{"id":2593,"date":"2015-12-07T20:25:56","date_gmt":"2015-12-08T01:25:56","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/uberpool-transportation-for-everyone\/"},"modified":"2015-12-08T23:18:08","modified_gmt":"2015-12-09T04:18:08","slug":"uberpool-transportation-for-everyone","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/uberpool-transportation-for-everyone\/","title":{"rendered":"UberPool \u2013 Transportation for Everyone"},"content":{"rendered":"<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>UberPool, a service where a user\u00a0shares a ride and splits cost with another traveler(s) who happens to be going in the same direction,\u00a0is revolutionizing transportation by making it affordable to everyone, reducing congestion and pollution. Launched in Aug&#8217;14\u00a0in selected cities, UberPool has already created significant impact. UberPool makes half of all trips in San Francisco and\u00a0in the first eight months of operations in Los Angeles, it cut the number of miles driven across town through\u00a0ride-sharing by 7.9 million and prevented CO2 pollution by 1,400 metric tons.<\/p>\n<div>\n<p><strong>Business model<\/strong><\/p>\n<p>Biggest value to users is cost saving. Riders can save up to 50% by adding a few minutes of time per trip. With lower prices, people can move past car ownership, as taking Uber becomes less expensive than using and maintaining a personal vehicle.<\/p>\n<p>Users are price sensitive, a behavior that is seen often when users do not call an Uber during price surge. Uber\u2019s business model is to get exponential increase in number of rides even though at lower price points to increase overall revenue and stickiness. For drivers, more users and ride requests result into higher overall revenues. Drivers&#8217;\u00a0utilization increases and driving cost\/user reduces through\u00a0optimal routes to minimize commute and maximize\u00a0riders. More number of drivers ensures higher availability and lower turn-around times for users and in-turn gets more users, creating a self-reinforcing virtuous cycle.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-2574 aligncenter\" src=\"https:\/\/i4tsk12in2b2y7uts14c528g-wpengine.netdna-ssl.com\/wp-content\/uploads\/sites\/4\/2015\/12\/screenshot-300x253.png\" alt=\"screenshot\" width=\"300\" height=\"253\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2015\/12\/screenshot-300x253.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2015\/12\/screenshot.png 354w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>Another business goal of Uber is expand and own the transportation market by\u00a0capturing users across multiple segments, from those who want affordable UberPool to those who want premium experience through UberBlack, becoming the go-to transportation service for everyone.<\/p>\n<p><strong>Operating model<\/strong><\/p>\n<ul>\n<li><u>High liquidity<\/u>: For a match, many users need to going in the same direction at any given time. By lowering prices, Uber is gaining a large share of users. Its market leadership and strong brand also helps.<\/li>\n<li><u>Technology<\/u>: Uber\u2019s data centric platform\u00a0is key its success. Given a set of ride requests, it is very difficult to find the optimal route to minimize time and commute for a driver (Traveling Salesman Problem). UberPool is solving this in real time across millions of users while ensuring reliability and quick\u00a0service. Uber applies machine learning and data science to learn user behavior and predict rides\u00a0as well as predict macro trends based on the day of the week and prevailing price points.<\/li>\n<li><span style=\"text-decoration: underline\">Built on\u00a0existing infrastructure and network<\/span>: UberPool uses the same network of drivers, reaches users by a small icon in the existing app by providing the same user experience (instead of launching a new app), uses the same brand and is built upon the existing technology infrastructure. UberPool is leveraging everything that is successful with Uber, thus increasing Uber&#8217;s\u00a0network effects even further. The marginal costs of launching UberPool for Uber are much lower than\u00a0a new competitor.<\/li>\n<li><u>Leveraging external factors<\/u>: People\u2019s work hours are similar to a large extent. Many cities have concentrated business hubs and residential areas, as a result of which large number of users move from same source location to same destination around the same time frame. The fact that real estate is not increasing at the same rate as population is helping UberPool. Uber is utilizing these factors in choosing urban cities with dense\u00a0working population to launch (eg. San Francisco, New York, Paris) and also, positioning drivers at right locations at right times.<\/li>\n<\/ul>\n<p><strong>Alignment of business and operating models<\/strong><\/p>\n<p>UberPool\u2019s operating model leverages technology to be able to find &#8216;n&#8217; users, say 3, to share a ride, thus reducing the cost per user by 3 resulting in lower prices for users and lower cost\/user for drivers. This creates business value for both users and drivers. High liquidity or scale in terms of number of users is key for ride sharing to work. Lower prices enabled by its operating model enable it to get the critical mass of users needed for UberPool. Its technology is complex and advanced,\u00a0hard for competitors to replicate. As with machine learning, its technology gets much better with time as they are able to train their algorithms better and get more information about users and drivers.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-2575 aligncenter\" src=\"https:\/\/i4tsk12in2b2y7uts14c528g-wpengine.netdna-ssl.com\/wp-content\/uploads\/sites\/4\/2015\/12\/1screenshot-300x162.png\" alt=\"1screenshot\" width=\"581\" height=\"314\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2015\/12\/1screenshot-300x162.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2015\/12\/1screenshot-600x324.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2015\/12\/1screenshot.png 749w\" sizes=\"auto, (max-width: 581px) 100vw, 581px\" \/><\/p>\n<p>References<\/p>\n<p>&#8211;\u00a0http:\/\/venturebeat.com\/2015\/12\/08\/uber-is-testing-a-new-commuter-transit-service-in-seattle-and-chicago\/<\/p>\n<p>&#8211; http:\/\/newsroom.uber.com\/la\/2015\/04\/its-a-beautiful-pool-day-in-the-neighborhood\/<\/p>\n<p>&#8211; http:\/\/abovethecrowd.com\/2015\/01\/30\/ubers-new-bhag-uberpool\/<\/p>\n<p>&#8211;\u00a0http:\/\/www.huffingtonpost.co.uk\/jo-bertram\/uberpool-london_b_8716652.html<\/p>\n<p>&#8211;\u00a0http:\/\/recode.net\/2015\/04\/16\/uber-says-that-millions-of-people-have-taken-uberpool-its-carpool-option\/<\/p>\n<p>&nbsp;<\/p>\n<\/div>\n<div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>UberPool is providing affordable transportation to riders and increased number of rides and revenues to drivers using its data-driven technology platform.<\/p>\n","protected":false},"author":974,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","categories":[164,7],"class_list":["post-2593","hck-submission","type-hck-submission","status-publish","hentry","category-transportation","category-winner"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/the-tom-challenge-tom-winners-and-losers-assignment\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - 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