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Contextual analysis August 2012 (version)

This chapter should be read in its entirety and understood before conducting an area based contextual analysis.

This chapter is a guide to an area based contextual analysis. It is envisaged that this type of contextual analysis will have to be carried out in the following scenarios:

1) Following on from Country Strategic Planning; a process that has identified geographical areas that the country programme will work in, an area based contextual analysis will have to be carried out for each geographical area at least every five years.

2) Where a programme has come to an end and another programme is planned, it is important that a contextual analysis is carried out or an existing contextual analysis updated.

By the end of this section you will: Know what key questions guide the contextual analysis. Be equipped to examine the three dimensions of extreme poverty, which are (1) Lack of and

low return on basic assets (2) Inequality, and (3) Risk and Vulnerability, resulting in a more holistic understanding of the context.

Know the appropriate information to gather and analyse in order to be able to present ALL programming options in a given context. This will support you to take informed programming decisions; including identifying target groups and options for strategic partnership.

Know what to include in a contextual analysis report. Be able to proceed from contextual analysis to the next phase of the PCMS; Objective Setting

and development of a PCN (s) (See next chapters) Have learned from key recommendations based on lessons learned to date (July 2012)_

What is Contextual Analysis?

Contextual analysis (CA) is a holistic view of a context; the whole environment in which programmes operate. The environment spans all of the policies, institutions and processes, including the private sector, the demographics, and the social, cultural environmental and economic aspects of life in a specific area. It does not have a sector focus but rather looks at all aspects of people’s lives, with a particular focus on the extreme poor groups in a given context. A contextual analysis should provide the necessary information in order to determine what the various programme options are in a given context. This chapter forms the practical guidelines to carrying out a contextual analysis that is grounded in Concerns understanding of extreme poverty outlined in the policy paper “How Concern Understands Extreme Poverty” (2010), which focuses on the three dimensions of extreme poverty: Lack of and / or low return on basic assets, Inequality, and, Risk and Vulnerability. It is important that you read the policy document and understand the concepts that are presented in the paper.

Programme planning Area Based Contextual Analysis Programme Analysis Setting objectives

Start up phase Start up workshops M&E plan Baseline Community planning

Annual planning and review

Monitoring and periodic reflection

Mid-term review

Final evaluation

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Contextual analysis in both emergency and development contexts We carry out contextual analysis in both contexts of emergency and development, and they are generally area based. This chapter focuses on carrying out an area based contextual analysis in a developmental context, which should take place at the beginning of a programme cycle. The contextual analysis report should be a good source of information about the context during the lifecycle of the programme and should be reviewed and updated at regular intervals, ideally during your annual review, in order to inform the development of new projects/programmes. At the end of the contextual analysis process, a number of potential programming options should emerge. At this point it is essential that the country team have discussions with the Regional team in head office and technical advisors in order to get approval on the focus of any new programme, and development of any new PCN (s). For detailed project/ programme planning you will have to revisit the context and gather more in-depth information in order to fully develop any new intervention. Contextual analysis is also relevant in emergencies, where it is often called a needs assessment. The process is much faster than in development contexts and moves quickly into activity planning. However the focus of the needs assessment should not remain just on basic needs, but also take into account issues of Inequality, Risk and Vulnerability and how specific extreme poor groups are impacted differently. In many contexts issues of inequality will already prevail and during an emergency will tend to be exacerbated, increasing the inequalities experienced and vulnerability of particular groups. Information from existing programme contextual analyses can help inform a needs assessment and the approach to building up a detailed understanding of context can be applied or revisited as the demands of the emergency response allow.

Why do it?

Contextual analysis is critical for identifying who the extreme poor are, and understanding why they are poor and what keeps them in poverty. Extreme poverty, as defined by Concern, requires an analysis of three key factors (see diagram overleaf); 1) Lack of and / or low return on basic assets 2) Inequality 3) Risk and Vulnerability In order to carry out a contextual analysis it is critical that the team understand the conceptual model of extreme poverty as defined by Concern in the paper, ‘How Concern Understands Extreme Poverty’ and the Organisational Strategic Plan (2011-2015). As well as identifying who the extreme poor are, the analysis provides a broad understanding of the environment in which they live. It should result in programmes that address extreme poverty in a holistic manner. By understanding and tackling the immediate and root causes of poverty in the particular context in which you are working, you are more likely to bring about significant and lasting changes in the lives of the extreme poor. By asking and actively listening to the views and understanding of those who live in extreme poverty to guide the analysis, programmes will be relevant and appropriate for improving their lives and context.

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Concern’s Conceptual Model of Extreme Poverty

Extremely Poor

People

Low Assets

Lack of Return on Assets

Risk & Vulnerability

Inequality

Key questions for contextual analysis Below are the 5 key questions that underpin this process and that the process aims to answer:

1) Who are the extreme poor in this context and where are they? 2) Why are they poor? 3) What keeps them in extreme poverty? 4) What opportunities are available to extremely poor people? 5) What needs to change – who is responsible1, what is already happening?

Who should lead a contextual analysis?

The chapter is aimed primarily at Assistant Country Directors (Programmes) whose responsibility it is to facilitate this process with programme managers and other staff (see Capacity Building section), who might be more intimately involved in carrying out the steps in the contextual analysis. This chapter should also be helpful for technical advisers (SAL and Emergency unit) and Desk Officers who should be involved in the contextual analysis process and for Regional Directors who are responsible for approving Project Concept Notes (PCNs). Whilst not aimed at partners specifically, partner organisations may also be interested in looking at this chapter to learn about how Concern understands contextual analysis, and the role of partners within carrying out contextual analysis. If you are contracting a consultant to facilitate the process they need to be aware of and understand the guide and the document “How Concern Understands Extreme Poverty”. It is vital that the lead facilitator or consultant has a clear understanding of the approach before starting the process. Also remember if you are hiring a consultant to facilitate the process, make

1 This requires an identification of duty bearers, with a focus on governance and sustainability.

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sure that they can speak the official language of the country, in order to minimise the loss of detail in translation.

Role of partners and community in a contextual analysis

Country teams should consider at a minimum hosting a formal session for partners giving guidance on Concern’s approach to understanding extreme poverty and the planned contextual analysis process itself. The degree to which partners are involved will depend on country context, capacity and whether the resultant interventions will be delivered directly or through partners. If the country programme implements entirely through partners, they should ideally be an integral part of the contextual analysis process. Partners also in many cases have a lot of skills in using Participatory Learning Approaches (PLA), which is important for the primary data collection phase. Information dissemination of the process you are undertaking during primary data collection needs to be well communicated to communities and ideally should be facilitated by community representatives, so it is important they have a clear understanding of the purpose and process itself. There are a number of tools and guiding documents on the partnership Intranet site.

Consider the critical importance of: 1) Good facilitation of the process. A facilitator can hold the thinking together, keeping the contextual analysis

focussed and reprioritising issues as the data collection and analysis moves on. 2) Training: Participants in the contextual analysis process should have adequate training and understanding

of the process prior to starting the contextual analysis process, especially of the paper and concepts in “How Concern Understands Extreme Poverty”, namely the three key dimensions of Extreme Poverty; Assets, Inequality and Risk & Vulnerability.

3) The importance of good management of the process: ensure that a key contact person is identified as the link person between head office, consultants and the field team.

4) Communication and consultation between the field team and head office is really important right throughout the process, to ensure that people are engaged to support the process at the appropriate stages.

5) Importance of a diverse team to minimise on bias: Utilise staff from other programme areas or engage partner staff to ensure gender balance and a range of knowledge and skills are on the team.

6) Good analytical skills: A good facilitator can bring a team through a process of analysis. If capacity is low on the team you can bring support in through using advisors or consultants.

7) The amount of information you are collecting! For each piece of information you want to collect, ask yourself, “What will we do with this information? Is it needed? Will it help answer one of the ‘5 key questions for contextual analysis’ outlined above?”

8) During the data collection phases you will be collecting both quantitative and qualitative data. It is important to understand the differences (see page 16 for more clarity)

9) Time: In a development setting with staff available to dedicate sufficient time to the process it would take about 3 months to get to the end of the process.

10) Reflection Time: During Primary data gathering, ensure that time is set aside at the end of each day to reflect on the process, identify where the gaps are, what worked well, what not so well, and what needs to be done differently the next day. It is also critical that field notes are typed up every night to capture the information gathered that day.

11) During the primary data phase, build in accountability mechanisms in line with the organisations accountability strategy.

12) Breadth versus Depth: During the Primary data phase, if you are under time pressure, it is better to focus on fewer communities, and spend more quality time with them. Dropping into communities for one hour visits is not advisable.

13) Not to be bound by your Strategic Plan: Do not let your strategic plan determine areas of focus in the contextual analysis. Keep the contextual analysis very broad guided by the three dimensions of Assets, Inequality, Risk and Vulnerability, and when you come to programme options rationalise why particular initiatives are being presented.

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Step 1 Communication & Planning: It is really important that you plan the contextual analysis well, allowing adequate time for the planning process. Make sure that you communicate with your Regional Director and Desk Officer regarding your timelines and who is leading the contextual analysis team. If you don’t have capacity within the team and want to take on a consultant to facilitate the process, communicate with your regional desk as they will be able to advise you on a number of recommended consultants who may be appropriate for your country context. The Contextual Analysis Plan Template should be used for initial planning purposes. This can be found in Annex 10 and annexed to the PCMS guide. Begin to raise awareness amongst the team about ‘How Concern Understands Extreme Poverty’ and the process of the contextual analysis. The CD or ACDP should lead this process and get buy in from the whole team.

Step 2: Preparation & Set Up. Define the scope of your contextual analysis, set objectives and make a plan. Understanding what you need to know Include the geographical area it will cover, and explain the rationale for geographical area to be focused on, the time frame, the budget, who will be involved, and the time commitment required. Agree the contextual analysis objectives and write up the implementation plan for the contextual analysis. The plan needs to be submitted to and approved by the Regional Director. Further information on the plan and a format is included in the Programme Cycle Management System. Even if your Country Strategic Plan has a specific sectoral focus, it is important that the area based contextual analysis is broader and takes a look at the various drivers of poverty independent of a specific sector lens2.

2 Remember, that Strategic Plans are iterative, they can be changed and amended during their lifespan when deemed necessary, and so they should not restrict your focus during contextual analysis.

The Importance of a Clear Objective of why the contextual analysis is being conducted In order to keep the Context Analysis on track and the information manageable, it is vital to have a clear objective on why the contextual analysis is being conducted. For example in Zimbabwe the team wanted to revisit their programme to ensure it was reaching the extreme poor so the objective of their Context Analysis was for “developing programme options for the Gokwes, based on the aspirations and capabilities of the extremely poor, which are relevant and will have a sustained positive impact on their lives in the dynamic context which prevails in Zimbabwe”.

