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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:
- 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
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);
- Lack of and / or low return on basic assets
- Inequality
- 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.
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:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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?”
- 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)
- 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.
- 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.
- During the primary data phase, build in accountability mechanisms in line with the organisations accountability strategy.
- 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.
- 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.
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.
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)
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
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.
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)
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.
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).
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.
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.
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
