Zafar Anjum | Oct. 3, 2012 | MIS ASIA

It is common experience that when it rains, it is difficult to get a cab in Singapore-even when you try to call one in or use your smartphone app to book one.

Why does it happen? What could be the reason behind it?

Most people would think that this unavailability of taxis during rain is because of high demand for cab services.

Well, Big Data has a very surprising answer for you, as astonishing as it was for researcher Oliver Senn.

In 2011, Oliver Senn, a senior research engineer with the Singapore-MIT Alliance for Research and Technology (SMART), spent five months working on a joint initiative to give real-time data and insights to citizens to help them improve their city, according to storage and Big Data solutions company EMC. EMC revealed this case study at an event in Singapore on Tuesday (2 October).

When Senn was first given his assignment to compare two months of weather satellite data with 830 million GPS records of 80 million taxi trips, he was a little disappointed. "Everyone in Singapore knows it's impossible to get a taxi in a rainstorm," says Senn, "so I expected the data to basically confirm that assumption." As he sifted through the data related to a vast fleet of more than 16,000 taxicabs, a strange pattern emerged: it appeared that many taxis weren't moving during rainstorms. In fact, the GPS records showed that when it rained (a frequent occurrence in this tropical island state), many drivers pulled over and didn't pick up passengers at all.

Senn confirmed his findings by sitting down with drivers. And what did he learn?

He learned that the company owning most of the island's taxis would withhold S$1,000 (about US$800) from a driver's salary immediately after an accident until it was determined who was at fault. The process could take months, and the drivers had independently decided that it simply wasn't worth the risk of having their livelihood tangled up in bureaucracy for that long. So when it started raining, they simply pulled over and waited out the storm.

This unexpected revelation, a direct result of the data study, stunned the company.

Now, armed with this insight, they are strategising about how to fix a policy that obviously doesn't work for customers, drivers, or the parent company. Says Senn: "This was a powerful example of how one of the world's most data-driven countries is improving the lives of its citizens by providing scientists and researchers with access to that data."