It took only three years for Grab to become the biggest ride-hailing service company in Southeast Asia. Three years ago, there were only one million devices that used to download Grab’s app. Today, the number has increased to 63 million devices. They also receive thousands of bookings per second from its customers. Impressive, right?
In order to keep up with this rapid growth, Grab decided to add hundreds of database so that they can save the data track record from the customer’s booking history. Grab now has more than dozens of terabytes (TB) worth of data and logs.
But such huge data doesn’t only stay in Grab’s system. The ride-hailing service company utilizes the data to improve its operational system. With a better day-to-day operational system, Grab believes they could improve its products and services, thus creating a much more satisfying experience for customers.
Regularly upgrading its platform
In order to maintain its’ huge amount of data and keep it relevant, Grab always rewrites its system once in two years. That’s why Grab’s engineering team focuses on providing a solution that is realistically applicable for two years period. The challenge is, of course, predicting what problems that might emerge in the next couple of years.
Thankfully, Grab’s engineering team consists of a handful of experienced people. They use their past professional experiences to predict the trends so that they can provide the solution, as well as upgrade Grab’s platform to become more scalable. In the last five years, Grab has performed a system-rewrite for three times. This year, the company did it for the fourth time.
Collaboration between engineers in various countries
Grab realizes how important data is to their company. Through the data utilization, Grab is able to get an insight into their customer’s behaviors. This allows them to create more-targeted products and services that could fulfill the customer’s needs in terms of ride-hailing service.
It’s no wonder that Grab is willing to make a big investment to build research and development center (R&D center) in various locations. Until today there are at least six research and development centers Grab has built, which are located in Seattle (AS), Ho Chi Minh (Vietnam), Singapura, Beijing (Tiongkok), Bangalore (India), and Jakarta (Indonesia).
Please keep in mind that Grab chose those locations based on specific reason. Grab always considers the availability of local engineers that have enough skills and competence to help them grow their business. For locations that are actually not in Grab’s business area—such as Seattle, Beijing, and Bangalore—Grab decided to choose them because those cities have good-skill engineers due to the presence of A-class technology companies.
What’s more interesting is that Grab’s engineers, who work from various countries, literally make a collaboration so that they can learn from each other. For instance, engineers in outside Southeast Asia are assigned to help all Grab’s engineer teams to solve problems whenever it arises. On the other hand, local engineers focus on providing a solution because they have a better knowledge of Grab’s market.
Rush Hour Optimization
Grab also uses its data analytics to handle the service in rush hour, such as after-office hour or weekend. The data utilization will optimize customer’s booking process, as well as driver’s order pick-up. It will also help Grab to find out which area has a high demand for the ride service, thus allows them to fulfill the demand with the right amount of supply. On the other hand, the data utilization also enables Grab to provide special bonus or promo to its customers and drivers in the area.
You also must notice every time you order a Grab, the app will show you the driver’s estimated time of arrival (ETA). This is also the product of Grab’s big data analytics. By knowing the driver’s ETA, you’ll know what time the driver will arrive and you can use the time to do other things.
GrabShare and GrabNow: Grab’s Big Data Innovations
There are many innovations Grab has created by utilizing big data. Two of them are GrabShare and GrabNow. GrabShare allows you to carpool in a car or a taxi with another party headed in the same direction. By using GrabShare, you can reduce your fare and your carbon footprint, too. Grab even guarantees that there will be no more than one additional drop-off point, so customers won’t have to make any unnecessary detours.
Meanwhile, GrabNow digitizes the street-hailing experience by enabling passengers to flag down and connect instantly with a Grab driver via the app. Through GrabNow, Grab wants the customer to have the immediacy of street-hailing as well as the benefits of the Grab app, including cashless payment, GrabPoints, and safety standards.
Helping government to make traffic jams less awful
Grab’s big data journey doesn’t stop there. They have also worked together with the World Bank to provide data to transportation agencies in the region through an open source tool called OpenTraffic. This source converts GPS data from Grab’s 250,000 drivers in six countries in the region into anonymized traffic statistics such as speeds, flows, and intersection delays. The aim is, of course, to help the government combat the traffic jam.
Handing the data to government means transport agencies will now be able to monitor traffic conditions in real-time and make decisions based on information that was previously not available. When OpenTraffic was first implemented in the Philippines in 2015, the result was quite interesting. The platform discovered that the maximum average travel speed in Manila during weekdays is 38 KM per hours, way lower than Singapore’s 55 KM per hour.
Grab’s data will help the government analyze peak hours for major roads and highways, identify areas most available to bad weather, and spot those with the most accidents. This way, public agencies can better manage travel demand and cut travel time, design flexible routing schemes, and assign traffic personnel where they are needed the most.
Access to big data means access to insightful information. Whoever controls the information, controls the decision-making. With this accurate information, Grab is able to make fact-based decisions that do not only help them improve the operating system, but also create better service for the customers.