Oxfam Poverty Footprint Methods Toolkit

Oxfam Poverty Footprint Methods Toolkit V9 DRAFT for CONSULTATION ONLY – Not for General Use

Oxfam Poverty Footprint Methods Toolkit V9Methods Toolkit V9

Research methods and tools for conducting joint Oxfam-Company studies on the effects of agricultural business

on the livelihoods of people living in poverty

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Table of ContentsIntroduction..............................................................................................................................3

Primary and Secondary Data.......................................................................................4Quantitative and Qualitative Data.................................................................................4Random and Purposive Sampling................................................................................6Ensuring Attention to Gender.......................................................................................9Types of Methods.......................................................................................................10Triangulation...............................................................................................................12

Section 1: List of Research Methods and Tools.....................................................................13Company Data Sheet.................................................................................................13ERR Models...............................................................................................................14Flow Diagrams...........................................................................................................15Focus Groups.............................................................................................................16Hidden Costs of Employment Analysis......................................................................17I-O and SAM Analysis................................................................................................18Life Cycle Analysis.....................................................................................................19Local Multiplier 3 (LM3)..............................................................................................20Market Analysis..........................................................................................................21Matrices (Ranking Exercises).....................................................................................22Observation................................................................................................................23One-To-One Interviews..............................................................................................24Oral Histories..............................................................................................................26Participatory Maps......................................................................................................27Participatory Social Auditing.......................................................................................28Participatory Value Chain Analysis............................................................................29Prioritisation Tools......................................................................................................30Rapid Market Analysis................................................................................................31Stakeholder Analysis..................................................................................................33Surveys......................................................................................................................34Timelines....................................................................................................................35Transect Walks...........................................................................................................36Value Chain Analysis (VCA).......................................................................................36Venn Diagrams...........................................................................................................38

Section 2. Data Analysis........................................................................................................40Section 3. Ensuring Quality in Research Practice..................................................................42

Research Ethics.........................................................................................................42Access........................................................................................................................43Further information.....................................................................................................43

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Introduction The Oxfam Poverty Footprint Methodology (OPFM) combines local assessments of livelihood impacts, value chain analysis, and an assessment of economic contributions into one comprehensive approach. This approach consists of a Methodological Framework, which outlines the process for carrying out a Poverty Footprint (PF) Study, along with a number of related resources and tools that can help throughout a study. The complete OPFM consists of:

Methodological Framework: Process document outlining steps to conduct a PF study. Methods Toolkit: Guidance on research methods for sampling, data collection and

analysis. Research Template: Sample research questions, indicators and data collection

methods. Analytical Framework (proposed): Framework for analysing data and report writing. Resources: Samples of PF study project management and research materials. Case Studies: Examples of completed PF studies.

This document constitutes the Methods Toolkit (MT); it describes the methods that can be used to carry out a PF Study with a company. This document should be used by the Project Team and research teams alongside the Methodological Framework (MF), and is extensively referenced within it. It will be especially useful during Phases 2 and 3 of the PF process – the Study Design phase and the Primary Research and Data Analysis phase. Before selecting specific research methods to use in the study, the Project Team will need to make decisions on a number of key research issues, which are set out in greater detail below:

Primary and secondary data Quantitative and qualitative methods Random and purposive sampling

The decision process is illustrated in tree diagram below.

Methods Decision Tree

There are also three further issues that the Project Team need to be mindful of when designing the research in Phase 2 of the Framework. These issues, which are also set out in greater detail below, are:

Ensuring attention to gender Types of methods Triangulation

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Data collection

Primary data Secondary data

Qualitative methods Quantitative methods

Purposive Sampling Random sampling


Primary and Secondary Data The Project Team will need to consider the collection and analysis of primary and secondary data. Primary data is information collected directly by the researcher in the field. Primary data can be collected using a variety of different research methods, many of which are outlined in Section 1 of this document.

Secondary data is information already collected by someone else that is available for the researcher to inspect. Secondary data encompasses a wide range of sources. These include government statistics, regional/local archives, unpublished university manuscripts, historical and/or anthropological research, local records and land registries, maps and cartographic surveys, and newspapers and photographs. There are a number of advantages and disadvantages of using secondary data.

Advantages of using secondary data include:

It enables the comparison of primary data with other areas at the same scale, or with larger areas. It can also be used to construct a time series that extends back from present-day observations.

It can be quick to access and is often low-cost and can therefore save considerable sums of money.

It can be useful for crosschecking data from primary sources.

Disadvantages of using secondary data include:

It might be subject to issues of ‘representativeness’. For example, a particular source might be personal, choosing to represent certain events in a certain way. It is therefore important to view secondary data as reflecting, to some extent, the aims and attitudes of the people and organisations that collected the data.

Secondary data can be hard to verify and difficult to customise to the particular needs of the study.

Ideas – Identifying Gaps and Ambiguities

Because of the accessibility and low-cost of secondary data the research team would normally aim to access these sources of information first. When this has been done it should be possible to identify gaps and ambiguities in the data, thus demonstrating where primary data collection is warranted. The Project Team might decide to check secondary data by conducting primary research in the field. For example, they might decide to compare secondary records of organisation membership with primary data collected by the research team. It is likely that additional secondary data will come to light as primary data collection progresses. This data can be incorporated into the analysis as appropriate.

Further information:

Pratt, B. and Loizos, P (1992) ‘Choosing Research Methods: Data Collection for Development Workers’ (Oxford, Oxfam).

Quantitative and Qualitative Data The Project Team will need to decide what mixture of qualitative and quantitative methods to pursue in the primary research phase of the PF. Ensuring that this is a well-informed decision requires that the team have an understanding of the kinds of research questions

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and indicators that can be answered and measured through the application of each type of research method.

Quantitative research is concerned with the collection of numerical data in the form of various measures, and its description and examination by means of statistical analysis. Quantitative methods ask questions such as ‘how many?’, ‘to what extent?’ and ‘how much?’.

Qualitative research is concerned with the collection of data of a verbal form. Qualitative methodologies belong to a family of approaches concerned with collecting in-depth data about human social experiences and contexts. Qualitative methods ask questions such as who, which, what, where, when and why? These questions are particularly useful for increasing understanding of complex or sensitive issues, or where quantification would be too time-consuming and costly. The table below summarises the advantages and disadvantages of quantitative and qualitative methods.

Advantages and Disadvantages of Quantitative and Qualitative Methods

Quantitative methods Qualitative methodsAdvantages Often seen as more objective and

therefore ‘scientific’. Easier to generalise findings to

other contexts than with qualitative methods.

Often easier to analyse than qualitative methods.

Data is ‘rich’ and contextual, so less risk of oversimplifying or caricaturing processes and issues being investigated.

More flexible to pursue specific issues as they arise in the field.

Disadvantages Attribution: how can you be sure that you are correctly linking cause and affect?

More technical methods are arguably less accessible to people with limited experience in social research.

Often high resource demands of data collection.

So-called ‘objective’ quantitative analyses can in reality be biased if poorly designed.

Often criticised for being overly subjective and dependent upon preconceptions of small subset of people.

Harder to generate representational data – thus generalisation of findings to other situations more difficult.

Qualitative techniques are less systemic than quantitative techniques, therefore data analysis is more difficult.

Ideas – Balancing Qualitative and Quantitative Methods

It is recommended that a mixture of qualitative and quantitative methods be utilised by the Project Team. This step in the research design (Phase 3.2 of the MF) will help to adequately explore all facets of the research areas identified in Phase 2.5. For example, a single research indicator (such as ‘Extent to which farmers feel they can implement new techniques’) can be investigated using both a quantitative questionnaire and a qualitative focus group exercise. A researcher might also decide to conduct a number of in-depth qualitative focus group meetings and interviews with key informants first, and then use the insights from these exercises to design a series of quantitative questionnaires on key topics of interest.


George, C. (2001) ‘The Quantification of Impacts’, Enterprise Development Impact Assessment Information Service.

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Mayoux, L. (2001) ‘Qualitative Methods’, Enterprise Development Impact Assessment Information Service.

Random and Purposive Sampling Sampling is the process whereby the researcher decides with whom they are going to conduct the research. After selecting their research methods, the study team will need to consider whether they are going to pursue a random or purposive sampling strategy for each method.

Random sampling can enable you to claim that your data are statistically representative of a larger population. However, this approach requires a reasonably large sample to be convincing, and this condition might not exist in all circumstances. For example, there might not be enough respondents available in a population to achieve a representative sample.

Ideas – Ensuring Transparency in Selection of Random Sample

The selection of the random sample for a community may be done using a public draw so as to maximise transparency and participation. If it is a small population, respondents could be drawn from a hat. Alternatively, if it is a larger population the selection could be done on an Excel spreadsheet projected in front of all community members ‘live’ on screen.

