Expanding SOIL’s Data Concepts and Analyses Using DataCamp

SOIL’s Research & Operations teams collaborating 

SOIL’s research team is always looking for ways to improve our EkoLakay processes so that we can continue to provide our customers with the highest quality sanitation service. To do so, the team regularly undertakes projects and analyses that inform strategic and operational improvements to our services. An important way for the researchers to identify and understand the specific changes that need to be made is by generating solid, data-driven evidence for analysis and study.

DataCamp, an online, interactive learning platform that teaches users data science and skills, has partnered with SOIL over the past two years to provide its subscription service pro bono to our research team, allowing our team access to a variety of data tool courses and tutorials. With its DataCamp Donates program, the company aims to stay true to its mission of democratizing data science and fighting data illiteracy by offering free services to non profit organizations serving historically disadvantaged communities. 

DataCamp’s analysis tools support the SOIL team in building their technical capacity in order to help them more efficiently and effectively achieve its strategic goals. Two of our researchers, Maya Lubeck-Schricker and Julie Jeliazovski, have worked through several of DataCamp’s data management courses, focusing specifically on software programs like Excel and R that have proven to be extremely valuable to their work. 

Maya regularly uses R for research projects, including her recent analysis of the effectiveness of special, incentivizing offers aimed at improving our EkoLakay customer payment behavior. Analyzing the data Maya learned that most of our special offers were effective in improving customer payment behavior! And, in exciting news, her analysis has been accepted for a poster presentation at the UNC Water and Health conference in October where it will be shared with other global WASH practitioners. 

In another probe, using analysis tools developed through DataCamp, Maya found that a newly implemented KPI target for collection staff has significantly reduced the number of households that had been accidentally missed during collections. This important discovery will help our collection teams ensure that we are servicing all of our customers in a regular and timely manner.


Julie has used R to compare the results of different composting processes, investigate the causes of variations in compost yield and determine the most efficient option for composting–an analysis that will guide the team’s next steps as they apply what they have learned to windrow composting.

Increasingly, running these types of statistical tests not only informs the research team’s decisions about the specific operational interventions, but has led them to think more about data management in general. Prompting new questions like: How can we use the data that they collect regularly? Is there other data we would ideally like to be collecting? Are there better ways to keep track of all the data that we already have? All of these analyses and methods of data collection will help further SOIL’s goal of providing access to safe, dignified sanitation that produces rich, organic compost as a natural resource for Haiti’s badly-depleted soils, while also creating economic opportunities in some of the world’s most under-resourced communities.

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