Uber Travis Kallanick Interview Transcripts

https://www.cnbc.com/2016/03/28/cnbc-transcript-interview-with-travis-kalanick-ceo-and-co-founder-of-uber.html

https://www.washingtonpost.com/blogs/mike-debonis/post/uber-ceo-travis-kalanick-talks-big-growth-and-regulatory-roadblocks-in-dc/2012/07/27/gJQAAmS4DX_blog.html?utm_term=.0a0226ee1e4e

https://www.youtube.com/watch?v=rQ6GoY2_Ujw
Talk in 2012

Avg Pickup time in SF is 2.48 mins
In NY, first it was 12 mins. now, it is 5 mins.

In NYC, taxis operated based on medallions. 13,000 medallions since 1946. Same number of taxis in the city. Each medallion cost $1 million. $13 billion industry and vested interest to fight against.

50% of those who users the last time they paid was in the last 30 days.

Demand Prediction. Congestion Prediction. Supply Matching. Supply Positioning (predict demand 20 minutes ahead will be heat. Potential problem of all drivers going there. Supply right now is anti-heat. The remaining is the residual heat, underserved demand on a neighborhood-to-neighborhood basis). Smart Dispatch Algorithms. Dynamic pricing.

http://abovethecrowd.com/2015/01/30/ubers-new-bhag-uberpool/

Armed with this new data, Uber leaned on its legendary “math department” to help drive prices even lower. This is the name that founder and CEO Travis Kalanick has given to his team of scientists and hardcore mathematicians who own the back-end routing algorithms for Uber. Uber’s technology goes well beyond its client side smartphone applications; there is also a server-side intelligence system that provides demand prediction, congestion prediction, supply matching, supply positioning, smart dispatch, and dynamic pricing. These are the systems that help balance the more than one million rides per day that are matched on the Uber system.

The “math department” and management realized that if they could increase driver utilization (the number of rides per hour for a driver), then they could lower the price for the end user while maintaining earnings quality for the driver. Higher efficiencies through higher volumes and better algorithms could help deliver the desired lower price points and better cash flows. Interestingly, these lower price points would lead to more demand, even more liquidity, an even higher utilization, and then another incremental price decrease. Pretty quickly UberX passed UberBlack to become the highest volume service on the Uber platform.