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Initial Stakeholder Analysis. Identify stakeholders and determine how each group needs to be involved in the contextual analysis process. Stakeholders include; local people who represent different potential target groups, staff (at different levels and from different teams), local authorities, potential and existing partners, government, civil society organisations, private sector, other NGOs, technical advisors and the regional desk at head office. Some of the staff (including the partner staff if applicable) should know the area and the community so that the community have confidence and trust in the activities being carried out. Stakeholder respective roles can vary from being fully involved in the process, providing information or just being informed.

The process of carrying out a contextual analysis will not always happen in a linear manner. Instead, the process will be iterative, with the picture of the context emerging over time. Focus is maintained by having a clear objective and the 5 Key Questions and it is important to keep referring to these.

Ensure that you have a technically diverse and gender balanced team. If you require translators make sure you have female translators on the team to enable open discussions with women & girls.

What do we do about sectors? It is rare that Concern conducts Context Analysis in an area that we have never worked in before, so existing interventions and Country Level Strategic Plans will to some extent set the stage for context analysis. However, regardless of the expected focus of an intervention, there needs to be a broad area based contextual analysis preceding any programme intervention. The sector analysis will succeed this during programme planning, and will involve more specific analysis based around sector guidelines. This will be looked at in the next chapter. “How Concern Understands Extreme Poverty” is a holistic model and it is important that all aspects of the data gathering framework are addressed. Services are not delivered in a vacuum and it is often social, cultural and economic issues which prevent the extreme poor from accessing a service rather than the quality of the service alone. A context analysis which takes the sector as the primary focus runs the risk of asking questions only about systems (e.g. the health or education system) and the related outcomes, for example; ‘where are the areas with the highest mortality rates, malnutrition prevalence or lowest coverage of key health outcomes?’. These types of questions do not always help identify who the extreme poor are, or why they are extremely poor, and so consequently can lead to programmes that do not target or benefit the poorest.

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Understanding what you need to know: Concern’s conceptual model of extreme poverty forms the basis of contextual analysis. Concern believes that by understanding the context and the lives of the extreme poor in terms of the three dimensions it will be possible to identify the most important constraints and opportunities to moving out of extreme poverty. To help us bring together data on the three dimensions (“Lack of/low return to assets, inequality, risk and vulnerability”) of poverty needed for contextual analysis a Framework for Data Gathering has been developed. The framework allows us to further breakdown into areas of assets, livelihood strategies, access to services, respect, recognition and voice, specific gender issues, hazard and risk and vulnerability. The Framework also draws attention to the importance of disaggregation of vulnerabilities, marginalised, gender etc throughout data collection and analysis and the need to bring into the analysis the wider environment in terms of policies, institutions and processes. The contents/components of the framework are detailed below and guidance on doing this is to be found in Step 4. Using the Framework to set up and guide the contextual analysis is a way to break down the context and the lives of the extreme poor to ensure that all the appropriate information is collected and fed into the analysis. Specific questions about each aspect of the framework should be generated for each contextual analysis and these help further refine data collection and narrow areas of enquiry. Disaggregation is vital when collecting data. Concern’s approach to contextual analysis relies on recognising the unique situation of the extreme poor and the differences that exist between different groups of the extreme poor. Therefore disaggregation of data in contextual analysis is an important way to understand these differences and ensure interventions are really appropriate in reaching the extreme poor. As a minimum standard it is essential that ALL data is sex disaggregated. In terms of the different groups of extreme poor identified, they might be disaggregated between different age groups, disability groups, social status groups (castes), special needs groups, livelihoods strategies.

Bangladesh Urban Strategy identified Specific Impact Groups Based on analyses of the livelihood strategies of various groups of extremely poor people living in urban areas as well as taking into consideration the numbers of people in each group and their relative neglect in terms of access to services and support, Concern Bangladesh decided to focus its programming on the undeveloped slums, undeveloped parts of developed slums, squatter settlements and pavement dwellers. Nine priority target groups were identified in these areas, including: Two-Parent Families whose household heads are unemployed or engaged in day labour or rickshaw pulling living in undeveloped slums in major cities, in undeveloped slums in secondary cities or in squatter settlements (Three target groups) Two-Parent Families living on footpaths, or in transport or marketing centres as pavement dwellers (One Target Group) Any Women-Headed Households, including informal women-headed households in which husbands have migrated, living in undeveloped slums in major cities, in undeveloped slums in secondary cities, in squatter settlements, or on footpaths, or in transport or marketing centres (Four target groups) Children and Youth not attached to families who are engaged in waste collection (One target group)

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Key recommendations: Recognise the need for a diverse range of technical skills and gender balance in the team

conducting contextual analysis, especially for any primary data collection needed. If you feel you don’t have this, look to bring in external support from Concern or partners. Bringing partners staff on board, including government representatives, can really help for them to understand the direction that Concern is taking, as well as building capacity where appropriate. There would need to be a clear understanding that involvement in the contextual analysis process is not a commitment for collaboration on any resulting interventions.

The process of collecting secondary data is an important step, but this does necessarily need a diverse team to do this. However, there is a need to quality check data collected with advisors to highlight any gaps that may exist, as the data will be used to set up questions for any primary research conducted, so identifying gaps is important.

The need for understanding ‘who else is doing what’ in the area is a significant part of secondary data analysis. NGOs, CBOs, faith based organisations etc should be visited during the process to understanding what they are doing and information that they are willing to share.

Step 3 Orientation and Training: Anticipate training needs of staff and stakeholders. All participants will need orientation on Concern’s approach to contextual analysis and the process itself. At this stage there should be a focus on making sure there is a clear understanding of ‘How Concern Understands Extreme OPoverty’ and unpacking this. Hosting a workshop prior to the commencement of the process should be prioritised initially. Prior to starting data collection it is vital that the team understand the Data Gathering Framework, “How Concern Understands Extreme Poverty” and the related concepts of sustainable livelihoods, risk, vulnerability, capacity and equality. Training needs should be assessed and addressed prior to starting the process. There are a large number of tools and resources to help with data collection and analysis and these are referenced at the end of this chapter. Teams may need additional training or familiarisation with the specific tools that will be used, this training should be done after stage 4, when all secondary data has been collected and it is clear what primary data collection and corresponding tools need to be used . Training can then be focused on data collection using a defined set of tools.

Step 4: Data Gathering and Analysis Phase 1. Developing the Framework for Data Gathering by using secondary data to set the context specific questions.

Using the key questions from the data gathering framework (see table), begin to gather information from secondary data sources to build up a comprehensive picture of the context that you are analysing. Gathering information from secondary sources in some contexts will provide you with the majority of information required for your contextual analysis.

For a more detailed narrative description of each component of the framework: PIPS, Assets, Livelihoods Strategies, Inequalities, Risk, Vulnerability and Capacity, see Annex 1

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Framework for guiding data gathering (See Annex 1 for expanded version)

Extreme Poor Impact Groups

Effects of PIPS on each Impact Group

Questions to be answered by the Contextual Analysis: in relation to the wider community PLUS the specific extreme poor impact groups identified Male Female

ASSETS ( NATURAL, PHYSICAL, FINANCIAL, HUMAN, SOCIAL, POLITICAL) & RETURN ON ASSETS (1) What assets do they have? (2)What basic assets are lacking? (3) What are the benefits derived from these assets and are returns limited? Why? (4) To what extent do they have voice / control over these assets? How? Why? (5) What assets exist that are not being used by the extreme poor and why?

LIVELIHOODS STRATEGIES (1) What are the main Livelihoods Strategies within these groups? What are the returns from these strategies? (2) What other strategies could be available and why are they not used? (3) How are markets linked to livelihood security? What is the status of markets? (4) Are there any potential opportunities for engagement with the private sector

ACCESS TO (QUALITY) SERVICES (1) What services are relevant to them? Why? (2) To what extent do they have access to these services? Why / why not? (3) To what extent do they have voice / control over these services? Can and how do they participate?

RESPECT, RECOGNITION & VOICE (1) Do they have representation at local & National Government either directly or through CSOs? (2) What cultural practices impact the lives of these groups? Do they experience social stigma, discrimination or exclusion? How does it affect their lives? (3) What are their valued livelihood outcomes?

GENDER Specific issues related to gender inequality (gender roles, relations, GBV etc.)

HAZARDS & RISKS: (1) What are the main hazards, what causes them, what are their impacts, and where and when do they occur (natural and human-made, including HIV)? (2) What are the felt and predicted impacts of changes in the wider context (climate change, food and fuel prices, politics and conflict etc) (3) What are the key risks (impact vs. probability)? What are the extensive risks? Include HIV. VULNERABILITY: (1) Who, and what (assets) are vulnerable to these risks? (2) Why are they vulnerable? CAPACITY: What assets are available for use in responding to disasters (institutions and communities)? What are the coping strategies of the vulnerable people?

For a more detailed narrative description of each component of the framework: PIPS, Assets, Livelihoods Strategies, Inequalities, Risk, Vulnerability and Capacity, see Annex 1

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If good comprehensive secondary data exists you may not have to carry out primary data collection

Throughout this secondary data collection process, the dedicated team will be analysing information, having discussions within the team, other agencies and key informants, which should start to highlight any gaps in information, or areas that require further exploration or triangulation. During the secondary data phase, begin to start addressing the five key questions. And only when you get to the point that the key questions cannot be answered from the secondary data sources should you start to design the primary data collection phase. The information gaps from the secondary data will guide you in the setting of the specific questions with the team for the primary data collection. The questions must test existing assumptions as well as fill in gaps in knowledge to answer the 5 Key Questions. Use the Data Gathering Framework to ensure that you are gathering relevent information that relates to each aspect of the framework. The guiding questions in the Data Gathering Framework are the minimum set of questions that need to be answered and will also focus the data gathering and stop it becoming too broad and unmanageable. This however is a guide and not an exhaustive list of questions. It is up to the team in country to develop a more detailed set of questions relevant to the context, based on the information and gaps being revealed in the secondary data collection phase. Populating the framework with information from secondary data sources will assist you with the filtering of information. This process will also assist you in identifying any gaps in information, and help you to formulate the key questions for further data gathering, either secondary or primary. During the secondary data phase remember gather information on the Policies, Institutions and Processes (PIPS). For each area in the Data Gathering Framework it is important to identify and analyse the relevant policies, institutions and processes at local, district and national levels; what exists, what are the features and functions of importance to the extreme poor and how well is it performing or being implemented. PIPS include; institutions and organisations (both public and private sector), services, policies and legislation and socio-cultural practices and norms. They also include the market.

