Monitoring & Evaluation
Designing monitoring workflows, indicators, reporting structures, and systems that support evidence-based decision-making.
01 / Who I Am
I build systems that make data work harder.
My work sits between monitoring and evaluation, data management, and technology. I work with information that needs to be collected, organized, validated, analyzed, and ultimately turned into something people can use.
Rather than treating data as something that simply ends up in a report, I look at the entire workflow behind it. Where does the information come from? How is it captured? Where can errors occur? How can the process become easier for the people doing the work?
This approach has led me to design and build dashboards, databases, validation tools, automated workflows, and web-based systems that support real operational needs.
Role
M&E Officer
Focus
Data & Systems
Building
Web-based Tools
Approach
Problem → System → Impact
02 / What I Do
Turning problems into systems.
My work combines M&E practice with practical technology to create tools that support the full data lifecycle.
Data Systems
Building structured systems for collecting, storing, validating, managing, and retrieving operational data.
Dashboards & Analytics
Turning complex datasets into dashboards, visualizations, and reporting tools that make information easier to understand.
Automation
Reducing repetitive work by designing automated workflows for data processing, reporting, validation, and routine operations.
Data Quality
Creating validation and correction workflows that identify inconsistencies before they become larger reporting problems.
Web-based Tools
Developing practical interfaces that allow users to interact with data and operational processes without requiring technical expertise.
03 / How I Build
Building with AI.
I use artificial intelligence as a development partner when designing and building systems. It helps me explore ideas, prototype solutions, write and understand code, troubleshoot problems, and accelerate development.
But AI does not replace the thinking behind the system. I define the problem, understand the workflow, determine the requirements, make architectural decisions, test the results, and decide what ultimately belongs in the product.
For me, AI is another tool in the toolbox. The goal isn't simply to generate code faster. The goal is to solve better problems, build better systems, and learn along the way.
→
AI-assisted development · Human-led decisions
04 / My Approach
Understand the problem before building.
01
Start with the workflow.
I first look at how people actually work, where information comes from, and where the current process creates friction or errors.
02
Design around the user.
A system should make work easier, not simply introduce another layer of technology. I prioritize practical interfaces and understandable workflows.
03
Build, test, and iterate.
Systems rarely become right on the first attempt. I build incrementally, test the workflow, identify what breaks, and improve the system from there.
04
Keep the outcome in sight.
Technology is only useful when it improves something. The final measure is whether the system produces better information, better processes, or better decisions.
I don't just analyze data.
I build the systems that make it
useful.
Explore the systems, tools, and data workflows I've built.
Explore My Projects →