Purposive sampling refers to the selection of respondents being linked to the purpose of the research. For example, it can be used to pursue sources of information that are particularly information rich. However, in some research situations employing this strategy may not be feasible. For example, if you are investigating a highly sensitive research topic, such as anti-retroviral treatment, you are unlikely to have a list of the relevant population from which to select your sample. The costs and time required to obtain a complete list of the population might also be a factor.

The most common types of random and purposive sampling strategies are shown in the table below. The population refers to the complete set of units about which generalisations are to be made (e.g. all villages in a district), while the sampling frame is a complete list of all the units in a population (e.g. a list of villages in a district). When using a random sampling strategy, it is important to make sure that there are not ‘hidden’ sub-populations (e.g. women-headed households or the elderly) that are not represented in the sample frame. In some cases, it might be better to have two “levels” within the sample frame. For example, a list of villages, where a number of villages are randomly selected from a list, followed by a list of households within each village that is selected. This cuts down on the cost of a survey and is often the only feasible survey design for household surveys. This approach is known as a multi-stage cluster sample.

Random and Purposive Sampling Strategies (adapted from Laws, 2003)

Type of sample

Definition Example Further considerations

Random sampling Simple random sample

A sample designed so that each unit in the population has an equal chance of selection.

Names (or numbers) drawn out of a hat.

Relies on obtaining a detailed, accurate sampling frame for the full target population.

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Systematic sample

A version of simple random sampling in which the sampling frame is arranged in order, then every nth unit is selected.

Visit every, say, third house in a village.

Fieldwork can be expensive due to widely dispersed units.

Stratified sample

A version of simple random sampling which is used when there is a need to represent all groups of the population in the sample.

Divide target population into strata e.g. males/females, urban/rural, etc; select simple random or systematic samples from each group or strata; merge samples into one.

- Helps ensure that sub-groups are accurately represented within the sub-population.- Great deal of information about target population required.

Purposive sampling Quota sampling

Uses information about the target population to describe the types of units to be included in the sample. Individuals are then sought who fit these characteristics, e.g. by age, sex, housing type or location.

In a study of informal water sellers, specify a small quota of informal sellers in each housing area, based on the number of on-plot water supplies (available from local water authority); researchers locate their quota through talking to those carrying water.

- Quick and cheap to organise. - Must state clearly that data is not representative (sampling units not drawn randomly).

Snowball sample

Start with one or two respondents, and ask them to refer you to others who share characteristics with them, and so on.

A study of smallholders who illegally break their contracts starts with a few contacts and asks them to invite friends who also broken their contracts.

Best approach for investigating particularly sensitive topics.

Convenience sample

Sample includes whoever happens to be around at the time.

Interview households that are living nearest a tarmac road for easy access.

- Simplest strategy in terms of resource demands. - Biases can be introduced into the data.

Random and purposive samples are often associated with quantitative and qualitative methods respectively. However, the Project Team might quite legitimately choose to utilise a random sample to collect qualitative data and vice versa depending upon the demands of the research at the time. For example, the researchers can use a purposive snowballing strategy to conduct a questionnaire with hard-to-reach respondents.

Random and purposive sampling strategies can also be employed in stages. For example, the researcher might conduct a quantitative questionnaire to identify key lines of division within a social group (e.g. male/female, young/old etc.) and use a snowball strategy to access respondents within groups.

Sampling in a Poverty Footprint Study:

In a PF, the ‘population’ refers to the different groups of stakeholders, about which generalisations will be made, and will include:

Female and male employees working in different divisions/departments of the Company

Representatives of suppliers of products and services to the company

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Managers from different parts of the organisation Sub-divisions of the company Other civil society organisations (such as trade unions, NGOs etc.) Government departments Competitors Customers / clients of the Company Women and men living in the community surrounding Company operations, its

suppliers, or employees Women and men within the Company’s geographical market area, but which do not

necessarily interact with it Producers operating in the value chain that the company is engaged with (including

women and men who are not directly trading with the company) Other women and men in the producer communities, such as teachers, traders, or

transporters

Determining the sample size:To be expanded – EDP presentation

The variability in the population is the most important determinant of the optimal sample size (rather than the size of the population, which is irrelevant). There are a number of moving parts in calculating sample sizes and it is important to get guidance from someone with a good understanding of statistics.

Different scenarios require different sample size calculations…

There are two types of errors associated with samples - sample error (where the sample is not a good representation of the population) and non-sample errors (errors associated with the process of managing data collection. In general, it is better to go for relatively small samples (approximately 70 observations for each population of interest) and to manage the process very carefully, treating each survey response as ‘gold-dust’. The alternative – trying to collect data from very large samples (1000s of respondents) – inevitably leads to a lack of control over the process of data collection and a large rise in non-sample error.

Key issues to consider when deciding on samples are:

How can differentiation between subgroups be drawn out, particularly based on gender? Is gender analysis fully integrated?

What are the implications of engaging with different stakeholders, including the powerful/powerless?

How should the research team go about its sampling strategy when dealing with highly sensitive topics?

Does the sample frame give adequate representation to the different interests involved? How is representation of the most vulnerable to be ensured? For example, are separate workshops and investigation's planned for these groups? Are women and men going to be interviewed together or separately? Are the specific needs of these groups (in terms of timing and location of meetings) taken into account?

How is participation of those currently in powerful positions in the value chain to be enlisted? How will potential sensitivities and conflicts of interest be dealt with?

How will access to respondents be gained? Who are the gatekeepers through whom access will be attempted? What impact might these have on the research? How is the anonymity of respondents to be protected?

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Ideas – Ensuring Adequate Representation of Women

Women will be more difficult to sample than men because their roles tend to be less visible and recognised, so that a community may report ‘there are no women processors/suppliers’. Therefore a representative may be necessary to request meetings with women who work in these organisations. As research progresses, it will also be necessary to constantly adjust the sampling focus to ensure adequate female stakeholder representation.


Laws, S. (2003) Research for Development (London, Sage) Chapter 19. Mayoux, L. (2001) ‘Whom D We Talk To? Some issues in sampling’. Enterprise

Development Impact Assessment Information Service. Roche, C. (1999) ‘Impact Assessment for Development Agencies’ (Oxfam GB, Oxford),

Chapter 3.

Ensuring Attention to Gender There are underlying inequalities in every society between women and men, in terms of their roles in the household and the resources that they each have to deliver them. Therefore in a PF Study there is a need to ensure attention to gender at every step of the research process. The table below summarises how this can be done. Ensuring Attention to Gender at Every Step of the Research Process

Research step Measure Selecting criteria Ensure fair female and male ‘representativeness’ when selecting criteria. Selecting indicators

Consider what indicators to include to show how women and men are women are impacted differently.

Sampling respondents

Make greater effort to seek out the opinions, ideas, and attitudes of women.

Choosing research methods and conducting research

Pay attention to how female and male respondents 1) react to different types of methods and 2) male and female interviewers and facilitators.

Analysing data Where possible, disaggregate data by gender. Writing up the report

Ensure that the voices of women and men are represented fairly.

Women who have been systematically denied their rights and been subject to greater degrees of marginalisation than men will be less able to articulate their perspective in a focus group or interview. Women’s experiences, opinions, and ideas will therefore tend to be underrepresented in a PF Study. For this reason, as research progresses it will be necessary to constantly adjust the sampling focus to ensure adequate representation of women. This should take place at the beginning of each cycle of primary research.

When conducting exercises with informants, the researchers will probably find that women take longer to relax and respond openly to questions, sometimes as a result of being shy, or through a lack of understanding of what is being asked. Women might take longer to build up trust in the researcher conducting the exercise, particularly if the researcher is a man. The researchers might also find that different methods are better suited to women, and others to men. For example, women might avoid taking about sensitive issues in a one-to-one interview, but might be more open with their opinions and beliefs in a well-designed and guided focus group discussion.

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But really getting at the differences in impacts on women and men means more than questioning, and cataloguing the responses of, women and men separately. It means asking questions that are relevant to the priorities and livelihoods of women as well as those of men. Therefore while both women and men are interested in income levels, women may be more affected than men on the issues such as the time required to produce/improve a product, the risks or uncertainties of income in a value chain, or the distances of travel required to participate. It is common for women living in poverty to find little value in small increases in income if the workload rises or there are conflicts with unpaid caring work.

It is important that the study team is aware of gender issues before the research progresses, but also that they provide the researchers on the ground with the freedom to pursue different methodological approaches with women and men as necessary.


Auret, D. and Barrientos, S. (2004) ‘Participatory Social Auditing: a practical guide to developing a gender-sensitive approach’, IDS Working Paper 237.

FAO (2007) ‘Women, Agriculture, and Food Security’, http://www.fao.org/worldfoodsummit/english/fsheets/women.pdf

Kidder, T. and Raworth, K. (2004) ‘Good jobs’ and Hidden Costs: women workers documenting the price of precarious employment’, Gender and Development, Vol. 12, pp. 12-21.

