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Divvy
Bike share
rebalancing
program
Kelly Fan & Oswald Vinueza
Kelly fan
Data Analyst
Oswald vinueza
Data Analyst
Our team
outline
The problem
The data
01
02
Our recommendation
Benefits + Constraints
03
04
Future steps
05
context
➢ 2018: Lyft bought Divvy bike share’s
parent company + introduced ebikes
➢ Since Covid 19: bike share programs
much less negatively affected than
mass transit
○ Focusing on pre-covid data
Problem
➢ Several high-demand bike stations
run low on bikes by EOD
➢ Current bike rebalancing system by
Divvy is not effective enough
➢ User assistance to rebalance bikes
needed
objective
➢ Create a new bike rebalancing
program incorporating user
assistance
➢ Ensure user safety when
traveling
➢ Divvy Bike Data 2016-2019
➢ Chicago Crime Data 2016-
2019
○ https://data.cityofchicago.org/
Public-Safety/Crimes-2001-to-
Present/ijzp-q8t2
➢ Divvy Data
○ Trip ID
○ Start and End Time
○ Station Name
○ Latitude
○ Longitude
○ Docks
➢ Crime Data
○ Crime ID
○ Date
○ Crime Type
○ Latitude
○ Longitude
The data Key columns
➢ Most popular times for bike share are work
commute hours:
○ 6am - 9am
○ 5pm - 8pm
➢ Trips lasting > 1 day are considered stolen
➢ Trips with negative durations are
considered bad data
Assumptions/Limitations
➢ Create a program that:
○ Incentivizes users traveling to
overpopulated end stations to
change end station to nearby in-
demand station (trip credit rewards
for subscribers)
○ Alerts users if end station is a crime
hotspot
Our recommendation
Our recommendation
Add credit rewards
here!
Benefits
➢ Takes into account user safety
➢ Recommends end station based on
location, demand, and bike occupancy
➢ Helps with rebalancing issue for higher
system efficiency
➢ Credit rewards system encourages
customers to become subscribers
➢ Pricing strategy to be further investigated
by finance team
➢ Need to notify users once implemented to
increase awareness and combat potential
initial resistance
➢ Crimes can still occur in historically low-
crime areas
constraints/risks
➢ Bike share programs are not as negatively
affected by Covid 19 + Lyft owns Divvy →
○ Consider partnering with Lyft’s travel
rewards partnerships (Delta Airlines,
JetBlue, Hilton Honors)
○ Further incentivize users to become
subscribers + assist with rebalancing
Future Steps
Resources
➢ https://www.divvybikes.com/
➢ https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-Present/ijzp-q8t2
➢ https://energynews.us/2020/02/21/chicagos-bike-friendly-investments-not-benefiting-all-
parts-of-the-city-equally/
➢ https://chicago.curbed.com/2018/7/2/17526918/lyft-divvy-motivate-acquisition
➢ https://citymonitor.ai/transport/the-decisions-cities-made-about-coronavirus-had-a-big-
impact-on-bike-share-ridership
➢ https://www.forbes.com/advisor/credit-cards/the-best-credit-cards-and-rewards-programs-
for-lyft-rides/
Data dictionary
Thanks
Questions?
Contact Us:
➢ Kfan@talentpath.com
➢ Ovinueza@talentpath.com

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Divvy Bike Share Rebalancing Program

  • 2. Kelly fan Data Analyst Oswald vinueza Data Analyst Our team
  • 3. outline The problem The data 01 02 Our recommendation Benefits + Constraints 03 04 Future steps 05
  • 4. context ➢ 2018: Lyft bought Divvy bike share’s parent company + introduced ebikes ➢ Since Covid 19: bike share programs much less negatively affected than mass transit ○ Focusing on pre-covid data
  • 5. Problem ➢ Several high-demand bike stations run low on bikes by EOD ➢ Current bike rebalancing system by Divvy is not effective enough ➢ User assistance to rebalance bikes needed
  • 6. objective ➢ Create a new bike rebalancing program incorporating user assistance ➢ Ensure user safety when traveling
  • 7. ➢ Divvy Bike Data 2016-2019 ➢ Chicago Crime Data 2016- 2019 ○ https://data.cityofchicago.org/ Public-Safety/Crimes-2001-to- Present/ijzp-q8t2 ➢ Divvy Data ○ Trip ID ○ Start and End Time ○ Station Name ○ Latitude ○ Longitude ○ Docks ➢ Crime Data ○ Crime ID ○ Date ○ Crime Type ○ Latitude ○ Longitude The data Key columns
  • 8. ➢ Most popular times for bike share are work commute hours: ○ 6am - 9am ○ 5pm - 8pm ➢ Trips lasting > 1 day are considered stolen ➢ Trips with negative durations are considered bad data Assumptions/Limitations
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. ➢ Create a program that: ○ Incentivizes users traveling to overpopulated end stations to change end station to nearby in- demand station (trip credit rewards for subscribers) ○ Alerts users if end station is a crime hotspot Our recommendation
  • 15. Benefits ➢ Takes into account user safety ➢ Recommends end station based on location, demand, and bike occupancy ➢ Helps with rebalancing issue for higher system efficiency ➢ Credit rewards system encourages customers to become subscribers
  • 16. ➢ Pricing strategy to be further investigated by finance team ➢ Need to notify users once implemented to increase awareness and combat potential initial resistance ➢ Crimes can still occur in historically low- crime areas constraints/risks
  • 17. ➢ Bike share programs are not as negatively affected by Covid 19 + Lyft owns Divvy → ○ Consider partnering with Lyft’s travel rewards partnerships (Delta Airlines, JetBlue, Hilton Honors) ○ Further incentivize users to become subscribers + assist with rebalancing Future Steps
  • 18. Resources ➢ https://www.divvybikes.com/ ➢ https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-Present/ijzp-q8t2 ➢ https://energynews.us/2020/02/21/chicagos-bike-friendly-investments-not-benefiting-all- parts-of-the-city-equally/ ➢ https://chicago.curbed.com/2018/7/2/17526918/lyft-divvy-motivate-acquisition ➢ https://citymonitor.ai/transport/the-decisions-cities-made-about-coronavirus-had-a-big- impact-on-bike-share-ridership ➢ https://www.forbes.com/advisor/credit-cards/the-best-credit-cards-and-rewards-programs- for-lyft-rides/

Editor's Notes

  1. kelly
  2. both
  3. kelly
  4. kelly
  5. kelly
  6. kelly
  7. kelly
  8. Kelly When looking into data, found thousands of trips lasting over a day  per company policy, considered stolen
  9. oswald
  10. oswald
  11. oswald
  12. oswald
  13. oswald