The Monitor Institute has a new data visualization tool designed to help funders see relationships between their funding and grantmaking by other foundations but potentially useful for community planning applications. Itâ€™s a very cool tool â€“ it offers clear, clear visualizations of multiple data layers, itâ€™s easy to navigate, and they obviously put a lot of thought into the user interface. This could be a useful tool for mapping all of the organizations that work on a specific issue within a particular community, for instance, or for mapping the relationships between different issues in a community or regional planning process.
On first blush, there are two important elements Iâ€™d love to see on the next iteration. One is a Gapminder-type capacity to show change over time. I like that you can change the date range, so you can see the relative longer-term investments across sectors, etc., but you canâ€™t see trends unless you manually change the date from one year to the next â€“ clunky and not easy to do. The trends matter . . . a large investment this year in a subsector or by a particular foundation may mask a downward trend, which would be just as important to notice if you are trying to understand the relationships, seams, and opportunities. The other would be some capacity to show multiple dimensions at once, again like Gapminder does. This basically shows a single set of flat relationships on each screen. In your mindâ€™s eye you can build a less-flat model of how each of the flat pieces relate to one another, but the tool doesnâ€™t really help you do that.
The distribution model is also unclear to me. If their vision is a closed, proprietary system run through the Monitor Institute, well, that might be useful for whichever funders want to play ball, but itâ€™s a lot less useful to the rest of us. If their vision is a stand-alone, self-contained tool, I can picture a lot of very useful ways organizations could use the tool to help them map their landscapes more effectively and more clearly through strategy.
And as the Philanthropy 2173 blog reminds us, with every data visualization tool you have to ask about the data themselves. Garbage-in-garbage-out is still the rule no matter how cool the visualization tool is.
Cross-posted on the PlaceMatters blog.