Why Companies Need M&E: Lessons From International Development with Sabine Topolansky

Speaker A: I'll say that the move to Osepia Nutri Crops was also not neatly planned. It was kind of found me as an opportunity first. Just sending all the good vibes and empathy to those malprofessionals globally who continue to struggle to find long term roles within this field because it is a tough time. A private sector working in the agricultural sector that has an in house MAL team working on farmer adoption and food security at scale. My guess is that we will see more and more MNE practices being adopted or integrated into private companies workflows moving forward.

Speaker B: Today on survey and beyond, we are joined by Sabine Topolansky, Process and Impact Evaluation Manager at OCP Nutri Crops. With more than a decade of experience in monitoring, evaluation and learning in the international development space, Sabine has built a career helping organizations and companies turn complex field realities into measurable learning and smarter decisions. So today Sabine is here to show us how strong M and E practices can travel across sectors. Sabine, uh, welcome to our podcast. It's a pleasure to have you here.

Speaker A: Thank you so much for having me.

Speaker B: So, to kick off our conversation, could you just share a bit about your journey, specifically your journey into monitoring and evaluation and what through to this sector.

Speaker A: On the beginning of how it all started, Exposure to M and E was somewhat accidental, but in hindsight I would call it more serendipitous I guess since the world of Mel made a lot of sense to me, made a lot of sense to the way I was thinking, the values I held and still do. And uh, it just clicked to be honest. So my original background is in international relationship and then uh, international affairs in international security. But my first full time job was actually with a private evaluation consulting firm called Encompass llc which was a great place to grow and quickly as a project assistant, I was exposed to tasks that involve data collection efforts, joining data analysis and interpretation sessions following evaluations from start to finish, both on logistics but also technically speaking. So that was a great exposure and from there I knew I was in the right place and this would be the thing I want to do moving forward. So I wasn't planning on it, but I kind of stumbled upon it thankfully because it worked out so far.

Speaker B: That's usually how good things enter into our lives, I think. So you have a lot of experience and you've worked across different types of organizations, from NGOs, consultancies, donor funded programs and now into the private sector did this. This whole experience across so many different types of organizations, companies, sectors shape the way you think about data collection and learning and Evaluation?

Speaker A: Yeah, definitely. I think in general, the more perspectives one can witness from the inside, the better, because learning from others, learning how certain contexts operate are helpful, but it doesn't necessarily give you the ins of what it looks like from the inside. That's where the good, bad and the ugly become apparent, which I think are essential for doing good and meaningful and honest monitoring and evaluation work. So a couple of things that I think I learned along the way were first, on interests and motivations, how understanding different agencies, teams and individuals have very different interests and priorities when it comes to M and E, which should be considered when designing a monitoring system, evaluation, or any type of learning effort. Second is terminology. While there are many terms across different entities, the general concept is the same across the board. Whether we're tracking democracy indicators in Libya, indicators on anti corruption reforms in Hungary, or fertilizer adoption on smallholder farms in Morocco. The M and E is fundamentally about making decisions under uncertainty. So the tools, the funders, the vocab changes, but the discipline and the commitment to asking how we actually know doesn't. So terminology can be very different. Third, harmful power dynamics around MNE practices, how we commission evaluations, how data is collected and shared reporting requirements, et cetera, need to be called out and I think addressed more, even if it becomes uncomfortable, which often it does, or it means that I'm undermining my own professional interests. So that can be uncomfortable, but very necessary. And then fourth, I think the culture of fearing failure is still very present. It's changing, shifting. But I think in most international organizations and companies, it's still there. So to shift this, I think the messaging needs to be clear on this from the very top to make people trust their leadership or donors. Right. Funders, and to be transparent with them with whatever they found out through mne. So those are just a couple of things that I think I've learned along the way.

Speaker B: Now, I was thinking when we hear about M and E, and we have talked about M and E many times in this podcast in different episodes, but a lot of times people simplify M and E as this idea of creating reports and mostly creating reports to share to donors that would like to see the main outcomes and outputs. But it's way more than that. MNE is not just about those reports. It starts way before that in designing the theory of change, for example. So can you just maybe share what it covers?

