
larger access to such technical resources Options 2 and 3 are much more feasible to implement.
However, in order to ensure local capacity is developed Option 2, which gives DFID greater
oversight and involvement in the programme, is more likely to achieve this goal vis-à-vis Option 3
(higher net benefit despite some additional oversight costs).
D. Impacts on Climate Change and the Environment
4. On the margin the generation of better quality data should help identify, and therefore make it easier
to target resources towards vulnerable groups. This should help DFID Sudan and other stakeholders
focus resources in a more effective manner. As all the options, apart from Option 0, will require the
generation of the same activities (data collection etc.) it is not anticipated that there will be much
variation in climate change impact amongst them.
Table 4: Climate Change Impact Assessment
Option Climate change and environment risks and
impacts, Category (A, B, C).xxiv
Climate change and environment opportunities,
Category (A, B, C,).
0 C C
1 C B
2 C B
3 C B
5. Specifically, all options, apart from Option 0, do not present any potential operational risks to climate
change or the environment. Other than low levels of emissions from travel to undertake polling/
workshops/inspect sites. Nor is it likely that the project will itself be affected by climate change or
resource scarcity.
6. In general the generation of better quality and disaggregate data (Options 1,2, and 3) regarding
such things as agriculture, industry, and health might, in the long-run, facilitate a greater awareness
and response to climate change in Sudan. The programme does not have a direct impact on climate
change risks or opportunities (see detailed environmental assessment for more detailsxxv
).
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11. E. Impact on social development
7. Overall, the net social benefits of DFID’s support for the development of a more robust evidence
base are positive. As long as the identified risks are mitigated during the design, procurement, and
implementation stage (see Management Case below). These risks do not vary significantly by
implementing options (Options 1, 2, and 3).
8. Improved availability and quality of sex and age disaggregated data should contribute to improved
Social Development Indices for Sudan, enabling measurement of change in these indices over time
(and hence the well-being of men, boys, women and girls). Fundamentally, it should support the
analysis of poverty and of sex discrimination in different social spheres, including access to health,
education, water and sanitation, political participation, economic participation and so on.
9. Overall, this should support improved gender analysis in Sudan, including support for the design,
implementation and targeting of gender sensitive development policies and programmes, The
programme should benefit national and international stakeholders who need gender sensitive data
for policy and planning purposes, especially to target poverty and improve basic service delivery. It
should also support accountability processes with national and subnational government, improving
capacity of local stakeholder groups to understand and use the data generated.
F. For fragile and conflict affected countries, what are the likely major impacts on conflict
and fragility, if any?
10. By improving the effectiveness of DFID Sudan’s current and future interventions (whose objectives
include conflict mitigation) all the options, apart from Option 0, will indirectly contribute to conflict
mitigation. All DFID programmes are screened for conflict sensitivity. Therefore, improving their
effectiveness should either have no impact on conflict levels or mitigate conflict.
11. One potential source of increased conflict is the fact that interviewers going into communities to
collect information may create local tensions and misunderstanding, especially if they are using
technology such as smart phones. Under Options 1, 2, and 3 the contracted agents will have to set
out in their bid/strategy how they will mitigate risks around interviewer safety and the creation of local
tensions (see conflict analysis for detailsxxvi).
G. What are the costs and benefits of each feasible option? Identify the preferred option.
12. The Table below presents the costs and benefits of each option. The analysis leads us to conclude
that Option 2 – the ‘Hybrid World Bank DFID’ (sole source provider/UNICEF/PEAKS/Open
tender/World Bank) is the preferred one. This is because the option meets the criteria of being able
to: (1) provide the technical outputs required, but also (2) (jointly) minimizes the administrative and
oversight costs of the proposed programme.
Table 3: Costs and Benefits
Option Benefits/compliance with
screening criteria
Cost/risks/preventing factors
Do Nothing
(Option 0)
None Risks perpetuating a poor use of resources, lack of
lesson learning, heightened risk of fraud and
corruption and lack of pressure on government to
address development needs.
