The Real State of Impact in the Social Economy in South Africa

An Inconvenient and Uncomfortable Truth

Right on the heels of the research report on the state of the social, solidarity and impact economies in South Africa is the outcome of another research project that I have concluded over the past few months. One of the trends identified in the research report was the growing importance of understanding impact performance across the social economy in South Africa.

This article supports and expands on findings and insights gained in the process and focuses extensively on the practice of impact management and measurement (IMM).

The research indicates that while there is a greater adoption of (i) new impact investment funding structures (e.g. outcomes- and performance-based), (ii) new impact measurement standards and guidelines (e.g. SDG Standards, Operating Principles for Impact Management and the Impact Frontiers’ Impact Management and Reporting Norms), the practice of impact management and measurement (IMM) in South Africa is not ingrained, nor is it pervasive and adoption is unequal.

This research project focused specifically on understanding whether the social economy is able to achieve meaningful and sustainable impact and what barriers and challenges exist to measure the impact that we are aiming for.

This was done specifically as the 2024 Trialogue research indicated that:

• Only half of corporate social investors have an M&E policy, which also declined from three previous surveys.
• The research indicated that only 47% of companies have dedicated resources for M&E, whilst they dedicate less than 5% of their financial resources to this function.
• Similarly, only 34% of nonprofit organisations have a budget for M&E which is also down from previous research periods, and those who have allocated budget, it is less than 5%.
• Interestingly however, with little budget dedicated and limited resources for M&E functions, still, 93% of companies still state that they use M&E data to report to their boards, and 80% use M&E data to inform strategic, operational and programmatic decisions. And to make matters worse, only half of companies and a third of NPOs share impact data with their recipients or beneficiaries.

This dismal state of affairs then begs the question, how is it even possible to understand collectively or individually whether the resources we invest are making a difference and even more importantly, how do we know what works?

Research Approach:

The idea for this research project was based on the premise that it seems all stakeholders agree that success in the social economy in South Africa depends on a data-driven approach to understand the current challenges and opportunities of the sector.

Also, as an impact advisor, I have often emphasised the importance of data – and I am not changing my tune. Clear, reliable, and traceable metrics are essential to understanding if social economy solutions are working, where it can improve, and whether it’s worth investing in. My fundamental belief is that impact data move resources and inspires innovation.

The project was informed by my own work related to requests from funders to develop impact strategies, impact management plans and impact measurement frameworks which allowed me to evaluate current approaches, processes and systems used to understand and determine impact. In addition, impact assessments conducted for clients included a review of strategic, operational and programmatic aspects as it relates to performance management activities which allows for a more holistic perspective. Furthermore, feedback, engagement and contribution of practitioners during the impact management and measurement masterclasses also informed some of the issues highlighted. And lastly, I have conducted an extensive desktop research project to review impact reports as well as data provided in integrated and sustainability reports to consider what impact data is shared, what approaches are used to collect, analyse, verify and share impact results.

I synthesized the data obtained through these primary, secondary and tertiary data sources to identify patterns, trends and insights and to draw conclusions which then allows for insights into the real state of the impact in the social, solidarity and impact economies.

Key findings:

The most critical finding of the research project was that whilst there is an attempt to understand impact across the social economy in South Africa, it is so limited in its application, that the only conclusion is that as far as impact achievement is concerned, it is in a very early or nascent stage.

Of course this indicates the real opportunity of untapped potential to grow impact outcomes across the board for all stakeholders. I conclude that while many organisations lack the tools, resources and processes, I also found widespread dedication to meaningful change. This indicates that the intention to achieve impact is real, but persistent challenges like resource constraints and poor understanding of the potential value of impact data and the importance of data sharing, will hamper our collective ability to achieve meaningful, large scale and sustainable impact.

But unfortunately this also highlights the gaps between data and action. Furthermore, a lack of evidence of either success and failure leaves us vulnerable to uncertainties and shocks. And the sobering reality of unfulfilled promises, frustration and critical risks.

The key takeout from the research is: 

Ultimately, we must recognise that our best and brightest talent are not working effectively on our biggest challenges. They still lack critical data and technology, tools, knowledge, processes, and best practices. To do better, we must face this reality head on, and improve.

I have distilled the findings into 7 trends critical to the sector’s growth. Each trend, which probably merits its own dedicated study, is further explained and analysed below.