Speaker A: Mne absolutely and very true. That's kind of where people's mind goes like, oh, reporting requirements. And unfortunately, I think in many cases MNE is still thought of as a burden that needs to be done on top of busy work people are already doing. But in reality it can be leveraged as the biggest asset there is for capturing one's work, showing others the results of your work, and being able to improve the work even further while saving a lot of money. So it really is a good thing. It just needs to be understood more. I think there needs to be more sensitivization around it of, uh, what it actually covers. So I think in terms of what it actually covers, as you mentioned, theory of change, a thoughtful design where a theory of change is used as an anchor for, for the work ahead and is continued to be referenced and revised as needed throughout the program. Next step would be to build, I'd say a thoughtful measurement plan, including indicators, research or learning questions, some kind of data response framework that includes an overarching data strategy plan and then through implementation, survey design and administration, focus group methodologies, key informant interviews, all the means of data collection, then analysis, data quality assurance, visualization, then reporting. So which would come at the very end, and I'm sure I forgot a lot to mention, but there's so much work that goes into it. And then to actually create a cycle of learning, you would really need to invest time in interpreting and asking questions. Even post reporting would be so what? And now what? Like those are my two favorite questions because they both lead to actionable changes or pivots or reflections that kind of improves the future work. So without that it doesn't become a cycle.

Speaker B: That's the main purpose is, uh, how can we apply what we have learned? And in your specific case, you also have experience with third party monitoring and verification. Could you just explain what that is? What's the difference between General M and E and this third party monitoring and verification?

Speaker A: Absolutely. So I was working with BXL supporting USAID Libya missions. The USAID Libya mission through the MELA activity, which was the Libya Monitoring, Evaluation and Learning activity for close to a year. This ended post the USAID debacle in February 2025. So once the Stop Work order came in from the Trump administration, that meant an immediate halt to our work. But my work as well, unfortunately. But until then, on the work itself. So imagine you're funding a project in a place you cannot easily visit, or cannot visit at all. How do you know the activities are actually happening? How do you know if they're happening in a way that meets quality requirements the way you plan them to be? Were the people actually reached? Was the data inflated? Was it Real. So that's what TPM MV really solves. Many cases, the context you're working in are active conflict environments where independent data collection is just not logistically like it's not possible and also dangerous. So I was never physically in Libya, only our trusted monitors were. So this is where I think the most important element comes in, which is the human dimension. Often the subcontractor field monitors you might be working with or oversee the work, or local staff working in difficult conditions under pressure, often at personal risk. So managing their performance while maintaining data integrity requires a very different kind of relationship than just a standard quality control process. You're primarily ensuring that they know their safety comes first, above everything, and that there's no data that comes close to that importance. If everything is lost, that's fine, as long as they're safe. So there needs to be solid trust built, which I think is the hardest in many cases. On teams, TPMV teams takes a while where your actions should speak for themselves instead of empty promises. Otherwise you have nothing. And I think beyond the human element, the core challenge in context like Libya is often not building the data collection tool itself. It's more of the verification layer that comes on top of it. So anyone can design a survey, but the harder questions are, how do you know if the survey was actually administered? How do you know the person who said they attended the training actually attended? So that's where the TPM work gets complex and very different from just standard monitoring and evaluation efforts. There's a lot more steps built into the process. On the verification part, that's quite interesting.

Speaker B: So what's the difference if we look into the data collection portion of it specifically, what would you say, uh, are the main differences from a general M and EE and the CPM?

Speaker A: I think there's more steps involved and there has to be a very specific standard operating procedure of who does what and how are things verified. In addition, I think piloting efforts are critical, even more critical with tpmv, you just need to make sure that in real life it's going to work well as opposed to on paper. I heard some teams would do fake launches where the data collection team would think the tools are live. But to me that seems a bit deceiving, maybe a bit too extreme. But the idea is great that there should be some kind of mock or trial launch. That's a very serious effort. It's not just asking my colleague, hey, can you check this survey? Do you think it's okay, or give it a go? It's a more involved process to ensure that the actual instruments are contextually up to par, the translations are working and kind of resonating with folks. So it's more important, I think, to pilot and take a more serious piloting effort on TPMB efforts than it is with regular traditional monitoring.

Speaker B: But do you usually use the similar methodology? So surveys, focus groups, or uh, back checks? So all the same methodology, but more rigorous and being more cautious and mindful?

