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Principle SIX

Practise data collection methods that are accessible for diverse entrepreneurs


6. Principle six

Practise data collection methods that are accessible for diverse entrepreneurs

Ensure inclusivity and equity in your data collection methods by purposely making data collection tools and processes accessible for a wide range of entrepreneurs from diverse backgrounds, abilities, and experiences.

Ensure inclusivity and equity in your data collection methods by purposely making data collection tools and processes accessible for a wide range of entrepreneurs from diverse backgrounds, abilities, and experiences.

Home 5 The IMPES Principles 5 Principle Six: Practise data collection methods that are accessible for diverse entrepreneurs
6.1 Demonstrate sensitivity towards gender, culture, inclusivity, and other diversity factors within your data collection methods

Entrepreneurs may not want to share some information. Take the time to understand the context of the concern, fear, or hesitancy. Consider the diversity of your own team, who are collecting the data from entrepreneurs, and how you can ensure it is done in a respectful and sensitive way. Ensure that you are communicating clearly and transparently with entrepreneurs about why you are collecting this data and what it will be used for. 

Wherever possible, representatives of diverse groups should be involved as active participants and decision-makers at every stage of the data collection process. This may require providing capacity building, training, or committee recruitment to those wishing to take part in data collection. For example, an ESO might create a project consultative or advisory committee with local people with disabilities and/or work with a local Disabled Peoples’ Organisation as a mechanism to support representation in the data collection process.

6.2 Consider whether your data collection tools are accessible and inclusive

Take into account the factors that could impede data collection and have alternative plans and support ready. Factors such as digital literacy and skills, disability, gender, and access to the internet can affect how (and to what degree) an entrepreneur can fully participate in data collection methods.

6.3 Acknowledge and accommodate for existing power imbalances that may exist within your data collection methods

Consider whether surveys, interviews, or other data collection methods may be intimidating or if there are other power imbalances that may make people uncomfortable or respond inaccurately. Are interviewees responding positively because they think it is what you want to hear? Are you conducting interviews in the local language and creating a safe space for honest feedback?

6.4 Disaggregate data by organisation, sex, gender, class, disability, ethnicity, and other diversity factors as much as possible

Sex-disaggregated data tells a story of how people identifying as men, women, non-binary, or other sex or genders are impacted (positively or negatively) by an ESO’s programs. 

This can be particularly useful when considering metrics such as ‘jobs created’ by a business. Are women accessing employment opportunities to the same extent as men? Are they more or less likely to be full-time, equally paid jobs?  

Failing to disaggregate project data can have negative consequences. For example, failing to recognise gaps in participation or outcomes for specific groups of people can perpetuate or further contribute to existing societal inequalities.

Additional considerations such as religion, disability, and ethnicity as well as other factors can provide deeper insight into who is being impacted by an ESO’s work and how.

6.5 Practise responsible data privacy and be transparent about this with entrepreneurs

Ensure confidentiality of data through internal policies, secure databases, and controls. Communicate this with your team internally and with entrepreneurs externally. Do not collect data from entrepreneurs unless they fully understand and consent to providing this data. Consider why entrepreneurs may be hesitant to provide some data and what you can do to assure them that their information will be kept safe and confidential. 

Consider how best to protect Personally Identifiable Information (PII), which can potentially identify an individual either by itself or when combined with other information linked or linkable to them. Simple demographic information can be PII, especially in smaller communities in which minority groups may face stigmatisation. ESOs need a plan to protect the privacy and confidentiality of individuals who provide them with information. Accordingly, ESOs should think about developing a data management plan to support data privacy and confidentiality.

6.6 Educate staff and other stakeholders
Proactively address attitudes and assumptions about culture, gender, and disability among staff and stakeholders. Raising awareness about inclusion and educating staff are important first steps towards creating an enabling environment for inclusive research and data collection. The ability of programmes to collect data effectively and respectfully is dependent on staff having informed, positive, and sensitive attitudes and behaviours towards people of diverse backgrounds and identities.