DFID Commissioning
(Option 1)
Ensures that quality and
design of activities adheres
strictly to DFID agenda.
Minimizes oversight costs.
Maximum administrative/transaction burden on DFID
Sudan resources.
Hybrid World Ensures that DFID quality Oversight costs of ensuring World Bank delivers
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12. Bank/DFID
(Option 2)
criteria are met. Significantly
reduced burden on DFID staff
time (transaction costs).
quality outputs.
World Bank Focus
(Option 3)
Minimize DFID Sudan
administrative/transaction
costs.
Difficult to ascertain quality of World Bank outputs and
loss of DFID engagement with other stakeholders over
the design and evolution of the programme.
J. Summary Value for Money Statement for the preferred option
13. This project will help ensure value for money of the rest of the DFID Sudan portfolio by supporting
projects to become more relevant to the beneficiaries, and by identifying weaknesses and
inefficiencies.
14. There will be break clauses in all contracts (following delivery of discrete outputs), so that if the
project ceases to be value for money or if circumstances change we can terminate the arrangement.
15. In the event that all/some of the Components are found to be useful it should be possible to extend
their funding beyond the current 3 year period.
16. The economic appraisal uses a break-even analysis to test what indicative results are needed to
justify the programme on a net present value basis. The appraisal shows that modest results are
needed to justify the £1.9 million expenditure. See QUEST 4552283 for a more detailed economic
appraisal.
Methodology
17. The economic rationale for the Evidence Base Programme is based upon information asymmetries
and how, with better quality and quantity of data, decision makers can make more informed
decisions.
18. The break-even analysis is used due to uncertainties around what definitive impacts the programme
will have. Rather than assess costs and benefits it assesses what results would be needed to justify
the programme1. The analysis uses three benefits streams to do this; 1) numbers of children
completing education, 2) numbers of individuals brought out of poverty and, 3) numbers of under-five
deaths averted.
19. The first benefit stream uses estimated income differences to show how many more children would
need to complete education over and above those that already do. It estimates returns to education
to estimate the additional benefit. The second benefit stream focuses on the average distance poor
people are away from the national poverty line (poverty gap) and assumes that the necessary lump-
sum to pull them out of poverty is given to them at no additional cost. The final benefit stream uses a
similar methodology to the first in that it estimates a ten year income stream in the future for an
individual child who would have died before the age of five. This shows how many deaths need to be
averted to justify the programme.
Results
20. The results of the appraisal show that modest numbers are needed to justify the programme. Just
over 850 children would need to complete education, 24,000 individuals would need to be brought
out of poverty, and just under 100 under-five deaths would need to be averted. The table below
shows the results:
Table 6: Results of Central Scenario
1
All costs and benefits are discounted at a rate of 10% and costs are broken down into 3 equal parts for use
against the 3 benefits streams.
1

13. 2014/15 2015/16 2016/217 Totals
Costs £1,040,000 £380,000 £380,000 £1,800,000
Costs Discounted £1,040,000 £345,500 £314,000 £1,699,500
Costs per benefit stream (discounted) £346,700 £115,200 £104,700 £566,500
Benefits Stream 1: Numbers of children completing school 560 190 170 920
Benefits Stream 2: Numbers of adults brought out of
relative poverty
15020 5490 5490 25990
Benefits Stream 3: Numbers of averted U5 deaths 60 20 20 100
Note: Excludes contingency funding of £100,000.
Sensitivity Analysis
21. Sensitivity analysis is applied to test the assumptions of the model. There are three scenarios (low,
central and high) due to: 1. increase or decrease of 5% in the returns to education; 2. poverty gap is
increased or decreased by 50%; or 3. estimated income of a child is increased or decreased by 50%.
The table below shows the results of the sensitivity analysis.
Table 7: Sensitivity Analysis
Low Central High
Benefits Stream 1: Numbers of children completing school 3390 920 420
Benefits Stream 2: Numbers of adults brought out of relative poverty 51980 25990 17330
Benefits Stream 3: Numbers of averted U5 deaths 210 100 70
22. The table shows that in the high scenario, only 600 children would need to complete education,
16,000 individuals would need to be brought out of poverty, and 65 under-five deaths would need to
be averted. Conversely in the low scenario 1,600 children would need to complete education, 48,000
individuals would need to be brought out of poverty, and 200 under-five deaths would need to be
averted. This shows how results vary due to changes in the underlying assumptions.