UNDP (2001) ‘Gender in Development Programme’, Learning and Information Pack, Gender Analysis, http://www.gdrc.org/gender/mainstreaming/index.html

Types of MethodsThere is no single approach to conducting a PF Study, but the Project Team should utilise a combination of macro-policy research methods and community-based research methods, which should be both ‘traditional’ and ‘participatory’ in nature.

Macro-policy research methods include document analysis, key informant interviews and modelling approaches. Many of the techniques in the latter group are based on statistical analysis of quantitative economic data. Such methods outlined below are: Input-Output (I-O) analysis and Social Accounting Matrices (SAMS), Value Chain Analysis (VCA), and Economic Rate of Return (ERR) models.

Community-based research methods are primary data collection techniques utilised with stakeholders outside of the Company. The methods can be divided into two categories: traditional methods and participatory methods. Many of the traditional methods will already be familiar with the study team. These methods are common in social science research. Such methods considered below are: one-to-one interviews, focus groups, questionnaires, and observation.

Participatory methods have become established in recent years as a powerful tool for development research. This kind of research aims to enable people who traditionally have been merely the ‘subjects’ of research to take an active role in making their voices heard. Participatory research gives participants the opportunity to share their perceptions of a problem, to find common ground, and then to engage a variety of people in identifying and testing out possible solutions. This is said to increase the effectiveness of development initiatives as well as lead to shared learning for all involved.

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http://www.gdrc.org/gender/mainstreaming/index.html

http://www.fao.org/worldfoodsummit/english/fsheets/women.pdf

Participatory

Traditional

Qualitative Quantitative

Participatory social auditing and VC analysisMapsWalksDiagramsTime-trends analysis

Focus groups InterviewsObservation Questionnaires

Matrices


In a PF Study, participatory methods should lead to more relevant identification of affects and interactions with the Company and enable better identification of who is affected by its business activities, policies, and practices. The participatory methods considered below are: participatory social auditing, participatory value chain analysis, participatory maps and transect walks, diagrams (Venn diagrams, flow diagrams, matrices) and time-trends analysis (timelines and oral histories).

Ideas – Getting the Most out of Participatory Methods

All of the participatory methods included in this document share a number of common characteristics and are therefore can be made most effective by following two key tips. Firstly, choosing people who are connected in certain important ways (e.g. by age, gender) this can help participants relax and facilitate discussion. Secondly, in all cases, the discussion that accompanies the creation of the map, diagram, or timeline is just as important as the finished product itself. The discussion should be noted down as in an interview.

In the figure below, the community-based research methods have been populated on a matrix according to whether they are qualitative or quantitative and participatory or traditional.

Types of Community-Based Research Methods


Laws, S. (2003) Research for Development (London, Sage), Ch. 3 and Ch. 17.

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Mayoux, L. (2001) ‘Participatory Methods’, Enterprise Development Impact Assessment Information Service.

Roche, C. (1999) Impact Assessment for Development Agencies (Oxford, Oxfam Publications), Chapter 4.

TriangulationTriangulation means gathering and analysing data from more than one source to gain a fuller understanding of the situation that you are investigating. There are two main types of triangulation: source triangulation, which involves discussing the same issues with different respondents to compare claims made by those respondents, and multi-method triangulation, which is carried out using a combination of methods to explore one set of research questions. Triangulation is generally required to increase the reliability and credibility of traditional and participatory social science methodologies. The technique is essential to the multi-methods approach taken to a PF Study.

Triangulation is particularly important when qualitative methodologies are used in order to produce a rounded and multi-faceted view of a particular issue or problem. During triangulation it is important that researchers bear in mind that differences in opinion or versions of events do not necessarily invalidate the perceptions of different groups. Therefore, although triangulation is a way of verifying the views expressed by different groups, it still allows for and helps us to understand differences between groups.

Ideas – Researcher Field Diaries

Each researcher should keep a field diary to note down impressions from each day’s activities, including an interpretation of data and general observations such as the weather.

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Section 1: List of Research Methods and ToolsThis section presents the key research methods and tools that can be used to conduct the primary research for a PF Study. In the list that follows a basic outline of each method is presented with references to further information.

Company Data SheetMethod type Macro-policy; traditionalData type Quantitative Suggested sampling strategy

N/A.

What is a company data sheet?

A company data sheet is a useful research tool to help in gaining basic quantitative data on the company. An example of a company data sheet is included below.

Example Company Data Sheet

N.B. $m's (consider use of constant prices); data should be captured for all years between 1990 and 2009

Indicator Research brief Source 1990 1991… …2009FDI ($m's)

Central officeRegion

Sales/Turnover ($m's)LocalForeign / exports

Supplier payments ($m's)LocalForeignWaterLabellingMerchandising /

marketingFormula (intra-company

payments)Other raw materialsEquipmentServices

Distributor payments ($m's)SmallLargeForeign

EmploymentSalariesOther contributionsLocalForeign

Pre-tax profitsTaxes

EmploymentLocalCorporate

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PayrollPost-tax profits

DistributedLocalForeign

RetainedAccumulated potYearly re-

investmentsImportsExportsForeign Exchange activity

SellingBuying

Intra-company payments (foreign)

BoPTotal payments to TCCC Foreign suppliers/distributors ($m's per year) Total payments from foreign buyers ($m's per year)Total financial transfers to foreign recipients ($m's per year)Total financial transfers from foreign stakeholders ($m's per year)Published BoP (for comparison)

Tips for data collection and analysis:

The indicators included in the company data sheet should be those identified in the in the development of the research brief during the study design (Phase 3.2 of the MF). It is also important that the data sheet is used in conjunction with interviews of company employees to gain as full range of quantitative and qualitative data on company activities.

ERR ModelsMethod type Macro-policy; traditionalData type Quantitative Suggested sampling strategy

Random and purposive

What is an ERR Model?

The purpose of an ERR (Economic Rate of Return) model is to gain insight into the affects of a given project on a company’s diverse stakeholders, including labour and the local economy. The ERR is based on the notion of ‘opportunity cost’ or on what the various social actors involved with the company’s operations would lose if it were not present in the local marketplace. An ERR enables researchers to ask questions such as: if the company were to leave the focus country tomorrow, what kind of jobs would employees be able to find in other industries and at what wages? Would they lose income as a result? If so, the income loss would be one measure of the opportunity cost or real economic value of the company’s operations in the national context.

An ERR is useful when:

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You are interested in what the national poverty situation would be if the Company were not operating in the country.

You want to understand how a company ‘adds value’ for the stakeholders that it engages with.


ERR analysis is a data-intensive and technically demanding process which relies on the existence of information about company’s other than the focus company. It might be possible to combine an ERR study with an I-O and SAM analysis (outlined below. In this way, I-O models help capture the company’s macro influence on employment, incomes, and government revenues, while the ERR models focus on the company’s ‘value added’ for a variety of stakeholders. Where quantification is not possible, the costs and benefits of a company’s operations for different stakeholders can be described qualitatively.


Esty, B., Ferman, C., and Lysy, F. (2003) ‘An Economic Framework for Assessing Development Impact’, Harvard Business School Case Study.

Flow DiagramsMethod type Community-based; participatoryData type QualitativeSuggested sampling strategy

N/A

What is a flow diagram?

Flow diagrams are used to illustrate and analyse the consequences (both positive and negative) of particular issues or actions. Flow diagrams are therefore fundamentally maps, except that the various ‘features’ represent qualities or phenomena that people consider to be important (e.g. health or hunger).

Flow diagrams are useful when:

You want to explore a specific issue in depth. You want to explore who in a social group is experiencing particular impacts arising

from a company’s activity.


To create a flow diagram participants take the impacts to be considered, for example, a particular company policy or operation, and then explore the consequences. Usually this is done by asking ‘What happened next?’ or ‘What affects did this have?’. Features highlighted can be joined up using whatever local materials come to hand (e.g. twigs, lines of stone) in order to demonstrate cause and effect. This should then be drawn up into a diagram by one of the researchers.


Roche, C. 1999. Impact Assessment for Development Agencies: Learning to Value Change (Oxford, Oxfam), Chapter 4.

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Generic Example of a Flow Diagram

Focus Groups

Method type Community-based; traditionalData type QualitativeSuggested sampling strategy

Random and/or Purposive

What is a focus group? A focus group is a group of people, usually between six and twelve, who meet in an informal setting to discuss an issue that has been set by a researcher. A key difference between a focus group and an interview is that the former is defined by the interaction between members of the group, whereas the latter is defined by the interaction between interviewer and interviewee.

There are essentially two kinds of focus groups. In the first type participants share a common characteristic, such as age, sex, educational background, religion, or something directly related to the topic. This is said to encourage a group to speak more freely about the subject without fear of being judged by others thought to be superior, more expert, or more conservative. In the second type a diverse group of people is brought together, often to ‘test’ a specific idea or policy. Sometimes this diverse group is seen as partly representative of the wider population.

