From Field to Decision: How WPF Uses Data to Build Better Poultry Programs
Inside WPF’s data-driven approach to the PMI program and how real-time insights are helping partners course-correct, strengthen farmer support, and deliver lasting impact.
By: Maureen Stickel, Tokozile Ngwenya, Thierry Binde, Earl Pearce, and Jan de Jonge
In most development programs, data tells you what happened. At the World Poultry Foundation, we want data to tell us what is happening — right now, on the ground — so we can act before small problems become big ones.
Across the Poultry Multiplication Initiative (PMI) program, currently operating in Senegal, Sierra Leone, Madagascar, The Gambia, and Zambia, WPF has built a data ecosystem to do exactly that. From CommCare field collection to Power BI dashboards to annual pulse surveys, every layer is designed to get the right information to the right people at the right time.
WPF’s CommCare Coordinator, Tokozile Ngwenya, oversees the system that FSRs use to record field data during every farm visit: flock numbers, bird weights, mortality, feed usage, vaccination records, and health observations. That data flows directly into a central dashboard for program teams and partners to review in close to real time. “CommCare helps connect the farmer’s experience directly with programme management and decision-making,” she says.
Collecting good data in the field is rarely straightforward — connectivity is inconsistent, farmers estimate numbers differently, and flock performance can be unpredictable. The WPF team has adapted the CommCare forms over time to be more flexible while maintaining quality and places strong emphasis on training FSRs to understand the context behind the numbers, not just fill in fields.
One of the most striking patterns she observes is how FSRs change once they understand the bigger picture. “At first, many of them see data collection as simply filling in a form. As training progresses, they begin to see how the information they capture influences program decisions and how partners interpret what is happening across countries. That shift in perspective often changes how carefully they approach their work.”
In one instance, routine data showed an area performing well — visits recorded, activities completed. But pulse survey data revealed that farmers technically reached by the program did not report the same level of understanding or practical benefit as others. Disaggregating by gender, disability status, and income level sharpened the finding further: being included in activities did not automatically mean an equitable experience of them. The result was more intentional segmentation, adapted communications, and a shift toward tracking inclusion at the outcome level, not just participation.
“Operational performance is necessary, but not sufficient,” Thierry reflects. “Without farmer-voiced evidence, we risk mistaking reach for impact.” He is also focused on extending MEL into training to move beyond counting sessions and participants toward measuring whether training is actually changing knowledge, behavior, and livelihoods. “The goal is to build evidence of training value, not just training delivery. That is the path from activity to impact.”
Looking ahead, Earl sees the biggest opportunity in parent stock performance tracking. Just a handful of weekly data points per flock, total eggs produced, females and males alive, a measure of hatchability, would allow each partner to fine-tune their production plan in real time and against standards tailored to their specific environment. “No published standard really fits every situation,” he notes. “Each customer’s challenges are different.” Building that feedback loop is, in his view, the next frontier for WPF’s data infrastructure.
Another contribution Earl is looking forward to implementing is a set of automated reminders derived from each flock’s age — flagging upcoming vaccines and procedures at the FSR and flock level, so our partners know exactly what is due in the coming weeks and can plan their travel and call schedules accordingly. “This is the same method I used during my first 14 years managing birds,” Earl explains, “so I could sleep well knowing all was done.”
Moving Beyond Baselines: A Real-Time Approach to Measurement
Traditional development programs follow a familiar rhythm: baseline, midline, endline. Each evaluation is rigorous, but the gaps between them can span years during which programs keep running without knowing whether their approach is working. WPF’s Vice President of Innovation and Initiatives, Maureen Stickel, describes the approach simply: “WPF’s strategy is to ensure that teams have access to the information they need, when they need it, to make informed decisions without creating overly complex or expensive measurement systems.” Central to this is an automated monitoring pipeline, from data collection to visualization, that lets our private-sector partners see performance as it unfolds. This is complemented by annual Pulse Surveys: short phone surveys with the same cohort of farmers each year, tracking leading indicators such as farmer perception of the birds, profitability, and behavior change. “Instead of waiting until an endline evaluation to understand what worked and what did not, pulse survey data allows WPF and its partners to refine their approach in real time,” Maureen explains, “doubling down where messages are landing and making adjustments where adoption or outcomes are lagging.”What Happens in the Field: CommCare and the Data Collection Pipeline
Tokozile Ngwenya reviewing Power BI dashboards with a PMI partner.
Turning Data Into Decisions: The MEL Perspective
For WPF’s Monitoring, Evaluation and Learning (MEL) Analyst, Thierry Binde, the starting principle is clear: “Data is only useful if it helps us see reality clearly and act early enough to make a difference.” Thierry works across two complementary systems, routine monitoring through CommCare and Power BI and the annual pulse survey, which together provide, in his words, “both the operational heartbeat of the program and the lived experience of the people we serve.” “When routine data suggests strong reach, but pulse data tells a different story for certain farmer groups, that tension is often where the truth lives.” — Thierry Binde, MEL Analyst, WPFThierry Binde leads a data training for FSRs.
The Infrastructure Behind the Insights: Data Analytics at WPF
Behind every dashboard and data flow is Earl Pearce, WPF’s Data Analyst. Every morning, Earl verifies that CommCare’s connection to WPF’s cloud-based data system is running normally, then updates custom dashboards for each partner, confirming that data is flowing correctly. Those dashboards give partners and internal teams a daily window into program performance and gives Tokozile information she needs to help improve data quality with on-the-ground FSRs. Earl also leads flock planning and DOC production forecasting, a discipline he has practiced for over 40 years. The process is a careful balancing act between sales targets, placement frequency, flock size, grow facilities, lay facilities, and biosecurity standards. “It’s like squeezing a balloon,” he says. “Every change impacts everything else. Rebalancing is key.” When birds underperform against targets, flock sizes can be adjusted to compensate; when placement timing shifts, the entire production flow adapts accordingly.”WPF Forecast Dashboard example.
Data as a Partnership Tool
For Vice President of Operations Jan, WPF’s data investments are only valuable if partners use them. “Without data we’re working in the dark,” he says. “Good data shows us where to adjust, where the issues are, and where we’re making progress.” The system tracks field staff performance, bird health, brooder unit progress, and demographic data and crucially, works offline, so connectivity gaps don’t create data gaps. Real decisions have followed. In Senegal, Power BI dashboards revealed strong engagement in a specific region, leading to a decision to increase staffing there. Data on women’s participation rates informed a marketing decision to feature women exclusively in program communications. The team is now building farmer profiles across regions to enable more tailored campaigns. “You need a good amount of data before you can see trends,” Jan notes, “but equally, we need to help partners actually use what’s available, moving them from data recipients to data users.”WPF Power BI dashboard example.
A System Built to Learn
What emerges from these conversations is a data system genuinely designed to serve programs, not the other way around. Every layer exists to answer a practical question: Is this working? For whom? And what should we do differently? As Maureen puts it: “The goal is not simply to collect more data, but to continue strengthening how data flows through the system, from collection to analysis to decision-making, so that insights are used consistently to improve program design and outcomes.”The post From Field to Decision: How WPF Uses Data to Build Better Poultry Programs appeared first on World Poultry Foundation.
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