Secondary Data Sources: Secondary data might include; demographics, population census, literacy, mortality, morbidity, HIV and malnutrition rates and causes, services available, infrastructure, household economic zones, key policies, key duty-bearers, climate change predictions, risk maps etc. Existing Concern and partner programmes will have a wealth of information and if there are other programmes operating in the same geographic areas check whether they already have any relevant data. Concern technical advisors have compiled a list of secondary data sources which is a good starting point for finding information (see Annex 4, Annex 5, Annex 6). This should be enough to give you a broad overview of the context and to start seeing which groups are most likely to be extremely poor. You should also contact your Desk Officer who is in a good position to liaise with technical advisors on the sourcing of relevant country data.

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Recommendations:

The collection of data on policies, institutions and processes (PIPS) is critical, especially when it later comes to defining programme options and relating these back to the information collected.

Often secondary data can be focused at the national level, but where possible, regional/district data should be collected, as this is more relevant to the context. Administrative offices and organisations should be visited for the collection of any relevant data they are willing to share.

It is advisably to have a separate secondary data report, this can be useful tool for the team that is updated annual or as needed.

It can take time to go through secondary data, and this needs to be factored in. Be prepared to challenge data with staff, verify and triangulate sources where possible to be confident it is painting a representative picture.

Broadly Identify the Extreme Poor Groups. Identify groups of people that share common

characteristics who are likely to fall into Concern’s definition of extreme poverty. It is vital to conduct this step early on in the contextual analysis because the descriptions of the different characteristics of people who are extremely poor become the unit of disaggregation (in addition to disaggregation by sex) for the remainder of the contextual analysis. Identifying the characteristics of the extreme poor can be done through a combination of brainstorming (using the knowledge of key stakeholders, including communities as well as their leaders), and information collected through the initial secondary data analysis. The box overleaf contains some examples. From this initial brainstorm try and pull together some descriptions of the extreme poor which cover sufficient numbers of people to include in the analysis.3 Groupings (common characteristics) should be reviewed throughout the analysis to ensure that they are the most effective in describing the extreme poor. As you continue with the analysis you will find that groups are removed or merged and other groups added but the analytical process will ensure that you end up with the right groups.

3 Once included in the analysis a significant amount of data needs to be assembled for each group; to undertake this process for a group of people who are very small in number might not be valuable in terms of understanding the context. Excluding people from the analysis does not mean they will not fall into the target group of the final programme. Remember that there will be overlap between different groups of the extreme poor as different people may possess more than one common characteristic..

Secondary Data Review and Analysis in Concern Rwanda Concern Rwanda enlisted the help of an intern to review and analyse the extensive secondary data available on poverty and service provision. The intern produced a comprehensive report and was able to describe both the characteristics of extreme poor households in the target areas, as well as give an indication of the determinants of poverty in each case.

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Identify the risks in the context Firstly broadly identify the hazards; these may range from natural

hazards (geological, hydro-meteorological and biological which includes HIV) or human-made hazards (economic, social, political and technological). By looking at past experiences we can estimate the magnitude of the effects; and by looking at frequency and trends (predicting the effects of climate change, urbanisation, population growth and environmental degradation) we can estimate the probability of disaster events happening. The combination of the magnitude of the effects of disasters and the probability of the disaster happening gives us the risk.

Do not forget to focus not only on the high risk hazards, but also the highly probable/frequent extensive risks. Remember that scientists and other analysts may identify hazards that local populations may not be aware of, or do not consider to be high risk. We must also remember to acknowledge and analyse risks we may impose on our beneficiaries though the decisions we make. HIV should always appear as a risk even when the incidence is low. Once the risks are broadly identified, develop questions to be answered by the contextual analysis about location and seasonality of risk, causes and effects, vulnerability of the extreme poor to these hazards and the reasons why, their coping strategies, available capacities and the institutions responsible for mitigating the risk or responding to disasters.

Step 5: Data Gathering and Analysis Phase 2. Answering the Questions in the Data

An Example of generating the key Questions using the ‘Framework for Guiding Data Gathering: Context Analysis in DRC: The key questions to be answered by the Context Analysis were generated through desk research (programme documents and evaluations from Concern and others, collecting monitoring data from current interventions and reviewing research and surveys from the area) and discussions with managers and staff. The Framework for Data Gathering guided the questions, some examples of which are below: Assets: What does household food insecurity look like? What are the seasonal dynamics around agriculture, seed

production, selling surplus and consumption? Is increasing production the solution to food security? Is food security linked to the availability of work?

Services: What is the status of access to education? How much of a drain is it on family resources? What is the quality of education received? What education infrastructure exists?

Respect, Recognition, Voice: What representation do people have at local level? What community structures and institutions exist? What can they do, and do they take collective action? What happens when people are displaced? What was the case historically? Is the information collected truly representative of the community (has it been triangulated)

Gender: What are attitudes and behaviours around ensuring the well-being and safety of children and women? What actions are taken and who is responsible? What is happening regarding SGBV against women, how is that impacting on the lives of women?

Risk and Vulnerability: What is the risk of HIV? Do people know how to prevent it? What are the attitudes to those who are HIV positive? Are there PLHIV in the communities?

Inequality: What can we learn about Pygmy people? How should we work with them in the future?

Example characteristics of some Extreme Poor Groups which may be identified:

Livelihood strategy (migration for work, farming, specific profession such as artisans or sex workers, selling labour)

Health status (PLHIV, people with leprosy) Ability/Disability Marital or family status (female headed households, newly married couples, single women, child

headed households) Economic (wealth ranking groups, landholding (or lack of), homeless) Ethnicity or language group(Batwa people Burundi, Pygmy people in DRC) Caste (Dalits in India and Nepal, landless scheduled caste in India) Age (older people, children, adolescents) Education (literate/illiterate or level of attainment)

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Step 5: Data gathering and Analysis Phase 2. Populate the data Gathering Framework using primary and secondary data

At this point the contextual analysis becomes a piece of research to answer the questions generated by the initial secondary data gathering and analysis. It is likely that further secondary data collection will be required and possible that primary data collection will also commence. For each question it will be necessary to decide how information will be collected and importantly how this information will be triangulated. Key informants, local data sources and participatory approaches with communities may all be used at this stage. Bear in mind through the Humanitarian Accountability Partnership, and the organisational accountability strategy, we have a commitment to be transparent, to share and to enable beneficiaries and their representatives to participate and have influence in programme decisions, so it is important to consider what we can do to facilitate their participation e.g. ask what time is it most suitable to meet with communities and their representatives, and how they will be included in the process. You might find it useful to use some stakeholder analysis tools to do this (see the Tools and Resources Index in the PM&E Guide). *If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Constant review is needed to check the questions are understood and being answered and to reprioritise. Cycles of data collection and analysis may be repeated as further questions arise. You should look at how the data are related to one another to deepen your understanding of the context. It is important to keep consulting community representatives and to randomly triangulate data with communities to check that they think the information you are collecting makes sense and is capturing important factors. Capturing the aspirations and valued livelihood outcomes of the extreme poor is also an important activity for this step. Good practise has seen facilitators lead a review of data collection at the end of every day during the process. This allows a quick analysis on all information gathered and to help plan for the next day. This helps to make sure data collection is on track, and for any strange results that are emerging to be taken into account. It is important to remember that there is an iterative relationship between qualitative and quantitative data and that analysis of one will raise questions to be answered by the other. For example, when presented with a high level of stunting (quantitative) information needs to be gathered on whether it is due to it access, use or health (qualitative and quantitative). Or when access to land emerges as a theme in Focus Group Discussions (qualitative), it is useful to collect some quantitative data on actual land holding to give a sense of scale.

Stakeholder analysis: identify all the stakeholders or interest groups within your particular context. Stakeholders can be organisations, groups, departments, structures, networks or individuals. The analysis should give you a good idea of who is doing what in the context. Through the analysis you may be able to identify capacities of CSOs and of existing/potential partners (including government and Private Sector). This will give you a sense of what is achievable with existing capacities and ensure that your work can be both complementary, inclusive of others and assist to identify the critical gaps in service provision.

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Examples of Stakeholders Private sector Stakeholders

Public sector Stakeholders Civil society stakeholders

Corporations and businesses Business associations Professional bodies Individual business leader Financial institutions

Ministers and advisors (executives)

Civil servants and departments (bureaucracy)

Elected representatives (legislature)

Courts (judiciary) Political parties Local government/councils Military Quangos and commissions International bodies (World

Bank, UN)

Media Churches / religions Schools and Universities Social movements and

advocacy groups Trade unions National NGOs International NGOs

In Darfur, the team carried out an initial stakeholder analysis of various stakeholders that had an interest in humanitarian objectives. The map was later used as a resource to identify key sources of primary and secondary data for the data gathering process.

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Quantitative Vs Qualitative Data

Below is a brief overview and explanation of the difference between quantitative and qualitative data collection. Quantitative Qualitative

Objectives Quantify Variation (produce figures) Predict Causal Relations Describe the Characteristics of the Population

Describe Variation Probe and explain relationships Describe individual experiences and group norms

Instruments and Question Formats

Rigid and highly structured, using methods such as questionnaires and surveys

Exploratory, flexible, iterative, using semi-structured methods, such as in-depth interviews, focus group discussions and observation

What type of Questions Close Ended Open Ended

Type of Data Numerical Textual

Degree of Flexibility Minimal – once the data collection tool is produced, very little change can be made. Questions are asked in the same way to every respondent

Iterative – data collection is adjusted according to what is learned, the order of the questions are flexible and participant responses can influence what the data gatherer asks next.

Type of Sampling Simple random sampling (SRS) Cluster sampling Stratified sampling

Quota sampling Purposive or Judgment sampling Snowballing

Context Analysis in DRC: Collecting Primary Data Training in PRA techniques (see Annex 3) was done prior to each piece of field work and tools were reviewed and changed depending on their utility. Tools which were used included; 24 hour clock, Harvard Task Analysis, Seasonal Calendar, Social Mapping, Market and Mobility Maps, Income and Expenditure Mapping, Key Informant Interviews and a mini-survey to look at land holding and use. All tools were used with separate groups of men and women to pick up gender differences. At the end of each day, findings were reviewed and methodologies adapted and changed as appropriate.

Selection of Sites for Primary Data Collection; The first stage in the selection process is to identify the population, the set of individuals or objects having some defined characteristic(s) – this could be the beneficiaries of a programme, or the villages in a particular area, for example; coastal, highlands, close to main road (note – the population is not always ‘people’). There are different approaches which can be used for the purposes of carrying out a contextual analysis, but you are likely to utilise a combination of purposive sampling and snowballing.

