Armed with data and nowhere to go

Armed with data and nowhere to go

More and more companies are building teams to collect information, but putting it to use isn't easy

Analysts say Thailand is in the early stages of data analytics and needs at least half a decade to catch up with the US. Illustration courtesy of Google
Analysts say Thailand is in the early stages of data analytics and needs at least half a decade to catch up with the US. Illustration courtesy of Google

On the ninth floor of True Corporation's sprawling digital park in Bangkok, a team of 150 parses billions of data points, attempting to shape the sea of information into sense.

Simply collecting the data is the easy part. As a provider of telecom services, digital entertainment and broadband internet, True has access to a massive trove of user data, from TV-show preferences to real-time location metadata. Finding a way to apply this data into producing tangible benefits takes highly skilled analysts, compelling use cases and leadership to bring it all together.

Companies across Thailand are beginning to build teams like this as harnessing big data becomes vital for corporations to stay competitive and avoid being completely overtaken by disruptive newcomers. The coming decade will be defined by how the public and private sectors use this data to benefit the lives of ordinary people or stifle them with increasing encroachment on their privacy.

Starting in May 2020, Thais will have better data protection by law under the Personal Data Protection Act, as daily life is increasingly catalogued and tracked by the country's most ubiquitous companies.

DATA TO PROFITS

Bernd Vindevogel, chief analytics officer of True Digital, says his department, which he describes as the biggest data analytics outfit in Thailand, could potentially generate 3-4 billion baht a year in revenue for the company, or 2-3% of total revenue, if the data they collect is optimised to its fullest extent. His team logs and analyses 20 billion data points a day from True customers.

"It is not exceptional for companies to have a large data team and for it to not make an impact," he said. "You need people to make a bridge between the data team and the business interests."

Without use cases, the data sets do not mean much for the company's bottom line. Mr Vindevogel says data teams need to communicate with the business side and find out what they need to make their jobs easier or their connections with customers smoother and then find out how data analytics can solve these problems.

For instance, True uses customers' personalised data profiles, drawn from TrueID media consumption habits or their mobile top-up spending, to better inform their sales team when they call customers to recommend new products. For instance, a customer who only tops up a prepaid plan in small amounts is more likely to default on payment when switching to postpaid, so the salesperson would be advised not to recommend postpaid to that customer.

Mr Vindevogel says the data team is becoming more crucial as disruptive technologies threaten True's telecom business. E-SIM, a new technology in which a SIM chip is implanted inside the phone, allowing users to switch carriers and data plans without having to get a new SIM card, may disrupt the entire business model of many telecoms, especially as new paths to connect to existing networks emerge. Mr Vindevogel says this may push True to move beyond simply selling access to its network and prioritise the TrueID multimedia platform as its core revenue driver.

Before use cases are considered, companies must develop a platform with which to analyse the data. This requires a team of highly skilled programmers and data scientists, fields that are in short supply in Thailand.

"While our turnover is not too high, my people often get poached by other companies," Mr Vindevogel said. "The trick to retaining good people is to give employees cool and interesting things to do and make sure our top talent are intellectually challenged."

As more and more companies rely on data for their decision-making, top data analysts will be more and more in demand. While some are brought in from overseas, the majority remain Thai and companies are scrambling to hire at increasingly higher salaries. As artificial intelligence (AI) automates many of the simpler tasks required to analyse data, less-skilled data analyst jobs are drying up, while higher-skilled ones are increasing to manage the increasingly complex algorithms being developed.

According to a report by Robert Walters, data analysts made 1.2-2.4 million baht for the year in 2019. Of all mid- to high-level tech workers, 32% stay less than two years in a role and expect a 15-30% salary increase when switching jobs. Among tech workers, 56% expect a 7-15% salary increase each year for staying at the same job.

A woman walks past a sign advertising 4G mobile technology by True Move. The telecom uses customers' personalised data profiles drawn from TrueID media consumption habits. NARUPON HINSHIRANAN

PLAYING CATCH-UP

While Thai corporations rush to become leading data pioneers, Vilaiporn Taweelappontong, consulting lead partner at PwC Thailand, says Thailand is still in the early stages of data analytics and needs another 4-5 years to catch up to cutting-edge data countries such as the US.

"I think companies in Thailand see data as very critical for growth, but the maturity and level of understanding is not quite there yet," she said. "Many are investing a lot and buying the tech without looking at the data they actually have."

A 2018 survey by PwC found that only 27% of business leaders in Thailand used data analytics in decision-making and just 38% used data analytics to predict and monitor skills gaps in the workforce.

"The volume of data will only increase, and Thai companies must hasten to develop infrastructure to make sense of all the incoming information," Ms Vilaiporn said.

The advent of 5G, the next generation of mobile networks that will be rolled out over the next few years in Thailand, will mean millions of new products connecting to the mobile network through the Internet of Things.

"Self-driving cars are the best example of technologies that could operate on the 5G network and require a huge amount of data to function," Mr Vindevogel said.

As he puts it, older corporations are having the toughest time building data infrastructure, which has to be built on top of older, clunkier legacy systems, while new digital companies like Grab and Lazada have been able to build their data collection from scratch and have a data-driven decision-making strategy.

"As an incumbent, the investment in a platform is bigger than for digital-born companies," Mr Vindevogel said.

DIGITAL NATIVES

Perhaps no company has a better grasp of Thailand than Grab, one of Southeast Asia's most successful startups. The ride-hailing app has evolved into an all-purpose super-app.

"No one understands the region better than we do," said Tarin Thaniyavarn, country head of Grab Thailand. "We use this data to elevate the experience of our marketplace participants, including consumers, drivers and merchants, and to solve some of the biggest problems in the region. This includes building AI solutions that improve user safety and traffic congestion, break down language barriers to enable seamless communications among marketplace participants, optimise dispatch system and overall efficiency in our marketplace and provide the most personalised and relevant services to users."

Some examples of insights that Singapore-based Grab was able to draw from data are finding the best location to open its "cloud kitchen", a collection of delivery-only restaurants accessible through the Grab app alone, by finding an area with low costs but a high volume of delivery orders. The company also worked with the Transport Ministry and various public and private organisations to use GPS data from GrabTaxi to reduce traffic congestion on Rama IV Road.

"As we grow our application to cater to more users, we will need to better understand our users to be able to provide solutions that help, whether they are new services, features, promotions or deal packages," Mr Tarin said. "For consumers, the pain points are always about finding services that bring the most convenience and safety. For our merchant partners, the challenge is maintaining growth in offline sales as online behaviours continue to develop, while our driver-partners receive better income opportunities."

Singapore-based Lazada, Southeast Asia's largest e-commerce company, has a massive logistics network in Thailand to manage, keeping track of millions of orders and parcels, as well as creating personalised experiences for millions of customers. But according to Lazada's deputy chief executive for Thailand, Jack Zhang, the key to a good data strategy is restraint.

"People ask Lazada why we collect customer data, but if you do a transaction on the platform, of course it is saved," Mr Zhang said. "We don't proactively collect data, but the transactions leave a footprint in the system."

The key areas where Lazada uses data is to create individualised customer profiles to recommend relevant products. For instance, he says his wife's Lazada home page is filled with fashion and beauty products, while his own skews towards electronics.

To improve the overall platform, Lazada uses the metadata of all customers, but it does not have the ability to parse out individual customers' information.

"We have very strict policies for privacy protection and do not sell data to individuals and third parties," Mr Zhang said. "Our job is much easier than that of social networks, as the data recorded is pretty straightforward -- just the things they buy on our platform."


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