TECHNICAL GUIDANCE SHEET No.10
INTRODUCTION ON QUALITATIVE DATA AND METHODS
FOR COLLECTION AND ANALYSIS IN FOOD SECURITY ASSESSMENTS
Lezlie Morinière, (consultant), ODAN, World Food Programme – September 2007
Table of contents
1 – What are qualitative data? ...................................................................................................... 2
2 – What is the difference between qualitative and quantitative data? ................................... 2
3 – What are the main advantages and disadvantages of qualitative methods? ................... 3
4 – What are the approaches leading to qualitative data? ........................................................ 4
5 – How are qualitative approaches and qualitative data useful for food security
assessments? ................................................................................................................................ 5
6 – What types of qualitative data can inform on food availability, access and utilization,
and on the causes of malnutrition? ............................................................................................. 6
7 – What skills are needed to collect and analyse qualitative data?........................................ 9
REFERENCES ................................................................................................................................ 9
Annex – Emergency Food Security Assessment Conceptual Framework ............................ 10
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Lezlie Morinière, (consultant), ODAN, World Food Programme – September 2007
TECHNICAL GUIDANCE SHEET No.10
INTRODUCTION ON QUALITATIVE DATA AND METHODS
FOR COLLECTION AND ANALYSIS IN FOOD SECURITY ASSESSMENTS
This Technical Guidance Sheet (TGS) is intended to assist staff with little or no experience in
collecting and analyzing qualitative data for food security assessments. It does not aim to provide
guidance in the analysis of food security concepts per se, but rather in the use of qualitative data
for food security analysis. Readers are referred to TGS No.11 on Qualitative Data Collection and
Analysis for more practical guidance.
1 – What are qualitative data?
Qualitative data describes virtually any information that is not numerical in nature and often hard
or even impossible to quantify. Another way to consider qualitative data is as textual observations
that portray attitudes, perceptions or intentions. Qualitative data are typically expressed as words,
rather than numbers, and they are used to describe and provide meaning and context to a
situation --the story behind the statistics. More important than its expression (as words, not
numbers), qualitative data have a unique perspective (a look from the inside) and answer
questions such as ‘how’ and ‘why’ rather than ‘what’, or ‘how many’.
Qualitative data can also be obtained from quantitative methods. Vice-versa, quantitative
data can also be obtained from qualitative methods. The distinction between the two types
of approaches is often blurred because:
 All qualitative data can be coded quantitatively (assigned an arbitrary number or code)
 The interpretation of all quantitative data is based on qualitative judgement (understanding
and establishment of thresholds).
Main differences between the two approaches lie in the underlying objectives and
perspectives. See Table 1 in Section 4.
The following definitions are used in this TGS:
 Data are the products of a collection effort.
 Approaches describe the main types of data collection and analysis, driven by an overarching
objective. There are qualitative and quantitative approaches. ”Rapid” and “Participatory”
approaches tend to be mostly qualitative.
 Methods refer to the organization of data collection (examples include observations,
discussions, interviews or household surveys) or analysis (for example: memoing or coding).
 Tools describe the concrete or tangible elements that assist in data collection or analysis. Two
examples are questionnaires and recording devices.
2 – What is the difference between qualitative and quantitative data?
 Quantitative data are expressed in numbers, frequencies, rates or proportions; for example
the number of meals eaten daily, the number of respondents who answered a particular
question in a particular way, rates of malnutrition, proportions of income lost, etc.
 Qualitative data tend to reflect perceptions, opinions, intentions and observations.
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Qualitative data are more likely to provide a contextualisation of a particular problem—or insight
into how that problem affects a community. Qualitative data provide meaning to the quantitative
outputs (and vice versa); therefore, both should be present in all food security assessments.
It is generally accepted that qualitative data are more easily obtained during rapid appraisals than
quantitative data. However, as mentioned, rapid appraisal can be used to generate both
qualitative and quantitative data. During a rapid appraisal, quantitative data is not typically
measured or objective (i.e. an investigator may ask a village key informant how many sacks of
cereal an average household harvested, but s/he cannot count those sacks). However, this is
also the case with most food security data collected via sample surveys (e.g., the number of
shocks to which a community or household is exposed is reported but not counted).
It is often challenging to distinguish quantitative from qualitative data. One way to do so is to
review the objective driving the method or question that produced the data, as illustrated in the
examples in Box No.1.
Box No.1 - Examples of quantitative and qualitative data
Example 1:
 A mother is asked how many days her household has eaten meat in the past week and she answers "2",
this is a numerical answer (thus quantitative data). Because this does not attempt to capture attitudes,
perception or intention, and because the answer is expressed directly as a number, it is not considered
qualitative data.
 What an enumerator may have heard and observed while asking that question during a household
interview (more often a quantitative method), however, is richly laden with qualitative elements, such as
size, food storage, cooking items in and around the house, husband-wife dynamic, etc. If noted, these
become qualitative data. Enumerators should be encouraged to record this kind of information to enrich
the data collected and inform its interpretation.
Example 2:
 In a focus group (classic qualitative method, see Section 6), five men are guided to pile sort stones to
answer the question "where do you get your food?" The question is open-ended, which is a sign of
qualitative methods. The method is participative thus enforcing the qualitative approach.
 The answers that result, however, can be easily quantitative (i.e. "50% from production, 25% from the
market"…) and do not produce information on attitudes, perception and intentions. What is heard (or
taped) and observed while the process is happening can produce qualitative data, but the answer itself is
not qualitative.
The major distinction between the two is that qualitative approaches do not seek statistical
significance and thus, cannot be extrapolated without a certain level of critical judgement. Any
extrapolation of qualitative data to represent larger areas will inevitably be general and not
statistically rigorous. Qualitative approaches make up for lack of statistical rigor with rich
explanation and insightful understanding. Qualitative approaches are sometimes considered to be
less rigorous than quantitative approaches, but quantitative approaches have also been criticised