Purposive / judgement sampling; The selecting of sample units because of their particular features or characteristics which will allow you to explore specific issues. They may be members of a demographic group or representative of a particular location.

Snowballing; The practice of selecting samples of extreme poor groups or specific individuals as a result of introductions or recommendations by other participants, that have been interviewed by the team. (See Annex 7 for details of all sampling approaches).

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Quantitative and Qualitative Data Collection During a contextual analysis process you will be accessing both quantitative and qualitative data from secondary data sources. If you are carrying out primary data collection it is more likely to be qualitative in nature, using samples that are not intended to be statistically significant. This section does not deal extensively with data collection methods and analysis. For further information about this see the sections on Data Collection and Storage and Data Analysis and Use and the recommended tools at the end of the section. *If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Recommendations

Quantitative representation is not what you are after when collecting qualitative data. Think quality over quantity. You do not have to get data for every single permutation of disaggregation.

Collection of qualitative data needs careful thought and an understanding of the research methods used. Do not try to train the entire team in PRA methods, this is not something that can be done in a short training/over a short timeframe

Teams must build the space to reflect on any primary data that is being collected, ideally after each day spent in the field, and periodic longer periods of reflection e.g. a breaks after every

Expanding knowledge on important areas in Zimbabwe After initial work on a data gathering framework, Concern Zimbabwe spent 2 weeks developing background papers on different issues they had identified as important including; lessons from current projects and interventions, women and gender and building local institutions. They also visited other NGOs and projects who they thought were doing interesting work to see what additional data was available and what could be learned about interventions which worked.

Key Institutions at a local level: When collecting primary data don’t forget to physically visit and meet with staff and users of institutions at a district and community level to triangulate information e.g. Schools, health clinics etc.

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few days of data collection. Discussing the findings of meeting annotations can better reflect the richness of discussions. Feedback sessions should also be held with communities.

Step 6: Analysing the information. During data gathering, it is inevitable that some initial analysis will have taken place and the team will have started to form ideas for interventions. However it is important to set aside specific time in an analysis workshop for analysis of the data and to focus on this rather than jumping to the development of a programme.

How to do this? The 5 Key Questions are the primary basis for the analysis: 1) Who are the extreme poor in this context and where are they? 2) Why are they poor (immediate causes) 3) What keeps them in extreme poverty? 4) What opportunities are available to extremely poor people? 5) What needs to change – who is responsible4, what is already happening?

The additional questions below are more specific and might assist with detailed analysis of the data.

What assets do we need to increase in order to improve the wellbeing and livelihood security of the extreme poor?

What assets do the extreme poor have or could have access to that have low returns and how could we increase returns?

What are the major risks the extreme poor and poor face and what are their causes? How might they impact on proposed interventions and Concern’s work? How are people vulnerable to these risks and what should be done to reduce the risk and/or mitigate against the risks? How will risk and vulnerability to HIV be addressed?

What are the particular obstacles and barriers the extreme poor, and women in particular, face in terms of access and control over the assets they need for secure livelihoods, access to quality services, influence over decisions which affect their lives (consider accountability and influence in programme decisions and agreement on selection criteria) and in terms of discrimination or social exclusion? How do they need to be addressed for interventions to be successful and have sustainable and long term impact?

Identify who should be involved in the analysis workshop. It can help to bring in some ‘outsiders’ (e.g. staff from a different team, another NGO, civil society organisations, academics, etc) at this stage to present your findings to them and to justify your decisions. Beneficiaries and their representatives can also play an important role in validating information. They can play ‘devil’s advocates’ to really test you and make sure that your analysis is sufficiently robust. Use analytical frameworks such as the livelihood security framework, frameworks in the equality analysis toolkit and frameworks in the risk analysis toolkit. See “Resources & Tools” section Annex 3 for more information. In the Concern Planning Monitoring and Evaluation guide: Section 2.4 Data Analysis and Use details key steps to reviewing data. Question the data, find patterns/ trends/common themes, and check for contradictions. Are there any gaps in the information or do you have to collect more? Have you used the three lenses to

4 This requires an identification of duty bearers, with a focus on governance and sustainability.

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thoroughly examine the table (Lack of and / or low return on basic assets, inequality, and risk analysis)? By now you should be able to answer the ‘5 key questions’ and have solid evidence for each answer. Document what you have done. Back up your claims/ conclusions with the evidence. If you recognise a gap then make a plan to fill it. If you are finding analysis difficult you may want to revisit the conceptual paper “How Concern Understands Extreme Poverty”.

Description of the extreme poor: It is useful at this stage to try and describe the extreme poor based on the characteristics that you have found to be important. This description will ensure that the interventions and targeting you develop subsequently are appropriate. To be sure that you are satisfied with the groups you have ended up with, take another look at the data and analyse it carefully. Look for overlaps between groups, compare the issues they face, and capacities of each group, as well as what support these groups receive (e.g. from government, civil society, other NGOs).

Recommendations:

It can be good to revisit the stakeholder analysis at this stage and review who is doing what in the proposed area of intervention, this is important when starting to propose programme options

Analysis of data can be very time consuming – it has been suggested by facilitators that if there were to allocate more time to any single phase it would be here!

How to Describe the Extreme Poor; experiences from Zimbabwe and DRC Concern Zimbabwe found two different clusters of extreme poor people:

Adults who are either elderly or disabled or households of orphans who make up about 5-

10% of the total households. It is difficult for them to move out of extreme poverty and they might require long term social protection.

About 10-15% of households are without productive assets or food stocks but have labour power and are caught in a cycle of low paid casual work. They could move out of extreme poverty with appropriate support and if they could avoid shocks.

In DRC, poverty is related to conflict and displacement so their descriptions were very different: Insecure: a high threat of banditry and pillaging and various armed groups who put pressure

on the local community. Large numbers of recently displaced people who are without basic livelihood assets.

Medium security threat: infrequent banditry with fluid communities, a mix of recent and long term displaced as well as returnees. Large farms and more subsistence agriculture.

Secure: communities have experienced a wave of returns and there is a mix of local people and long term displaced. There are a number of big farms under pasture and tension over land. There is an accumulation of livelihood assets.

Deepening the Analysis of Poverty in Cambodia Having completed an initial analysis of context, Concern Cambodia realised they needed to go back and collect the same kind of information for specific groups of people; households dependent on wage labour including landless households, women headed households and smallholder farmers with less than 1Ha of land. They therefore had to initiate a second phase of context analysis.

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Step 7: Identify Programme Options At this stage you need to put forward ALL of the potential programme options in the context explored. You should have the answers to the five key questions which should inform the programme options. You should specify the target group(s) identified and directly address the problems they face. Potential options should address the immediate and root causes of the problems and take into account who is responsible for (causing and/or solving) these problems (from your wider contextual analysis), what others are already doing (from your stakeholders’ analysis) and the resources and skills available to Concern and partners. For more information on how to set objectives and think through possible interventions see Objective Setting, Chapter 2.2, in the PM&E Guide. Once all options are presented you will need to analyse them further and present a filtered overview of programme options that you are going to explore, giving clear rationale for your choices. This rationale will be based on but not limited to:

Concern’s own competencies and sectors of focus as set out in policies and strategies. The humanitarian imperative – does this intervention save lives and alleviate suffering? The likely impact of the intervention, how effective it will be in making a change in the

lives of the extreme poor and whether the change will be sustainable. The efficiency and cost benefit of the different interventions and the distribution of

benefits amongst the extreme poor.

Recommendations: Engage with Overseas and SAL at this juncture, to assist with pulling options for the analysis and

problems trees. All programme options should be presented here, not just filtered options.

These steps are built on in the Programme Development Guide. The team/consultant should be careful in ruling out options at this stage; all options should be carefully

thought through. Step 8: Summarise your findings in a concise form in a contextual analysis report. A template for the format of the contextual analysis report is attached in Annex 8. Keep the report short and focused and include:

An explanation of who was involved in specific parts of the contextual analysis. This should discuss which beneficiary representatives and community members were involved, how, when and why, as well as explaining who was not involved and why.

Answers to the five key questions, each backed up with evidence. This should demonstrate how you have taken into consideration risks, livelihoods strategies, inequalities, and, basic assets and returns on these assets.

An outline of the different programme options which might be appropriate with a rationale.

Important data can be annexed.

The contextual analysis report will be the basis for management decision making and approval for PCN(s) development. The contextual analysis report has to be approved by the Regional Director before the team begins to develop the PCN (s). The contextual analysis report should be

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annexed to PCNs when sending to the relevant Dublin desk. A contextual analysis could result in more than one PCN; a variety of programmes might suggest themselves from one contextual analysis. The final report can also be used to distribute findings/plans to partners and other stakeholders. It is important to type up and compile and field notes on a daily basis, organised in line with the key questions being explored during the primary data collection phase. Organised data and notes will assist you during the analysis of data and for use in programme design.

Key things to remember

Contextual analysis should look at the three key factors that determine extreme poverty: lack of and/or low return on basic assets, inequality, and, risk and vulnerability.

Contextual analysis is not the same as a baseline – it comes at the very beginning of the programme cycle and is used for providing programme options and to inform the inital setting of objectives. A baseline comes after the programme has been designed during the start up phase, and a logical framework is in place where key indicators are measured.

By sticking to the key questions to be answered you should avoid unnecessary data gathering; always ask yourself, “will this information help to answer these key questions” ?

The most important opinions in the process are those of intended target populations and their representatives. When working in partnership, contextual analysis should be done with partners or potential partners as far as possible.

The Secondary Data review phase is a key step in the contextual analysis process. It is secondary data which will provide most of the information for the CA, with some primary data to validate or fill in gaps in the secondary data. The gaps identified will assist you in developing your primary data questions. It is important to invest sufficient time at the beginning of the processs on secondary data collection and analysis.

Contextual analysis does not require detailed analysis and planning in all target communities but some level of primary data collection is highly likely. A more detailed planning process should happen after programme approval in order to avoid unfulfilled expectations and create additional buy in when funds have been approved/received (See Section 2.8 of the PM&E Guide on Community Planning).

Be cautious of jumping to conclusions too rapidly without taking time to analyse and reflect on the data collected, as this is the most common error made in contextual analysis. The result is that programmes may only replicate interventions familiar to the team rather than seek to address poverty as experienced by the extreme poor.