Speaker A: I think so. I think the only difference is probably a more involved observation protocol that I can think of that would be more relevant to events where you cannot be present. So in that cases it has to be much more prescriptive, much more detailed, and again tested and piloted. But generally speaking, yes, a lot of the methods are the same, a lot of the processes would be the same, but there would probably be more quality back checks, more coordination, just a bit more complexity.

Speaker B: Overall, I'm taking a quick pause from the episode so I can tell you about a great opportunity happening right now for PhD or MD students. We at Survey CTO run the primary data collection research grant every year and the application window for this year has just opened and will run until September 30th. We provide this grant and do all the work that goes along, organizing logistics and reviewing applications, because we really want to support those who do the important work that comes from collecting data. This grant is specifically for PhD or MD students, so if you or a colleague can benefit from this grant, make sure you apply or share. You can get the application link in the show notes okay, back to our conversation. I would like to focus now on your recent transition. So you have been working in the international development sector for quite a while and recently you transitioned to the private sector. You are now working for OCP Nutri Crops. So could you just share a bit about that shift in your life?

Speaker A: Absolutely. I'll say that the move to OCP nutri crops which happened about five months ago, was also not neatly planned. It was kind of found me as an opportunity which I was very very grateful for. And it came out a period of genuine disruption and uncertainty with this 11 month pause of having a full time position or full time role that a lot of people in the international development community and mel community globally faced since February 2025. So similarly to others, I was looking for footing, a solid footing like my peers, many of my peers. And while I kept Busy Working with two local Moroccan NGOs partially volunteering, I received a message from my current supervisor on LinkedIn. So LinkedIn can be very helpful about an Unexpected and really interesting opportunity. A private sector working in the agricultural sector that has an in house MEL team working on farmer adoption and food security at scale for context. OSEP Nutri Crops is part of the OSEP Group ecosystem, one of the world's largest phosphate and fertilizer producers. And Nutri Crops specifically sits at uh, the intersection of agricultural input supply and farmer development. It's not just selling fertilizer, it's investing in whether farmers succeed with it. And that's where my role and my team's role play lives. So to my knowledge, Nutri Crops is quite novel in its approach of essentially having an internal in house MEL team to help their program teams. This signaled to me that this isn't just a reporting compliance function solely for optics, but rather it's more designed to generate actual insight that feeds back into how programs are designed and delivered. So it's taken seriously, which is great. From now on, the MNE vertical we're focusing on partnership building, MEL system building, partner led evaluations, and our uh, learning vertical, in addition to system building is also conducting training for staff, which is great. Offering regular webinars, dissemination events. And once we fully staff up the farmer adoption, that's what the name is vertical within our team, we'll be researching drivers behind factors that lead to behavior change, which will be super interesting as well. We're not there yet, but it's definitely planned.

Speaker B: And I mean we already discussed the one assumption around M and E, which a lot of people think M and E is just for reporting to donors. The other assumption is M and E might be just for NGOs or for the international development sector, but no, I mean it is also for the private sector, which is quite interesting. Can you just speak about this assumption and now that you have a new perspective, a new angle, why is it so important to have MNE in the private sector too?

Speaker A: Absolutely. I think from what I've seen, international development requirements and commitments are increasingly mandatory and scrutinized companies working with smallholder farmers across Africa would also need to demonstrate impact to be taken seriously, not just claim it. Before, I think it was enough to say, yeah, we've done this, we've impacted this many people, but now, like people are okay, show me the data, show me the proof, show me the evidence. So there's much more demand around that which is good and important. And I believe my current role exists because OSAPN recognizes that farmer adoption is not self evident. You can't just claim it and say, oh yeah, this is why they've adopted you have to know the reasons and understand much better, which does require more depth, has to be measured, understood, then improved. So my guess is that we will see more and more M and E practices being adopted or integrated into private companies workflows moving forward. They might call it different, they might have different framework titles or terminologies I kind of mentioned before. But ultimately they're going to be looking at the same result, which is more documentation, more rigorous documentation throughout and learning from it and adapt from it. Go beyond analytics.

Speaker B: Was it easy enough to transfer your skill set from working in international development sector into the private sector? Was it easy or uh, what kind of skills do you think you had to develop or even to reuse?