Trend 1: Data immaturity cannot drive impact:

Data maturity is an organisation’s capacity to identify, integrate, adopt, measure, and continuously improve data tools, knowledge, processes, culture, and talent into its strategic and tactical work. Data driven decision making is not uniform nor recognised for its power.  There is a strong link between data and performance. However, a lack of data is also indicative of non-performance – as data is directly related to investment, funding and revenue across the sector, as well as operational and program efficiencies, partnerships and rates of innovation. 

Spending more time on data architecture is critical as it is the foundation of a well-organised system, ensuring information is accurate, accessible, and usable. For organisations, this means structuring data to inform strategic, operational and programmatic decisions and linking all activities to achieving impact. This goes beyond lofty goals, ensuring every action, project, and decision aligns with measurable outcomes and continuous improvement.

Trend 2: Resource constraints cannot support impact goals:

Across the ecosystem, the shortage of resources is constant, and real. While there is recognition for the importance of understanding, managing, measuring and reporting on impact, a lack resources is blamed for the inability to take proactive action.

For the vast majority, funding shortfalls, whether due to inefficiencies or genuine lack of resources, create a cascade of challenges. Talent retention suffers, strategic planning is limited, and innovation is stifled. This constant resource-balancing act leaves leaders more focused on survival than maximising impact, turning the pursuit of social good into an uphill battle. Addressing resource gaps and transitioning from scarcity to sufficiency requires targeted strategies tailored to the specific constraints of each sector in the social impact ecosystem. These strategies will demand significant effort, involving organisational change, operational flexibility, and strategic foresight.

The first step, however, is confronting a critical truth: traditional approaches to resource challenges – especially funding – are increasingly ineffective.

The second step is to leverage what we have, including:

• Leveraging resources to invest in collaborative platforms and forge technology partnerships that translate data into insights.
• Leveraging partnerships to share costs and test new (collaborative and collective) measurement and reporting tools and platforms.
• Leveraging knowledge by providing meaningful training and capacity building resources to encourage data maturity, data interpretation and data analytics.
• Leveraging existing guidelines, frameworks and standards by developing and enforcing standardised frameworks to measure impact.
• Leveraging impact data tools and infrastructure that enable data sharing and integration into decision making across the ecosystem.

Trend 3: Acknowledging measuring impact is hard:

The idea that data can seamlessly link activities to impact is an oversimplification. Limited data access, unclear attribution models, and incomplete measurement practices make demonstrating the full impact a persistent challenge, despite growing pressure to do so.

Most organisations still track inputs and activities rather than outputs, outcomes, and impact. The inability to demonstrate real results and lack of interpretation of impact results puts social impact leaders on the constant defense to justify investment and fund allocation. Stakeholders across the board now expect clear, measurable connections between funding, activities, and sustainable outcomes. For most organisations, creating this through-line impact management and measurement process remains a complex and daunting task. Without a clear demonstration of impact, organisations often struggle to raise funding, build strong sustainable brands, and secure the support of internal and external stakeholders.

While the reasons for ineffective impact measurement are varied, we have identified the following as the most common across organisational types and sectors:

• Defining impact: Organisations often lack a consistent definition of “impact,” even within the same sector. This subjective interpretation leaves too much room for individual biases or manipulation. Without a shared framework, assessing, benchmarking or comparing results becomes difficult.
• Fragmented data: The social impact sector lacks a centralised repository for tracking activities, funding flows, and results. Despite widespread recognition of this need, the vision of a unified data system remains elusive. Without this infrastructure, tracking and attributing impact is a challenging, fragmented process.
• Time horizons: Stakeholders frequently expect monthly, quarterly, or annual updates, but meaningful change, particularly in areas like public health or education often requires years or even decades. This misalignment leads to a demand for short-term metrics that don’t accurately capture the gradual nature of social change.
• Sector variations: Impact measurement challenges vary across sectors. For example, private sector organisations engaged in social impact work often have better practices and resources to measure and report results whereas social impact organisations lack the resources (human, financial and technology) to effectively measure impact.
• Size matters: Our analysis also reveals that impact measurement effectiveness differs by organisational size.
• It appears that small organisations face the most significant challenges, lacking the resources to invest in advanced data systems.
• Private sector organisations engaged in social impact work often have better practices and resources to measure and report results but they rely extensively on self reported and third party data which influence the materiality, effectiveness and efficiency of their data management systems.
• Large organisations, despite their extensive resources, struggle with the complexity of managing multiple initiatives across a variety of programmatic areas, which dilutes their ability to track and impact report on either a portfolio or investment level.
• The sweet spot seems to be with mid-sized organisations which are reporting the most effective levels of impact measurement by focusing on a single vision, cohesive teams, internal collaboration, and clear measurable outcomes.
• Lack of strategy, structure, system and processes: Improving impact measurement requires a strategic mix of tools, processes, and cultural shifts, spanning resources, personnel, and organisational knowledge and learning. It’s not a quick fix but a deliberate, iterative process. Having a clear impact strategy, impact management plan and impact measurement framework will support effective and efficient impact measurement and of course reporting activities. Without intentionally mapping the impact achievement and delivery process, impact measurement risks falling short of its potential to drive meaningful change, a practice that is clearly lacking from existing approaches.