Likelihood Statement
23. The above results may not occur as it is unclear how the data will be used. However, what the
appraisal does show is that modest results would be needed to justify the Evidence Based
Programme and that there is potential for large rates of return from the programme if it properly
mitigates risks and the data is used appropriately for improving development needs.
24. The appraisal only judges the programme based on what it would need to achieve to break-even.
However, ranking the options should be done qualitatively. It is assumed that option two minimises
the costs of achieving the results the most due to its hybrid approach. DFID minimises its costs by
maintaining an oversight role, quality assuring the results. Therefore this is the preferred option.
Commercial Case
A. Clearly state the procurement/commercial requirements for intervention
25. The different components of the EBP have different procurement and commercial requirements. The
soft market test (see Appraisal Case) facilitated the identification of the most appropriate routes to
market.
26. Given the number of partners involved it is helpful to further disaggregate the different components of
the EBP. Namely:
1

14. • Household Component: refers to the procurement of data collection, for the DFID Sudan
Household Survey, by a sole source supplierxxvii
. This sub-component will run for the entire
period of the programme (3 years).
• Component 1a: refers to the analytical elements of Component 1 that will be undertaken by
the World Bank. As these will be governed by the same Externally Funded Output (EFO) as
Component 3 this sub-component will be referred to below as the World Bank Component.
Both elements of the programme will run for 3 years.
• Component 1b: refers to the MICS survey. UNICEF will be responsible for this sub-component
and held accountable via a Memorandum of Understanding (MoU). This element of the
programme will run for less than one year (completed by early 2015).
• Component 2: The component will be put out to an open tender either in the Official Journal of
the European Union (OJEU) or the Global Evaluation Framework Agreement (GEFA). This is
based on DFID best practice and evidence that this will provide the largest number of
potentially viable suppliersxxviii
. The procurement exercise will begin as soon as possible, taking
into account the need to develop cross-office ownership of the details of the component, and
the programme will run for 2 years thereafter.
• Component 3: The World Bank will be responsible for this component and held accountable
via an EFO (as noted above).The component (hereafter World Bank Component) will deliver
capacity building and analytical products. This element of the programme will run for 3 years.
• Quality Assurance: The EBP will not have a formal evaluation. However, small scale and
essential independent research on the data quality of the pilot versions of the DFID Sudan
Household Survey (already developed) will be commissioned via DFID’s Professional Evidence
and Applied Knowledge Services (PEAKS).This element of the programme will run for 3
months after programme approval. The aim of this component is to ensure that, going forward,
the DFID Sudan Household Survey meets the highest standards for data collection.
1. Any elements of the programme can be extended beyond the proposed timeframes, as long as this
can be justified.
B. How do we expect the market place will respond to this opportunity?
• Household Component: Given the pilot polling we have already commissioned (see Appraisal
Case) we know that the route to market is limited. In consultation with the DFID Commercial
Adviser we have agreed that: (1) there is only one credible supplier, and therefore (2) we will
seek a sole source procurement process to deliver this sub-componentxxix.
• Component 2: Given experience of other DFID offices and the soft market test (see Appraisal
Case) we expect the market to respond favourably through an ‘Open Tender’ process (either
GEFA or OJEU).
• Quality Assurance: Given the uniqueness of the data generated and the large number of
suppliers available through PEAKS, we expect a very favourable market response.
C. How does the intervention design use competition to drive commercial advantage for
DFID?
1. All components included a careful engagement with the market. As a result it was possible for DFID to
select partners whose quality and costs were competitive. Specifically:
• Household Component: As noted above an initial assessment of market conditions was
made in 2012 and reviewed in 2013. These assessments indicated that the sole source
procurement route is the most commercially viable option.
