Building Trust and Impact Through numbers: Why Non-Profit Organizations Need Better Data

Non-Governmental Organizations (NGOs), also referred to as Non-Profit Organizations, play a crucial role  by showcasing civil society's ability to address public and transnational issues governments may fail to resolve due to limited capacity or willingness. These issues range widely, from gender violence and climate justice to development cooperation and human rights defense.

They can be highly valued allies of governments in addressing complex issues due to their unique capabilities in research, advocacy, mobilizing populations, and influencing policymaking. However, these critical functions are undermined by an increasing credibility crisis facing many NGOs.

The credibility issue stems from multiple interconnected factors: a perceived lack of transparency regarding funding sources, suspicions of political biases or partisan agendas, and inadequate reporting of outcomes and impacts. According to Sascha Sheehan, this credibility challenge arises partly because some organizations prioritize advocacy and subjective narratives without providing clear, objective data to back their claims. As a result, stakeholders—including the public, donors, and governmental entities—may question the impartiality and effectiveness of NPO activities, reducing trust and support.

Moreover, the overreliance on qualitative evidence, anecdotal success stories, or limited context-specific reports can unintentionally foster skepticism among funders and partners who seek tangible evidence of impact and efficiency. hile moral imperatives and human stories drive much of the non-profit sector's appeal, the lack of measurable outcomes can undermine their perceived legitimacy and capacity to demonstrate their real-world effectiveness clearly.

How Better Data Supports Non-Profit Organizations

• Optimizing fundraising

While NGOs are private organizations, one of the cornerstones of their credibility is a transparent record on fundraising. After all, their source of revenue for both their projects and their own infrastructure comes from voluntary contributions from the civil society, private companies or the State and, as a general rule of “good practices”, according to the World Bank, NGOs should not allow fundraising over 25% of their total budget, in order to grant the independence. In Spain, this rule is made an incentive to encourage transparency as a tax reduction of 10% on the taxable base per donation under such threshold, according to “Law 49/2002, 23rd december on patronage”.

In this regard, unlike private companies or public institutions, the proper optimization of fundraising becomes a moral imperative as for NGOs. In fact, Rocha Valencia et al. found a statistically strong correlation between the degree of transparency and the efficiency of NGOs in Spain: those NGOs with better transparency in financial reporting, have a higher degree of “allocative efficiency” (defined as “the percentage of total revenue used for project implementation rather than administrative expenses”). Another interesting observation is that, out of four most strongly-associated factors with efficiency, inquired donors showed over 47% higher interest in “Use of Funds” than the others (such as “the source of funds”, “Project details”, or “Management transparency).

The logic before these results probably spins around a common question made by donors: “Where does my money go”? This is actually the opening title of many “transparency” sections of NGO’s websites, since the lack of open databases on how their funds are being used nourishes donor’s right to make the NGO accountable, and thus, their trust in the project. One paradigmatic example may be Haïti, whose dependence on NGOs to provide up to an 80% of public services (specially education and education) after 2010’s Earthquake created a parallel system of governance where such organizations count on more international recognition and foreign economic support than the government itself. However, The case of Haïti remains in collective memory, mainly, because of financial and sexual abuse scandals surrounding widely-known transnational NGOs such as Oxfam Great Britain or the Red Cross in 2018. As a result, Oxfam lost approximately 14 million pounds from donors support and 22 million pounds from UK’s government foreign aid, causing the cutting of 220 of 500 jobs on the island.

• Enhancing Operational Efficiency.

Data analytics provides invaluable insights that enhance the operational efficiency of NPOs by guiding decision-making processes. Coy found that “The NPOs between $6 million and $10 million in annual revenue were more likely to have adopted performance measures at a higher rate than those with less revenue”, since “data collected for performance management helped to inform decisions pertaining to programmatic changes and adjustments.”.

Within the academic field of social impact, there’s a misleading belief that quantitative research is “the poor relative” in social sciences but recent studies like Michael Sheppard’s proves otherwise: analyzing up to 1,490 quantitative and qualitative articles in UK’s main social work journals within 10 years, results show no negative correlation between statistical sophistication of methods, like multivariate analysis, and the number of  downloads and citations. The real divide is not between quantitative or qualitative research methods, but about “empirical” and “non-empirical” (theoretical, papers, reviews), etc. Schooling-focused NGOs, for instance, have used quantitative methods to compare active learning practices with traditional teaching methods, revealing that students in active classrooms learned more despite perceiving they learned less. As previously stated, mixed methods with high-quality contrastable data is the most proper equilibrium for research, including social impact.