Some challenges to keep in mind “People often jump ahead to conclusions and strategies looking for their own focus – it is difficult to be objective. We tend to fall back on what is familiar to us and therefore come up with the same old interventions.” Be aware of the potential for bias according to staff and partners’ previous work and own interests. It is very easy to draw conclusions that fit with work that you have already been doing or that you are familiar with. Make it clear that you are looking for impartial analysis; and make sure that any decisions you make (i.e. about target groups, about possible interventions) can be backed up with evidence. Evidence based decision making should prevent people from falling back into their ‘comfort zones’. “We don’t always have the skills needed to do this level of data collection and analysis. We are not very good at analysing or interpreting data.”The ability to analyse, and interpret the data and the ability to facilitate such a process is critical. If you don’t have a good person in-house with highly developed analytical and facilitation skills then get someone in! The facilitator should promote ownership of the process and findings within the team. S/he can provide skills where necessary, but

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s/he should be building the capacity of the team wherever possible. Note that this might take longer but the long-term benefit will be a better programme with skilled staff. “Involving partners is risky – we might decide later we don’t want to work with all of them.”Partnership agreements do not have to be made for all partners at the beginning of the process – some can be involved as potential partners. The process could be demanding for small partners. If they have to commit a lot of time you might consider a short term funding agreement for them to support the contextual analysis in the capacity of a consultant. This will also help to ensure that the partner makes available staff with appropriate ability. See also section 1.6 in the PM&E Guide on PM&E with Partners. “Donors tend to ask for proposals at very short notice. We don’t always have time to do a proper contextual analysis.” Contextual analysis is part of the programme cycle; to this end, it should be done regardless of donor proposals – to inform programmes that may be funded through a variety of donors. In addition, the conclusions of the contextual analysis need to be revisited periodically (preferably at least annually) during the life of the programme to see what has changed and to update the contextual analysis as appropriate; information collected through monitoring and evaluation can be valuable here. So each programme should always have an up to date contextual analysis that can be used for donor proposals.

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Annex 1 :

Framework for guiding data gathering

Situation in the wider community

Specific Impact groups in your context e.g. Elderly, Orphan headed household, specific ethnic group…

The impact / effects of policies, institutions and processes on the Extreme Poor groups

Highlight Questions for further exploration either Secondary or Primary

Questions to be answered by the Contextual Analysis General Male Female

ASSETS & RETURN ON ASSETS (1) What assets do they have? (2)What basic assets are lacking? (3) What are the benefits derived from these assets and are returns limited? Why? (4) To what extent do they have voice / control over these assets? How? Why? (5) What assets exist that are not being used by the extreme poor and why?

Natural (land, forest, marine and wild resources, water, air quality, biodiversity and rate of change)

Physical (transport, shelter, buildings, water supply and sanitation, energy, tools)

Financial (income, savings, credit, remittances, cash transfers, welfare, pensions, liquid assets e.g. livestock)

Human (skills, knowledge, ability to labour, health)

Social (networks, kinship systems, support mechanisms, relationships of trust, reciprocity and exchange)

Political (make up and capacity of civil society, formal and informal groups or associations, local government structures and accountability, links to governance structures, influence, participation in decision making)

LIVELIHOODS STRATEGIES (1) What are the main Livelihoods Strategies within these groups? What are the returns from these strategies? (2) What other strategies could be available and why are they not used? (3) How are markets linked to livelihood security? What is the status of markets? (4) Are there any potential opportunities for engagement with the private sector

ACCESS TO (QUALITY) SERVICES (1) What services are relevant to them? Why? (2) To what extent do they have access to these services? Why / why not? (3) To what extent do they have voice / control over these services? Can and how do they participate?

RESPECT, RECOGNITION & VOICE (1) Do they have representation at local & National Government either directly or through CSOs? (2) What cultural practices impact the lives of these groups? Do they experience social stigma, discrimination or exclusion? How does it affect their lives? (3) What are their valued livelihood outcomes?

GENDER Specific issues related to gender inequality (gender roles, relations, GBV etc.)

HAZARDS AND RISKS: (1) What are the main hazards, what causes them, what are their impacts, and where and when do they occur (natural and human-made, including HIV)? (2) What are the felt and predicted impacts of changes

in the wider context (climate change, food and fuel prices, politics and conflict etc) (3) What are the key risks (impact vs. probability)? What are the extensive risks? Include HIV.

VULNERABILITY: (1) Who, and what (assets) are vulnerable to these risks? (2) Why are they vulnerable?

CAPACITY: What assets are available for use in responding to disasters (institutions and communities)?

What are the coping strategies of the vulnerable people?

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Annex 2 Narrative explanations of the key components of the framework for guiding data gathering

Policies, Institutions and Processes (PIPs): At the Macro, Meso and Micro levels, includes the social, political, economic and environmental factors that determine; access to assets, choice and returns to livelihood strategies, sources of influence and the terms of exchange between different assets. These include; institutions and organisations (both public and private sector), services, policies and legislation and socio-cultural practices and norms. They also include the market. For each area in the Data Gathering Framework it is important to identify and analyse the relevant policies, institutions and processes at the different levels of Macro, Meso and Micro; what exists, what are the features and functions of importance to the extreme poor and how well is it performing or being implemented (in terms of policy). This analysis should help you identify both the extent to which duty bearers are or are not fulfilling their duties as well as where Concern or partners might be able to influence this. When thinking about the extent to which PIPs are not fulfilled, ask whether this is due to a lack of political will, or a lack of resources or expertise. The intervention required will be different depending on this.

Assets Within How Concern Understands Extreme Poverty, assets are classified as the range of assets to achieve positive livelihood outcomes; no single category of assets on its own is sufficient to yield all the many and varied livelihood outcomes that people seek. This is particularly true for the extreme poor whose access to any given category of assets tends to be very limited. As a result they have to seek ways of nurturing and combining what assets they do have in innovative ways to ensure survival. In defining extreme poverty as opposed to poverty, it is essential to show what is unique to it. What is unique to extreme poverty is the lack of basic assets and/or the low return to these assets: this is the first and core dimension of Concern’s definition of extreme poverty. .

The various assets are Natural, Physical, Financial, Human, Social and Political. Natural Assets are the resources such as water, land, forest, wildlife and other environmental sources useful for livelihoods. Physical Assets include housing (shelter, water supply, transport, communication methods and production equipment and means which enable people to pursue their livelihoods Financial Assets are made up of Income, savings, credit, pensions, salaries or regular remittances, liquid assets such as livestock. Human Assets represent the skills, knowledge, education, ability to labour and good health that together enable people to pursue different livelihood strategies and achieve their livelihood objectives. Social Assets are the networks; kinship supports mechanisms, relationships of trust, reciprocity and exchange. Political Assets relate to the make up and capacity of civil society, formal and informal groups or association, local government structures and accountability, links to governance structures, influence and participation in decision making. Analysis of assets includes identifying what the extreme poor already have but also looking at what other assets there are which are or could be used but are not available or are underused by the extreme poor. Return to assets is an important focus of analysis

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so it is important to ask, for example, what prevents people getting a good wage for their labour, a good price for their produce or a high yield from their land and what opportunities exist to transform this situation? Livelihoods strategies Livelihood strategies are the range and combination of activities and choices (including productive activities, investments, reproductive choices etc.) that people make in order to achieve the livelihood outcomes they value. These strategies include short term considerations such as ways of earning a living, coping with shocks and managing risk, as well as longer term aspirations for children’s futures and old age. Analysis of livelihood strategies involves understanding what people currently do as well as exploring what opportunities and alternatives exist in the context. It is essential at this point to carry out a market analysis (need reference to a tool). The private sector may play a key role in expanding livelihoods opportunities for the extreme poor so it is important that you aware of and engage with them to build up this understanding in your particular context. Equality Equality is a human right. The Universal Declaration of Human Rights states in Article 1 that ‘all human beings are born free and equal and dignity and rights’, that ‘everyone is entitled to all the rights and freedoms set forth in the Declaration without distinction of any kind, such as race, colour, sex, language, religion, political or other opinion, national or social origin, property, birth or other status’ and that ‘all are equal before the law and are entitled without any discrimination to equal protection of the law’. However, everyone lives in unequal societies in an unequal world and equality is a multi-dimensional concept. Concern’s interest lies in how inequality intersects with extreme poverty. How inequality creates and furthers the condition of poverty and prevents people taking opportunities to better their lives and improve their livelihoods.

The emphasis must be on the specific dimensions of inequality that creates and maintains a condition of extreme poverty in the contexts where Concern works. The most obvious manifestation of inequality is extreme poverty itself; however the condition of poverty and extreme poverty is not experienced in the same way by all. Just as geographic targeting recognises that people are poorer in certain places, it is vital to recognise that what keeps people in extreme poverty and what prevents them getting out can differ according to social characteristics such as gender, caste, ethnicity, physical impairments such as ability, HIV status and age. Within the group of people identified as extreme poor there may be significant differences Through disaggregation, an initial analysis of inequalities will be embedded in the contextual analysis. However it is important to note: The assets available to different groups of people amongst the extreme poor will differ as will the return to assets. It is important that disaggregated information is collected about assets and that the barriers (institutional and social) and opportunities to access and control assets are identified.

Often the extreme poor are forced to adopt livelihood strategies which are marginal or which have a very low return on labour, for example sex workers, migration and child

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labour. A full understanding of why these strategies are being pursued and the obstacles to adopting more advantageous strategies is needed for contextual analysis.

The quality of service provision, access to services and influence over the implementation of services is rarely egalitarian. Men and women who are extremely poor may be excluded on the grounds of geography (distance from the service), livelihood (for example nomadic pastoralists) and ethnicity, for example. These specific obstacles must be identified as part of contextual analysis.

Having influence over decisions which affect your life is a powerful tool in development and emergency contexts. Therefore it is critical to understand who has respect, recognition and voice. Who speaks in local development councils, who can advocate to government, whose opinions are valued and what is the impact of discrimination and stigma on the lives of extreme poor? Also, it is important to identify which institutions exist that have the potential to represent the interests of the extreme poor. We need assurance that the voices from the community are also representing the most vulnerable – therefore triangulation and random interviewing is key.

Gender Inequality: “Gender is the most fundamental organising feature in all societies and as such affects the entire population5” There can be no dispute over the fact that women are disproportionately represented amongst the extremely poor or that gender inequality is a reality in almost every country in the world. Gender inequality comes about because of the differences between what is expected, allowed and valued from men and women in a given society at a particular time. In general, this places women at a disadvantage in terms of their expected roles, their access to and control over resources and their decision making potential. So, while women themselves are a major target group for Concern’s work, it is issues of gender inequality that contribute to their poverty and prevent them moving out of poverty. Addressing gender inequality necessarily involves looking at both men and women as transformation of male and female gender roles is required to address some of the issues discussed below Specific gender issues, for example gender based violence may need to be elaborated and captured separately.

