Hetal Sheth 8/27/21 8:52 AM 14 min read

How to use impact learning to scale social impact?

A Growing Movement Of Social Purpose With Profit

Social enterprises and nonprofits sectors play a pivotal role in society for addressing societal and environmental issues. The movement can significantly change the world if they understand and use their impact learnings to scale the social change.

Social enterprises step up when the community looks for innovative solutions to solve racial disparities in criminal justice, healthcare, education, voting, or housing. Social enterprises are quite tricky to define as the concept is changing rapidly in recent years and increasingly blurs the line of the for-profits, government, and nonprofit sectors. However, they uniquely advance the social mission and financial sustainability of the organization. The social enterprise also plays a vital role by combining the social impact objectives into business operations and prioritizes social goals alongside financial returns. This approach is quite promising as it fulfills unmet needs and fosters business organizations – those simultaneously seeking profits, social impact, and environmental sustainability. Recently, social enterprises have captured the attention and interest of impact investors and consumers. Measuring financial return is easy, but how do social enterprises learn and use their social impact? How does it matter to them?

GIIN 2020 Annual Impact Investor Survey (1) (1) (1) (1)

Social Enterprise -Survive To Thrive And Then Scale

Today, funders/investors drive the impact measurement and management for social enterprises. They have to report selected metrics to the funders. But we are learning that they need more data to succeed. Social enterprises are actively engaged with the people they are supporting, and even though the social benefits for various stakeholders are considerable, they are challenging to measure. The success of a social enterprise can hardly be assessed using standard measurements such as return on investment (ROI). They need to continuously learn how their stakeholders perceive their products and services before scaling their solution.

For example, ABALOBI is a social enterprise creating a marketplace through a series of applications to improve the value chain for sustainable fish and improve the financial stability of fisher people. The application directly provides safety and sustainability data to the fishers to change their long-term behavior to bring about the intended change. The key here is that fishers must use their applications for success. If fishers do not adapt mobile applications, there will be little or no social impact. For them engaging with stakeholders is not just for reporting to investors, but it is simply surviving! 

Impact Learning To Go Deep And Then Scale

How can social entrepreneurs learn and improve their product and service adaptation and fully understand their impact on those they support? First, start simple and gradually build your learning to achieve your impact goals. For example, social enterprises such as ABALOBI work with vulnerable communities. These communities are affected by complex issues involving multidimensional factors and numerous actors. Addressing such issues requires a step-by-step approach to save substantial financial and human resources. We call them "impact experiments." So, what are impact experiments? As explained in the previous article, MEASURING SOCIAL IMPACT NEEDS NEW APPROACH: CONTINUOUS LEARNING, impact experiments produce high-quality evidence and learning through short, frequent, and efficient feedback loops. Depending on the nature of the project, it can involve one-on-one conversations, interviews, and surveys with stakeholders that yield collective insights or external confirmation of results.

Organizations can use the longitudinal stakeholder data and one outcome at a time. A feedback loop should start with a small group of stakeholders and end with the entire group. For example, ABALOBI has access to application data. But some impact insights come by asking the right questions to fishers and hold community forums to learn about the barriers to continuous engagement. For them digging deeper is more critical before scaling big. How to convey this challenge to your funders and investors? 

ABALOBI 

       ABALOBI case study

Let us take another example of one nonprofit, Mamatoto working to create healthy black communities in the United States. The impact goal here is not just to know positive birth outcomes but to understand how black women have acquired and retained autonomy to advocate for themselves.

In this example, we can see that they conduct many activities to achieve the goal, and the outcome is dependent on many dimensions. Measuring a number of positive birth outcomes, the number of women served, or collecting intake health data will not help to learn if women retained autonomy to advocate for themselves. Enabling women to advocate for themselves is manifested if they can decide on birth spacing, family planning, the health of the baby, or food security. It demands data from multiple dimensions. While economic indicators are more easily quantified and measured, social impact and change analysis are more challenging. It requires the use of mixed methods that include both quantitative and qualitative indicators.

Mamatoto, a nonprofit working with black women, also has to understand their social impact by aligning data from the doula application, observation by the health workers, positive birth outcomes, and cultural and social deterrents of achieving autonomy. Having all this impact learning continuously will enable them to make data-driven decisions to create a scalable change. 

Mamatoto - SoPact

Investing For Deep Impact Learning 

As we engage with more and more social enterprises and nonprofits, we learn that their investors are rewarding them for the scale but not necessarily for going deep and learning from their stakeholders. As we see from the examples of ABALOBI and Mamatoto, scaling comes when you understand what is working for your stakeholders. 

Our recommendation is radically different than the conventional impact investing guidelines. Traditionally, leaders in the field, such as Global Impact Investor's Network, recommend aligning with standards metrics, but it does not work for social enterprises or investors. They are just collecting results, which can not bring intended transparency in the space or help make any decisions for either of them. Investment decisions on the washed impact data or cherry-picked 2 or 3 IRIS metrics do not hold any value. Furthermore, social enterprise/investee/grantee put the effort in scraping/calculating results to report do not serve them. 

In conclusion, creating and scaling social impact is a collaborative process. It requires continuous impact learning with stakeholder data to make informed decisions at every stage from due diligence, investing, supporting, sustaining, and scaling. Learning impact is an iterative process and requires step-by-step impact experiments with one or two outcomes at a time. Deep impact learning is a pathway to scaling impact. 

Impact Learning Quick Recap: 

  • Social enterprises and nonprofits need continuous learning to survive and scale their social impact. 
  • Funders can support the journey by starting from a completely different direction than conventional wisdom. 
  • Start by understanding what their prospective or invested social enterprises need to succeed?  
  • Support them in building their internal data capacity. 
  • Support impact experiments. Help them take one outcome at a time and collect stakeholder data to learn what is working and not. 
  • Engage and learn from enterprises' data where the gaps are and how you can further support them to bring intended impact and scale.
  • Use continuous impact learning to make future investment or program decisions.

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Hetal Sheth

The founder of Ektta, and co-founder of SoPact, Hetal holds a deep passion for establishing enduring impact management practices in the social sector to have built-in learning and accountability.