The Bigger Picture

Data is messy. Monitoring and evaluation data, collected across countries and projects by different people with different priorities and using different tools is particularly difficult to streamline. Different teams also view data differently, and may prefer to start off with thinking about where an activity is happening, when the activity is taking place, what is being reported, or who is involved. 

To help you better consolidate your data without losing any of the nuances that different teams bring to the table, DevResults enforces a data structure that captures these many approaches while making it easier for users, teams, and organizations to slice and dice results by the metrics most important to them. At the end of the day, DevResults is the expression of the format that your data should take. 

We've laid out our approach to Data Structures and highly recommend you read this before starting to set up your DevResults site. 


One of the building blocks of any data framework is noting what the big picture is: what the work being done is going to achieve. On DevResults, we refer to these as Activities, and every indicator has to be linked to at least one Activity. You can define an Activity to be whatever makes the most sense to you, so this could be an award that you're working on, or awards or sub-awards you're managing, or any other central organizing feature that you use. We've talked about how we think about Activities and Organizations in detail. 


The what of development work is often denoted by indicators. Indicators give us a clear and replicable way to measure the impact of work being done in each Activity. We've put together a quick walkthrough on how to think about indicators in the context of DevResults in our Indicator Guidebook.

One of the ways in which organizations can judge relative impact of what they're doing is by looking at disaggregations within specific indicators. For example, you may want to look at whether there have been more men than women at a series of trainings, which in turn could help you restructure the way you select trainees in the future. We provide several options for handling Disaggregations.


All work happens somewhere. We believe adding geographic information about the work you're doing (whether it's at specific location or at the country level) helps better organize data. We've written extensively about Geographies and how to make it work. 

Want to try it out yourself? You can get a feel for DevResults (and how everything fits together) on our demo site.

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