Recently, colleagues in the cleantech cluster at MaRS were trying to understand where their clients are located, specifically looking at the concentration of cleantech clients in Ontario and Quebec. This kind of information is useful not only in their decision-making, but also in telling the story about the cleantech cluster and the work it does.
We saw this as an opportunity to test out some of the new tools and techniques we’ve been exploring over the past few months.
To help create these visualizations, we turned to Tableau because it has built-in geocoding. Tableau automatically recognized the first three digits of clients’ postal codes (known as the Forward Sortation Area or FSA) and placed the clients on a map based on the location of their postal codes. This was a much faster and simpler solution than getting an exact latitude and longitude from the street address, and it also gave a sense of hot spots where a number of firms were clustered in a single location.
The preliminary maps below show MaRS clients from Kingston to Montreal. Clearly, quite a few clients are in the Ottawa area.
We also wanted to take this work a little further, so we decided to explore client density. By increasing the size of the dots where there is a higher density of firms, we noticed that the K2K FSA in Kanata, ON, has an especially high density of cleantech clients.
How does this compare to the larger MaRS portfolio in the same geographic area? We added all MaRS clients to the map and colour-coded them to identify their sectors.
These kinds of visualizations give us a good way to explore our impact and reach, and they help MaRS advisors make better decisions about where and how to target their services. We’re convinced that this kind of data can help all kinds of organizations working in the innovation support ecosystem.