You should use focus groups when:

You are interested in the range of opinions and ideas that people have about an issue (but not their distribution).

You want peoples’ ideas about what would be better for them.

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You want to ‘test’ an idea or hypothesis about a certain topic or issue, or gauge peoples’ responses to your findings.

Tips on data collection and analysis:1

Focus groups require a skilled facilitator to conduct. It is important that the facilitator allows everyone to talk, and is not tempted to join in the discussion. In addition to a facilitator, a focus group observer can assist in note taking, observe non-verbal communication, and help the facilitator in putting people at ease before and after the session. This frees the facilitator to concentrate on listening to and steering the group. Questions put to the focus group should be open and straightforward – closed questions will stop the group dead.

For further guidance on designing and conducting a focus group discussion researchers should consult the Example Focus Group Discussion Guide provided in the Resources and Tools section of the OPFM.


Dawson, S. and Manderson, L. (1993) A Manual for the Use of Focus Groups, (Boston, International Nutrition Foundation for Developing Countries).

Law, S. (2003) Research for Development: A Practical Guide, (London, Sage), Chapter 17.

Hidden Costs of Employment AnalysisMethod type Community-based; traditional Data type Quantitative and qualitativeSuggested sampling strategy

Purposive

What is a hidden costs of employment analysis?

Precarious conditions of employment generate many ‘hidden’ costs for women workers. These costs are referred to as ‘hidden’ for several reasons.

Some are not explicitly recognised by workers to be costs because they lack information about their rightful benefits under law or because the costs only materialise in the longer term.

Such costs are usually missing from official statistics of export-oriented employment made by economists and policy makers.

In addition, some costs are implicit subsidies to the true cost of production because women workers are forced to pay out of pocket or forgo their rightful earnings.

In order to capture the full range of hidden costs faced by workers in these sectors, a matrix can be created (as shown below), which brings together the various contextual determinants and forms of costs that lead to the hidden costs incurred.

Determinants of Hidden Costs for Women Workers

Contextual determinant of cost

1 Many of the points raised here on focus groups are also relevant for one-to-one interviews.

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DETERMINANTS OF HIDDEN COSTS FOR WOMEN WORKERS

Supply chain pressures

Labour law enforcement & compliance

Householdrelations

Community relations

Form of hiddencost

Out of pocket

Income/ benefitForgoneHuman developmentSelf-esteem and equity

When should hidden costs of employment analysis be used?

(Questionnaire) When you want to examine the gendered effects of a company’s value chains and/or its impact on institutions and policy quantitatively.

(Focus groups) When you want to understand women’s perceptions of the hidden costs of employment, which are not available in quantitative data.


There are two research methods that can be employed in relation to this matrix. First, researchers can ascribe monetary values to benefits forgone and out-of-pocket expenses through detailed surveys of the needs and spending patterns of the workers concerned.

Second, the matrix could be completed in-depth for a particular set of women workers during a focus group discussion. Identifying and documenting hidden costs in this way can help raise awareness among workers of their rights at work, while also provide using data for analysis.


Kidder, T. and Raworth, K. (2004) ‘‘Good jobs’ and hidden costs: women workers documenting the price of precarious employment’, Gender & Development, 12 (2), pp. 12-21.

I-O and SAM Analysis Method type Macro-policy; traditional Data type QuantitativeSuggested sampling strategy

N/A

What is I-O and SAM analysis?

Input-Output (I-O) analysis is a method of assessing the effects of various industries on macroeconomic variable such as output, income, and employment. The purpose of an I-O table is to reconcile what goes into an economy with what emerges from it. The difference between the costs of the inputs and the price of the outputs indicates the value-added that is associated with the economic activity. In short, by examining a country’s input-output table, analysts gain a clearer idea of what resources are being used for what purposes, and how much value-added is generated through the production of goods and services.

SAM (Social Accounting Matrix) analysis also makes use of national accounts but this time to determine how incomes and employment are distributed among different industries,

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regions, social groups, and households. For example, a SAM analysis will indicate how the effects of a certain production process is distributed between economic units such as regions and households, and can even be broken down by gender and ethnicity, to the extent that such data are available.

I-O and SAM analysis is useful when you:

Want to generate a ‘snapshot’ in time of a single company’s economic activities. Want to understand which national-level sectors are affected by the operations of

the company, and potential vulnerabilities that might exist with respect to certain company operations and stakeholders.

Have large amounts of secondary economic data relating to inputs and costs in the national economy.


I-O and SAM analysis are data-intensive and technically demanding processes. Their accuracy depends largely upon the availability and quality of both national and company-level data, and this information may either be unreliable or even non-existent in many developing countries.

Life Cycle AnalysisMethod type Macro-policy; traditionalData type QuantitativeSuggested sampling strategy

N/A

What is a Life Cycle Analysis?

A graph is drawn with productive revenue on the Y-axis and time on the X-axis (see Figure 5 below). Examining the graph enables the researcher to determine whether the product is growing, mature, or in a decline, as well as whether it is new or known to the market.

Product Life Cycle Curve

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Source: Trump University Business Briefings, http://www.trumpuniversity.com/business-briefings/lib/resources/images/graphs/product_life_cycle.gif

Life Cycle Analysis is useful when you want to:

Identify different stages (characterised by the revenue generated by the product) in a product’s life cycle to identify how to respond to new challenges and opportunities.


Trump University Business Briefings, http://www.trumpuniversity.com/business-briefings/lib/resources/images/graphs/product_life_cycle.gif

Local Multiplier 3 (LM3)Method type Community-based / traditionalData type QuantitativeSuggested sampling strategy

Purposive (for questionnaire)

What is an LM3?

LM3 is a measurement tool that looks at a specific local economy and calculates the ‘local multiplier effect’, or the benefit created by an economic activity within a defined area.

The multiplier is a concept from economics that is used to denote how much a specific inflow of income into an area circulates (or multiplies) in that area. It has been used widely in the measurement of food supply chains, local purchasing initiatives, and other procurement programs.

LM3 is useful when you:

When you want a quick and easy economic evaluation of a company’s local economic impact.


There are five steps / three rounds to an LM3 analysis -

1. Determine what you ‘local’ area is2. Identify what your starting point or income source is – the company’s (local)

turnover (Round 1)3. Identify how income is spent by the company locally (Round 2)4. Through a questionnaire, identify how income is spent by suppliers and

smallholders locally (Round 3) 5. Collate all the responses, do some quick maths, and you have an LM3 score


LM3, Proving and Improving: Quality & Impact Toolkit for Social Enterprise, http://www.proveandimprove.org/pdfs/pdf_24_tools.pdf

Market Analysis

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http://www.proveandimprove.org/pdfs/pdf_24_tools.pdf

http://www.trumpuniversity.com/business-briefings/lib/resources/images/graphs/product_life_cycle.gif




Method type Macro-policy / traditionalData type QuantitativeSuggested sampling strategy

N/A

What is market analysis?

Market analysis is the process of systematically gathering, recording, and analysing data and information about the market in which a company is operating. Market analysis aims to 1) build a model of the particular market in which a company is operating, 2) analyse that market to identify potential economic opportunities, and 3) develop and implement a strategy to secure the company’s financial success in that market. Market analysis therefore plays a major part in a company’s planning activities. It guides decisions on inventory, purchase, work force, expansion and contraction, purchases of capital equipment, and promotional activities.

Market analysis can be conducted in terms of:

Market structure (e.g. highly competitive, monopoly); Market position (e.g. market niche, market leader); Market objectives (e.g. national and international growth, shareholder value); and Market segment (e.g. income level, age, social class).

One specific form of market analysis is market research. This is the process of systematically gathering, recording, and analyzing data and information about customers, competitors, and the market. Its uses include creating a business plan, launching a new product or service, fine-tuning existing products and services, and expanding into new markets. Market research can be used to determine which portion of the population will purchase a product or service, based on variables like age, gender, location, and income level.

Market analysis is useful when you want to:

Understand the structure and key characteristics of a market and identify business opportunities within it.

Better understand the general conditions in a market. Rapid Market Analysis can be undertaken if small-scale producers are being

targeted, or if there is limited time and resources.


Companies can choose from a wide range of techniques to conduct market analysis, but many are based on statistical analysis of secondary data. Many companies conduct various types of market analysis as a standard practice. It is likely that much of this information will be usable as secondary data in a PF Study. Rapid Market Analysis should involve or be undertaken by target producers. This process can be facilitated by a market specialist and, if feasible, should involve other local market actors.


Kress, G. J., Webb, T. and Snyder, J. (1994) Forecasting and Market Analysis Techniques: A Practical Approach, http://www.questia.com/PM.qst?a=o&d=9614310

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http://www.questia.com/PM.qst?a=o&d=9614310


Matrices (Ranking Exercises)Method type Community-based; participatoryData type Quantitative and qualitativeSuggested sampling strategy

Rand and purposive

What is a matrix analysis?

