Assistance Delivery

Indicator Phrasing

% of beneficiaries reporting that humanitarian assistance is delivered in a safe, accessible and accountable manner

Indicator Phrasing

INDICATOR PHRASING: % of beneficiaries reporting that humanitarian assistance is delivered in a safe, accessible and accountable manner

What is its purpose?

Protection of emergency-affected population must be one of the key aspects of humanitarian assistance. This indicator therefore measures the proportion of the target population who report that the provided assistance was delivered in a safe, accessible and accountable manner.

How to Collect and Analyse the Required Data

Collect the following data by conducting individual interviews with a representative sample of the target group members. The sample needs to have a proportional representation of women and men (if relevant, also other groups, such as certain ethnic groups).



Introduction: Now I would like to ask you several questions related to your experience of accessing and receiving [specify the assistance] from [specify who delivered it].


Q1: Can you please show me on this paper which picture best represents how safe you felt when coming for [specify the assistance]? [explain the meaning of each picture on the scale – see attached below]

A1: very safe / fairly safe / rather unsafe / very unsafe


Q2: Can you please show me on this paper how easy or difficult it was to come for [specify the assistance]? [explain the meaning of each picture]

A2: easy / a bit difficult / very difficult / impossible


Q3: When accessing [specify the assistance], were you given any way of how to provide feedback or complaints on the quality of [specify the assistance], such as any [specify various options – phone number, e-mail address, contact of a responsible person]?

A3 Select one of the following:

1) does not remember

2) was given a way of providing feedback/complaints

3) was NOT given way of providing feedback/complaints

4) was given a way of providing feedback/complaints but no one responded when I used it


To calculate the indicator’s value. 

1) Count the total number of respondents who:

-   said that they felt “very” or “fairly” safe when coming for the assistance;

-   at the same time said that it was “easy” or “not too difficult” to come for the assistance; and

-   were given a functional way to provide feedback/complaints on the quality of the assistance (if they did not remember, exclude the question from the data analysis – see comment below)


2) Divide the number of respondents who provided the above listed responses by the total number of respondents. Multiply the result by 100 to convert it to a percentage.


Disaggregate by

Disaggregate the data by gender, age groups, ethnicity, persons with disability and other categories relevant to the local context.

Important Comments

1) It is recommended that instead of asking people whether they felt “very safe”, “fairly safe”, “rather unsafe” or “very unsafe”, you use a visual scale (see example below) where the enumerators ask people to indicate the face that best represents their feelings (the same applies to measuring the accessibility of the provided assistance). It is important that the enumerators always clearly explain the meaning of the scale (the most positive face meaning feeling “very safe”, the most negative feeling “very unsafe”). Before you decide to use the scale, pre-test it among the target group members, so that you are sure that it is appropriate to the local context and people easily understand the correct meaning of each symbol.


2) Unless you collect the data shortly after the given assistance was provided, it is likely that some people will not remember whether they received information about the Feedback Response Mechanism (FRM) or not. In this case, you will have to analyse their responses related to the safety and accessibility only. When reporting on the indicator’s value, always acknowledge that the last question had a smaller number of respondents who were able to say whether they knew about CRM or not and, as a result, the FRM-related data has a larger margin of error.


3) If you are able to use such data for your current or planned programming, also assess why some people did not feel safe and why it was difficult for some people to access the provided assistance.

This guidance was prepared by Tearfund ©

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