for their inflexibility, mechanical responses and results that do not offer explanation. In fact, both
approaches are necessary in food security assessments to complement, verify and triangulate
the information.
3 – What are the main advantages and disadvantages of qualitative methods?
Qualitative methods include:
 Observations: for example observations of the way populations interact with food (at home, at
the market, in the field);
 Semi-structured / unstructured interviews with key informants;
 Focus group discussions.
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The main advantages of qualitative methods include:
 opportunity to understand cultural differences;
 engagement of communities in a participative way;
 can be used to improve both the quality of interaction with beneficiary populations and crosscultural communication (between beneficiaries and outsiders);
 possibility to rapidly obtain useful information regarding a disaster situation;
 opportunity to explore the reasons behind and/or causes of identified phenomena;
 incorporation of the perception of affected communities.
The main disadvantages of qualitative methods include:
 need for skilled interviewers and facilitators who are able to guide discussions, and analyse
qualitative data for decision-making purposes (for example on the need and type of assistance
required);
 data cannot rigorously be extrapolated for larger populations; the tendency to generalise
qualitative findings across large population groups (e.g., farmers, nomads, etc) should be
addressed cautiously;
 subjective results, difficult to verify results without triangulation of many sources;
 time and cost to invest in the development of suitable methods, need to adapt them to every
new context and challenges to analyze the data (see Technical Guidance Sheet No.11).
It is important to employ both quantitative and qualitative methods as they complement each
other’s strengths and weaknesses:
 Qualitative methods might be used to explore issues prior to an in-depth assessment,
enabling a better understanding of what closed-ended and focused questions need to be
asked as part of a quantitative study or a new monitoring system; the qualitative data obtained
can also help provide contextual explanations to a set of quantitative findings.
 At the same time, qualitative methods can also used after a quantitative study—to clarify
and/or further explore a particular theme.
4 – What are the approaches leading to qualitative data?
As noted, qualitative data can be obtained using either qualitative or quantitative approaches.
Table 1 illustrates the main characteristics of both.
Table 1 – Comparison of qualitative and quantitative approaches
Objective
Data format
Answers the
questions
Perspective
Study design
and instruments
QUALITATIVE APPROACH
To explore, understand phenomena
Textual mostly, but also numerical
and categorical
How?
Why? (open-ended)
 Looks at the whole context, from
the inside
 Can lend itself to community
participation if time allows
Flexible, the assessor is also an
instrument
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QUANTITATIVE APPROACH
To quantify, confirm hypotheses
Numerical and categorical mostly, but
sometimes also textual (observations)
What?
How many? (generally closed-ended)
Looks at specific aspects, from the
outside
Fixed, standards control for
assessor’s bias
Qualitative approaches aim to explore and understand while quantitative approaches strive more
often to confirm hypotheses. Qualitative approaches are based on flexible observation and
discussion while quantitative approaches are most often based on fixed formal surveys.
Qualitative approaches include participatory appraisal and rapid appraisal. Although participatory
appraisal is designed to empower communities in their own development, rapid appraisal is often
called participatory without honestly achieving participation. They can be used in rapid or in-depth
assessments.
 Participatory approaches aim to gain deeper understanding of a situation, and often to
increase knowledge, skills, and capacities of focus group, community mapping or other
beneficiaries;
 Rapid appraisals are similar to these, but are less participatory; they offer quick, low-cost ways
of generating qualitative data (e.g., direct observation or transect walks).
Many assessments claim to use participatory approaches but, in reality, do not engage the
community. While participatory methods may help communities take ownership of proposed
interventions, they are difficult and rarely appropriate in rapid food security assessments.
5 – How are qualitative approaches and qualitative data useful for food security
assessments?
Qualitative data is not just an explanatory add-on to quantitative data collection. In rapid onset
emergencies, and when time and/or access are limited, qualitative approaches frequently form
the core of the assessment. If applied properly, such approaches can produce high quality
information that feeds the whole programme planning process.
In the context of a food security assessment, qualitative approaches and data aim to understand
food and livelihood security by determining who is, and who is not, food secure, and why.
Incorporating perceptions of livelihoods and food security by both those who are and who are not
food secure will greatly enrich the analysis. In general, qualitative approaches can be used within
an assessment when:
 The causes of food insecurity are unknown and it is necessary to generate (rather than
confirm) hypotheses; for example, in a brand new crisis situation poorly understood;
 A broader understanding of the nature of a food security problem is required on a particular
topic; for example, quantitative data do not suffice to explain the causes of malnutrition from a
previous anthropometric survey, or from secondary data analysis
 Information is needed about attitudes linked to food and livelihood security choices or
priorities, perceptions and intentions regarding food security; for example, why people behave
in a certain way to achieve their level of food security;
 In volatile contexts, such as conflict and continuous displacement, making quantitative data
(such as household surveys) rapidly outdated if even feasible to collect.
 When time and funding are less than sufficient to conduct comprehensive food security
assessments, it is generally accepted that qualitative data are more easily obtained during
initial and rapid assessments, than purely quantitative data; however –because
comprehensive is not synonymous with quantitative-, all food security assessments should
seek to combine qualitative and quantitative approaches, to the extent possible.
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6 – What types of qualitative data can inform on food availability, access and utilization,
and on the causes of malnutrition?
Qualitative data can be collected on all food and nutrition security aspects (see the Food Security
Conceptual Framework in Annex). Table 2 below shows the variety of qualitative data that can be
obtained using different qualitative methods (observation, discussions, semi-structured
interviews) to inform on each element in the conceptual framework. Please note that these are
only illustrative examples and are in no way exhaustive.
It is generally understood that structured questionnaires seek quantitative data and are not
discussed in detail here except when qualitative observations accompany them.
Table 2 - Examples of qualitative data collected from observations, discussions and
interviews, following the Food Security Conceptual Framework (see Annex)
METHODS
Observation