Consider the path to inclusive data collection as an ongoing journey. Repeated cycles of learning, adapting, improving, and taking action will strengthen ESOs and refine inclusive data collection approaches. An ESO must foster an atmosphere of acceptance, inquiry, and learning.

6.7 ‘Do no harm’ in inclusive data collection practices

Ethics in research and data collection increasingly recognises that the rights and interests of subjects must be primary. The principal aim is to ensure that the subjects of research are protected from harm that might result from their participation in the research. Before engaging in data collection with a view to inclusivity, an ESO must recognise the potential negative effects of data collection and engagement with marginalised groups. Take every measure to mitigate the negative effects of your actions, not only to target respondents but also the wider community environment.

6.8 Share your findings with the people you serve

Close the loop on data collection by sharing key findings and lessons with the people you have collected data from. Rather than only reporting to your own organisation, board, and funding partners, report back to the key stakeholders: entrepreneurs and businesses you have engaged with in the data collection process. Remember that they have contributed their time and valuable information for the purpose of your organisation’s learning. Make sure that is not the first and only time they hear from you.

Case Study - Inclusive Cambodia

Limiting respondent exposure to risk or social harm in urban poor communities in Cambodia

For Inclusive Cambodia, a local NGO conducting research within impoverished communities, inclusive data collection is an essential organisational function. 

Disability is an extremely sensitive topic in Cambodia, particularly among urban poor and rural communities whose stigmas and discriminatory attitudes are rooted in longstanding traditional beliefs.

For this reason there is often hesitancy for people to participate in research initiatives focussed on disability for fear of exposure to community condemnation and discrimination.

During Inclusive Cambodia’s research cycles in urban poor and rural areas, the organisation practises several measures to mitigate risk and ensure the participation of respondents is efficient and does not contribute to their discrimination or reputational harm.

PRACTICE #1 - Limiting Respondent Exposure To Intrusive Research Methods and Community Risk Through Comprehensive Preliminary Research

Before performing sensitive data collection in communities that might place respondents at risk (physical risk, reputational risk, or risks to their privacy), Inclusive Cambodia endeavours to exhaust all resources that might provide necessary research context and limit the time spent by conspicuous data collectors in the field. Existing data about disability is an important source of information, particularly at the situation analysis and initial project design and planning stages. Consulting existing data extensively will provide a starting point for project planning and design, for example by helping to identify target locations, communities, and key stakeholders, but will typically then need to be complemented by further investigations once situation analysis and project design work gets underway. Following a comprehensive preliminary research period, the follow-up participatory research is targeted, efficient, and timely and poses a significantly lower risk to respondents.


In the Cambodian context, caution is an essential requirement for data collectors when carers (including service providers) or family members are supporting the participation of people with disabilities in data collection. People who require interpreters or other support in communication, for example those who are hearing impaired and those with communication difficulties related to intellectual or psychosocial impairments, may not be able to provide information freely or safely in the presence of family members. Questions exploring participation should be considered sensitive information and treated as such. For example, an analysis of participation requires exploring issues of decision-making power in between family and community members. The impact of drawing out such information on people with disabilities needs to be carefully considered. Inclusive Cambodia seeks to collect information in a safe environment, free from influence, and assess the risk of repercussions to the participant from family or community members.


A set of living, open source Guiding Principles for ESO Impact Measurement, led by a Community of Practice, and developed with input from key stakeholders.

Explore by Principle, or start with

1: Understand what success looks like for entrepreneurs

2: Measure the Health of your ESO

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3: Measure immediate, intermediate and long-term outcomes

4. Understand and align with the goals of key stakeholders

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5. Invest in Monitoring, Evaluation, & Learning (MEL)

6: Practise data collection methods that are accessible for diverse entrepreneurs

7: Validate what you measure

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