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Unmesh Sheth 6/9/22 9:43 AM 7 min read

How can social impact data be used to measure and manage the impact?

Before digging deeper into the details of what it takes to measure and manage the impact, let’s look at what measuring impact really means. In very simple terms, the impact is the effect of activities of an organization on the people (and the planet) they serve through their products and services. Going by this definition, it is clear that organizations need to be in touch with their people on a continuous basis in order to measure the impact of their activities on them using social impact data. There is absolutely no magic here. Want to understand the outcomes of your activities? You MUST be close to the people (stakeholders) and talk to them and continuously improve your methods to talk to them as well.

So, this brings us to the question. What does it really take to measure and manage the impact? 

There are fundamentally 2 ingredients that every organization needs.

  1. A simple (not simplistic) strategy that helps an organization to focus on the most important outcome they want to learn about from their stakeholders about their activities.
  2.  Pretty sophisticated data pipelines that help organizations to execute on the strategy above, which ultimately leads to impact learnings that can be acted upon.

The whole article is actually summed up below diagram which represents what we call Impact Experiment. It is essentially smaller but continuous cycles of learning about the most important outcomes at any given point in time.

impact experiment

Having worked with many organizations, we can tell with a pretty high degree of certainty that IMM doesn’t happen even if one of the ingredients is missing. 

With that let's get started.

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What is a simple (and not simplistic) strategy?

The definition of “strategy” is beyond the scope of this article. If you are interested in understanding our perspective on the role of a sound strategy in IMM, download Actionable Impact Management. It will do you a ton of good if you can read up on “Understanding Michael Porter” to get a better grasp of what a sound business strategy looks like.

Let's start with the first ingredient. In general, a simple strategy permits organizations to put something into action and follow it until they see it working (or not working), as long as it can be executed. Organizations that dwell upon their theory of change, consisting of 30 outcomes and 80 metrics, for 6 long months are on the wrong foot. Because it is nearly impossible to execute that kind of a thought process. 

Strategy is as much about knowing what NOT to do as it is about knowing what to do. 

 

Read More: Demystifying Social Impact Management

A simple strategy for IMM is to start with

  1. One or two most important outcomes an organization wants to learn about from their stakeholders (Outcomes must be directly related to the activities of the organization)
  2. Next, think about what data you may already have that helps you answer the question from step 1
  3. Figure a way out to collect additional data that may be needed to fill the data gap from the perspective of learning about the outcomes 

Step 3 is where an organization thinks about additional stakeholder surveys (or interviews) that might be needed to understand what outcomes stakeholders are experiencing. 

Impact Data Pipeline_spilt (1)

The three steps above constitute the first part of the diagram. Sounds easy in this article but very treacherous when you try to follow it through. Again the trick here is to start small. The more complex this step, the harder it gets to execute. And the faster you go from strategy to it being just a wish list.

The work doesn’t end at putting all of the thought processes together, it begins there. Executing the thought process is where technology comes into the picture, especially the ability to create a data pipeline. This is much like water pipelines that get water from different sources all the way till we get the water in our taps. 

Onto the second ingredient, data pipelines….

Read More: Attribution vs Contribution in Impact Measurement

Social Impact Data pipelines, it is hard and tricky

Impact Data Pipeline

What’s the big deal about data pipelines and why do we say it's hard and tricky? The biggest reason is that impact data is not just data that we collect in the survey, it comes from every corner.

Example

One of the organizations we are working with helps fishers to improve their income through access to a marketplace where they can sell their catch at better prices, ultimately helping them improve the quality of their lives. To accomplish this, the organization has developed an accounting application where the fishers log their fishing trips and their catches and get connected to the marketplace.

To help the fishers learn how to use the application, the organization has developed an LMS (learning management system) that helps the fishers go through accounting courses and there is a test at the end of each of the courses.

In addition to the above, the organization is doing a baseline survey on the fishers to understand their pressing needs and socioeconomic condition.

As you can imagine there are several sources of data and they are all related to the fishers. The diagram below shows what it looks like.

image (4)

Now let’s take one of the obvious questions that the organization may want an answer to.

Are fishers more likely to use the accounting application as a result of passing the course in our LMS? In short, what is the impact of the LMS course on the fishers?

To answer this question, data from two systems need to come together

  1. The LMS system where fishers are taking the course and where we get to know their general ability to read and understand accounting practices.
  2. The data from the accounting app that fishers use to log their catch.

Without a systematic data pipeline, there is absolutely no way this question can be answered on a continuous basis. And without understanding this, the organization loses its ability to learn quickly and continuously.

This is where technology, especially around data pipelines, comes into the picture. With technology,  It has gotten a lot easier but is still complex. not easy. The picture below depicts what really needs to happen for the organization to develop this core ability to learn. 

Read More: Empowering Small-Scale Fisheries- Abalobi Case Study

A data pipeline created to answer the above question needs to do three things

  1. Connect to the existing data source which is the APP usage database and the LMS database
  2. We need to bring in appropriate data from each of the sources that will help us in answering that question
  3. Finally, the ability to combine the two data sources lets us analyze the data and answer the question.

On top of that, this pipeline should work on a continuous basis, giving the organization the ability to learn if things have changed. And when the need for analyzing some other information arises, the data pipeline should be flexible enough to accommodate such changes. 

While the data pipeline above helped in answering the organization’s question, the pipeline shouldn’t be rigid or restricted to answer only that question. The ability to integrate additional sources of data and ask varied questions gives the organization the capability to run these impact experiments on a continuous basis.

This helps the organization not only measure impact but also manage impact as it can make data-driven decisions. This is the hard and the tricky part. If the system to connect and fetch data from different sources is not flexible and easy enough to implement, organizations would find it hard to even bring this data together in the form that lets them ask questions and get answers. 

The final piece of the puzzle is the dashboard that lets organizations learn from the data. Even here we emphasize learning as opposed to proving. 

Read More: Can Impact Work Without Diversity Be Racist?

Conclusion

I truly hope this article is able to throw some light on what it really takes to measure and manage the impact on a continuous basis. It is hard, and it is tricky but all is not lost and we can say this with experience of working with many organizations and helping them learn about their impact through data pipelines.

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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.