• Component 2: The use of an ‘Open Tender’ process (GEFA/OJEU) for Component 2 means
that DFID will benefit from access to a significant number of partners.
• Quality Assurance: The use of the PEAKS facility will ensure commercial advantage for DFID
because the pre-selected group of suppliers have been identified, through a competitive
process, as representing value-for money.
1

15. 1. All the selected suppliers will be subject to Terms of Reference that will (as applicable):
• Describe the approach they would use to deliver results.
• Describe the costs necessary to deliver results.
• Describe the organisational arrangements for delivery, including any local partnerships.
• Describe their approach to sustainability and capacity building of Sudanese staff and
organisations.
• Demonstrate that they have the capacity to deliver their proposed approach.
• Clearly articulate the specific outputs that must be delivered in order to ensure payment
(payment-by results).
D. What are the key cost elements that affect overall price? How is value added and how
will we measure and improve this?
1. Key cost drivers of operation will be: staffing (international and local), polling implementation, field visit
logistics, security management, IT and other systems to underpin data collection and handling.
Challenges will include the cost of security provision and management (for local and international
staff), premiums for any internationals based in Sudan, and procurement of data input devices, such
as smartphones. Specifically:
• Household Component: The major cost drivers of this sub-component are transport costs and
changes in the level of conflict in Sudan that could disrupt data collection. Value added will be
determined based on the quality (and hence) usability of the data by DFID programmes,
academic researchers, and other partners.
• Component 2: The number of field visits and the type of data collected will be the main drivers
of costs. Payment by results is possible so costs will reflect value added
• Quality Assurance: consultant fees are the only cost driver for this component. Payment by
results is possible here so costs will reflect value added.
E. How will the contract be structured and how will contract & supplier performance be
managed through the life of the intervention?
1. All three contracts will be output based. This process will allow DFID to make payments by
deliverables. Each of the contracts will have appropriate reporting and payment schedules.
Payments will be governed by a detailed work plan and cash flow statements. This information will
be managed by the programme team to ensure accurate forecasting, budgeting, and delivery of
results on time.
2. Specifically, within 21 days of the end of each quarterly reporting period, the implementing partners
will:
• Provide the DFID Sudan project team with a written statement of progress against the work
plan and the logical framework, to include explanation of any slippage against all time-bound
deliverables,
• Provide a quarterly update of cash flow forecasts to the end of the financial year,
• Provide an update of the annual work plan for the balance of the financial year, with any
revision to the annual work plan agreed before the start of the financial year signed off in
advance by the DFID Sudan programme team.
1. The implementing partners will engage actively with DFID staff or external suppliers employed for
Annual Reviews and the Project Completion Report, or in response to internal or external
information requests.
Delivery through a third party entity (multilateral organisation; civil society organisation
or support to government)
1

16. A. Why is the proposed funding mechanism/form of arrangement the right one for this
intervention, with this development partner?
2. Component 1b and the World Bank Component (1a and Component 3) are delivered via multilateral
agencies (UNICEF and the World Bank respectively).
3. The ‘ soft market test’ (2013) of most multilateral organizations engaged in statistics capacity building
in Sudan identified the World Bank as the only supplier who could provide all the activities deemed
essential for the successful delivery of this intervention.
4. For Component 1b: UNICEF is an expert in the field of health surveys and the only global supplier of
MICS. It has a track record of successfully implementing these surveys- including previous rounds of
MICS in Sudan.
5. As noted above the World Bank agreement will be delivered via an EFO arrangement while the
UNICEF agreement will be delivered via an MoU. In both cases partners will be obliged to report within
21 days of the end of each quarterly reporting period/end of programme in the case of the UNICEF
MICS, the following information (as applicable):
• Provide the DFID Sudan project team with a written statement of progress against the work plan
and the logical framework, to include explanation of any slippage against all time-bound
deliverables,
• Provide a quarterly update of cash flow forecasts to the end of the financial year,
• Provide an update of the annual work plan for the balance of the financial year, with any revision to
the annual work plan agreed before the start of the financial year signed off in advance by the
DFID Sudan programme team.
