For social impact organizations aiming to scale, success depends on more than having a strong program. It also means generating evidence for actors with wider reach and resources – such as governments and funders – so that they can confidently implement and finance a program.

This is where many organizations get stuck. Often, their operational, monitoring, and financial data live in separate systems that do not speak to each other. This makes it hard to determine the unit cost of a program, to see which components are driving impact, or to give potential scaling partners confidence that results can be managed at a larger scale. Robust data infrastructure enables these sources of data to interact and to be used for real-time decision-making. Yet many organizations assume that fixing this problem will require a long, expensive overhaul of all their systems, which is not always the case.

SOIL (Sustainable Organic Integrated Livelihoods), a nonprofit revolutionizing urban sanitation in Haiti, faced a similar challenge as it prepared to scale through government partnerships and results-based financing. Their existing data systems could not support the reporting rigor and cost analysis required for sustainable expansion. In response, SOIL partnered with IDinsight over a period of 14 weeks to build a data platform that strengthened its data management, enabled high-quality reporting, and laid the groundwork for deeper government support.

About SOIL’s sanitation model

In Haiti, less than 1% of human waste receives safe treatment, creating severe public health and environmental risks. SOIL addresses this through an innovative urban sanitation model that combines dignity with sustainability.

Their flagship EkoLakay service provides households with small, mobile, locally produced container-based toilets. SOIL manages the entire value chain: toilet production, sales, weekly waste collection, ecological treatment that transforms waste into compost, and compost sales. Customers pay a monthly fee that covers a portion of the service’s true costs, which helps keep the service accessible to low-income urban households while maintaining high-quality standards and accountability to customers.

Currently serving more than  4,000 households in Cap-Haïtien and surrounding northern Haiti, SOIL plans to reach 8,000 households before replicating its model in other Haitian cities.

The scaling opportunity and its requirements

As EkoLakay matured and demand grew, government interest increased. Haitian authorities and development partners began exploring how SOIL’s model could fit into the country’s broader urban sanitation strategy and what it would take to expand coverage to new neighborhoods.

A pilot results-based financing arrangement with the Inter-American Development Bank Lab created an important opening. The arrangement now provides a framework through which public funders can help close the gap between what households can pay and what it actually costs to deliver the service. The long-term vision is that SOIL and potentially other private or social enterprises will continue to provide dignified sanitation, while the public sector in Haiti steps into a larger role as financial supporters.

To seize this opportunity, SOIL needed reliable data on costs and performance to make a stronger case for cost-effective scale. Specifically, they needed to:

• Track the cost per toilet serviced and per household over time
• Identify efficiency patterns across neighborhoods
• Analyze the margin between revenue and expenses at a granular level

Meeting these requirements depended on robust, integrated data systems. That is where SOIL began to encounter constraints.

The data infrastructure gap

SOIL has always treated data as central to its work. Field teams collect detailed operational data. Finance staff track revenues and costs. Leadership relies on key performance indicators to steer the organization.

For years, however, these data lived in separate systems. Operational information from field teams flowed into one platform, while financial information was maintained in accounting software. To create a unified view, SOIL staff built a Google Sheets dashboard that used data manually pulled from these sources and attempted to present consolidated indicators for leadership.

This setup served SOIL for a time, but several constraints became more pronounced as the organization grew and as conversations about scale and results-based financing advanced:

• Manual integration: Each month, staff exported data from different systems and updated spreadsheets by hand, which was time-consuming and prone to error.

• Version drift over time: When changes were made in the source systems – for example, when adjusting financial categorizations – updating historical data in the Google Sheet dashboard was not straightforward and led to discrepancies that reduced overall trust in the data being reported.

• Inconsistent metrics: Definitions for core concepts such as “client” or “toilet” varied across indicators and reports, so not everyone was working from the same numbers.

• Opacity in the calculations: The Google Sheets formulas that calculated the indicators were complex and not properly documented, making it difficult to understand how the indicators were calculated and to pinpoint issues when discrepancies in the data were found.

“Over the course of the year, I would spend more and more time ensuring data accuracy as I was unable to rely on the systems without significant manual review. This represented a significant inefficiency for the organization and meant that I was spending time verifying key performance indicators instead of working with the team to improve them.” 

 

– Nick Preneta, Chief Operating Officer (SOIL)

Building a robust data infrastructure

IDinsight partnered with SOIL to build a comprehensive data platform that would bring their data together, support better decisions, and enable high-quality reporting for current and future partners.

