From manual to automated: Transforming Living Goods’ monthly reporting process

In the world of public health, data isn’t just numbers on a spreadsheet—it’s a lifeline that connects communities to the healthcare they desperately need. For organizations like Living Goods, which supports digitally empowered community health workers (CHWs) across multiple African countries, timely and accurate reporting is crucial for saving lives.

However, as a data-driven organization, Living Goods recognized their existing reporting processes weren’t as efficient as they could be. This case study explores how IDinsight partnered with Living Goods to transform their data systems through automation, turning a cumbersome reporting cycle into an efficient operation, delivering timely, actionable insights. Our thanks go out to the Children’s Investment Fund Foundation (CIFF) for their generous financial support for this engagement.

The challenge: A reporting marathon hindering impact

Living Goods is “fanatical about numbers” and committed to infusing “data into end-to-end operations” to drive cost-effective, high-quality community health programs. Yet, their previous monthly reporting process was holding them back from reaching their goals.

For nearly two weeks each month, the analytics team across Kenya, Uganda, and Burkina Faso embarked on a labor-intensive “report season“. Key challenges included:

• Manual & time-consuming processes: Analysts spent hours downloading data from disconnected databases, running individual data analysis programs (often complex R scripts stored on personal laptops), manually checking calculations, and copying visualizations into presentations. The entire cycle took approximately two weeks.  
• Fragmented systems: Each country often operated a separate data ecosystem with its own collection methods and reporting standards, making cross-country comparisons difficult and prone to inconsistencies. If leadership wanted to compare performance, teams had to align definitions manually and recalculate metrics.  
• Decision delays & data distrust: By the time reports were finalized, the data was often outdated, hindering timely decision-making. The manual process and inconsistencies could also lead to errors and data distrust among field staff.  
• Resource drain: The process consumed significant analyst time that could have been used for deeper, value-added analysis.
• Knowledge silos: Like many organizations, critical knowledge often resided with specific individuals rather than being embedded in documented systems. This reliance on individuals (“institutional knowledge lived in people, not systems”) created risks and inefficiencies, especially during staff absences or departures.

These inefficiencies took a toll, limiting capacity for innovation and hindering the ability to optimize the life-saving work of CHWs who perform critical services like treating children, registering pregnancies, and providing family planning guidance.

A vision aligned with strategy: The catalyst for change

Living Goods’ 2022-2026 strategic plan emphasizes saving “lives at scale through country-led, digitally-enabled community health systems”. To achieve this vision, Living Goods recognized they would need to transform their existing data infrastructure. As an organization dedicated to using high-quality data for decision-making, they knew enhancing their data systems was essential to empower CHWs and achieve greater impact and cost-effectiveness. The goal was clear: create a unified, automated analytics platform.

The transformation journey: Building a new foundation

Partnering with IDinsight, Living Goods embarked on an ambitious project focused on three core areas:

1. Breaking down data silos: A centralized data warehouse was established, standardizing information from all sources (including CouchDB, ODK forms, SurveyCTO data). This created a “single source of truth” with consistent data definitions and metrics, allowing for true cross-country comparisons while respecting local contexts.

2. Automating the reporting pipeline: The manual data processing steps, including those run on individual devices, were replaced with a modern, automated data transformation framework (using tools like dbt). This new system runs automatically on a schedule, includes built-in quality checks, creates clear documentation, and handles updates efficiently. The process moved from hundreds of manual steps to a system that essentially runs itself overnight.

3. Democratizing data access: Instead of static monthly reports arriving weeks late, the new system provides stakeholders with timely insights through interactive dashboards and automated reports delivered promptly via email and SharePoint. Consistent metrics and role-based access ensure users get the trusted information they need.

The results: Faster, smarter insights for better health

Living Goods transformed its reporting process from a multi-week manual effort to an automated system delivering fresh insights every 24 hours. Key outcomes include:

• Efficiency gains: Reporting time dropped from over two weeks of effort to a few hours at most, freeing analysts for higher-value work.
• Timely, reliable data: Standardized, fresh metrics now reach decision-makers days earlier, enabling quicker action across countries.
• Smarter decision-making: living goods can now:
  • Detect issues and disease outbreaks earlier
  • Evaluate interventions consistently across contexts
  • Optimize allocation of staff and supplies
  • Share trustworthy results with donors and government partners
• Scalability: The system easily adapts to new countries or data sources with minimal effort.

This shift goes beyond efficiency—it’s enabling better decisions and better health outcomes.

This aligns perfectly with Living Goods’s DESC (Digitally-enabled, Equipped, Supervised, Compensated) approach, ensuring their internal systems embody the efficiency and data-driven principles they promote externally.

The technical journey: From fragmented to unified

While the benefits are clear, the transition wasn’t without challenges. The IDinsight team needed to:

1. Understand legacy systems: Document and decipher years of accumulated R scripts and manual processes
2. Standardize definitions: Work with stakeholders across countries to align on consistent metric definitions
3. Build data lineage: Create clear paths showing how raw data becomes actionable insights
4. Automate quality checks: Implement tests to ensure data accuracy and completeness
5. Train users: Help team members transition from consumers of reports to empowered data users

The hardest part wasn’t the technology—it was getting everyone aligned on what each metric actually means. When you have different countries with different health systems, creating truly comparable metrics requires both technical skill and diplomatic finesse.

The team ultimately succeeded by focusing on the end users—the program staff and CHWs whose work directly impacts community health. Every decision about the system was guided by how it would help these frontline workers deliver better care.

Lessons for other organizations: A roadmap for transformation

Living Goods’ journey offers valuable insights for other nonprofits and health organizations facing similar challenges:

1. Invest in data infrastructure as a program priority, not just an administrative function
   1. Recognize that good data systems improve efficiency and directly impact program outcomes
   2. Budget appropriately for data transformation initiatives
2. Standardize metrics across programs and geographies while respecting local context
   1. Develop a shared data dictionary with clear definitions
   2. Create governance processes for managing metric changes
3. Automate routine reporting to free up analyst time for deeper investigation
   1. Start with the most time-consuming, repetitive processes
   2. Build in quality checks throughout the automated pipeline
4. Create clear data lineage and documentation so everyone understands where numbers come from
   1. Document calculation methodologies transparently
   2. Make it easy to trace from raw data to final reports
5. Democratize access to insights through user-friendly dashboards and reports
   1. Design for different user personas and their specific needs
   2. Provide training to build data literacy across the organization

From reports to results: The true impact

The transformation of Living Goods’ reporting system highlights that the true value of data lies in the actions it enables. By removing the reporting bottleneck, Living Goods has accelerated its ability to deliver on its mission: saving lives at scale by empowering CHWs and the communities they serve. Automating reporting should enable program managers to resolve problems faster, CHWs to get timely support, and ultimately, more families to access the care they need to survive and thrive. That’s the real power of turning data into action.