Risk Risk is defined as the magnitude of the impact combined with the probability of a hazard occurring. The magnitude of impact is a function of the scale of a hazard and the vulnerability of the individual members and families of the affected population. Vulnerability is the susceptibility of people and their assets to damaging events, related to their ability to anticipate, cope with and recover from disasters. Concern sees hazards as wider than just natural hazards (geological, hydro-meteorological and biological which includes HIV); we also consider human-made hazards – political (some types of conflict, policy related hazards derived from no policies, non-enforced policies, and bad policies or development practices), economic

5 Concern Equality Policy, 2005

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(inflation, rising prices of essential commodities etc) social (including crime, GBV, marginalisation etc), and technological (industrial, infrastructure failure etc). Understanding risk analysis involves identifying the hazards that the extreme poor and communities face, understanding the probability of these hazards occurring (by examining their location, seasonality, frequency and trends), and identifying what the causes and impacts would be. In a rapidly changing world, we must also monitor, analyse and be able to anticipate the effects of changes in climate, food and fuel prices, politics, population dynamics etc. Concern is interested in more than just the large-scale high impact disasters (known as intensive risk); we also have a focus on extensive risk, which are small-scale and localised events, often with small impacts, but capable of affecting a relatively high proportion of a poor families total assets, and happening very frequently. Examples of extensive risks include landslides in farming areas, seasonal run-off and crop diseases. Because they are so frequent, these risks can be highly corrosive to assets and are an important factor in keeping people poor. Be aware that there may be some risks that are not perceived to be important by the wider community, but that affect some portions of the community differently – for example HIV. There may also be risks that are known and understood by some members of a society (for example scientists) but not the communities we work in, as they may have been communicated badly. We cannot rely just on information from one source (like the extreme poor); we must collect information from multiple sources; as an international NGO we have access to knowledge and practise from elsewhere that we can include in the analysis. It is important to identify whether there are differences in the risk of a hazard occurring, the likely impact or the capacity to deal with this risk amongst the different groups that make up the extreme poor. You should also think about whether there are any groups you have missed that might be particularly vulnerable to risk but that are currently not included in your list of groups. Equally, you might find that there are certain risks that some group(s) face that are a priority risk amongst the wider community, for example HIV. These risks should be analysed for these groups. Vu Vulnerability Vulnerability is extremely specific; and vulnerability differs according to numerous factors including geographical location, poverty, inequality, gender, age and access to and return from assets. Even extremely large disaster events affect different people in different ways, so our identification of who are relatively the most vulnerable must be specific and disaggregated at least according to sex, age and location. You should also think about whether there are any groups you have missed that might be particularly

Who do we target? The importance of thinking about risk in Concern Zimbabwe After undertaking their context analysis, Concern Zimbabwe found that in the context of the Gokwes; there was a strong case to work with both the extreme poor to enable them to get out of poverty and with the poor to prevent shocks edging them into extreme poverty

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vulnerable to certain risks but that are currently not included in your list of groups. An example could be people not categorised as extreme poor but who live in the pathway of a major hazard. Beyond who is vulnerable, we must also identify what is vulnerable: the assets that are important to the livelihoods of the extreme poor. To complete an analysis of vulnerability we also need to know why they are vulnerable – what are the assets that are lacking, that make people vulnerable? Capacity Capacity is the ability to do something – in this context, to help communities manage the different aspects of risk they face and safeguard their lives, health and assets, in order to underpin and strengthen sustainable development activities. Capacity to anticipate, cope with and recover from disasters is related to availability and access to assets, including awareness and knowledge, early warning and appropriate preparedness plans. When thinking about capacity, don’t just think about the group’s or community’s capacity but also think about the role of potential partners (including Concern and the government) and civil society play in this. Who is responsible for decreasing this risk and what are they doing about it? For example, if a group is at risk of flash flooding, is this partly because of poor environmental management of the upper watershed, insufficient infrastructure to deal with heavy run-off or a lack of cleaning and maintenance of the drainage system? If so, what is being done or who needs to be engaged to address this?

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Annex 3 : Resources & Tools: this relates to Step 6: Analysing the information. The table below summarises recommended resources and tools for data gathering and analysis. They are all available on the Concern Intranet. Your choice of tool will be determined by the kind of data you require, who it is being collected from and the amount of analysis and discussion that is needed to get answers to your questions. Many of the tools are for primary data collection and for use within the community and at a local level. The notable exception is the “Information sources for contextual analysis” which were compiled by SAL advisors and highlight good potential sources of secondary data. The compendiums of tools can be used interchangeably and it is often wise to use tools which members of the data collection team are familiar with, are tried and tested or which they can receive training in. *If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Area of data collection Recommended Tools and Methodologies (available on intranet) Assets and return on assets

Livelihood Assessment Resource Pack, SAL, 2007 Livelihoods Connect Portal for an explanation of terms and related tools and approaches.

Risk and Vulnerability Approaches to Disaster Risk Reduction, Emergency Unit, 2005 Community Risk Assessment Toolkit http://www.proventionconsortium.org/?pageid=39 (ProVention Consortium) Livelihoods Connect Portal for an explanation of terms and related tools and approaches.

Access to quality services

Secondary Sources for Context Analysis, SAL, 2010

Respect, recognition and voice

Local Institutions and Livelihoods, Guidelines for Analysis, Module 5, FAO

Wider Context/Secondary Data Sources Secondary Sources for Context Analysis, SAL, 2010 Gender Equality Analysis Resources, SAL, 2008

Compendiums of Tools for PRA/PLA

Tools Together Now: 100 Participatory Tools to Mobilise Communities for HIV/AIDS, International HIV & AIDS Alliance, 2006 - http://www.aidsalliance.org/includes/Publication/Tools_Together_Now_2009.pdf

Making Sense of Focus Group Findings, AED - http://www.globalhealthcommunication.org/tools/62 International HIV & AIDs Alliance: Tools Together Now: 100 tools for PLA -

http://www.aidsalliance.org/publicationsdetails.aspx?id=229 IIED: PLA A Trainers Guide IFAD Guide on M&E Annex D - http://www.ifad.org/evaluation/guide/ Help Age International: Participatory Research with Older People -

http://www.helpage.org/resources/publications/ Help notes for problem analysis Help notes for dreams and visions Help notes for mapping Overview of PLA

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s). Where to go for more information For some detailed examples of contextual analysis in an area based programme, the following documents can be found on the

intranet: Case study: Urban Programme Framework – Contextual Analysis and Targeting, Concern Bangladesh, 2008 Contextual Analysis Report, Masisi DRC. February 2011 Contextual analysis and Options for the Extremely Poor in the Gokwes. September 2010. Contextual analysis: Secondary Data Review and Analysis, Emma Bradley for Concern Rwanda, March 2011

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Annex 4 : Some Suggested Sources of Secondary Data for Context Analysis Planning: general and sector specific data sources: this relates to the list of secondary data sources which Concern technical advisors have compiled which is is a good starting point for finding information, and relates to Step 4 & 5 :Data Gathering and Analysis Phase 1 & 2. Internationally comparable sources of data (General): These help to (a) compare one country to others in the region and (b) compare from two points of time, giving an indication of whether things have been improving or getting worse. Some also include country specific reports in the annexes. *If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Description Data Available on Description Weblink Human Development Report

In addition to the HDI and GII, the HDR contains data on a variety of indicators which could be used to develop our own index, particularly interesting ones:

Produced by UNDP and published on an annual basis in the HDR. Data available for most of our countries, also shows historical trends. Data generally checked and verified by UNSD

http://hdr.undp.org/en/media/HDR_2010_EN_Complete_reprint.pdf Country specific data can be downloaded from http://hdr.undp.org/en/data/profiles/

Human Development Index - calculated using: Life expectancy at birth: UNDESA Mean years of schooling: Barro and Lee Expected years of schooling: UNESCO Gross national income (GNI) per capita: World Bank and IMF Gender Inequality Index - calculated using Maternal mortality ratio (MMR): Unicef Adolescent fertility rate (AFR): UNDESA Share of parliamentary seats held by each sex (PR): Union’s Parline database (2010) Attainment at secondary and higher education (SE) levels: Barro and Lee Labour market participation rate (LFPR): ILO

Global Hunger Index Calculated Using Proportion of undernourished in the population (%) Prevalence of underweight in children under five years (%) Under five mortality rate (%)

Produced by IFPRI, WHH and CW Data available for most of our countries, also shows historical trends.

http://www.ifpri.org/publication/2010-global-hunger-index

MDG Progress Index Contains specific data on the following: % of population without access to improved water source Prevalence of HIV (in population 15 – 49 years) Maternal Mortality Ratio (per 100,000 live births Under-5 Mortality Rate (per 1,000) Ratio of Girls to boys in Primary and secondary education Primary completion rate Prevalence of undernourishment (% of population) Proportion of population below $1.25 per day

Centre for Global Development Use data primarily from the World Bank World Development Indicators and the Lancet articles on MMR to develop an MDG progress score. – could be good to use this, but avoid double counting

http://www.cgdev.org/content/publications/detail/1424377

Website with a lot of data available in the form of an interactive map

http://www.mdgmonitor.org/map.cfm?goal=0&indicator=0&cd=

World Development Report

Population below poverty line -Based on World Banks International Poverty line of $1.25 per capita – has the advantage of being comparable across countries (if country’s own line is used, o guarantee the measure in country X is the same as in country Y).

World Bank http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTWDRS/EXTWDR2010/0,,menuPK:5287748~pagePK:64167702~

Income per capita Gross National Income (PPP) per capita The World Bank has a variety of data available on a number of other indicators at its Poverty Reduction and Equity page as well

World Governance Indicators

Contains a single point score for six different elements of governance Voice and Accountability; Political Stability and Absence of Violence; Government Effectiveness; Regulatory Quality; Rule of Law; Control of Corruption.

Brookings Institute and World Bank, published on an annual basis, with data going back a number of years. Is an index of indices – use is strongly favoured by the MCC (has advantage of utilizing FHI, BTI, CPIA and putting in one place) Data available for all of our countries

Global Gender Gap The Index benchmarks national gender gaps on economic, political, education- and health based criteria, and provides country rankings that allow for effective comparisons across regions and income groups, and over time. The rankings are designed to create greater awareness among a global audience of the challenges posed by gender gaps and the opportunities created by reducing them. Includes a country profile

Produced by the World Economic Forum

Ease of Doing Business Index

A simple average of country rankings for 10 indices aiming to measure how easy it is to open and close a business, get construction permits, hire workers, register property, get credit, pay taxes, trade across borders and enforce contracts. The Report also contains an individual country profile, with an indication of trends.

Produced by the World Bank. Collects its own data from 8,000 country informants (KIs), and is produced for 183 countries. Data available over a number of years.

Index of State Weakness in the Developing World

This index uses 20 economic, political, security and social welfare indicators to provide an aggregate rating.

Brookings Institute Contains meta-data on the indicators used, not sure it is going to be updated on a regular basis.