The use of quantitative data is particularly noticeable in healthcare-related NGOs (like public healthcare or non-profit hospitals) and the public administration. As visible in figure 1, logistic regression and multivariate logistic regression are the dominating techniques for data analysis on patients’ conditions; whereas Knowledge management within hundreds of documents and reports are more prominent in the public sector because it offers a clearer insight on the “actual” roles and impacts of civil society organizations when facing housing crisis, gender violence cases or school abandonment. Artificial Intelligence - based techniques like predictive models or machine learning are emerging as well, especially in the healthcare sector, although NGOs still prefer classical statistical methods for real-life implementation. Yet, even though Data analytics can help NGOs reduce costs, predict demands, and improve decision-making, similar to its application in profitable organizations, the quality of quantitative studies hugely depends on the each ones’ technical skills, financial resources, and human resources.

• Accountability and Transparency for Legitimacy.

According to United Nations’ report  “Open data support government transparency and accountability (···) to make smarter policy decisions, increase citizen engagement and promote government efficiency and effectiveness”. For this reason, the fact of ceding information on definitions, data quality, methods in collecting data and other important metadata must be a moral standard for any NGO. It’s not only about systematically evaluating their performance, but also about building trust with stakeholders through evidence-based reports. Now, whether the capacity or willingness of NGOs to share statistical data to third parties are thigh to significant challenges:

According to Calvari Sale’s et al. main conclusion on the records of over 100 NGOs in Brazil, NGOs with annual revenues over 300 M reales, like “SOS Mata Atlántica”, “AACD” or “Viva Rio” use to have the best accountability mechanisms, while not necessarily on transparency. Once again, inequity in resources within NGOs not only infer in their respective “accessibility”, “relevance”, or “capacity of diffusion” but also in the “quality” of statistical data that these organizations not only “want” to provide but “can” provide to public institutions or private stakeholders, which may make smaller NGOs look as more opaque than the largest ones to popular opinion.

Another study, this time carried out in Spain, exposes the lack of consensus on the importance of the very quantitative indicators used during inquiries, depending on the stakeholder that asks for it. Concretely, by using the Best-Worst Method (BWM) to assign the proper relevance to each one of the transparency indicators proposed by ONGD-España (CONGDE in English), concluded the following: indicators like the “Existence of the quantitative data of NPO employees” (TR3.2) was overrated by public authorities, whereas private stakeholders privileged way more the “Definition of mission, vision and values” (TR2) by 0.252 or the “Structure and composition of the budget process and activities, and its economic and financial structure” (TR4) by 0.517. Therefore, even quantitative data can suffer subjective biases depending on who asks for them, although they are usually easier to adjust than subjective biases based on a complete pre-conditioned mindset.

Conclusions

Non-Governmental Organizations (NGOs) play a crucial role in addressing global challenges, from human rights to climate justice. However, their effectiveness and credibility are increasingly dependent on their ability to integrate quantitative methodologies into their operations. While qualitative approaches remain essential for understanding context and human experiences, the underutilization of quantitative data limits NGOs' capacity to optimize fundraising, enhance operational efficiency, and ensure transparency and accountability. The disparity in resources between large and small NGOs further exacerbates these challenges, as smaller organizations often lack the technical and financial capacity to implement robust data analytics. Nonetheless, the integration of mixed methodologies—combining qualitative insights with quantitative analysis—can significantly improve decision-making, donor engagement, and stakeholder trust.

At Luminata, we work closely with non-profit organizations to help them integrate quantitative data into their existing approaches. Our experience shows that combining qualitative insights with reliable quantitative analysis significantly strengthens how organizations assess and communicate their impact.

Our services enable NGOs to accurately measure key concepts such as trust, governance, and inclusion through customized metrics. As part of our Custom Metric Creation service, we establish close communication with each organization through Discovery sessions, where we collaboratively define objectives, key concepts, and specific indicators that truly reflect their impact.

