USAID Guatemala

The Vision

The USAID Guatemala Mission needed a systematic way to answer a deceivingly simple question: “Where are we working?” Previously, answering routine operational and geographic questions required hunting down data across more than 60 disjointed Google Sheet trackers and manually synthesizing it. The Mission needed a robust, centralized data infrastructure to manage “activity location data”—but crucially, they needed to do it without introducing overly complex enterprise software that staff wouldn’t adopt.

The Solution

We built Atlas, a data management approach and suite of tools that leverages the interfaces the Mission already uses while enforcing rigorous data standards behind the scenes.

• Data Hub: A publicly available Google Site serving as the central portal for the Mission to share data, tools, and guidance with staff and nearly 100 implementing partner representatives.
• Automated Pipelines: Instead of asking for data multiple times, Atlas uses automated pipelines (via Google Apps Script) to pull activity data directly from decentralized field trackers into a centralized PostgreSQL/PostGIS database.
• Custom Web Applications: With data centralized, we built out-of-the-box interactive applications—including a Data Catalog, a Map Viewer for contextual indicators, and a public Activity Location Data Portal—using Google Apps Script, Tableau, and Esri ArcGIS.
• Institutional Framework: Established a dedicated “Data Steward” role and formalized the Digital, Data, and GIS Program to foster a true culture of data use.

The Outcome

The Mission successfully transitioned from managing 60+ disconnected trackers to a streamlined, geospatial approach. By adopting a “customer service” mentality to data requests, the MECLA team organically grew support across the Mission, drastically reducing the time required to answer operational questions and enabling rapid, data-informed decision-making.

The takeaway: Sometimes the best solution isn’t complex new enterprise software, but a disciplined approach leveraging the tools users already know. By building automated pipelines between familiar front-end interfaces (Google Workspace) and robust relational backends (PostgreSQL), organizations can achieve high user adoption rates without sacrificing data integrity.