1. The implementing partners will engage actively with DFID staff or external suppliers employed for
Annual Reviews and the Project Completion Report, or in response to internal or external
information requests.
B. What assurance has been obtained on capability and capacity to deliver?
• World Bank Component: Through the soft market testing exercise, the concept note, and
evidence of activities in Sudan, and other fragile states the World Bank has been able to
demonstrate that it has the expertise, programme capacity, and local network to deliver the
proposed programme activities. As the unit of the World Bank leading on this programme is
based in Washington DC it has also been assessed via the Multilateral Aid Review (MAR).
DFID will work with the World Bank to review and monitor programme activities- thereby
ensuring value for money.
• Component 1b: Through its concept note, programme proposal, and DFID’s due diligence (for
the delivery of DFID’s Female Genital Cutting Programme) DFID is confident of the capacity of
UNICEF to deliver on this component.
C. Is there an opportunity to negotiate on anticipated costs?
1. No, there is limited opportunity to negotiate costs with either the World Bank or UNICEF. However, we
will ensure that the programme is value for money at all stages. As the agreement with the World Bank
will be via an Externally Financed Outputs (EFOs) there is no administrative charge. UNICEF, under
the global framework arrangement, sets an 8% administrative fee.
Financial Case
A. Who are the recipients of all proposed payments?
1

17. 1. Payments will be received by: (1) the sole source supplier, (2) supplier identified via PEAKS, (3)
UNICEF, (4) the World Bank, and (5) the supplier identified via the ‘open tender’ process.
A. What are the costs to be incurred directly by DFID?
Table 8: Total Costs
Implementing Partner Total Amount
Sole source supplier £175,000
Supplier through PEAKS £50,000
UNICEF £166,500
The World Bank £1,408,500
Open tender supplier of TPM* £2,700,000*
*The total costs for this supplier emanate from the use of this service by other DFID Sudan programmes.
The total amount was calculated based on an indicative number of field visits per programme following the
example of DFID Yemen.
B. What are the costs to be incurred by third party organisations?
1. None- subcontractors may receive funding for activities (especially for Component 2) and these will
be explicitly accounted for in the budgets submitted by our implementing partners.
A. Does the project involve financial aid to governments? If so, please define the
arrangements in detail.
1. No- DFID provides no financial support to the Sudanese government.
A. Is the required funding available through current resource allocation or via a bid
from contingency? Will it be funded through capital/programme/admin?
1. Funds are available within DFID Sudan programme resources.
A. What is the profile of estimated costs? How will you work to ensure accurate
forecasting?
1. Funds will be paid against invoices upon delivery of outputs (non-multilateral partners) and payment
in arrears or against committed funding requests (UNICEF and the World Bank). The implementing
partners will notify DFID in advance of any significant planned or unforeseen deviations to the work
plan, staffing requirement, or expenses, especially where they are likely to result in substantial
changes to forecast monthly expenditure (where ‘substantial’ is defined as being of the order of +/-
10%).
Table 9: Indicative Budgetary Forecasts by Year
Component Year 1 Year 2 Year 3
1 2 1 2 1 2
1aa £35,000 £35,000 £35,000 £35,000 £35,000 £35,000
1b £165,000
2 750,000* 750,000* 750,000* 750,000*
World Bank £520,000 £520,000 £92,125 £92,125 £92,125 £92,125
Quality Assurance £50,000
Note: * Not direct spend but spend via other programmes. The total costs for this supplier emanate from the use of this
service by other DFID Sudan programmes. The total amount was calculated based on an indicative number of field
visits per programme following the example of DFID Yemen.
Table 10: Indicative Budgetary Forecasts by Component
1

18. Component Cost Assumptions
for Maximalist
Options
Spending profile (by
year) Components 1 &
3
Component 1 £ 665,000
Year 1: £1,040,000
Year 2: £380,000
Year 3: £380,000
Component 2 £2,700,000*
Component 3 £1,135,000
Note: Figures rounded to nearest £ 000.
