Categorising spatially enabled dashboards

Lately I’ve been working with dashboards quite a bit. For clients who don’t really understand spatial data, it’s easier for them to digest the information on the map when it’s presented along with the graphs and indicators they are familiar with from Excel or Power BI.

Over the last few weeks, Julian has spent quite a bit of time setting up a number of dashboards using Operations Dashboard, each with a different purpose. On one project, we have a dashboard showing the client the real-time progress of fieldworkers on a map, along with some graphs showing the breakdown of assignments which are in progress and completed per district. It enables the client to answer questions such as which worker is causing a bottleneck. This dashboard consumes the workers and assignments layer from the Workforce for ArcGIS project, along with the various Survey123 feature services.

On another project, we have a dashboard showing the results of an asset life cycle cost analysis model. This dashboard includes graphs depicting when the client can expect to incur the greatest cost to replace key assets, as well as helping to answer questions such as: Is it cheaper to replace an asset in 5 years, or to spend an additional amount on maintenance in 3 years in order to extend the remaining useful life of the asset by 7 years?

We also have a number of ideas in dev at the moment, including the actual software we use to display the dashboard (that will have to be a post by itself). I’ve been mulling over how to package these different dashboard types as solutions to offer to a client. I decided to adapt the traditional categories to our purpose.

  • Operational: This is the basic dashboard, as detailed in my first example. This type will normally display two maps – one showing real-time progress of fieldworkers and their assignments, and another showing the surveys they submit along with actual data. Graphs may include the amount of assignments completed per worker, per area or along whichever dimension is most logical (or whatever the client prefers). Filters are included to drill down through the live data.
  • Analytical: This dashboard shows the results of analysing the data displayed on an operational dashboard (my second example). A single map can be used to display the analysis results per survey or per area. Graphs will vary according to client needs, but will be based on the survey points in the map. The user can interact with the dashboard by drawing various reports that they need, creating pivot tables, filtering etc.

My current dev efforts are focussed on a third type of dashboard. For a large project last year, I designed and implemented a mobile data capture solution which incorporated a QA process (to be carried out by professional engineers) as well as an invoicing process (to reduce turnaround time between carrying out the work and getting paid by the client). I’ll have to use another post to brainstorm that idea.

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