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How to become an Impact Measurer

PCDN Global

December 3, 2019

By Meeghan Zahorsky (Bio Below)

December 3, 2019

After a quick scan of any job board for the social sector, the demand for impact measurement/data specialists is blatantly evident. Unlike finance and human resource positions, though, the roles that focus on impact measurement or monitoring and evaluation opportunities are often nebulous in their titles, requirements and responsibilities.

Briefly, a note on semantics: We have become accustomed to creatively defining this space, and by association, the titles of roles - Monitoring & Evaluation (M&E) Officer, Monitoring, Evaluation and Learning (MEAL/MEL) Lead, Impact Measurement and Management (IMM) Director, Data Scientist, Research Associate, Evaluation Specialist, Impact Wizard, etc. Arguably, they all mean generally the same thing in theory, but in practice, define an enormously diverse range of expectations. Which is why, I frequently get asked by potential practitioners and employers, what exactly it means to work in this space. For the sake of simplicity, I will refer to this as the IMM space.

I am frequently asked – how do I get started? What do I need to study? Do I need to be a math whiz? For those who want to work in IMM, here is my quick-and-dirty guide to getting started:

  1. You don’t need a statistics degree. You do, however, need strong analytical skills and knowledge of research methods. Whether it came from your English literature or behavioral economics degree is less important. If you don’t believe you have these from your academic background, pursuing further studies might be helpful. (Tip: check out which research methods courses are available online)
  2. Google it. I wish I could tell you that there is a universal source for all IMM knowledge. There isn’t. There are, however, some general terminology and frameworks that are important to familiarize yourself with (even if you don’t agree with them). (Tip: there are a variety of guides and forums online to explore)
  3. Get your hands dirty. Your experiences in the field will inevitably be more valuable than anything you’ve learned in a classroom. The more exposure the better. As with anything, most organizations will be reluctant to pay for someone to learn these skills. Therefore, volunteering to help an organization is usually the first point of call. Even if you’re just helping type up survey results, you’ll start getting a sense of what this work really entails. These experiences will also be your reference points down the road.
  4. Make friends. Those of us already in this space have a wide of range of experiences and expertise to draw on. Clearly define what you’d like to know more about (e.g. mobile applications for data collection), and then reach out. The more contacts, friends, mentors, and resources you can develop, the wider your knowledge base will be.
  5. Start specializing. This could be picking a sector/sub-sector, a technology platform, o ra component of the monitoring, evaluation and learning process that you are particularly suited for. For example, you may specialize in designing IMM strategies, crafting tools, using technology for data collection, data analysis, data visualization, etc. Someone may be a specialist in mobile platforms for gender equity evaluations, while another may specialize in running randomized control trials (RCTs) for public health. While many of us end up working across an array of sectors and in a variety of methods, our specialization(s) will often determine the initial suitability for a role. (Tip: never stop learning and specializing. I’m currently taking a course on R through Datacamp).

Once you’ve figured out what you’re good at and what you’re passionate at (not always synonymous), there are some important, albeit reversible, forks in the road of an IMM career:

  1. Academic vs. Pragmatic: You won’t be openly asked this question. You won’t see this distinction in job postings or on resumes. However, if you’ve worked in this space, you’ll know exactly what this means. The academic approach to IMM will focus on theoretical frameworks and conduct research in a manner akin to think tanks. There is great value to this approach for scientifically evaluating the impact of various approaches, for instance running an RCT, and for publishing that information. The pragmatic approach, on the other hand, is adopted by practitioners who focus on the tools and measurement that grassroots organizations use day-to-day. They tend to incorporate solutions from the lens of practicality and efficiency, including technology. You’ll find that you are naturally drawn to one approach or the other.
  2. Consulting vs. In-house: There are individual consultants or consulting firms that support IMM for external organizations. Alternatively, there are roles within social impact organizations. I often recommend starting with the consulting path simply to gain exposure to a variety of methods and organizations. Once you’ve got that under your belt, moving into an organization is a great way to drill down into more long-term solutions.

If you’re starting to wonder why anyone would go down this path, the answer is simple. It matters. We need more, not less, passionate individuals to take up the yoke of IMM to ensure that we are doing what we said we would and heading where we want to go. Best of luck, fellow data geeks.


Meeghan has an eclectic background in impact measurement, technology, consulting, and public health, melding all of these passions to support social entrepreneurship and grassroots projects globally. She currently is a Principal Consultant for Thoughts In Gear, a Malaysia-based firm focused on Social Impact & Sustainability. Meeghan has previously been the CEO of an Indian NGO focused on malnutrition prevention. She has over 10 years experience in monitoring, evaluation and impact measurement with organizations in Africa, North America, Europe, the Middle East, and Asia. Meeghan received her MA in Conflict Resolution from Georgetown University and a BA in International Relations from Brown University.

See her recent post on PCDN on Why I love Data and You Should Too


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