The data platform focused on three core components:

1. A cloud data warehouse: The warehouse centralizes SOIL’s operational and financial data in one place, replacing manual data pulls from multiple systems. Cleaned, analysis-ready tables now sit in a single environment, which makes it easier to maintain consistent definitions and to trace how any indicator is constructed.

2. Automated data pipelines: Automated pipelines extract and transform data from SOIL’s existing systems on a regular schedule. This removes the need for monthly manual reconciliations and reduces the risk of silent errors in complex spreadsheets. Dashboard users see up-to-date information without staff intervention and can connect headline indicators back to the underlying tables and transformations when they need to interrogate the numbers.

3. Interactive dashboards and a data catalog: On top of this backbone, an interactive dashboard brings key indicators into one place for both executive leadership and operational managers. Executive leadership can see strategic metrics such as client growth, service coverage, and high-level cost patterns, while operational managers drill down into service delivery metrics by neighborhood, team, and client status (including where toilets are active or suspended). A supporting data catalog documents how key concepts such as “active client,” “suspended service,” and “cost per toilet” are calculated, creating a single reference point for indicator definitions and increasing confidence in the data used for decisions.

How the new data infrastructure is making SOIL more cost-effective

Since the platform went live, SOIL has seen several tangible shifts in how it uses data.

• A single source of truth: Leadership and managers now have one place where they can see up-to-date operational and financial indicators. Instead of reconciling multiple spreadsheets and system exports, they can trace metrics back to a shared data warehouse and clearly documented calculations. This has increased confidence in the numbers that guide internal decisions and external reporting.

“Aesthetically, it is night and day between what we were using and what we have now… I do not need to check different reports, because we know the data is going into a warehouse, and we can look back at the calculations. We have a single source for our data,”

 

– Nick Preneta, Chief Operating Officer (SOIL)

• Clearer visibility on costs and margins: The new dashboards make it possible to regularly analyze cost versus revenue per toilet and to understand how margins shift over time. SOIL can see how new revenue sources complement user fees to cover a larger share of costs through innovative revenue generation. These insights are essential for managing the existing results-based financing contract and for having informed conversations with funders and government about how to share costs while keeping services affordable.

“When the system is a ‘black box’ and the team does not see the inner workings, it can reduce trust. The collaborative process with IDinsight helped build that trust. Throughout development, we were able to validate the calculations and expected outputs, ensuring the formulas and logic were sound… going through that validation gave us confidence that the numbers are accurate,”

 

– Sasha Kramer, Co-Founder and Executive Director (SOIL)

• More targeted operations: The platform has also made it easier to manage operational issues that were previously hidden in raw data. For example, SOIL can now track clients in a prolonged suspended service state because of non-payment and see where these cases cluster. With that information, sales and customer service teams can target follow-up, bring more households back into active service, and save staff time that previously went into manual troubleshooting. Dashboards showing where toilets are active or suspended and where service gaps are emerging allow managers to identify bottlenecks and rebalance workloads much more quickly.

Taken together, these shifts mean that SOIL’s leadership can now manage its program more cost-efficiently by seeing where resources are being used well, where there is waste or unmet demand, and how different choices affect both service quality and finances. The same system also automates the performance and cost reporting required for results-based financing, giving funders and future government partners confidence in the numbers. SOIL can now manage its program more deliberately and move over time toward more cost-effective, scalable service delivery.

Building for scale

SOIL’s experience is not unique. Many mission-driven organizations reach a point where their program is working, demand is growing, and there is interest from governments or large funders – but the data systems underneath are not yet ready. Once there is evidence that a model works, the central question shifts to “How do we make it work at scale, reliably and affordably?”

That question is especially pressing in today’s funding climate. As foreign aid budgets come under pressure, domestic public finance and careful use of limited resources matter more than ever. Governments need credible information on what it costs to deliver a program to their citizens, how performance will be tracked, and what different coverage scenarios would imply for both budgets and results.

At IDinsight, we help partners build the data foundations that make this kind of scaling possible. In Haiti, that has meant working with SOIL to bring operational and financial data into a single system, make unit costs and margins visible, and automate the performance and cost reporting that underpins results-based financing and potential future government support.

For organizations preparing to partner with governments or enter RBF arrangements, the lesson is not that every tool must be rebuilt from scratch. Instead, investing in the right-fit data infrastructure, systems that decision-makers trust, that reveal the true cost of delivering impact, and that speak to the information needs of public and philanthropic actors, is often what turns a successful program into one that can be sustained and scaled.