Speaker A: So was it easy? Yes and no. So on, um, the yes part, the skills like mel, system building, program design, theory of change, development analysis, data collection tools, a lot of these things, these were all fully transferable, even if the terminology is different. The context, vocabulary and the funding logic are very different. Now on the no part, which is not a, uh, no, but it was a learning curve, it didn't start from day one and I'm still learning a lot because agriculture was a new sector for me. So I had to kind of start almost from scratch, close to starting from scratch, learn the fundamentals. And beyond agriculture, I think I also had to refresh my knowledge and familiarity around research grade evaluations and impact evaluations because my background was from at least seven years of it was from the nonprofit sector where impact evaluations were rare, very rare, because they are resource heavy. And if you don't have a research partner you're working with or collaborating with, it can be difficult to commission those or to secure funding for those type of really rigorous, true randomized, controlled trial type impact evaluations. So I had to become more familiar with that. And also quantitative data analysis. There is a bit more reliance, I'd say, in the private sector on, um, numbers understandable for profit. It's a bit different than with nonprofits when it comes to the actual program and performance tracking. So I'd say these would be the things I'd highlight. But overall it's definitely possible. So I'm encouraging folks to discover opportunities because a lot of the same skills can be transferable and a lot of the things that can be learned can be learned in a couple of months.

Speaker B: That's very encouraging. Are there any other similarities or differences that you like to highlight between M and e in an NGO and M& E in the private sector?

Speaker A: Well, broadly speaking, in my previous work, M and E existed more to satisfy accountability upwards so to donors like USAID or State Department and learning downwards towards implementers and implementing partners. Whereas here the logic shifts. So the evaluations need to demonstrate that these farmer centric initiatives are actually working. They're not for donor reporting but to inform nutri crops own strategic and program decisions, commercial strategy and international development commitments. So that's just broadly speaking. I think on a more practical level beyond analytics, structured project and program monitoring practices are somewhat novel to the private sector. So I think the rigor from um, like USAID funded MEL requirements like indicator definition sheets, logical frameworks can be leveraged more within companies. And my hope is that I would introduce some of this on the monitoring side as well as build out some of our internal map frameworks for the program teams that I work with. Second significant difference I noticed so far is the heavy reliance on um, quantitative data like I mentioned before due to considerations around scalability, statistical rigor and how all key performance indicators at the end of the day need to be linked back to cost. So that's important for sure. But regardless I think there is a huge potential to bring in more qualitative data as well as qualitative methods like most significant change outcome mapping, outcome uh, harvesting, ripple effect mapping. So that's the part I'm really excited about because I'm a big fan of these methods. So I think there's a lot of potential there.

Speaker B: So you are encouraged to bring things from your past experience from the international development sector into the private sector. And I'm wondering, you already mentioned a few of the things that you think the private sector would benefit from, but are there others? I know that for example maybe in terms of the methodology around data collection, I don't know if you are using the same methodology around focus groups more a participatory approach. Is this something that you think would work well in the private sector?

Speaker A: Yeah, in terms of the question is around like lessons from the international development sector that could be applied. Yeah, I think some of that would be thinking about how cost is not everything, how finding the right balance between being fiscally responsible, also efficient when it comes to meaningful pathways of change then the discipline of indicator definitions, what exactly are we measuring? How, from whom, how often. This is something that I think development professionals take for granted for sure, but that many corporate impact teams have never formalized before. So there's definitely opportunities there. The theory of change thinking in development I think no one starts a program without mapping the causal logic from activities to outcomes. It's a pretty standard practice but in corporate setting, again, that mapping of that causal logic from activities to outcomes is not adopted yet fully I think so there's potential there. And then last but not least, I think in my case, I think for my role is centering farmers voices. So the development sector has hard won lessons about community participation and co design as a given. Like that's what you have to do in the private sector. Even when it's well intentioned, it's often skipped as a step. There's more assumptions on what folks might be thinking or feeling about and it ends up being with adoption failures that our upfront engagement would have predicted. So I think just more co design practices, more participatory designs, more qualitative methods I think can be really leveraged to avoid these kind of situations. So yes, I think there's a huge potential.

Speaker B: So wrapping up our conversation for uh, other professionals that have a lot of experience, experience in the international development sector and are now thinking about making this shift, this transition to the private sector, what would you tell them? What would be your advice?