Failed States Index Contains scores for a variety of measures of governance Demographic Pressures / Refugees / IDPs / Group Grievance / Human Flight /

Uneven Development / Economic Decline / Deligitimisation of the Sate / Public Services / Human Rights / Security Apparatus / Factionalized Elites / External Registration

Foreign Policy (Journal) – I am not familiar with this one up to now – has annual data on their website from 2007 to 2010.

Country Indicators for Foreign Policy

Contains four individual scores for Fragility Authority Legitimacy Capacity

But does not include a summed amount

Carleton University

Social Institutions and Gender Index

Contains five individual; scores that can be used to vary Family Code Civil Liberties Physical Integrity

Done by team at University of Gottingen, based on data available from OECD.

Son Preference Ownership Rights

Also produces a single figure score, which has been included Natural Resource Management Indicator

The Natural Resource Management Index (NRMI), 2010 Release is a composite index for 157 countries derived from the average of four proximity-to-target indicators for eco-region protection (weighted average percentage of biomes under protected status), access to improved sanitation, and access to improved water and child mortality.

The dataset is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Yale Center for Environmental Law and Policy (YCELP), Yale University. To assist in the country selection process for the Millennium Challenge Account by providing indicators of natural resource management that complements the governance, social, and economic indicators.

Environmental Performance Index

A composite of 25 component series grouped under 10 headings – climate change, agriculture, fisheries, forestry, biodiversity and habitat, water (2), air pollution (2) and the environmental burden of disease. The 2010 Environmental Performance Index (EPI) ranks 163 countries on 25 performance indicators tracked across ten policy categories covering both environmental public health and ecosystem vitality. These indicators provide a gauge at a national government scale of how close countries are to established environmental policy goals.

Columbia and Yale Ranks 163 countries

Emergency events database

The main objective of the database is to serve the purposes of humanitarian action at national and international levels. It is an initiative aimed to rationalise decision making for disaster preparedness, as well as providing an objective base for vulnerability assessment and priority setting. EM-DAT contains essential core data on the occurrence and effects of over 18,000 mass disasters in the world from 1900 to present. The database is compiled from various sources, including UN agencies, non-governmental organisations, insurance companies, research institutes and press agencies. Specifically groups them by:

Complex Disasters / Drought / Earthquake (seismic activity) / Epidemic / Extreme temperature / Flood / Industrial Accident / Insect infestation / Mass movement wet / Miscellaneous accident / Storm / Transport Accident / Volcano / Wildfire

WHO Collaborating Centre for Research on the Epidemiology of Disasters (CRED) has been maintaining an Emergency Events Database EM-DAT. EM-DAT was created with the initial support of the WHO and the Belgian Government.

Financial Access Deals with issues of financial inclusion on a number of fronts (commercial banks, micro finance institutions)

World Bank

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

General Country Documents (including National Legal and Policy Frameworks) Data Available on Source

Poverty Reduction Strategy Paper (may have a specific name in a local language, or be called a National Development Plan) – these should be available from the Ministry of Finance and / or Planning, but can also be downloaded from

World Bank

The World Bank has supported a series of Poverty Assessments through their Poverty Reduction and Equity group; these are not updated on an annual basis but provide a good overview of available data and information

World Bank

Millennium Development Goals Progress Reports are generally obtainable from the UNDP country office, but can also be downloaded

UNDP

National level Human Development Reports are available from the UNDP website UNDP

The Economist Intelligence Unit (EIU) provides annual and monthly updates on both political and economic developments in a country – available from (this is subscription based, but Concern has a corporate subscription to this – contact PALU in SAL if you are having difficulties downloading the most recent report)

Economist Intelligence Unit (EIU)

Up to date country population estimates are available at the United States Census Bureau website (these may be more up to date in terms of projections than those available in country as they are being re-estimated on a regular basis), however, for a more detailed regional level breakdown of population, this will have to come from C/NSO.

United States Census Bureau

All national (or Central) Statistical Offices will have a variety of reports for a specific country

Government publication offices will have a variety of other documents such as the constitution

The US Central Intelligence Agency (CIA) and the US State \department have background or information notes on a variety of countries

Country profiles DFID

USAID

European Union

There will also be good information on the implementation of the Convention of the Rights of the Child (CRC)

UNICEF Annual “State of the World’s Children report and statistics

UNHCR & UNICEF

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Sector Specific

Health – Country and Sector Specific Data Description Data Available on Source

Various reports from Unicef on Maternal and Child Health

State of the World’s Children Unicef Multi Indicator Cluster Survey (MICS Unicef Unicef special 2009 publication (not periodic) Tracking Progress on Child and Maternal Nutrition (this remains usable for approx until 2012)

Unicef

World Health Statistics

The WHO have a variety of reports available, including an annual statistical report, however their website allows for individual country information to be identified on a number of key indicators, including

Mortality and health status - Mortality and burden of disease , Life expectancy; Mortality and death registration

Diseases - HIV/AIDS; Tuberculosis Coverage of services - Immunization; Maternal and newborn health Risk factors - Alcohol; Nutrition; Overweight and obesity; Tobacco Health systems - National health accounts; Health workforce

WHO

Demographic and Health Surveys

The Demographic and Health Survey cover a variety of years and countries. Generally the most reliable source of data in country for health, and are often used for updating other data (such as the population projections)

Measure / Macro (with USAID)

State of the World’s Mothers

Save the Children

Nutrition Information in Crisis Situation

Nutrition Information in Crisis Situation (NICS) (formerly RNIS) – results of past surveys in sub-districts different countries on Nutritional Status

UN Standing Committee on Nutrition

Humanitarian Dashboard

In preparation: (Global Clusters): this will be a good overview of basic statistics relevant to emergency situations, including health No source yet and no date when this will be finalised (as of July 2010)

OCHA

Integrated Food Security Phase Classification

The Integrated Food Security Phase Classification (IPC) is a standardized tool that aims at providing a “common currency” for classifying food security. Using a common scale, which is comparable across countries, will make it easier for donors, agencies and governments to identify priorities for intervention before they become catastrophic.

Policies, Strategies and Plans

National Ministry Website or general government website Ministry of Health (MOH): health related policies/ strategies/ plans; indicator performanceNational Bureau of Statistics: latest census and other surveys for e.g. sex/age break down for administrative areas, % children under five years of total pop, etc.

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s). See also information in the Global Hunger Index (described in the first section) There are a number of reports included on the (or Concern intranet: http://intranet/Programmes/Health/default.aspx - go to ‘Key documents’)

Education – Country and Sector Specific Data Description Data Available on Source

Country Education Statistics

Disaggregated data (to provincial, regional or district level) will only generally be available in country. This should be available from wither the Ministry of Education or the Central / National Statistical Office.

Ministry of Education / Central Statistical Office

Nationally comparative figures on an array of indicators Comes from the fast track initiative site

Education for all Global Monitoring Report and an interactive data set on a variety of indicators such as Enrolment, repetition, dropout, literacy

Variety of education statistics presented at a number of UN sites

Gender comparisons for education indicators

Available at national level for a variety of indicators (enrolment, literacy, completion, expected years of schooling, number of teachers)

Country Education Plans

National Education Plan

Country Reports on Education

International Conference on Education (ICE) countries presents a National Report on the Development of Education. Hosted by UNESCO

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Food Incomes and Markets – Country and Sector Specific Data

Description Data Available on Source Economic (General) Full economic overview of every country with comparative economic indicators and basic

country data (GDP, exchange rate, consumer price index, income, fiscal indicators) Economist Intelligence Unit

Consumer Price Index – disaggregable by food and non-food price trends (inflation, but also provide seasonal information)

National Statistical Office

Agriculture General Information on Agriculture and Agricultural Production – this is more detailed for some countries where there is a further breakdown of data The State of Food and Agriculture is the FAO’s annual flagship production There is also a country level profile

Food and Agriculture Organisation (of the UN)

Contains country specific reports on a monthly basis for a number of countries we work in, this includes identifying areas of the country which may prove to be insecure, and trends in the prices charged.

Famine Early Warning Systems Network (supported by USAID)

Rural Poverty – description and overview of make-up of the agriculture system in the country

IFAD

National and disaggregate figures on agriculture from the Ministry of Agriculture and the National / Central Statistical Office

Water Global Water and Climate Atlas (IWMI) - The IWMI World Water and Climate Atlas gives irrigation and agricultural planners rapid access to accurate data on climate and moisture availability for agriculture

Microfinance Institutions

Contains information on microfinance service providers by country, including loan portfolio and number of active borrowers.

Microfinance Information Exchange

Labour ILO statistics and databases – LABORSTAT International Labour Organisation (ILO)

Natural Resources EarthTrends (by Ecosystem and country)

Infrastructure Asia and Pacific Country Infrastructure reports (UNESCAP)

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Equality (incl. Gender and GBV) – Country and Sector Specific Data Check also the data on the gender related indices highlighted in the section on internationally comparable data. Where possible, all data should be disaggregated on a gender basis.

Description Data Available on Source Women in government Inter parliamentary Union Women and land rights (Gender and Land Rights Database) FAO Mandate and capacity of police, health service and judiciary to respond to GBV (On the

left side go to questionnaire and choose your country from the drop-down menu) UN study on violence against children

Social Institutions and Gender Index

GBV incidence, cases, implementation of laws - look up specific country profile OECD

Gender Assessment Country report available for most countries USAID

Child Rights Information Network

Child protection reports and programmes

Report on Beijing Platform for Action Type: ‘(your country) progress on Beijing report’ into the search box.

CEDAW Convention on the Elimination of Discrimination Against Women (CEDAW) – should look at both the country reports and the shadow reports

On-line reports and research

Eldis gender: : http://www.eldis.org/gender Siyanda: http://www.siyanda.org

National Plans National gender plan or strategy to combat GBV – can be available from Government publications

Legislation Legislation covering gender based violence can be downloaded from the OECD / SIGI site for a specific country profiles

OECD

There is also information available on the UN Secretary General’s Violence Against Women (VAW) website

UN

Legislation and policies related to child protection (children’s act) Convention on the Rights of Persons with Disabilities (CRPD) UN Enable

*If you do not have access to Intranet, please ask the Desk Officer to forward you the relevant document(s).