Visual records which become
qualitative data when noted

Discussion
Community
discussions (CD)
Focus group
discussion (FGD)


Interview
key informant semistructured interview (KII)
Household structured
interview (HHSI)
FOOD AND NUTRITION SECURITY OUTCOMES (examples)
Nutritional
Status
Mortality
CD: inventory major
health problems
Observe children for physical
signs of kwashiorkor or
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severe emaciation
FGD with mothers to gain
insight on major causes
CD: list most common
causes of death in village
In communities, observe
fresh graves or local funeral
rites to explore the burden
(e.g. financial, food-related)
on livelihood security.
FGD with families having
recent death of a
productive member to
explore strategies to
minimize the economic
burden
KII with local nurse on
traditional treatment of
malnutrition
KII with local doctor on major
causes
IMMEDIATE CAUSES OF FOOD INSECURITY AND MALNUTRITION (examples)
CD: open ended
brainstorming on coping
strategies;
Observations of available
utensils, and techniques
mothers use in handling food
and preparing meals.
FOOD
UTILIZATION
FGD: historical and
seasonal calendar (useful
to track birthdates if an
anthropometric survey
accompanies the
assessment)
Observe social dynamics
between husband and
wife/wives regarding food
ownership / storage or
between caste/ethnic groups.
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KII with local teacher to
understand how education
may play a role in local food
insecurity
HHSI: assess relative
importance of common food
items consumed among
various wealth or food security
groups, using open ended
questions (pre-coding of
answers may be done
however)
Inferences on the nutritional status based on observations of the physical appearance of individuals require
experience and should be done by staff with a health or nutrition background. Caution is required in drawing
conclusions based on such observations.
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METHODS
Observation

