Uber’s Success Is Deeply Tied To Its Success In India: Shirish Andhare
India is currently in a vital phase of its infrastructure, energy, and mobility development, which nicely sets the stage to leapfrog current or existing practices. According to sources, an estimated 40% of its population will be living in urban areas by 2025, and they will account for over 60% of the consumption of resources. Moreover, transportation in India is highly fragmented, disorganised across modes with poor infrastructure, congestion and low public transport density. Riders and drivers have to undertake multiple challenges daily such as lack of availability, reliability, quality, consistent pricing, safety etc. To know more about the current space and transportation in India, Analytics India Magazine caught up with Shirish Andhare, Director, Product Management, Uber India and South Asia. “Our goal is to change the Indian mindset and help people replace their car with their phone by offering a range of mobility options — whether cars, bikes, autos or public transport — all in the Uber app. By putting more people in fewer cars, we have the potential to build smarter and more liveable cities,” said Andhare. Using technology, Uber India has been trying to transform the mobility landscape and change how people move around in the country by playing a transformational role in addressing pain points for riders and adding efficiency into the system. With its multi-modal vision for mobility in India, Uber wants to make a variety of options available to help commuters get where they want to go at a price point that works for them. To that end, Uber has announced partnerships across airports and Metros in Delhi and Hyderabad to provide last-mile connectivity. Transformation of Uber India Andhare said that about seven years ago, Uber launched in Bangalore with just three employees. Today, Uber India has tech teams across Bangalore and Hyderabad. It continues its exponential growth journey, focusing on facilitating affordable, reliable and convenient transportation to millions of riders and livelihood opportunities for hundreds of thousands of driver-partners. The R&D teams located in Hyderabad and Bangalore continue to grow and currently host over a dozen global charters including rider, maps, customer obsession, infrastructure, money, and eats. These teams are driving global impact for Uber based on several India-first product innovations. Andhare said, “With over a billion trips in India and South Asia and counting, along with a large driver-partner base, we are focused on winning hearts and minds in the market. We plan to do this by doubling down on products that can solve for low network connectivity, congestion and pollution, as well as enable multiple price points with a varied set of offerings. Uber’s success is deeply tied to our success in India, we are in a strong position in India, and we are committed to serving the market.” He added, “As we gear up to deliver the next billion rides in the region, we remain focused on providing convenient, affordable rides to millions of riders and stable and sustainable earning opportunities to driver-partners.” Deep Tech At Uber Andhare stated that technology provides an incredible opportunity to improve road safety in new and innovative ways before, during and after every ride. At every step, Uber is maximising the usage of technology to bring transparency and accountability through features such as two-way feedback and ratings, telematics and GPS, among others. These will have a positive impact on furthering trust and empathy between riders and driver-partners. Uber’s Engineering Centre in Bangalore and Hyderabad are engaged in cutting-edge basic and applied technology solutions in areas that include rider growth, driver growth, digital payments, mapping, telematics, vehicle tracking/safety and fleet management, and the Uber core experience. Some of the India-first innovations include the in-app emergency feature, arrears handling, driver inbound phone support, cash trips, Uber Rentals for longer trips and UberGO. The company is investing heavily in research and resources. Some of the technologies used at Uber include computer vision, automation, Machine Learning(ML), Optical character recognition (OCR), and Artificial Intelligence (AI) techniques, NLP etc. These technologies are used in areas such as onboarding restaurant menus onto Uber marketplace, enabling earnings opportunities and more. It is also crucial to perform other tasks such as better routing, matching, fraud detection, document processing, maps editing, machine translations, customer support, and more. Training Model For Employees Andhare stated that the training model for employees is a multi-pronged approach. He said, “Right from robust onboarding programs to ongoing buddy/mentor support, from on-the-job learning opportunities to rotation experiences, from online modules to peer to peer sharing, we offer a plethora of ways for our employees to learn and grow.” He added, “We have resource groups and ongoing discussions on various topics across the company to exchange ideas, experiences and learnings. In our India tech sites, we regularly host tech talks and hackathons, so we can bring in the latest and best from the industry and can learn from them.” The company is looking to hire bright engineering talent from and in India and is focused on becoming the operating system of a city, enabling movement of people and things and thus, enabling and igniting opportunities for earners. Uber is also focused on serving the needs of the customers and making the product experiences magical, in turn allowing organic growth and stickiness on the platform. Effect Of Pandemic & How It Used Deep Tech To Mitigate The Issues Addressing this question, Andhare said that when the pandemic was spreading across the world, the priority of the company was the safety of the riders and partners. The company started creating awareness on ‘safety first’, and even discouraged the riders from taking rides unless absolutely necessary. They identified customer needs and estimated new business models to address those needs and move what matters, examples include delivery of essentials, transport of healthcare workers, partnering with governments, among others. Andhare said, “Even as many parts of cities were quarantined, we ensured that maps across cities around the world were updated and constantly modified based on the dynamic list of containment zones to better identify and service availability.” He added, “Our safety product team recognised that masks are going to be a necessity in the new normal and have invested heavily in building features that help keep our riders and driver-partners safe. One example is the application of mask recognition capabilities to ensure that our driver-partners wear masks for their safety and the safety of riders. Our teams in Hyderabad supported the sophisticated machine learning models that were deployed in this effort.” The tech teams accelerated digital payment integrations in some of the markets to enable social distancing measures. The company is also creating localised awareness campaigns to educate users of the platforms about safety measures. Staying Ahead Of Competition Andhare said that Uber has four advantages, i.e. customer obsession, operational excellence, technological innovation and a truly global network at a scale that helps them be ahead of the competitors. Being one of the largest global mobility platforms in the world, it allows the company to share learnings from one market to another and unlock economies of scale in engineering and operational elements of the business.
India is currently in a vital phase of its infrastructure, energy, and mobility development, which nicely sets the stage to leapfrog current or existing practices. According to sources, an estimated 40% of its population will be living in urban areas by 2025, and they will account for over 60% of the consumption of resources.  Moreover, […]
Using technology, Uber India has been trying to transform the mobility landscape and change how people move around in the country.
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["AI", "artificial intelligence", "machine learning", "ML", "NLP", "computer vision", "analytics", "RAG", "fraud detection", "R"]
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