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Impact experiments
Unmesh Sheth 8/9/21 11:30 AM 7 min read

Measuring Social Impact Needs New Approach: Continuous Learning

Most agree that impact measurement and management done right can help maximize social value.  Over the years, Social Impact Measurement and Management has experienced a proliferation of standards, frameworks, and tools. However, even with numerous standards, frameworks, and tools identifying impact evidence remains elusive. None ‌of‌ ‌them‌ ‌are enough ‌for enterprises to follow and learn, improve and scale social impact.

As a result, we often see asset managers (portfolio managers) and enterprises take the disconnected approach—the resulting lack of listening to stakeholders and improving outcomes. Investors need to invest in an enterprise to improve stakeholder outcomes instead of adding an unnecessary burden of collecting results that don't benefit anyone. Rather than understanding the importance of multidimensionality, enterprises tend to focus on impact justification and reporting. Enterprise success depends on many external factors, collaboration, and reducing stakeholders' financial and social constraints.

Impact experiments are a short and effective way to gather evidence of your immediate impact from your stakeholders.


  • Adopt direct stakeholder listening and a data-driven approach continuously to scale programs, products, or services.
  • A well-designed impact management technology platform intertwined with semantic AI technology, and Five Dimensions Of Impact from the Impact Management Project (IMP) can significantly help to improve understanding of the social impact and stakeholders' voices.


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Top-down Impact Standards are Barrier

Top-down impact standards have actually created more barriers as they are not prescriptive enough for enterprises.  As a result, everyone is free to interpret the way they like. Second, most of the top-down approach focuses on output-based reporting which is quite flawed. We are unlikely to make long-term progress until major players acknowledge their failure and help reverse this trend. Therefore, it is crucial to recognize this more significant challenge and reflect on making enterprises successful. Scaling social impact requires identifying the root causes and choosing the right approach.

New approaches to measuring and managing the social value 

“In order to go in a different direction, we need to build new roads.”

-Prof. Muhammad Yunus

We describe the journey of one of the many enterprises we have worked with, discussing practical difficulties and how a new road of an actionable approach helps accelerate growth.
A social enterprise, "Green Fish" (the name is anonymized), contributes to the sustainability of small-scale fishing communities. They use technology and marketplace creation through better market prices for fishers. They followed a common impact practice with a comprehensive impact map and connected outcomes, outputs, activities, and inputs. The next step was to align their metrics with sustainable development goals. In the process of building the theory of change, they realized that achieving and demonstrating final outcomes needed many more small steps in between. Many external factors influence its success, such as government policy changes, climate, and support. Green Fish's story is not unique, as most mission-driven organizations face similar challenges. Enterprises that are successful use direct stakeholder listening and a data-driven approach continuously to scale. Ultimately, their persistence and grit allow them to scale their program, product, or service. Their growth can be accelerated through more applied impact experiments, as described in this article.
Green Fish as a startup faces the same market and product adoption challenges as many other social enterprises. So instead of focusing on reporting, why not focus on:

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1) What can Social enterprises learn about their stakeholders to serve them better?  
2) How do you overcome the challenges of product and service adoption?  
3) How does the product contribute to stakeholder well-being, both socially and financially?  

Green Fish recognizes that the majority of its stakeholders are under financial and social pressure; therefore, technology adoption may prove to be challenging for them. As a result, Green Fish decided to focus on practical and achievable solutions. They also realized that they needed to run short, frequent, and evidence-based impact experiments to meet their long-term goals. These are new approaches to real Impact Measurement and Management.

Scaling with small and quick impact experiments 

Investors can bring real value by helping social enterprises to understand a culture of impact learning rather than cherry-picking metrics for reporting. Instead of creating a comprehensive theory of change with 15+ outcomes and often 25-50 metrics, they need to constantly focus on the short-term or mid-term outcomes that they wish to work on. Rather than choosing outcomes beyond their control, organizations should focus on those that they can directly influence. For each outcome, we recommend building impact experiments. 

So, what are impact experiments? Impact experiments produce high-quality evidence and learning through short, frequent, and efficient feedback loops. This can involve personal one-on-one conversations, interviews, and surveys of stakeholders that yield collective insights or external confirmation or proof of results. Instead of studying the theory of change and metrics for months, organizations should focus on designing short impact experiments that help improve outcomes with key stakeholders. A well-designed impact management technology platform, semantic AI technology, and Five Dimensions Of Impact from the Impact Management Project (IMP) can significantly improve understanding of the social impact and stakeholder sentiments while improving outcomes quickly.

A frequent impact experiment can be conducted with longitudinal stakeholder data. Typical impact experiments consist of four steps for one outcome at a time -

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Impact Experiments: Maximizing social value small and effective impact experiments.

  1. Start with your program's objective (Product or service) - what is the pain point you intend to solve (select the most critical outcome - one is the best, two is probably ok but not more than that)
  2. Who are the stakeholders for each objective? How many are using your product and services? For policy implementation, focus on tracking policy changes and policy implementation over time. For fish buyers, buying practices, restaurant owners, and patrons.
  3. What activities (through your products or services) do you do to solve these pain points. Before you design any measurement approach, start by talking to stakeholders. Talk to large enough stakeholders and make fundamental changes to gain their trust and adoption.
  4. Create a feedback loop that starts with a small group of stakeholders and ends with a large group of stakeholders.

Learning with longitudinal tracking

After collecting baseline data, focus on intensive program improvement, implementing changes based on stakeholder feedback and results from baseline data. Ask questions aligned to five dimensions of impact. Often we see many practitioners designing stakeholder surveys with limited data outcomes or multi-dimensional alignment. As a result, not enough impact learning is possible. Another limitation is that many survey tools aren't well designed for longitudinal learning.  

A well-designed survey must improve data collection responses time, reduce the burden of repeating questions, and improve automatic real-time understanding of stakeholder performance. There are many best practices for high-quality stakeholder tracking that goes beyond the scope of an article, but here are some important ones -

Based on baseline data, you must immediately change your program. A well-designed data collection and analysis can reveal a wealth of information. For example,

  • Could you concentrate your efforts on those underserved stakeholders that need the most improvement?
  • Are the stakeholders in agreement with the stated outcome? Without such evidence, adopting a product/service may be poor?
  • Is your contribution likely to make a difference? If not, what additional intervention or partnership may be needed to meet the stated goals?  

The organization should make all necessary changes before repeating the next level of improvements. Give the change sufficient time to take effect before repeating the test. The next test should allow you to understand outcomes based on different demographics such as gender, racial/ethnic group, income, and location. You can examine outcome changes using a dynamic dashboard. The easiest changes can possibly be made in those demographics where it is easier to make changes. 


Collaborate with external proof

Stakeholder surveys are very important, as they reflect sentiment, emotions, and performance, but they often need to be corroborated with performance improvements (e.g., results). This usually comes from external data collected internally or from a third party. For example, increased marketplace sale transactions improved the local economy, student attendance/grades, or mother and child mortality rates.

Positive and negative testimonial

Although data-driven approaches can be powerful, do not overlook the power of documenting small things, having impromptu but open-ended conversations (both positive and negative), and asking for short interviews. Conversations can reveal things that no other test can. To connect feedback and analyze potential, we need a simple system.


Feedback Loop 

Hold frequent meetings with staff and stakeholders to make continuous improvements. Creative teams with proper ownership are likely to succeed faster as they implement feedback more effectively.


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Unmesh Sheth

32 years of track record In technology companies, innovation, leadership. Deep understanding of bottom-up and top-down data trust challenges in high impact philanthropy and impact investments.