Visual records which become
qualitative data when noted
Health practices

CD: pile sorting on major
health problems
Observations of handicapped,
and elderly (vulnerable
groups)
Care practices
Observations at local clinics:
equipment, infrastructure,
regularity of clientele,
interactions between or with
clinic staff and populations.
Individual
dietary intake
Observe childhood weaning
practices (although rarely
feasible during rapid
assessments).
Discussion
Community
discussions (CD)
Focus group
discussion (FGD)
FGD with HIV victims on
major concerns and
priorities
CD: gain general
impressions on main
social concerns for village


Interview
key informant semistructured interview (KII)
Household structured
interview (HHSI)
KII with clinic staff to glean
impressions and concerns of
service quality
KII with female elders to glean
perception of cost/quality of
health care and water/san
FGD with mothers to
glean perceptions on the
importance of care/water
vs. food, using pile sorting
HHSI: female-headed
households to explain care
challenges, using open ended
questions (pre-coding of
answers may be done)
FGD with mothers of
poorest households to
explore child feeding
practices
KII with local clinic staff to
understand trends in child
feeding practices
UNDERLYING CAUSES OF FOOD INSECURITY AND MALNUTRITION (examples)
Household-level
food
consumption
FOOD ACCESS
CD: global pile sort on
major sources of food
consumed (production,
market, etc.) and
expenditures
Look for stoves, cooking
utensils and cooking fuel
CD: prospects for
household employment
and income generation
activities, food/cash
receipts
Observations of food stocks
and handling in nearby
markets, or of trucks and
other transport mechanism.
FGD with one rep from all
groups (M/F /
age/livelihood) to group all
households into 3 levels
of relative wealth
En route, observations of
road quality.
Household
livelihood
assets and
strategies
KII with teacher to learn about
what school children are
typically given for breakfast
KII with traders and sellers at
market to understand trends,
source regions and constraints
HHSI: with those practicing a
precarious livelihood to help
describe limits on and
sustainability of coping
strategies employed, using
open ended questions (precoding of answers may be
done)
CD: brainstorm on all
livelihood groups
represented in a village
Observations of gender
practices in different
livelihoods groups.
FGD: pile sort with each
livelihood group on
importance of income
generating activities
During a household survey,
observe signs of diverse
strategies.
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KII: discussion with fisherman
regarding recent trends
METHODS
Observation

Visual records which become
qualitative data when noted

Discussion
Community
discussions (CD)
Focus group
discussion (FGD)


