Citi Bike Dashboard — BIA Case Study
Disclaimer:
This case study is part of the assignment in Business Intelligence Bootcamp by Binar Academy. We are not working nor affiliated with Citi Bike.
Background
Lyft, Inc is a company that operates a bike rental system under the brand named Citi Bike which has more than 17.000 bikes and 1.700 stations spread in US.
During its journey, Citi Bike held monthly meeting to find out how business growth and the operational team is required to present data in graphical form because the meetings are held with other teams.
This certainly makes business processes difficult since operational team should work harder to process data from raw to graphical form and other teams have to wait until at the end of the month to find out how business is running.
To solve the problem, BI team proposes an idea to build a dashboard that can be accessed in realtime so that all teams can receive an information whenever needed.
About Dashboard
The dashboard, which be called NYC Ride Analyzer is expected can present data about total trips in six years, day and hour of bike use.
Based on the requirements, BI team will devided the dashboard into 2 parts — top level and detailed metrics. On top level, there will be an informations about total trips in six years, average trips per day, average bike used per day, and average trips duration in minutes. The information on detailed metrics will be average trips based on gender, most popular bikes by number of time used, the bussiest start station, most popular day in a week, activity throughout years, and peak riding times.
Dashboard
Top Level Metrics
From total target that has been set at 70M trips, 46.9M have been achieved from July 1, 2013 to May 31, 2018. The other 3 top levels function to measure support target — the average number of trips per day is 29.5 thousand with average of reused the same bike twice per day and average of duration trips for 14 minutes. To monitor and analyze in depth, detailed metrics is needed.
Detailed Metrics
On average, women use bike for 14.9 minutes and men for 13.4 minutes. From this chart explains that women use bike longer than men with a difference of 2.5 minutes.
Bike with code 18104 is the most popular bikes with 6.349 uses and the bussiest start station is Pershing Square.
The increase in bike use occurs at 8 am and 5–6pm which are the time for leaving and returning from work.
Based on the charts, most bike use by months occurs on May and September and by day of the week on Wednesday and Thursday.
Recommendation
Based on explanation, we could give some recommendations such as campaign marketing for women and placement of favorite bike at stations with the highest rental. Pay more attention for maintain the bike with making maintain schedule on weekend and placement of new stations that reach recreation areas.
Last but not least…
This project will not be completed without the help of my coworkers, shoutout to Bernadetha Emma, Fiera Amelya, and Ryzal Adnan. Thank you!
If you have any feedback or business inquiries do not hesitate to reach me thru my LinkedIn.