Trend 4 Lack of Audience Centricity:

Audience centricity means putting the people an organisation serves at the center of every decision and investment. Organisations that prioritise stakeholders in their design and delivery achieve stronger results. This audience-centric approach improves operational efficiency and aligns between activities and organisational mission and vision. Our research into audience centricity within social impact organisations uncovered some interesting findings.

• Little to no evidence of stakeholder engagement: Whilst the assumption can be made that impacted stakeholders were consulted during design phases of interventions, unfortunately this remains an assumption as impact reports provide little to no evidence of proactive, ongoing stakeholder engagement with their primary stakeholder audiences, i.e. direct and intended impacted stakeholders.
• This is supported by the fact that impact reports is not designed for or presented and shared with impacted stakeholders. The interpretation therefore is amplified in that at best, audience centricity and stakeholder engagement are lacking in basic impact data. 

Trend 5: Data silos persist:

Lack of standardised definitions, collection and aggregation methods, and data sharing practices still restrict the potential for meaningful collaborations. Despite efforts to create data collectives and aggregate insights through data lakes, ecosystems, and collaborative initiatives, social impact data remains fragmented across ecosystems, lacking clear structure and shared processes.

The reasons are varied, and the research has identified the following as most consistent and prohibitive:

• Data fragmentation: Many organisations operate in isolation, using siloed data systems that create fragmented insights and duplicate efforts. Hesitation to share data, driven by fears of competition, loss of control, or misinterpretation, persists, making it challenging to align incentives for open data sharing without compromising organisational goals.
• Data Governance: The sector lacks a unified approach to addressing data privacy and governance, let alone establishing agreed-upon protocols. Issues of data ownership, especially when engaging marginalised communities, often create tension as organisations grapple with balancing the need for insights and respecting individual privacy.
• Capacity and skills: Many nonprofits and social impact organisations lack the resources, skills, and funding to manage and analyse large datasets or integrate data tools effectively. This leads to underutilised data, missed opportunities, and reliance on external partners, further compounded by challenges in attracting and retaining talent. Data sharing is one of the most complex challenges facing the social impact sector. Pretending there’s a simple, one-size-fits-all solution is both reductive and counterproductive.

Trend 6: The storytelling imperative

Data-driven storytelling transforms abstract numbers into compelling narratives that inspire action. It builds trust, demonstrates transparency, and makes outcomes tangible for funders, partners, and communities.  My research suggests three main storytelling approaches in the sector.

• Some organisations emphasise the human side, using testimonials and case studies
• Others rely heavily on data and metrics
• Whilst others tell stories that only describe positive outcomes

However, what is most needed is comparative data to benchmark approaches, as this will contribute to credibility of the data presented whatever form of storytelling is used. The most effective stories, the ones that resonate and inspire action, combine three critical elements which is clearly missing from current practice:

• Narrative: A story that explains what happened, why it matters, and what could come next.
• Data: Tangible evidence that grounds the narrative in valid, representative insights.
• Visuals: Clear, engaging visuals to help audiences process and retain the information.

Trend 7: The power of artificial intelligence

AI is transforming the social impact possibilities, yet most organisations, especially outside the private sector, are only starting to explore this potential. The need to quickly adapt is not a choice, but an imperative. The adoption of AI/ML in social impact organisations presents challenges, including ethical concerns around bias, data privacy, and transparency.