Speaker A: Okay, so I think first just sending all the good vibes and empathy to those male professionals globally who continue to struggle to find long term roles within this field because it is a tough time and that needs to be recognized. So hang in there. Practically speaking, I think try to identify companies that have both for profit arm as well as social impact program arm that would benefit from having an M and E professional on board and then search for open opportunities within these companies. Because often the roles, the titles can be misleading. But you might be missing out on a couple of meaningful roles within these type of companies. Then connect with a former supervisor, maybe manager or peer who you looked up to and asked for advice in the past. Maybe they can mentor you. I had two senior professionals who helped me a lot throughout this 11 months. I'm very grateful to them. And sometimes that can just look like a boost of confidence when they express how they believe in you, that you can make a difference. So sometimes just a little bit of nudge can make the whole difference. On leveraging AI, there's three quick points I would highlight. First, go beyond ChatGPT and explore other tools like Claude Perplexity and many others. Because a lot of the work within AI is coming more and more standard I think. So just knowing which tool is good for what and how you can leverage them with your own skills, how you can enhance the work that you do, how can you cut down on time can be really critical. And that goes to translating nonprofit lingo and terminology. Into more private sector lingo. I have used AI assistance in the past and it has been very helpful actually and has got a lot of the time that I needed to kind of tailor my own resume, kind of look at the words, understand the differences and similarities and then use AI as a career coach. Because yes, there are trade offs of you sharing your CV or uploading it and maybe asking for help on cover letters, but it can cut down on a lot of brainstorming time and kind of aligning job descriptions with your own past experience. That's where I leveraged it the most of understanding. Oh, okay. That's actually my strengths. Often we don't see our strengths as well as someone from the outside. So having an outside coach, whether it be AI or an actual career coach, can make a huge difference. And one more point on taking a course on cost effectiveness analysis to have a very solid understanding of the difference and utilities of cost efficiency, effectiveness and benefit analysis because these can help you kind of get around a bit better in the private sector because they're used quite often. So it's handy not just for the interview but for the actual work itself to have familiarity. If you don't have the time, I think these things can be learned. You can take a course in your orientation or onboarding couple of months, but if you can do it beforehand, that can be really, really helpful.

Speaker B: Do you have any resources you'd like to share? Any communities or tools or specific courses? Anything?

Speaker A: Thankfully there's plenty of amazing resources out there, but specific resources that I personally lately found helpful and that I have used were J Pal resources, very rich and open access resources, rigorous evaluations, RCTs and cost effectiveness analysis. They have a great course and a lot of materials and supporting templates for these type of analyses and the differences between the three. So I highly recommend that. And then one course that I'm actually taking currently online time permitted but is the MIT J PAL online course on evaluating social programs. That's a great one. It's also great that it can be taken for free if you're not looking on a non certificate route. If you are, it's about $1,000 but it is available for free. You just sign up and it's a very involved course. There's a lot of great materials and the 102 version for that is the designing and running randomized evaluations which I'm planning to take next. So I'm currently taking the 101 and then going to the 102. So these are just a couple that I found really helpful and are free of charge. That's, uh, awesome.

Speaker B: Well, thank you so much Sabinha for your insights. It was great to have you here.

Speaker A: Thank you Marta. It's been a pleasure.

Speaker B: That wraps up today's episode with Sabine Mail, specialist at OCP Nutri Crops. Today, Sabini and I discuss the difference between mail and third party monitoring and verification, the differences and similarities between traditional mel in the international development space and MEL in the private sector, and finally, tips for career transitions from mastering cost effectiveness to leveraging AI tools. You can find links to Sabino's recommendations in our show notes and don't forget to subscribe thanks for listening to Survey and Beyond, the Data Collection podcast by Survey CTO. If you want want to learn more about how SurveyCL helps organizations collect reliable, secure and scalable data anywhere in the world, visit www.surveycto.com. and if you are a fan of Survey and Beyond, consider leaving us a rating or review on your favorite podcast app. Your feedback helps more listeners discover these conversations and stay connected to the latest thinking in data collection. Don't forget to follow us on Apple Podcasts, Spotify or wherever you get your podcasts so you never miss an episode. On behalf of the entire Survey CTO team, thanks again for joining us and we will see you next time.