There are many ways of ranking or ordering data in a participatory manner, including wealth ranking, problem ranking, impacts ranking, performance ranking, and preference ranking. The purpose of matrix analysis is to rank the value of a particular activity or item according to a range of criteria. This section outlines how to conduct a preference matrix.

Matrices are useful when:

You want to understand local concerns. When you want to evaluate local priorities for intervention and action.


A preference matrix is done with the help of a matrix, which has two identical lists of items, one across the top and the other down the left side. It can be used to rank issues of importance to people living in poverty such as livelihood strategies (see example matrix below) and access to services. Each item on the matrix is compared directly against the others until they are ranked from highest to lowest. Each open box or cell in the matrix represents a paired comparison of two items or alternatives. Key questions to consider in preference ranking are:

Which item (e.g. a problem with / service provided by the Company) out of several ones is looked upon as most important, favourable, necessary or pressing by a certain group within a village/ community?

Which are the criteria for preferring one item to another? How different are the preferences between different groups within the village/

community?


Freudenberger, K. S. (1994) Tree and Land Tenure Rapid Rural Appraisal Tools, (Rome, Food and Agricultural Organisation).

Roche, C. (1999) Impact Assessment for Development Agencies, (Oxfam: Oxford), Chapter 4.

Berg, C. et al. (1997) ‘Introduction of a Participatory and Integrated Development Process (PIDEP) in Kalomo District, Zambia - Volume II - Manual for Trainers and Users of PIDEP’, Centre for Advanced Training in Agricultural and Rural Development, Humboldt University Berlin (Weikersheim, Margraf).

Example of a Preference Ranking Matrix for Livelihood Strategies

PREFERENCE RANKING FOR DETERMINING PRIORITIESRank Score Activities

ranked(row by column)

Vegetable production

Livestock, small livestock rearing

Fruit tree cultivation, fruit gathering

Food processing/ distilling

Strawberry production

Bee-keeping

3 3 Beekeeping Vegetable Livestock Beekeepin Beekeeping Bee-

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production and small livestock rearing

g keeping

6 0 Strawberry production


Livestock and small livestock rearing

Fruit tree cultivation and forest gathering

Food processing; distilling

5 1 Food processing/ distilling



Fruit tree cultivation and forest gathering

4 2 Fruit tree cultivation and fruit gathering



1 5 Livestock and small livestock rearing


2 4 Vegetable production

Source: FAO (1998) ‘Gender and Participation in Agricultural Development Planning’, http://www.fao.org/WAICENT/FAOINFO/SUSTDEV/WPdirect/WPre0052.htm

Observation Method type Community-based; traditional and

participatoryData type Quantitative and qualitativeSuggested sampling strategy


What is observation?

There are essentially two types of observation. Systematic observation involves observing objects, processes, relationships or people, and recording these observations. You need to identify indicators that are important to your research questions, and which can be assessed by direct observation.

Participant observation is grounded in the anthropological and ethnographic traditions. It involves playing an active role in the situation or phenomenon being researched, and has no formal steps to doing it. The key differences between systematic and participant observation are set out in the table below:

Differences Between Systematic and Participant Observation (adapted from Laws, 2003)

Systematic observation Participant observation Observers look for specified behaviour at specific times and places

Observer learns from living and/or working alongside those they are studying

A checklist of items to be observed (indicators) is required

The observer notes everything they can

Quantitative data is generated Qualitative data is generated in large quantities

Observers are open but unobtrusive in making their observations

Consent can be an issue, if people forget that you are a researcher

Easy to analyse Difficult to analyse

Oxfam document.doc

http://www.fao.org/WAICENT/FAOINFO/SUSTDEV/WPdirect/WPre0052.htm


The rest of this section advises on systematic observation, which is likely to be more applicable to research in a PF Study.

Observation is useful when:

The information you want is about observable things. You need to crosscheck peoples’ account of what happens (i.e. compare what

happens with what people say happens). You wish to avoid the process of social interaction as little as possible, or want to

see how people behave in their normal environment.


When observing a complex event, different researchers can focus on different groups of people. The researcher should disturb the situation they are observing as little as possible by placing themselves somewhere unobtrusive and avoiding interaction with others.

A number of highly regarded participatory observation studies have been conducted in the past where the researcher has gone ‘under cover’ to report on a situation or event. However, this method is unlikely to be feasible in a PF Study. Researchers should normally be ‘overt’ (i.e. provide a full explanation of your role) rather than ‘covert’ (i.e. conceal your purpose and identity).


Laurier, E. (2003) ‘Participant Observation’, in Clifford, N. and Valentine, G. (eds.) Key Methods in Geography (London, Sage).

One-To-One InterviewsMethod type Macro-policy/community-based; traditionalData type Quantitative and qualitativeSuggested sampling strategy

Purposive

What is an interview?

In one-to-one interviews a series of questions are addressed to an interviewee, and their responses recorded. There are essentially three types of interview: 1) structured interviews, 2) semi-structured interviews, and 3) unstructured interviews:

In a structured interview the interviewer follows a rigidly structured set questions. In a semi-structured interview the interviewer has a pre-set list of questions to cover,

but s/he does not have to ask all the questions and can pursue another path of questioning if something of interest is opened up by one of the interviewee’s responses.

An unstructured interview is more like a conversation and often begins with the interviewer asking the respondent what they would like to talk about.

Interviews are most useful when:

You need to know about people’s experiences or views in some depths. You are able to rely on information from a fairly small number of respondents. The issue is sensitive, and people might not be able to speak freely in groups.

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Respondents would not be able to express themselves sufficiently through a written questionnaire.

The decision to select a particular type of interview will depend upon a number of considerations, including the data requirements of the study. The table below compares the interview types.

Comparison of Interview Types (adapted from Laws, 2003)

Structured Semi-structured Unstructured Useful when research questions are very precise, and quantified answers are needed

Useful where some quantitative and qualitative information is needed

Useful to help set the research focus, or to explore new or sensitive topics in depth

Questions must be asked in a standard way

Questions may be asked in different ways, but some questions can be standard

More like a conversation – no standard questions, just topic areas

All questions must be asked Questions can be left out and others added

Follow (or ask) the respondent to establish what is important to discuss

Results easy to analyse Analysis is fairly straightforward Analysis requires time and skill


There are many potential places where an interview can take place, such as in the respondent’s home or workplace, or somewhere ‘neutral’ such as a café or hotel. The interviewer should be aware of the implications of conducting an interview in one place as opposed to another. For example, an interviewee may feel they cannot speak freely in their place of work. Therefore all interviews with Company employees should be conducted away from factories, offices, etc. The key point is that the interviewers and interviewees feel comfortable in the space where the interview is taking place.

Interviews should begin with questions that the informant is likely to feel comfortable answering. Difficult, sensitive or thought-provoking questions should be avoided if the interviewee appears uncomfortable. It is also worth bearing in mind that people being interviewed value their time too, and therefore you should seek to set realistic expectations about the time commitment needed, and not exceed this.

There are three example interview guides provided in the Resources and Tools section, which also include further guidance for researchers conducting the interviews.


Law, S. (2003) Research for Development, (Sage, London), Chapter 17. Longhurst, R. 2003. Semi-structured interviews and focus groups, in Clifford, N. and

Valentine, G. (eds.) Key Methods in Geography (London, Sage). More suggestions on listening, understanding and questioning are available from the

Chronic Poverty Research Centre, www.chronicpoverty.org/CPToolbox/Interviewtechniques.htm

Oral HistoriesMethod type Community-based; participatoryData type Qualitative

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http://www.chronicpoverty.org/CPToolbox/Interviewtechniques.htm


Suggested sampling strategy


What is an oral history?

Oral histories tap into people’s memories to shed light on past events. They are essentially an interview, although the process can be facilitated with the aid of visual participatory methods such as timelines. For this reason, many of the issues and tips that apply to interviews and participatory methods also apply to oral histories.

Essentially there are two different types of oral history: researcher-led and informant-led. In the former, there may be a list of prompting questions, which elicit from the participant the sorts of issues that the researcher thinks are of importance for the research. In contrast, in the informant-led type, the researcher may simply ask participants to give an outline of their lives in an undirected, open-ended way, thus allowing them to put the emphasis on the things that they themselves regard as most significant.

Oral history exercises should be used when you want to:

Explore specific historical occurrences in depth. Understand how people have been affected and have influenced certain historical

processes and events.


During the oral history exercise it is important to be aware that no one is ever wholly truthful in the sense of remembering everything accurately. In other words, oral histories tend to be ‘edited highlights’ of a person’s experience. People tend to be able to recollect particular memories when they can place them in the original context. It is therefore often better to start an oral history exercise from a ‘landmark’ event (such as national independence, a natural disaster, an election etc.) and work forwards or backwards from there.