* Not new spend but indicative spend by other programmes on menu of service
A. What is the assessment of financial risk and fraud?
1. A robust and proportionate monitoring strategy will be put in place for this programme. The fact that
payments will only be made in arrears and based on documented evidence leads us to judge that the
overall risk of fraud is low.
2. Specifically, for each element of the programme:
• Household Component: in order to minimize risks payments will be made by reimbursement
against agreed outputs. Spot checks will also be carried out in line with good financial
management practises by the programme team. Overall risk is judged to be low/medium.
• Component 1b: Given the strong financial management capacity and accountability system in
place by UNICEF the financial and fraud risks are considered to be low.
• Component 2: in order to minimize risks payments will be made by reimbursement against
agreed outputs. Spot checks will also be carried out in line with good financial management
practises by the programme team. The supplier’s commercial effectiveness will be scored via
the open tender exercise. Overall risk is judged to be low/medium.
• World Bank Component: Given the strong financial management capacity and accountability
system in place by the World Bank the financial and fraud risks are deemed to be low.
• Quality Assurance: in order to minimize risks payments will be made by reimbursement
against agreed outputs in line with the terms of reference and agreed deliverables. Therefore,
financial and fraud risks are deemed to be extremely low.
A. How will expenditure be monitored, reported and accounted for?
• Household Component: The supplier will provide invoices and field reports upon completion
of data collection activities.
• Component 1b: As noted above, given the findings of DFID’s due diligence (for the delivery of
DFID’s Female Genital Cutting Programme) we are confident that the dedicated UNICEF team
will provide DFID with financial, and results statements as part of the final report.
• Component 2: The programme team will monitor activities quarterly, the supplier will provide
reports on results and financial costs per field visit, as well as annual reporting covering both
financial and results elements.
• World Bank Component: As noted above, given the outcome of the MAR exercise we are
confident that the dedicated World Bank team will provide DFID with financial, and results
statements quarterly as well as an annual report (these arrangements will be stipulated in the
1

19. EFO agreement). This evidence base will soon be augmented by a due diligence exercise
being carried out locally in support of our Sudan Multi-Partner Fund.
• Quality Assurance: this is a desk based process (no travel to Sudan is expected) and
payment will be made via reimbursement after DFID has accepted the outputs.
A. Are there any accounting considerations arising from the project?
1. No
1

20. Management Case
A. What are the Management Arrangements for implementing the intervention?
2. As detailed in their respective ToRs, MoU, and/or EFO implementing partners will be held
accountable by DFID for the delivery of technically sound outputs that are delivered within budget
and on time.
3. A Senior Responsible Owner (SRO) will be appointed to this programme by December 2014.
4. The day-to-day management of the programme will be undertaken by an A2 Statistics Adviser and a
B2 Programme Officer. The Statistics Adviser will meet regularly with implementing partners and
assess technical outputs while the Programme Officer will ensure the delivery of outputs on time and
within budget.
5. Each component of the programme will have appropriate governance structures to ensure sound
finances and results. Specifically:
• Household Component: The quality of the outputs will be subject to independent
quality assurance (via the Quality Assurance Component). Programme staff will
conduct field visits to ensure that the polling occurs and is of a high standard. After
every round of polling is conducted a break clause will allow the termination of the
contract if the results are deemed inadequate.
• Component 1b: The detailed financial information provided by UNICEF will be
reviewed by the programme team. A possible field visit to assess technical quality is
being negotiated.
• Component 2: The different DFID Sudan teams that make use of these services will
have the opportunity to provide feedback via the Statistics Adviser. Break clauses in
the contract will ensure that, if the quality of outputs is low, the contract can be
terminated after a 12 month period. An internal DFID committee representing all
programmes that use the service and chaired by the Statistics Adviser will draft, in
consultation with the provider, 12 month work plans.
• World Bank Component: The DFID Sudan Statistics Adviser and the lead from the
World Bank team will meet weekly to discuss the programme and quarterly to make
decisions about the quality and direction of programme activities.
• Quality Assurance: The DFID Sudan Statistics Advisor will review and contribute to
this output to ensure quality.