Risk and Vulnerability – Country and Sector Specific Data

Description Data Available on Source Country disaster profiles preventionweb http://preventionweb.net/english/countries/africa/

Country HFA progress reports: preventionweb http://preventionweb.net/english/hyogo/gar/2011/en/hfa/r

eports.htmlhttp://preventionweb.net/english/hyogo/gar/2011/en/hfa/viewer.html

Country climate change profiles: School of Geography and Environment

http://country

Climate change vulnerability profiles: DARA http://daraint.org/climatevulnerability

Multidimensional country profiles with links to other sites:

Eldis http://www.eldis.org/go/country

Country Health Statistics WHO http://www.who.int/countries/sle/en

UN Framework Convention on Climate Change (UNFCCC) – National Adaptation Programmes of Action (NAPAs) by Country

UNFCC http://unfccc.int/cooperation_support/least_developed_countries_portal/submitted_napas/items/4585.php

Policies, Plans and Statistics preventionweb Prevention web (DRR Resources) Countries: http://www.preventionweb.net/english/countries/

Early Warning Systems USAID FAO

www.fews.nhttp://www.fao.org/giews/english/index.htmFAO)www.Service, FAO)http://vam.wfp.org/WFP)www.reliefweb.orgthe above

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Annex 5: Questions to consider for contextual analysis for health: this relates to Step 4 & 5, Data Gathering Phase 1 & 2. Secondary data review

1) How does the area compare with the rest of the country, and international standards, in terms of under-five, maternal, and neonatal mortality? What are the primary reasons for high mortality (i.e. leading causes of death for each category)?

2) How big of a problem are child stunting and wasting, maternal underweight, micronutrient deficiencies, and infant and young child feeding within the country? Are there any reliable data available on causes of poor nutrition (e.g. food security, poor feeding and caring practices, high burden of disease, poor water and sanitation)?

Primary data collection or further analysis 3) How accessible are health services? Which key health services are easily available and which are not

(e.g. maternal care including skilled delivery, HIV testing and counselling, immunization, treatment of acute malnutrition)?

4) What barriers do community members face in seeking health care? (It’s particularly useful to find ‘non-doer’ respondents who did not seek care, for example a women who delivered at home). Probe around the ‘3 delays’ related to maternal mortality (delay in decision to seek care, reaching care, receiving care). Consult a range of respondents, and consider differences between population groups.

5) What do health workers and district health staff perceive as barriers for community members to access their services? Are these very different from the barriers mentioned by community members?

6) How do community members view health services in their area? How do they view the quality of services in their area?

7) What is the impact on a household when a member of the household becomes ill or dies? (Consider if there is a difference if it is the mother, father, or child who becomes ill). What costs are involved when a family member becomes ill or dies?

8) Who cares for sick children in the household? Who is responsible for feeding and caring for young children?

9) Does the household have soap? When do they use soap (probe)? (The purpose is to understand if they use soap for handwashing; focus especially on child caregiver and person who prepares food). On what occasions should you wash your hands with soap?

10) What sanitation facilities are available to households? Are they being used? Is the facility (including the sewerage water) at least 30m away from any water source?

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Annex 6: Questions to consider for contextual analysis for education: this relates to Step 4 & 5, Data Gathering Phase 1 & 2.

1. What secondary data is available on Education? (NER, GER, completion, repetition, retention, test scores – all disaggregated by sex)

2. Why do parents send/not send their children to school?

3. Do parents see value in completing education in this community? What is the added value for their family/children/community?

During a school visit: 4. What is the enrolment and teacher assignment (by grade and sex) in this school?

5. How many children and teachers are actually present (by grade and sex) on the day of the visit?

6. During a lesson observation – in general, what happens during the lesson? (teacher writing on blackboard, children with books/copies/pens, children asked questions etc.)

7. How are children’s reading levels in each grade? (Ask a few children to read a sentence from their copybook/book independently – start on the second/third sentence to ensure they do not know the passage by heart from rote learning)

8. Is the physical learning environment appropriate? (building, toilets, desks, blackboards etc.)

9. Do you see signs of gender inequality, GBV, corporal punishment etc. in the school or classroom?

10. During your observation, how much of the school day is spent on curricular learning? (Classes start, end, break times, teacher and students in the classroom, time for school feeding etc.)

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Annex 7: Approaches to Sampling: relates to Step 5: Data Gathering and Analysis Phase 2 (answering the Questions in the Data Gathering Framework using primary and secondary data) The following outlines various approaches to sampling, and is especially useful for Step 5: Data Gathering and Analysis Phase 2. Answering the Questions in the Data Gathering Framework using primary and secondary data

Simple random sampling (SRS)

In this approach, every member of the sampling frame has an exactly equal probability of being selected. Every member is assigned a number and individuals are selected by random numbers. This is an ideal (and expensive) approach, and is very rarely followed, not least because the lists are often not available.

Cluster sampling Follows the same approach as SRS, and involves successive random sampling of units within the population. An example of how this might look is as follows:

Randomly select villages in a district

Randomly select household in the village

Randomly select adults in the household

In this case the village is the primary sampling unit, and the households the secondary.

Stratified sampling In this instance, the population is divided into mutually exclusive strata (such as, men and women, or urban and rural, or young and old). From each of these we select an SRS. This is then pooled to obtain overall population estimates. The advantage of this type of sampling is it ensures the representativeness of certain key differences in the population; often small sub-groups are over represented to ensure that the results for the groups are accurate. As with the straightforward SRS, this is a very expensive approach to follow.

Quota sampling In quota sampling, a population is again segmented into mutually exclusive sub-groups, just as in stratified sampling. However, then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting). This second step makes the technique non-probability sampling. Quota sampling is useful when time is limited, a sampling frame is not available, the budget is very tight or when detailed accuracy is not important. Quota sampling is the non probability version of stratified sampling.

Purposive or Judgment sampling

The sample units are chosen because they have particular features or characteristics which will enable detailed exploration and understanding of the central themes and puzzles. These may be socio-demographic characteristics or relate to specific experience, roles or behaviour. Members of a sample are chosen with a ‘purpose’ to represent a location or type in relation to a key criterion, and to ensure some diversity is included so that the impact of the characteristic concerned can be explored.

Snowballing This is the practice of securing additional study participants via the introductions and recommendations of participants previously interviewed. This is one of the most widely used strategies for ‘reaching’ and researching ‘hard to reach’ populations.

Convenience sampling

This entails the researcher choosing the sample according to ease of access, and lacks any clear sampling strategy. In pure research, this approach would never be used.

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Annex 8: Template for format of Contextual Analysis Report: this relates to Step 8: Summarise your findings in a concise form in a contextual analysis report.

Title

Abstract / Summary

Introduction

Methodology Sample (including basic information on the participants) Materials (what data did we use) Procedure (account of administration procedures)

Results

Who are the extreme poor in this context and where are they Why are they poor? What keeps them in extreme poverty? What opportunities are available to extremely poor people? What needs to change – who is responsible, what is already

happening?

Discussion and Options Present ALL options – no decisions made yet

References and appendences incl. list of who was interviewed

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9: Template for Review of Contextual analysis Report The following is the format of the tool used to review the contextual analysis report. Country: Date Submitted:

Comments from:

Date Comments Returned:

General Comments

Does the report contain a good overview of the process involved, including selection of location for investigation (why are we doing this here), data collection and analysis?

Was there an opportunity to comment on the contextual analysis design before fieldwork started

Was there a series of training sessions held to enable the team to collect the data

Is the report clear in terms of who was involved in the exercise and over what time frame

How comprehensive is the Literature Review (Secondary Data Analysis) – specifically, does it examine the existing government policies, existing data (including reports produced by Concern) and available survey data

Is the secondary data used throughout to provide corroborating evidence for the findings in the primary data collection

Does the report contain an overview of the tools used to collect data and how they were designed to address questions of who are the poor, where are they, why are they poor, what opportunities are available for them, and what needs to change

Does the report contain an overview of different groups who are identified as being poor

Does the report contain an overview of who was interviewed

Does the report describe how those interviewed relate to the population of interest

How comprehensive is the institutional analysis

How comprehensive is the section on assets. Does it deal with

(a) Human

(b) Physical

(c) Financial

(d) Natural

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(e) Political

(f) Social

Does it deal with the returns on assets as well

Does the report describe the main livelihood strategies of the different group adequately

Does the report discuss access to services, and who has access

How comprehensive is the section on inequalities. In particular does it deal with

(a) Respect recognition and voice

(b) issues of gender inequality, roles, relations and GBV

How comprehensive is the section on Risk and Vulnerability. Does it identify the main risks people face (natural and man made), is HIV discussed, is unequal vulnerability to hazards mentioned

In the conclusion, does the report identify

(1) Who the extreme poor are in this context and where are they

(2) Why are they poor

(3) What keeps them in extreme poverty

(4) What opportunities are available to extremely poor people

(5) What needs to change? Who is responsible? What is already happening?

In general do the findings make sense?

In general, how well has the detail, depth and complexity of the data generated been conveyed, including identification and discussion of patterns of association

Are programme options presented for further consideration

Are they clearly reasoned through

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Contextual Analysis Plan Template Reference: PM&E Guide Contextual Analysis, Section 2.1

1. Programme Background Details (see caveats on Page 7)

Proposed Name of Programme (Please have as short a programme name as possible in order to help document uploading to the intranet i.e. max of 123 characters)

Programme Location (District / Province / Country) Anticipated Starting Month and Year of Programme Length of Programme (months / years) Is this a continuation on from a previous programme? If so, please attach a copy of the programme’s evaluation.

Yes No Programme Evaluation Attached

Name and Position of PCN Author Is funding required for proposal development? Yes No Who will design and manage proposal development? (Name and Position)

2. What are key questions to be answered during the Contextual Analysis process?

Key Questions to be answered by Contextual Analysis (see PM&E guide for key questions - box text p80)

What information do we already have to answer this question?

What additional information / data are needed from other institutions (secondary)?

What additional information needs to be gathered (primary)?

What informants to consult?

What methods / tools to use

Example Questions:

Area Based Programme: Who are the extreme poor in this context? Why are they poor? Sector Based Programme: Within the poorest communities, whose right to education / health / a livelihood is not fulfilled and why?

3. Stakeholder Involvement in Contextual Analysis

Stakeholder How do they need to be involved in contextual analysis process?

Level of Involvement (Full / Provide information / informed)

Sample Stakeholders:

Local authorities, community leaders, local people who represent different target groups, potential and existing partners, government, other NGOs, colleagues from other programmes, advisers and the regional desk at head office. Note that their respective roles can vary from being fully involved in the process, providing information or just being informed.

4. Contextual Analysis Plan

Contextual Analysis Activity

Why Activity is Required

Who will be involved

Tools Risk/Assumptions Timeline

EXAMPLE: Stakeholder Workshop

Deepen understanding of issues, views, opportunities. Invite participation in further analysis / fieldwork

Begin to identify potential partners Concern team, Programme Manager and ACD

Report of secondary data and stakeholder analysis. Map of who is doing what. Identification of information gaps.

Not jumping to conclusions. Understanding the stakeholders. Including relevant stakeholders.

February 2009

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