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A new super at 60 Turner place

DHUM 73000 – Fall 2019 – Blog Post 1

Research Question: Did the number of tenant complaints regarding building maintenance issues change after our new super was hired?

Audience: Tenants in our building may be interested to see these results also building management may want to see this. There was a lot of controversy in the building in late 2016 and a neighborhood council was involved as well. They may also want to see this data.

Description: Using 311 Service Requests available through NYC Open Data for complaints made by residents at 60 Turner Place, the dashboard below shows the volume of building maintenance related complaints generated by the tenants at 60 Turner Place, in Brooklyn, NY. Overall numbers show a swell of complaints from 2013 through 2017, then a decrease starting in Summer 2017 that is maintained through the current year, 2019. The detail bar chart shows quarterly complaints by type, to show the wide range of complaints. The heating issues of 2010 through 2014 appear to be corrected, while plumbing issues continue to be a problem in the building.

After downloading the 311 data for my zip code, 11218, I had over 160,000 data points. I further filtered that by address to get 650 complaints. SInce I live in the building of over 100 units, I thought that I may be able to give some context to the findings. In particular, the chaotic time in 2016 when there were so many complaints about the super, resulting in a protest march in front of the building, documentation of complaints in published news articles, a CBS television news report and a neighborhood council meeting with building management to try to air out grievances. The 311 data contained complaints that were under the control of the super (appliances, heating, plumbing, hallway maintenance issues) and issues that were out of the control of the super (street lights, noise, parking). I filtered the data by the super-related issues, and visualized that as a stacked bar histogram. The pop-up boxes display the count for that issue in that quarter. Tableau functionality also allows the viewer to click on any specific complaint type in the color legend to view complaints for that specific type over all quarters. I decided to show quarterly rather than annual data because it more clearly highlights the drop in the 2017, when Felix was hired. The two area charts below the histogram were added to show total ANNUAL complaints, both for the filtered maintenance type complaints, and for the total building complaints, to see annual totals instead of quarterly numbers. I added the column labels to display the total numbers over the area charts.

A limitation of this project is that selection of the complaint TYPE is made by multiple people at the time the complaint is made. The reason one person selects “General Construction” for window issues, while another selects “Door/Window” complaint types is unknown. For this reason, its important not to make decisions based on the distinct types of complaints, but rather the overall total, and in particular, the overall change in number of complaints. I’ve displayed types only to show the varied nature of complaints included in this visualization.

Next Steps: If we had not yet hired a new super at 60 Turner, I would have shown the increase in complaints to our building management company as documentation of complaints in the building that may be the responsibility of the super. This sort of visualization can be used to review complaints at any large building, especially if the neighborhood council has received specific complaints about the super. This could be a starting point in the review process.

In terms of addressing the data accuracy limitation, this would require that all complaints are coded according to a very rigorous rubric, which may impede the user-accessible nature of the 311 online and telephone systems. Perhaps another system might ask for key words in the complaint (data found in the “descriptor” column) then automatically assign a Complaint type. This would eliminate duplication of descriptions across multiple complaint types.