1. Partnership Principles: DFID has a policy of not providing direct funding or working closely with the
Government of Sudan. As our detailed analysis documentsxxx
our assessment for this programme is
that the Government of Sudan performs badly against all of the Partnership Principles. This
programme will therefore, not provide direct support to government. However this programme does
attempt to influence the Government of Sudan through its activities. As noted above (see Strategic
Case) by generating new data and providing technical capacity building opportunities it is envisioned
that, even if only marginally, the existence of such data will create some incentives for pro-poor
development decision-making.
2. Gender Equality Act 2014: As outlined in the strategic case, and noted above, the activities of this
programme will be developed to ensure that they are gender sensitive. Specifically, implementing
partners will be required to consider how their sampling strategy, the selection of enumerators, and
equal inclusion of men and women in capacity building workshops are taken into account when
implementing their respective activities.
2

21. B. What are the risks and how these will be managed?
3. The risks and mitigation strategies associated with the programme are identified in the Table below.
Overall the programme is considered medium risk due to Component 2. If this component is
excluded the overall risk rating is low.
Table 10: Risk Matrix
Risk Probability Impact Mitigating actions Residual
risk
Government
revokes right to
commission
DFID Sudan
survey
Low High The use of a local company with access and good
dialogue with the Central Bureau of Statistics (CBS)
will ensure that the ability to obtain permission to
conduct the polling is on-going. The dissemination
of the findings through scientific, English language
mediums will ensure that findings are not
sensationalized in the local media
Low
Inability of the
independent
monitor to
access sights
due to
government
interference
High-Medium High The procurement process will include an explicit
requirement that the provider explains and
provides evidence, in detail, how they will address
the issue of access. Component 3 engagement will
also facilitate accessxxxi
.
Medium-
High
Loss of
interest, by
DFID
programme
teams, in using
TPM
Low High Consultative and inclusive design process will
ensure that teams help shape the menu of
services available to suit their programme needs.
Low
Loss of
momentum
from
government
and/or civil
society -leading
to
abandonment
of the 3rd
Component
Low High The development of the programme will be based
on regular consultation with stakeholders. The
World Bank was selected as an implementing
partner because of its relatively good track record
of maintaining engagement with local stakeholders
and the flexible nature of the programme will
ensure that changes can be made to activities as
feedback is received.
Low
DFID
management of
the programme
is insufficient to
deliver results.
Low High DFID has a skilled statistician in post, and will
maintain an adequately resourced and skilled
team. Programme staff will ensure financial
accountability.
Low
Fiduciary risk Medium High We will demand comprehensive financial
information from partners and will closely
scrutinise the financial reports.
Medium
C. What conditions apply (for financial aid only)?
4. N/A – this is not a Financial Aid Project
D. How will progress and results be monitored, measured and evaluated?
2

22. 5. Overall responsibility for project monitoring and evaluation will rest with DFID Sudan, and will
be undertaken on the basis of the logframe (see QUEST 4550045).
6. The monitoring strategy for the project will be based on a systematic and regular collection of
data to assess the progress towards meeting the milestones (and, towards project-end, the
targets). This will be undertaken on a continuous basis by implementing partners and DFID,
during their regular meetings, and quarterly reports.
7. The project evaluation plan will be based on annual reviews and the independent quality
assurance provided by the PEAKS supplier. The process will be based on DFID standard
evaluation guidance and include project scoring and assessments of potential over- or under-
achievement against the project deliverables. This will in turn inform any adjustments to the
logframe.
