NYC Vs. Covid 19

  • Research Question: How was the movement of Human Resources during the NYC Pandemic?
  • Audience: Everyone in NYC, and maybe beyond, as this is a human resources analysis created with inside data that may respond to important questions of business administration, logistics, and, of course, Economics.
  • The data to embark on this question: Since February 2020, I have been working for the NYC Department of Health and Mental Hygiene as an ICS (Incident Command System) Staffing Coordinator (and been the only one in the city during 2 months, while my supervisor got infected with virus, until he safely returned). My mission has been to organize and mobilize agency personnel to work on the different areas where the city is in most dire need. Testing, contact tracing, schools, restaurants… etc. I have been collecting these personnel assignments data. By removing confidential data points, I may use that as a data source for analysis that would show how the movement of personnel across the agency has been.
  • A written Description of your visualization: This visualization seeks to break apart as much as possible the data available to me from the work I have been involved with during the pandemic period in NYC. The data belongs to the NYC Department of Health and Mental Hygiene and it is conformed by all the assignments covered by its employees since the beginning of the emergency response. I thought it would be nice for the viewer to get a brief and compelling introduction so they know what the subject is going to be while feeling identified with the difficulties such an event may cause. Then the viewer jumps right into the data analysis. The second slide of the story shows data on the number of assignments given to employees per month. Below, there is a detailed explanation of how these numbers are produced. The following slide shows another treemap that exposes which positions are mostly needed during the pandemic. I thought this would be specially interesting for people wanting to know the critical knowledge behind the fight against a virus and what type of skills are likely to lead to a career in the field. Good news is: Data analyst are among the leading roles.
  • An explanation of the data and design decisions you made: As mentioned before, the idea is to draw a story from numbers that may be a bit boring and meaningless to the average citizen, but with enough explanations here and there, and also some narrative and structure, I am confident that anybody may feel connected to this data in particular. That is why almost every slide contains an explanation that I call optional, because it is not in a prominent space, but could be easily accessed in case the viewer needs feels like learning more. I also chose tree maps because there were by far the simplest way to show at a glance the most and least of each category given that that titles were so numerous. Barcharts were chosen on the other slide, because it allowed for easy comparison and navigation.
  • Next steps. I would like to extend the number of visualizations showing more insights. I still have many more ideas of what can be acquired by continuing to analyze these data. The challenge is to present it while maintaining every slide as interesting as the other.