DePaul University Divvy Bikes Data Analytics Paper Please look at the docx for the details on the Divy Bike Assignment.Three short parts with everything ne

DePaul University Divvy Bikes Data Analytics Paper Please look at the docx for the details on the Divy Bike Assignment.Three short parts with everything needed included. Information for Decision Making
Data Analytics Assignment Part I
Summer, 2020
Name:
Divvy Bikes
Background Information:
Divvy is a bicycle sharing system in the City of Chicago and two adjacent suburbs that is
operated by Motivate for the City of Chicago Department of Transportation. The system includes
5,800 bicycles spread among 580 stations in an area bounded by 87th St. on the south, Central
St. in Evanston on the north, Rainbow Beach Park near South Shore Dr. on the east, and Harlem
Ave.in Oak Park on the west. Divvy is available for use 24 hours/day, 7 days/week, 365
days/year, and riders have access to all bikes and stations across the system
Divvy is a program of the Chicago Department of Transportation (CDOT), which owns the city’s
bikes, stations and vehicles. Initial funding for the program came from federal grants for projects
that promote economic recovery, reduce traffic congestion and improve air quality, as well as
additional funds from the City’s Tax Increment Financing program. On June 28, 2013, Divvy
was launched with 750 bikes at 75 stations from the Loop north to Berwyn Ave, west to Kedzie
Ave, and south to 59th St. Divvy currently has approximately 600 stations and 6,000 bikes.
Contract with City of Chicago:
In April, 2019 the city of Chicago entered into a nine-year contract with Lyft (owner of the
current Divvy operator, Motivate) to give them (Lyft) the exclusive rights to operate the cityowned system and retain a portion of future advertisement revenue. This arrangement
transferred the operating of Divvy Bikes from the City of Chicago to Lyft. The arrangement
requires Lyft/Motivate to collect the receipts from customers and pay an annual fee to the
city of Chicago.
The contract with Lyft dramatically increases the annual guaranteed revenues and reduces the
financial risk to the city. Lyft will pay the city an annual payment of $6 million, which will
increase by four percent each year. (first payment was in June, 2019) Further, the city will
receive $1.5 million in minimum guaranteed revenue from advertising and promotions, and five
percent of all rider revenue that exceeds $20 million per year. Over the nine year life of the
contract, this totals a minimum of $77 million in guaranteed revenue available for investment in
Information for Decision Making
Data Analytics Assignment Part I
Summer, 2020
Name:
transportation improvements and programming. This arrangement would also require Lyft to
invest $50 million to add 175 stations and 10,500 bikes to the Divvy system, expand to all 50
City of Chicago wards by 2021, and add electric pedal bikes which could lock to both Divvy
stations and conventional bike racks. The agreement between Lyft and the city of Chicago is
posted on D2L under Data Analytics.
Divvy Pricing:
Divvy has two primary classes of users: subscribers and customers. Subscribers pay an annual
fee of $99 for unlimited rides limited to 45 minutes in duration. Customers may pay either $3
for a 30-minute (or shorter) trip or a daily fee of $15. Subscribers make up approximately 76%
of Divvy’s total rides. As of December 31, 2019 there were approximately 40,000 subscribers.
In 2018, approximately 198,000 24-hour passes were sold to customers. The average subscriber
trip was 15.3 minutes long in 2018 while the average customer trip (both daily/individual rides)
was 62.6 minutes long.
Assignment Part I:
You have been hired as a business advisor to Divvy Bikes/Lyft. In order to become more
familiar with the Divvy system and the presentation of Divvy-related data, you will perform
some descriptive analytics tasks in the attached assignment. All data is available on the City of
Chicago data portal at https://data.cityofchicago.org/ .
This assignment should be submitted via D2L in the Submissions folder labeled Data
Analytics Part I by 11:59 p.m. on Sunday, July 19th, 2020.
Information for Decision Making
Data Analytics Assignment Part I
Summer, 2020
Name:
Directions:
A. Complete Table 1. The source of the information will be the Divvy Dashboard on the
Chicago Data Portal. https://data.cityofchicago.org/Transportation/Divvy-TripsDashboard/u94x-unre
B. Complete Table 2. The source of the information will be the Divvy Dashboard on
the Chicago Data Portal. https://data.cityofchicago.org/Transportation/Divvy-TripsDashboard/u94x-unre
C. Answer the questions listed after the tables. Your answers should reflect the
knowledge you gained from analyzing Tables 1 & 2 and the information provided about
Divvy Bikes/Lyft/Motivate.
Information for Decision Making
Data Analytics Assignment Part I
Summer, 2020
Name:
Table 1:
Total number of
trips
Number of trips
taken by
subscribers
Number of trips
taken by
customers
Identify the Top 3
Trip Stations
where Subscriber
trips begin (i.e.
From Station
Name) (Name/list
each of the top 3
stations)
Identify the Top 3
stations where
Subscriber trips
end (i.e. To
Station Name)
(Name/list each of
the top 3 stations)
Identify the Top 3
Trip Stations
where Customers
trips begin (i.e.
From Station
Name) (Name/list
each of the top 3
stations)
Identify the Top 3
stations where
Customer trips
end (i.e. To
Station Name)
(Name/list each of
the top 3 stations
February,
2018
July, 2018
June, 2019
November,
2019
Information for Decision Making
Data Analytics Assignment Part I
Summer, 2020
Name:
Table 2:
Total number of trips
Identify the month during
each year with highest
number of subscriber
trips
Identify the month during
each year with the
highest number of
customer trips
Identify the month during
each year with the lowest
number of subscriber
trips
Identify the month during
each year with lowest
number of customer trips
2017
2018
2019
Information for Decision Making
Data Analytics Assignment Part I
Summer, 2020
Name:
Questions:
1. What patterns of behavior in terms of frequency of rides do you notice during the year? (i.e.
during which month(s) are customers and subscribers using the bikes the most/the least)
2. Using the top 3 subscriber departure stations; identify what is located at/nearby those
departure points. Based upon these departure stations why do you think that the majority of
subscribers typically use Divvy Bikes?
3. Using the top 3 customer departure stations identify what is located at/nearby those
departure points. Based upon these departure stations why do you think that the majority of
customers typically use Divvy Bikes?
4. In terms of quantity of rides do more subscribers or customers use Divvy Bikes?
5. Assuming there are 40,000 subscribers in 2019 what is the approximate annual subscriber
revenue?
6. If an existing subscriber takes additional rides during the year will that provide additional
revenue to Divvy?
7. Impact of COVID 19: Using the insight you gained from analyzing the tables/answering
questions 1-6 answer the following:
a. What do you predict will happen to the total number of
subscriber rides for March, 2020 (remember that Shelter in
Place took effect Saturday, March 21, 2020) compared to
March 2019? Explain your answer.
b. Assume all subscriber renewals take place on the first day of
the month. Based upon your prediction in part (a) do you
think the subscriber revenue in be impacted in March, 2020?
Explain your answer.
c. What impact do you predict that COVID-19 will have on the
quantity of customer rides from April 1, 2020 – June 30,
2020? Provide at least 3 reasons to support your answer and
explain your conclusion.

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