People tend to remember relative change rather than absolute change. For example, rather than asking people what their income is this year and what is was last year, it might be more useful to enquire whether their income has changed compared to last year. The researcher might find it useful to supplement the interview part of the oral history exercise with the provision of visual material, such as photographs of key events or people in order to stimulate memory.


Pratt, B. and Loizos, P. (1992) Choosing Research Methods: data collection for development workers (Oxford, Oxfam).

Participatory Maps

Method type Community-based; participatoryData type QualitativeSuggested sampling strategy

Purposive

What is a participatory map?

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Participatory mapping is used to produce a simple visual description of the spatial geography of the area in which research is taking place. As participants themselves are encouraged to construct the map, this gives people the chance to point out to researchers the local features and landmarks that they consider to be most important.

Participatory maps are useful when:

You are interested in issues relating to the physical environment e.g. farming problems, access to water.

You are new to a community and want to learn more about its main landmarks and features.

You want to generate a simple baseline description of company-related affects and activities in the community, and to identify major issues for future research.

You are new to a community and want to engage informants in a simple exercise that can act as an ‘ice-breaker’.


To produce a community map a large open space should be found and the ground cleared. It is easiest to start by placing a rock or leaf to represent a central and important landmark. Informants are then asked to highlight important features in the area in relation to this central landmark.

Participatory maps displaying villages or towns can be supplemented with a social ranking exercise, a technique that allows the researcher to gather information on the relative standing of members of the area whilst avoiding any questions about absolute levels of wealth. In this case, the group drawing the map will be asked to indicate the relative social status of families using different markers (such as beans, seeds or pebbles).


Guijt and M. K. Shah (eds.) (1998) The Myth of Community: Gender Issues in Participatory Development (London, Intermediate Technology Publications).

Drawing a Participatory Map

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Source: Reed, Mark, ACES, http://homepages.see.leeds.ac.uk/~lecmsr/002_00A.JPG

Participatory Social AuditingMethod type Community-based; traditional and participatoryData type Quantitative and qualitativeSuggested sampling strategy

Purposive

What is participatory social auditing?

Social auditing is a way of measuring and reporting on an organisation’s social and ethical performance. An organisation which takes on an audit makes itself accountable to its stakeholders and commits itself to following the audit’s recommendations.

A participatory approach to a social audit makes use of a range of participatory methods to ensure that the views and voices of workers, especially women workers, are heard.

Participatory social auditing is useful when you want to:

Raise awareness of the standards and principles of the code of labour practice among local producers and workers.

Provide an opportunity, especially for workers who would have had little or no previous involvement in audits, to become familiar with the various steps in the process, their role in aspects of the final audit, and the participatory tools and techniques that can be used.

Tips for data collection and analysis

More genuine participation by workers requires the involvement of workers, representatives or shop stewards at site level, and sector trade unions and NGOs, both in awareness creation and the auditing process. Central to a participatory approach is the process involved, of which the final social audit is an outcome rather than the means in itself.

Prior to the final audit report, it is recommended that a general meeting be held with management, and worker representatives (including women workers) where possible, to inform both management and employees of its details.


Auret, D. and Barrientos, S. (2004) ‘Participatory Social Auditing: a practical guide to developing a gender sensitive approach’, IDS Working Paper 237.

Auret, D. and Barrientos, S. (2006) ‘Participatory Social Auditing’, in Auret, D. and Barrientos, S (eds.) Ethical Sourcing in the Global Food System (Earthscan, London).

Participatory Value Chain AnalysisMethod type Community-based; traditional and participatoryData type Quantitative and qualitativeSuggested sampling strategy

Purposive

What is participatory value chain analysis?

Oxfam document.doc


Participatory value chain analysis is a key method for identifying and assisting poor and disadvantaged stakeholders in value chains. The method is founded upon the principle of ensuring the participation of the most vulnerable and supporting their rights to information and communication. This is made possible by utilising visual and mapping techniques that are accessible to all stakeholders. Participatory value chain mapping typically involves the following steps:

Mapping the value chain (the different types of activity, geographical location, and actors in different roles at different levels). Attention should be paid here to hidden workers in the value chain, especially women.

Following up with quantitative and qualitative research investigating the relative distribution of ‘values’ and the reasons for inefficiencies and blockages in the chain.

Identify potential ‘leverage’ points for upgrading the chain as a whole and/or redistributing values in favour of those at the bottom of the pyramid.

Participatory value chain analysis is useful when you want to:

Identify and generate information on poor and disadvantaged stakeholders. Identify the governance structures that affect the ways in which values are

distributed between activities and geographical areas. Identify and evaluate potential interventions in the value chain for improving the

welfare of people living in poverty.


To kick-start a participatory value chain analysis a one-day workshop can be convened involving a number of key informants, including community building organisation (CBO) and non-governmental organisation (NGO) representatives.

A snowballing, purposive sampling strategy (see section on sampling in introduction above) can be adopted to identify stakeholder groups and subgroups in the value chain.

A number of the visual and diagram mapping methods listed here can be used within a participatory value chain analysis, such as Venn and flow diagrams.


Kaplinsky, R. (2001) ‘Globalisation and Unequalisation: what can be learned from value chain analysis?’, http://www.catie.ac.cr/econegociosagricolas/BancoMedios/Documentos%20PDF/what%20can%20be%20learned%20from%20value%20chain%20analysis-kaplinsky%202002.pdf

Bammann, H (2007) ‘Participatory value chain analysis for improved farmer incomes, employment opportunities and food security’, =http://peb.anu.edu.au/pdf/PEB22-3-bammann.pdf

Mayoux, L. (2003) ‘Trickle-down, Trickle-up or Puddle? Participatory value chains analysis for pro-poor enterprise development’, http://www.enterprise-impact.org.uk/pdf/ValueChainsAnalysis.pdf

Prioritisation Tools Prioritisation Matrix:

This prioritisation matrix can be used to help determine and prioritise strategic impact areas (Phase 1.2 of the MF). After using the table of questions in Phase 1.2 of the MF to identify

Oxfam document.doc

http://www.enterprise-impact.org.uk/pdf/ValueChainsAnalysis.pdf

http://peb.anu.edu.au/pdf/PEB22-3-bammann.pdf

http://peb.anu.edu.au/pdf/PEB22-3-bammann.pdf

http://www.catie.ac.cr/econegociosagricolas/BancoMedios/Documentos%20PDF/what%20can%20be%20learned%20from%20value%20chain%20analysis-kaplinsky%202002.pdf




strategic impact areas, the Project Team can help determine which of those areas to address in the study by completing a prioritisation matrix.

Plot ‘company priority’ on the x-axis, and ‘Oxfam/NGO priority’ on the y-axis. In this matrix, issues falling into zone 1 will be the most relevant to include in the study, whereas those falling into zone 2 can be excluded. Issues falling into zones 3 and 4 might be of interest depending upon the specific interests of Oxfam and the company.

Prioritisation Matrix for Determining Strategic Impact Areas

When prioritising strategic impact areas, you can plot ‘commercial benefits’ on the x-axis, and ‘impact on poverty alleviation’ on the y-axis. Such a matrix is illustrated below, with the areas of potential action identified.

Illustrative Matrix for Prioritising Strategic Impact Areas

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3

2

1

4

Oxfam/NGO priority

Company priority


Rapid Market Analysis Method type Macro-policy; traditional and participatoryData type QualitativeSuggested sampling strategy

Purposive

What is rapid market analysis?

Rapid Market Analysis is a package of methods that is often utilised by NGOs to identify whether there are potential sustainable economic activities for small-scale producers in the target area and what these are. The method relies on Oxfam’s market model (see diagram below) that divides the market into three layers: market chain, (dis)enabling environment, and market services. These three layers are expanded upon below:

The market chain identifies all the stakeholders that are involved in trading a product as it moves from producer to consumer. A value chain typically consists of producers, traders, processors, and retailers.

The (dis)enabling environment identifies all the key external factors impacting on the market chain. These external factors may be physical (such as infrastructure and natural resources); policies (such as legal frameworks and tariffs); practices (such as corruption and local customs) or attitudes and beliefs (such as consumer trends and beliefs about women’s roles).

Market services are needed for the market chain to function and develop effectively. Examples of market services include transport, insurance, and business development.

Rapid market analysis is useful when:

Oxfam document.doc


You need an overview of a market structure, and the main stakeholders/operators within it, focusing on smallholders living in poverty.

You have limited time and resources to conduct the analysis.


The final model should be as accurate as possible, but need not involve weeks of research. It can be developed using the study team’s and researchers’ prior knowledge of the particular sector in which they are working, and using information supplied by partners or potential partners. Other organisations already working in the sector may also be able to provide relevant information.