2

23. i
Ibid.
ii
The role of statistics in development is now well established: see for example DFID
(https://www.gov.uk/government/organisations/department-for-international-development/about/statistics ), UNFPA
(http://www.unfpa.org/public/datafordevelopment/overview ), the World Bank
(http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/0,,menuPK:476823~pagePK:64165236~piPK:64165141~theSitePK:469372,0
0.html); and the IMF (https://www.imf.org/external/data.htm).
iii
According to the most recent data UN data Sudan ranks 171 out of 186 countries in the Human Development Index (lower ranking
denotes worse socio-economic conditions). United Nations (2013) Human Development Report 2013: The Rise of the South: Human
Progress in a Diverse World. The United Nations: New York Available at < http://hdr.undp.org/en/media/HDR2013_EN_Summary.pdf
>.
iv
For a review of the conditions in Sudan and the work of DFID see : DFID (2013) DFID Annual Report and Accounts 2012-2013. DFID:
London. Available at < https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/208445/annual-report-
accounts2013-13.pdf >
v
The importance of data in understanding the key drivers of conflict is well documented in the academic literature e.g. Bateson (2012),
Blattman (2009), Beber et al. (2014) , Bellows and Miguel (2009), Hersh (2013), Rojo-Mendoza (2011).
vi
Development stakeholders is a large group that includes other donors, implementing partners, civil society, and to an extent, the
Sudanese government/elements of the government.
vii
See http://www.cbs.gov.sd/en/
viii
See http://www.mof.gov.sd/home.php#
ix
See http://www.cbos.gov.sd/en
x
For example disaggregate data from the 2008 Census (contested by the South) was never released. The household health survey was
delayed for a year (from 2013 to 2014) and results from the nutrition survey (due in October 2013), were only released in early 2014.
xi
Outlined in detail in our DFID Evaluation and Monitoring Strategy - 4315931
xii
Diplomatic missions (like DFID) and International Organizations (UNDP) face considerable hurdles in data generation (e.g.
requirement to obtain permits from the Central Bureau of Statistics and/or the Humanitarian Assistance Committee -HAC). However,
these are still less onerous than the actual constraints faced by INGOs.
xiii
DFID was a contributor to the funding of a nutritional survey and was also involved in the 2008 census.
xiv
For example, in collaboration with the Foreign and Commonwealth Office DFID Sudan commissioned two rounds of an opinion poll
that solicited information from a representative sample of the general public in 2012 and 2013; staff have been able to undertake
(intermitted) visits to the field to review DFID programmes and projects and DFID, via the IMF, has funded a technical expert to provide
technical assistance to the Ministry of Finance.
xv
The reasons for a lack of detailed data collection are numerous. The authorities have little incentive to solicit the needs of
marginalized groups (with no political voice), while the ability and willingness of other partners to invest in rigorous data collection
exercises has been limited.
xvi
Some of the budgets for existing programmes have no budget lines earmarked for third party monitoring activities (although many
newer business cases do have such explicit earmarking). However, experience from other offices shows that even programmes with no
specific earmarks can benefit from a TPM facility. As independent evaluators and teams can commission data collection relatively
easily-without having to procure and obtain these services directly- saving time and reducing the risks of being refused permits.
xvii
See DFID Sudan’s evaluation of the CRMA project QUEST 4409062.
xviii
This component will build the capacity of non-state actors who, however, enjoy an ability to obtain permission to collect data from
authorities (mostly universities). As such the Component will not directly be involved in engagement with government.
xix
This was a key concern for the DFID Sudan policy team that the development of local capacity for monitoring and evaluation should
be included in this programme.
xx
It is important to note that both in its terms of scope (bi-annual) and in terms of breath of questions asked the proposed household
survey is unique and is not a duplication of other data collection efforts.
xxi
See Annex A- QUEST 4552200.
xxii
For more information please see http://www.unicef.org/statistics/index_24302.html
xxiii
Defined as either going through DFID’s Global Evaluation Framework Agreement (GEFA) or the EU’s open procurement process
(OJEU).
xxiv
A, high potential risk / opportunity; B, medium / manageable potential risk / opportunity; C, low / no risk / opportunity.
xxv
Environmental Assessment – QUEST 4552243
xxvi
Conflict Analysis- QUEST 455223.
xxvii
The justification for sole source procurement of the polling company is based on an assessment of in-country expertise and quality
checks (see QUEST: 4412294).
xxviii
See QUEST 4412294.
xxix
See QUEST 4552308.
xxx
See QUEST 4552418.
xxxi
Market test confirmed that engaging on capacity development can facilitate