Data Science Disruptors: How Uber Uses Applied Analytics For Competitive Advantage
By now you’ve no doubt heard about Uber, the wildly popular app that connects riders with drivers in more than 200 cities around the world. While you may appreciate it as a great alternative to hailing a taxi the old-fashioned way, or are simply awestruck by its more than $40 billion valuation, there are other aspects of the company that are equally impressive. Specifically, I’m talking about how Uber combines mobile technology with cloud infrastructure, direct customer feedback, location data and other innovations to deliver a superior solution.
In fact, Uber’s use of data science is perhaps the most disruptive — and therefore awe-inspiring — aspect of what it does. It’s a great example of a company that’s innovating in what we at Georgian Partners calls applied analytics: the intersection of data science, information rights and business processes.
Data Science-Driven Approach
Uber invests significant resources in applying data science to interpret and analyze the vast amount of data it collects. In October 2014, for example, it had 15 open positions for data scientists and it continues to actively hire in this area.
The output of that investment is a range of insights that help Uber direct drivers to the best spots to get customers, estimate the arrival time of its vehicles, and create real-time pricing, among other things. The success of the company hinges on its ability to drive efficiency and create positive user experiences, both of which it accomplishes through statistical data analysis. Importantly, what makes a company like Uber stand out is that its data science-driven insights don’t just live in company reports or dashboards. They’re actually embedded into its app, creating a better user experience for drivers and customers alike.
Extensive Information Rights Are Key
Uber uses your personal data in an anonymised and aggregated form to closely monitor which features of the Service are used most, to analyze usage patterns and to determine where we should offer or focus our Service. We may share this information with third parties for industry analysis and statistics.
While Uber has recently been the target of a lot of criticism in the media for alleged misuse of customer data, it is to be commended for the focus here on getting insights from anonymous, aggregated data.
The benefits of Uber’s insight-driven model are not only apparent in the utility of its service, but also in terms of its overall performance. In a 2014 presentation, for example, Uber’s head of data science, Kevin Novak, claimed that the company could deliver 5 percent more trips overall with the same number of drivers by recommending where drivers should hang out. Just to be clear, a 5 percent increase in output for a company generating billions of dollars in annual revenue is a huge deal.
Here’s another example of the kinds of improvements that Uber has achieved thanks to its focus on data science-driven insights. According to a recent #UberData blog post, back in March 2011 in San Francisco (the only city where the company was operating at the time), you had an 80 percent chance of getting picked up within 10 minutes and a 94 percent chance of getting picked up within 15 minutes. By 2014, despite having expanded to become a global business, back in San Francisco things had improved. That year, customers had a 97 percent chance of being picked up in under 10 minutes and a 99.5 percent chance of being picked up within 15 minutes.
Uber has amassed a treasure trove of data in the past few years, which it’s now using to attract new data science talent, further compounding it’s data science-driven advantages.
It’s not just the major disruptors like Uber that are leveraging the convergence of data science, information rights and business processes to shake up industries or outsmart their competition. In our role as investors we talk to companies, both established businesses and new entrants alike, that are using applied analytics strategies in a wide range of industries. Whether it is agriculture, cyber security, education, financial services, healthcare, retail or almost any other industry you can think of, applied analytics is becoming a go-to strategy for software-enabled companies.
So the next time you find yourself in an “uber” experience, think about some of the data science that’s likely going on behind the scenes. The quality of service you’re enjoying is probably a direct result of countless data being analyzed, and insights applied, to create a better solution for you.