Issue link: https://resources.esri.ca/i/1313392
36 | GEOSPATIAL STRATEGY ESSENTIALS FOR MANAGERS MATTHEW LEWIN In terms of understanding past issues, we have a few opportunities. We could map and compare where voting place delays have occurred to look for trends. We could identify where clusters of delays have happened to pinpoint broader spatial patterns. And we could examine how external influences like road conditions and facility conditions impact opening a voting place. Historical analysis of this nature helps with comprehension and understanding. It's essential for making informed and actionable decisions. If the elections office is going to reduce opening delays, this knowledge is invaluable. The insights gathered from the historical analysis can also be used for future-trend analysis. This is where we start to see significant value— moving from past-tense analysis to future-state predictions. Here we have a few opportunities. We could develop predictive models to estimate the likelihood of delays at specific voting places. As well, we could design predictive models to suggest alternative sites where delays are less likely. These are a few examples, but the opportunities are tremendous if you take the time to explore the lens. By working through the use cases systematically, you can reveal some intriguing possibilities. To apply the Geospatial Lens, translate the general analysis patterns described in the lens into specific use cases relevant to a business capability of interest. Example Business Capability: City Electoral Management > Election Day Management > Voting Place Management Key Desired Business Outcome: Voting place setup tasks are completed and the voting place is open on time DESCRIBE Characterize the situation DIAGNOSE Identify root cause PREDICT Forecast future conditions PRESCRIBE Suggest actions Location Map and compare the "open and ready" status of voting places across the city Distribution Map and compare clusters of delayed openings Distribution Determine why delayed voting place openings were clustered in certain areas by examining associations with traffic conditions, public transportation access, facility conditions etc. Location Forecast delays in opening voting places based on current traffic, weather and facility conditions Correlation Estimate how delays in opening voting places will impact wait times Location Recommend alternative voting locations based on likelihood of opening delays