Throughout the process, we hold Client Feedback sessions, particularly during the metric development and measurement tool design phases, to ensure alignment with organizational needs. Once these metrics are developed, we support their implementation through our Data Collection and Dashboards service, ensuring effective data gathering and visualization for informed decision-making. At this stage, we provide Training to NGO teams, equipping them with the necessary skills to use analysis software and interactive dashboards. For all these methods, we rely on Data Analysis programmes like CRM, as well as Project management tools like “ClickUp”, Trello or “Asana” to grant the maximum efficiency in communication channels and data accuracy that we provide.

For organizations seeking a broader perspective, our Mixed-Method Evaluations combine surveys, interviews, and public data analysis, ensuring a comprehensive, evidence-based approach. Through these solutions and continuous communication, NGOs can strengthen their credibility and make well-informed decisions to maximize their impact.

References

1. Alsolbi, I., Wu, M., Zhang, Y., Tafavogh, S., Sinha, A., & Prasad, M. (2022). Data analytics research in nonprofit organisations: A bibliometric analysis. In Lecture notes in electrical engineering (pp. 751–763). Springer. https://doi.org/10.1007/978-981-19-1520-8_61

2. Bondalici, R. (2018, June 7). The use of qualitative research by non-profit organisations. Esomar Foundation. https://esomarfoundation.org/the-use-of-qualitative-research-by-non-profit-organisations/

3. Cavalari Sales, J., Portulhak, H., & Pacheco, V. (2021). Vista do Elementos Marcantes da Prestação de Contas Voluntária das 100 Melhores ONGS do Brasil. Periodicos.ufv. https://periodicos.ufv.br/apgs/article/view/9789/6460

4. Clarke, G. (2021). The credibility of international Non-Governmental Organizations (INGOs) and the Oxfam scandal of 2018. Journal of Civil Society, 17(3–4), 219–237. https://doi.org/10.1080/17448689.2021.1994200

5. Coy, H. S. (2018). The use of performance measurement data in nonprofit organizational sustainability [Doctoral dissertation, Walden University]. Walden University ScholarWorks. https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=6594&context=dissertations

6. Falabella, L. (2024, July 5). How can quantitative methods enhance research in HE? LSE Higher Education. https://blogs.lse.ac.uk/highereducation/2024/06/28/how-can-quantitative-methods-enhance-research-in-he/

7. McGann, J., & Johnstone, M. (2005). The power shift and the NGO credibility crisis. The Brown Journal of World Affairs, 11(2), 159–172. http://www.jstor.org/stable/24590554

8. McMahon, J. (2020, December 5). Lessons from ineffective NGOs in Haiti. BORGEN. https://www.borgenmagazine.com/ngos-in-haiti/

9. Moreno-Albarracín, A. L., Ortega-Rodríguez, C., Licerán-Gutiérrez, A., Labella, Á., & Martínez, L. (2021). Transparency indicators to improve accountability for non-profit organizations: A Spanish case study. Technological and Economic Development of Economy, 27(3), 763–782. https://doi.org/10.3846/tede.2021.14821

10. Sheehan, S. (2024, December 11). A crisis of credibility: Why non-governmental organizations are struggling. The National Interest. https://nationalinterest.org/feature/crisis-credibility-why-non-governmental-organizations-are-struggling-193084

11. Sheppard, M. (2017). The impact of quantitative research in social work. European Journal of Social Work, 22(1), 4–15. https://doi.org/10.1080/13691457.2017.1341386

12. United Nations Department of Economic and Social Affairs. (2016). Measure what we treasure: Sustainable data for sustainable development. In Millennium development goals report (pp. 10–13). https://doi.org/10.18356/5beab388-en

13. Valencia, L. A. R., Queiruga, D., & González-Benito, J. (2014). Relationship between transparency and efficiency in the allocation of funds in nongovernmental development organizations. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 26(6), 2517–2535. https://doi.org/10.1007/s11266-014-9527-1

14. The World Bank. (1997, May 1). Handbook on good practices for laws relating to non-governmental organizations. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/201351468332690971/handbook-on-good-practices-for-laws-relating-to-non-governmental-organizations

15. BOE-A-2002-25039 Ley 49/2002, de 23 de diciembre, de régimen fiscal de las entidades sin fines lucrativos y de los incentivos fiscales al mecenazgo. (2002). Boletín Oficial del Estado. https://boe.es/buscar/act.php?id=BOE-A-2002-25039