To collect additional primary data rapid market analysis can be undertaken through many of the participatory and standard methods set out in this list. For example, flow and Venn diagrams can be constructed with the participation of poor smallholders to better understand their positions and experiences in markets. Where possible rapid market analysis should involve or be undertaken by target producers. The analysis should be facilitated by the market specialist and, if feasible, should involve or interview other local market actors.


Jaspars, S. (2006), ‘From Food Crisis to Fair Trade’, ENN Special Supplement Series No. 3.

CIAT (2007) ‘Identifying Market Opportunities for Rural Smallholder Producers’, Good Practice Guide 3.

Oxfam's Market Model

Oxfam document.doc


Stakeholder AnalysisMethod type Community-based; traditional and participatoryData type Quantitative and qualitativeSuggested sampling strategy

Purposive

What is stakeholder analysis?

Stakeholders are people, groups, or institutions with interests in company activities. The process is essentially one of analysing information about the various stakeholders to assess their interactions with the company and the likely responses to any change in company policy/practice. The process followed can be summarised as follows:

Identify and list all stakeholders (see MF Phase 2.3); Draw out the stakeholders’ interests; Assess stakeholders’ power and influence; Assess which stakeholders are important for which company operations; Assess the assumptions which must be made about what the role each stakeholder

group will play in any changes to company policy/practice.

Analysing stakeholders’ power and influence is not a straightforward process. One approach involves identifying and mapping the amount of freedom of action or room to manoeuvre contained within social boundaries, as well as the resistance to change of such boundaries. This approach can be illustrated with the following example. Suppose a ‘disempowered’ woman attempts to extend her freedom of action by securing a better contract with her employer. There are many ways in which it is possible to examine the powers that limit her ability to secure a better contract. These can be thought of in terms of ‘power over’, ‘power within’, ‘power with’ and ‘social values/norms’.

Power over: Open conflict - The woman wants a better contract but there are other, more powerful people or social norms that stop her. Who? Why? How immutable is the opposition? Suppressed conflict: Is it impossible for the woman to say what she wants? Why? Hidden conflict - Is it impossible for the woman to even develop the desire to negotiate a better contract? Why? Power within:What does a girl need to do in order to pursue education? Power with:Are there any potential allies? Social values/norms:What are the factors that limit women’s ability to negotiate a better contract? How do the above values differ for women from different areas, different ethnic groups, etc?

In many cases direct discussion of the above issues with respondents might be tricky and sensitive. Instead, it might be possible for researchers to investigate a number of specific factors that indicate relative power and influence. Some examples of these are summarised in the table below.

Assessing Stakeholders' Power and Influence (adapted from Laws, 2003)

Within and between formal organisations For formal interest groups and primary stakeholders

Legal hierarchy (command and control, budget holders) Social, economic, and political status Authority of leadership (formal and informal, charisma, Degree of organisation, consensus,

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political, familial, or cadre connections) and leadership in the group Control of strategic resources (e.g. suppliers of hardware or other inputs)

Degree of control of strategic resources

Possession of specialist knowledge (e.g. engineers) Informal influence through links with other stakeholders

Negotiating position (strength in relation to other stakeholders)

Degree of dependence on other stakeholders

Stakeholder analysis is useful when you want to:

Identify various groups that have an interest in the company. Better understand stakeholder interests, needs and capabilities. Understand the interests, needs, and capabilities of other groups and identify

opportunities and threats for/to changes in company policy/practice.


The information needed to base a stakeholder analysis on can be collected through all the usual methods – interviews, observation, and participatory techniques. Qualitative methods are recommended for the exploration of particularly sensitive issues concerning power and influence, including semi-structured/unstructured interviews and focus groups. Observation is also a useful method to document the operation of power on the ground.


Laws, S. (2003) Research for Development (London, Sage), Ch.18. Mosedale, S. (2003) ‘Towards a framework for assessing empowerment’.

SurveysMethod type Community-based; traditionalData type QuantitativeSuggested sampling strategy

Random and/or purposive

What is a survey?

A survey is a list of questions the researcher asks respondents. Responses to questions in the survey can either be pre-coded or ‘open’. Pre-coded questions give the respondent a choice between a set of categories determined by the researcher. There are numerous ways to pre-code responses, for example through lists, ranking, or scales. Pre-coded responses limit the scope of the respondents answer, but are easier to analyse than open responses.

Surveys are useful when:

You need information from large numbers of respondents. You know exactly what data you need. The information you need is fairly straightforward, and you want it in a standardised

format.


Setting up a survey can be an intensive administrative task. Surveys should be very carefully prepared.

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Pilot any questionnaire carefully, including timing how long it takes to answer carefully.

The sample must be chosen with care (see the section on sampling in the introduction above).

There are two sample surveys provided in the Resources and Tools section of the OPFM, with further guidance for researchers on how to conduct the survey.


Law, S. (2003) Research for Development (London, Sage), Ch. 17.

TimelinesMethod type Community-based; participatoryData type QualitativeSuggested sampling strategy

Random or purposive

What is a timeline?

A timeline is used to understand the history of a community, and to capture broad changes in the life of the community as a whole or individuals within it. Timelines can also be used to stimulate discussions on how those changes occurred and what affects they had on peoples’ lives. This is normally done by asking people to recall important events in the past and then to reconstruct history by adding other events and processes of change.

One specific type of timeline is the seasonal calendar. This can be used to examine how peoples’ lives have changed over the course of a year. In such an exercise the informants themselves choose what kinds of seasons to represent and the types of factors that change in relation to these seasons.

A timeline is useful when you want to:

Build rapport with a group, or as an ‘ice-breaker’ exercise with a new community, due to its relative simplicity.

Understand the history of a particular community, or how it is moving into the future. Analyse sources of conflict amongst people, and how these have evolved over time. Situate a particular company impact or event in a longer historical timeframe.


To create a timeline a line can be drawn on the ground or on paper, with one end representing the present and the other some predetermined date. Participants can be asked to represent various key events and activities by placing markers along the timescale.


Guijt, I. (1998) ‘Questions of Difference: PRA, Gender and Environment’, in IIED Participatory Methodology Series (UK, International Institute for Environment and Development).

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Transect WalksMethod type Community-based; participatoryData type QualitativeSuggested sampling strategy

Purposive

What is a transect walk?

A transect walk takes place over an area to observe and document the similarities and differences of socio-economic and biophysical features.

Transect walks are useful when you want to:

Investigate the physical features of an area where there is spatial diversity. Relate discussion to the features being observed, as this can seem less intrusive

than if the same question is asked in a more formal interview situation. Compare the ideas and attitudes of different groups, in this instance NGO and

community groups. Find out what problems exist and what solutions have already been tried.


Before conducting a transect walk it is important to consider what factors will be taken into account (e.g. environmental impacts, mitigation measures etc.) and the route the walk will take. If the territory is relatively flat, a path should be traced which will allow for the widest variety of features/activities.

It is useful to include a high point of the territory if there is one, or the spot from which there is the best view of a large area, as it is often possible to see boundary markers, different activities, etc. from such a height. As the walk proceeds, questions relevant to the area being crossed should be asked and phenomena of interest observed. Transect walks can be used as a follow on exercise from participatory maps where participants specify on the map where they want to walk.


Guijt, I. (1998) Questions of Difference: PRA, Gender and Environment, in IIED Participatory Methodology Series (UK, International Institute for Environment and Development).

Mahiri, I. O. (1998) The Environmental Knowledge Frontier: transects with experts and villagers, Journal of International Development, 10, pp. 527-537.

Value Chain Analysis (VCA)

Method type Macro-policy; traditionalData type QuantitativeSuggested sampling strategy

N/A

What is value chain analysis (VCA)?

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The value chain describes the full range of activities that are required to bring a product or service from conception, through the different phases of production (involving a combination of physical transformation and the input of various producer services), delivery to final consumers, and final disposal after use. The activities in a value chain can be grouped under two headings: primary activities, which concern trading and/or adding value to a particular product, and secondary activities, which are not directly involved in production but which help move the product along the value chain (these are considered market services in Oxfam’s market model). A number of common primary and secondary value chain activities are described in the table below

Primary and Secondary Activities in a Value Chain (adapted from tutuor2u.net)

Activity Description

Primary Inbound logistics All those activities concerned with receiving and storing externally sourced

materialsOperations The manufacture of products and services - the way in which resource inputs

(e.g. materials) are converted to outputs (e.g. products)Outbound logistics

All those activities associated with getting finished goods and services to buyers

Marketing and sales

Essentially an information activity - informing buyers and consumers about products and services (e.g. benefits, use, and price)

Services All those activities associated with maintaining product performance after the product has been sold

Secondary Procurement This concerns how resources are acquired for a business (e.g. sourcing and

negotiating with materials suppliers)Human resource management

Those activities concerned with recruiting, developing, motivating and rewarding the workforce of a business

Technology development

Activities concerned with managing information processing and the development and protection of ‘knowledge’ in a business

Infrastructure Concerned with a wide range of support systems and functions such as finance, planning, quality control and general senior management

Value chain analysis can be broken down into three sequential steps:

Break down a market/organisation into its key activities under each of the major headings in the model;

Assess the potential for adding value via cost advantage or differentiation, or identify current activities where a business appears to be at a competitive disadvantage; and

Determine strategies built around activities where competitive advantage can be sustained.

