The sharing economy enables people to efficiently get what they need when and where they want them. There are many successful examples, including Uber, Didi Chuxing, Airbnb, Ofo, DriveNow, etc. All these companies would not be viable businesses without leveraging a platform and a foundation of big data. These companies don’t just represent a new way of thinking or new services, but a new way to use data effectively to provide efficient services. In this talk, we use a bicycle-sharing system, which can provide shared bike usage services for the public, as a case study on exploring big data for logistic planning of better services. In bicycle-sharing systems, people can borrow and return bikes at any stations in the service region very conveniently. Therefore, bicycle-sharing systems are normally used as a short distance trip supplement for private vehicles as well as regular public transportation. Meanwhile, for stations located at different places in the service region, the bike usages can be quite skewed and imbalanced. Some stations have too many incoming bikes and get jammed without enough docks for upcoming bikes, while some other stations get empty quickly and lack enough bikes for people to check out. We will discuss the various logistic issues and solutions that utilize data to improve service quality.