Interview
key informant semistructured interview (KII)
Household structured
interview (HHSI)
BASIC CAUSES OF FOOD INSECURITY AND MALNUTRITION
FOOD
AVAILABILITY
CD: open ended
brainstorm on foods
grown by major livelihood
groups
Observations of cultivated
fields, of farmers actively
sowing or harvesting during a
transect walk.
FGD with fishermen to
understand evolution of
local catch and its
contribution to their food
security
During a household survey,
observations of household
food stocks.
Policies,
institutions and
processes
Observing who is living
where, to ascertain if there is
marginalization of specific
groups within a community
Hazards and
shocks
Observe the effects and
impact of hazards (e.g., water
levels, houses destroyed,
etc.), or preparations for an
imminent hazard (such as use
of alarm systems or cyclone
shelters).
KII: transect walk with village
chief / admin officials
HHSI: with poorest households
to understand land tenure
problems, using open ended
questions (pre-coding of
answers may be done)
CD: open-ended listing of
institutions, NGOs active
in the neighbourhood
KII: flexible interview with local
authorities to glean perception
of agricultural policy impact
FGD: Venn diagram of all
village-level players in
food security
HSSI: weight the awareness of
and importance given to
various market institutions
CD: open-ended inventory
checklist of all hazards
occurring in past 5 years
KII: interview local disaster
manager to learn about
response efforts to date
FGD with survivors of
earthquake to understand
priority needs
During a household survey,
note emotional strain while
collecting information on
violent conflict.
If a food security assessment aims to understand the needs of the most vulnerable, qualitative
methods can help to rapidly group village households into levels of wealth (e.g., poor, less poor or
non-poor), or degree of food self-sufficiency (e.g., stocks for 12 months, 6 months or 3 months).
This allows Focus Groups to be subsequently organized with members of a single group, or indepth household surveys to start directly with the households considered to be the most
vulnerable. In this manner, time can be invested on those mostly likely to need assistance (the
poorest group) and local perceptions are utilized.
Time allowing, Focus Groups or interviews with more than one of the groups (asking the same or
similar questions to each) enable a comparison between the groups, thereby testing the validity of
2
village perception. This process, often called "wealth ranking", and many other tools and
techniques are detailed below.
2
There are several unresolved issues related to wealth ranking. Although relatively easy to identify the
extremes (the richest and the poorest), the middle class is identified with difficulty.
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7 – What skills are needed to collect and analyse qualitative data?
A facilitator is all-important in both collection and analysis:
 in collection: to extract accurate information from respondents;
 in analysis: to guide the teams through triangulation sessions.
Besides facilitators, other important profiles required for qualitative data include good trainers and
excellent translators / interpreters.
In the collection of qualitative data, the most useful skills are observing, listening and asking
questions in the most appropriate way to elicit an honest response. These skills may require
intensive training; recording these insights in a useful way that can later be retrieved (especially
by someone who was not present during the collection effort in a given village) demands a high
degree of expertise. Tool design also requires a high degree of expertise.
Examples of skills required for adequate ‘observation’
 In an area where the linkages between the harvest and fodder for livestock is an important issue, staff
need to be trained to look at fodder stocks, and ‘observe’ the differences in color, so they can differentiate
fodder from a previous harvest and that from a new one. This will give the sense of how harvests have
been – something that would have been completely missed if the assessor just merely ‘saw’ fodder
stocks.
 Another example is looking at livestock condition – a bony cow is not necessarily in poor condition, you
have to look at the rump and hollows on its back.
 Similarly, thinness in humans does not necessarily mean malnourished.
Sensitive topics (e.g., physical abuse in conflict zones, etc.) require other special skills to break
down cultural barriers and obtain useful information. General communication skills are key, as
well as high cultural sensitivity. Gender plays an important role in collecting and analyzing
qualitative data on sensitive topics, and an appropriate gender team composition must be
ensured.
Qualitative data analysis is challenging. Because there are very few set rules (as in statistics),
qualitative data collection, interpretation and analysis are crafted from experience. Careful design
and adherence to tools and adequate communication are the first step to assure insightful data
collection and qualitative analysis. Technical Guidance Sheet No.11 provides additional advice on
the design, collection and analysis of qualitative data.
REFERENCES
Kennedy, E. 2003. Keynote Paper: qualitative measures of food insecurity and hunger. FAO Conference on
Measurement and Assessment of Food Deprivation and Undernutrition Proceedings of the
International Scientific Symposium, Rome.
World Food Program. How to Consolidate, process and analyze Qualitative and Quantitative Data. United
Nations WFP Office of Monitoring and Evaluation.
Center for Refugee and Disaster Studies 2000. Training in Qualitative Research Methods for PVOs and
NGOs (& Counterparts). John Hopkins University School of Public Health.
Emerson, R.M., 2001. Contemporary Field Research: Perspectives and Formulations. 2001. Waveland
Press.
Shensel, S.L., J. Shensel and M. Lecompte, 1999. Essential Ethnographic Methods: Observations,
Interviews and Questionnaires. Ethnographers Toolkit. Altamira Press.
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Annex – Emergency Food Security Assessment Conceptual Framework
Immediate
Causes
Outcomes
EMERGENCY FOOD AND NUTRITION SECURITY (EFSA ) CONCEPTUAL FRAMEWORK
Mortality
Nutritional status
Disease
Individual dietary intake
Health
practices
d
iliz
ut
Feeding
practices
o
Fo
Household-level food
consumption
io
at
Underlying Causes
n
Household food
access
Care
practices
Health access and
environment
HH livelihoods assets and strategies
HH food
production, gifts,
transfers
HH cash
earnings, loans,
savings, transfers
Intra-household
control over
resources
Education
level of HH
members
Water,
sanitation,
housing
Basic Causes
Policies, institutions, processes
Food availability
Agroecological
conditions
Markets
availability and
access
Agricultural
services
Policies
Hazards, shocks
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Education
services
Security
Health
services