Introduction

NYC Business Acceleration is a program within Small Business Services that assists individuals and groups opening or operation a food and beverage, industrial, or retail businesses as well as pre-kindergarten programs. Designed to help these businesses open or expand more easily and faster, operate more smoothly and with fewer challenges, and recover from emergencies, the Business Acceleration program has benefitted thousands of small businesses across the five boroughs since 2010.

I am interested in how this program has benefitted businesses of a variety of backgrounds, and am using this lab to explore which sectors have benefitted most from this program, as well as which boroughs have the most business development and how many jobs have been created from the accelerator.

Materials

I was inspired by the visualizations produced by former Pratt student Menglu Gao, analyzing restaurants in NYC. Given the similarities between her data and my own, I sought to produce a map that could spatially demonstrate the distribution of businesses supported by the NYC Acceleration Program and how many jobs have been created as a result of it.

I found the data listed on the NYC Open Data’s portal. I searched for data on small business development, as it is an interest of mine, as well as something I work on at the Pratt Center for Community Development’s Made in NYC initiative. Since I work on supporting small business development at my work, I was interested in the Business Acceleration Program and am hoping to further study its overlaps with members of the Made in NYC organization.

I brought the data into Tableau Public, where I was able to analyze the fields in regards to location, type of business, cuisine (the vast majority of businesses are restaurants or other food establishments), and number of employees. It was with Tableau Public that I produced all of my visualizations for this lab.

In addition to Tableau Public, I also used geocodio to geocode the addresses from the NYC Open Data to create x/y coordinates for each of the businesses. By geocoding the addresses, I was able to produce a map that reflects the location of each businesses and also symbolize the establishments by the number of employees they have hired.

Methods

Once I had the businesses geocoded, I pulled them into Tableau Public and mapped them, using the number of employees to symbolize each business both using size and color. Here I noticed the vast majority of businesses are food establishments, with the largest number in Manhattan.

Results

I also looked into the composition of the program by borough from 2010 to 2018. Not surprisingly, Manhattan had the largest amount of businesses opened within the program for its first five years, before Brooklyn became the leading borough for nearly two years. Since 2017, the program has supported businesses from Brooklyn and Manhattan about evenly. The vast majority of these businesses are in the accommodations and food sector.

Future Directions

In the future, I intend to further study this program and its overlap with Made in NYC, a nonprofit organization that supports small businesses and manufacturers across the five boroughs. As a project assistant with Made in NYC, I work with our collection of members, which includes over 1,300 small businesses across the food and beverage, jewelry, and home goods industries. In a future lab, I plan to bring our organization’s data about our membership and compare it to the Acceleration Program, to analyze how our members have or have not benefitted from this program.