The research shows very limited application and extremely limited awareness by individuals in the social impact sector. This means not only are we lacking in adoption in South Africa, but there is also limited confidence across the sector in their organisation’s ability to integrate AI and ML into strategy and operations. The ones most impacted by the reluctance to understand, create, and adopt AI strategies and tools are the individuals on the ground. It is thus perhaps unsurprising to see that they are also the ones with the lowest levels of confidence in their current organisation’s ability to integrate AI and other advance technology opportunities into their work. Artificial Intelligence has and will inevitably continue to change and shape our world. It is important to remember that we are very much in the infancy of this massive change and that the outcomes of these dynamic shifts are happening in real-time. Organisations that carefully monitor and safely test new capabilities, ideas, and tools in this space will position themselves well to harness the opportunities and mitigate the inherent risk involved in any innovation. 

It is for this reason that we share 4 case studies that highlight best practice with regard to emerging best practices in impact management, measurement and reporting.

Case Studies: Local Best Practices

Case Study 1. Youth Development Fund: Moving from Outputs to Outcomes 

A prominent South African foundation focused on youth employment moved beyond counting beneficiaries trained to tracking long-term outcomes such as employment retention, income growth, and entrepreneurship success. By integrating predictive analytics into their IMM system, they could identify which interventions had the highest impact on long-term job creation.

Key Takeaway: Adopting AI and longitudinal tracking systems enables stakeholders to move beyond immediate outputs and focus on sustainable outcomes.

Case Study 2. Agricultural Social Enterprise: Linking Data Silos 

An agricultural cooperative used IMM to unify data from diverse sources including farm yields, market prices, and community development indicators. This integration enabled them to measure systemic impact, such as improvements in food security and rural livelihoods, while identifying bottlenecks in supply chains.

Key Takeaway: Breaking down data silos enhances the ability to measure interconnected outcomes across value chains.

Case Study 3. Renewable Energy Initiative: Leveraging IMM for Stakeholder Buy-In 

This organisation integrated AI to predict energy consumption patterns and identify households with the greatest need for solar installations. The impact included measurable reductions in household energy costs, increased community resilience, and lower carbon emissions. Then, the organisation used immersive impact storytelling to communicate its outcomes to investors and communities. This approach combined high-quality visuals, community testimonials, and rigorous data, which resulted in increased investment and community support.

Key Takeaways: Predictive analytics can bridge operational outputs and systemic impact, enhancing resource allocation and community outcomes. Impact storytelling, rooted in robust IMM data, can transform stakeholder relationships and increase buy-in.

Case Study 4. A Health Initiative: Leveraging impact data to improve impact 

Leveraging audience-centric IMM, this initiative co-designed healthcare programs with community members, addressing cultural barriers and improving health outcomes. Real-time data feedback loops allowed for program adjustments, significantly enhancing implementation effectiveness as well as increased impact.

Key Takeaway: Co-designing programs with program participants ensures relevance and maximises impact.

In conclusion: The Transformative Power of IMM for Social Economy in South Africa

The evolution of impact management and measurement (IMM) in South Africa is not just a technical challenge but a strategic imperative. The future of IMM lies in its ability to connect impact intent with outcomes, and aligning investments with measurable impact. In doing so, South Africa’s social impact ecosystem can set a global example of how IMM can transform not just organisations, but entire communities and systems.

Impact management and measurement hold immense promise for driving meaningful social impact, systemic change, transformative and inclusive sustainable development. However, realising this potential requires intentional action. By addressing current challenges and embracing the opportunities, we can move from mere monitoring to meaningful measurement and, ultimately, long-lasting impact in the social economy in South Africa.

It’s time for South Africa’s social, solidarity, and impact economies to fully embrace IMM, not just as a compliance exercise but as a powerful tool for driving change and demonstrating the value of every investment in our collective future.

About the Author

Reana Rossouw – Next Generation Consultants is a specialist in impact management and measurement. 

More insights, case studies, resources, articles and practice notes on the practice of Impact Management and Measurement are available on the Next Generation website:

Next Generation also conducts Impact Management and Measurement Masterclasses, and the next event is planned for 8 – 10 July in Johannesburg. For more information about the upcoming Masterclass, download the event brochure.