VCA is useful when you want to identify:

A company’s core competencies and the activities through which it develops a competitive advantage.

Which value chain activities the company specialises in and which it outsources. When you have a large amount of economic data


This method requires good quality Company-level data to be effective.

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Supply chains are rarely linear and at each point in the chain there are usually several markets to which a producer or trader can sell.

Illustrative Value Chain

Venn DiagramsMethod type Community-based; participatoryData type QualitativeSuggested sampling strategy

Purposive

What is a Venn Diagram?

Venn diagrams (also known as institutional or Chapati diagrams) illustrate the extent to which individuals, organisations, projects, or services interact with each other or overlap and the importance of each, and their efforts, to the issue being evaluated.

Venn diagrams are useful when:

You want to explore which individuals and groups have an influence on decision-making.

You want to understand relations between village institutions and outside forces such as government services or development agencies.


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A Venn diagram exercise can begin with a discussion of which influential groups and key individuals exist, and how important they are to the participants. The diagram can be produced by tracing on the ground or on a large sheet of paper. If using paper, it can be helpful to cut different sizes and shapes to represent the different kinds of institutions (women’s and men’s committees, for example) and individuals. If the papers touch, this means that there is some interaction or overlap of membership between the two groups. If the papers are distant, this means that the groups rarely come into contact.

The cards identifying community individuals and groups should be placed inside a big circle that represents the village. The cards representing exterior organizations are placed outside the community circle, and arrows can then be drawn to show how outside organizations interact with community institutions. These arrows can be symbolised to represent reasons for contact, or the frequency or quality of that contact.


Guijt, I. (1998) Questions of Difference: PRA, Gender and Environment, in IIED Participatory Methodology Series (UK, International Institute for Environment and Development).

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Section 2. Data AnalysisData analysis involves interpreting findings, checking data collected, and identifying further issues or sources of information that will contribute to answering the research questions. Although there is no ‘correct’ way to do data analysis, the central task is to seek out patterns and trends within the data. It is important to note that there are important differences between qualitative and quantitative data analysis.

Qualitative data analysis is essentially a task of drawing from the data a set of key themes that summarise the important categories within the data, and looking at how these relate to each other. A number of techniques can be used during qualitative analysis, including ‘cut and paste’, card indexing, and ‘charting’.

Quantitative data analysis can involve examining number-based data in terms of, for example, matrices, coding, and percentages. It is also possible to analyse quantitative data statistically, examining numbers in terms of averages, means, modes, and measures of spread. If a complex quantitative analysis is required then it is best to get the advice of an experienced researcher, preferably a statistician.

Question to ask when thinking about data analysis are:

What are the different kinds of data that have been collected (e.g. transcripts, photos, official documents) and what are the analysis requirements of each?

Who is going to analyse the data? What process will be followed? Will the types of data analysis chosen adequately answer the study team’s research

questions? Will computer programmes be used to analyse the data? What are the advantages

and disadvantages of using a computer?

Questions to ask during analysis include:

Are different people saying the same thing? Are there clear patterns of difference, for example where women and men have

different points of view? Are there some exceptions to the patterns being found? Were men present while women were interviewed? Do they come from a different

income group from the women? Where do the main trends, contradictions and gaps lie in the data? Do they fit in with

what you expect? Are they the result of a fault in the design of the research or an error in the field? Do they mean the research has uncovered new information and ideas?

Is the analysis process uncovering the right information to answer the research questions and address the study goals?

Notes:

In qualitative analysis it is best for those who undertook the fieldwork to analyse the data. This will allow the researcher to bring their learning to bear directly on the process. If the researcher is not experience in data analysis they should get help from someone who is.

In quantitative analysis, it is possible to hand data over to a consultant to be analysed. However, this should only be done where the consultant has been involved in the design of the research or has a very clear idea of the study’s goals.

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There are advantages and disadvantaged to using computers to analyse data. On the one hand, a computer can introduce speed and flexibility into the research process. On the other hand, use of computer programs can take time to learn, can exclude others from the research process, and requires the use of expensive resources. There are numerous computer programmes that can be utilised to carry out data analysis, such as Excel or SPSS for quantitative data, and Microsoft Word for qualitative data. For qualitative analysis there might be a number of additional fieldwork notes and reports that the researcher can use such as a field diary and digital images. These supplementary resources are likely to be especially important where participatory methods have been utilised.

Further Information:

Further ideas and more detailed information are provided in chapter 20 of Laws, S. (2003) Research for Development (London, Sage).

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Section 3. Ensuring Quality in Research Practice Research EthicsIt is important that all research adheres to ethical principles. But research ethics are particularly important for PF Studies due to the involvement of people as participants.

The three core principles of research ethics are:

Respect - the researcher must recognize the capacity and rights of all individuals to make their own choices and decisionsBeneficence - the researcher’s primary responsibility is to protect the physical, mental and social wellbeing of the participantJustice - the researcher must ensure that the benefits for participants are at least as great as the risks

Putting the principles into practice:

These principles need to be reflected in each stage of the research, including designing the research, selecting participants, gaining their consent, conducting the research, and using the research findings.

1. Designing research

The research must be designed to reduce risks for participants and increase their potential benefits from its outcome. In particular, the research must be designed to protect vulnerable participants – for example children or women workers in a garment factory. Questions for surveys and interviews should be respectful and phrased in culturally appropriate language.

2. Selecting participants

Participants should not be involved in research that will only be of benefit to others – i.e. that has no benefit for them at all. Possible outcomes, such as a safer society or better working conditions in the longer-run, may be benefits if the individual participants consider them to be so. Some participants may feel a benefit simply from having the chance to tell their story. But it is up to them to decide whether or not this is a benefit.

No individual or group of participants should face more risks than benefits from participating. If the research is higher risk-than-benefit for participants, then it should be redesigned to reduce those risks.

3. Gaining the consent of participants

Researchers must gain informed and voluntary consent before doing research with participants. This means that the participants must:

Have the relevant information about what the research is Understand it, including the possible risks and benefits to themselves Be free to choose whether or not to participant, without inducement Give their consent, either written or verbal Have the right to withdraw from the research at any time

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The depth of this consent-taking process will depend on the topic of research and the extent to which it could impact on the participants’ lives. If research involves children (as defined by national law, or those under 18) then their parents or guardians must also give consent. It is best to get their written consent, in (the rare) case of disputes later. Special care must be taken when seeking consent from vulnerable groups, for example prisoners, or people with no access to healthcare. Researchers must ensure that no participants are forced to take part, for example by their boss, by their parents, or by village elders.

4. Conducting the research

Researchers should be qualified and/or trained for the task. They need to have good self-awareness and strong listening skills. Research should be conducted in places that are socially comfortable for the participant, and where they are able to speak freely.

If the participant has incurred direct financial costs for participating then they can be reimbursed, but they should not be paid to participate. The participants must be able to contact the researchers, either directly or through local partners. If a participant reports any serious adverse effects as a result of participating – such as losing their job, or being beaten up – then this must be reported to the Oxfam project manager by the researcher.

5. Using the research findings

The participants should be informed of how the research findings will be used, for example in the PF report. They must then be asked, and must be free to choose, whether or not:

They can be quoted in PF materials Their real name can be used in PF materials Their photograph can be used in PF materials

Their choices must be clearly recorded along with their testimony and/or photograph. If it is agreed that all or any part of a participant’s testimony should be confidential then that commitment must be clearly recorded and respected. If the testimony is to be made anonymous, or with a false name, make sure that any other identifying details are also changed.

AccessFor many methods negotiation is likely to be needed to gain access to respondents. This might mean talking to the chief of a village, writing formal proposals to public bodies, or meting with Company managers. It is important not to rush this process, as time is required to build trust.

Further information

ESRC Research Ethics Framework http://www.esrc.ac.uk/ESRCInfoCentre/Images/ESRC_Re_Ethics_Frame_tcm6-11291.pdf

Family Health International online training course on research ethics http://www.fhi.org/en/RH/Training/trainmat/ethicscurr/index.htm

Web Centre for Social Research Methods http://www.socialresearchmethods.net/kb/ethics.php

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http://www.socialresearchmethods.net/kb/ethics.php

http://www.fhi.org/en/RH/Training/trainmat/ethicscurr/index.htm

http://www.esrc.ac.uk/ESRCInfoCentre/Images/ESRC_Re_Ethics_Frame_tcm6-11291.pdf

http://www.esrc.ac.uk/ESRCInfoCentre/Images/ESRC_Re_Ethics_Frame_tcm6-11291.pdf

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