@ the IERP® Global Conference, August 2023
Presented by Dr Khoo Guan Seng, Advisory Board Member of the Singapore Economic Forum’s EU-ASEAN Centre, this session focused on the evolution of data. Data, said Dr Khoo, may be divided into two types: structured and unstructured (or alternative). Structured data is formatted data such as what is found in passports, airline tickets or identification, he explained. Unstructured or alternative data is usually found on social media – Zoom, WhatsApp, Youtube, Instagram etc. information from GPS instruments and satellites also qualify as unstructured data, as does the information that e-hailing or public transport companies like Grab have on you through your use of their services.
Unstructured data has grown in popularity, and has been increasingly consumed, even prior to the Covid-19 lockdowns worldwide. “It’s particularly popular in the US,” he said. “There is a demand for unstructured data, especially for ESG data. This led news company Bloomberg to develop a data platform which divides the data available initially into six modules: company-level data, commodities, sentiment, healthcare, consumer and geopolitics.” Detailing each of these categories, Dr Khoo gave examples of how different applications could actually utilise unstructured data to support structured data in ways that could increase companies’ bottom lines, among other benefits.
For instance, Owl Analytics focuses on ESG consensus scores. “All data tied to environmental, social and governance factors is considered alternative data,” he said, further explaining Bloomberg’s move to develop its alternative data platform in 2019. “The standards used to rate ESG vary,” he said. “There’s no benchmark. What Owl Analytics does is take all the different company ratings and give it an average. Instead of telling you one rating is right or another is wrong, it tells you the average…and allows you to make your own decision.”
The other company he reviewed under this module, Apptopia, provides software development kits for companies which are not technology-based but want to use technology to create their own apps. Apps can be developed to capture all information produced by the business to help form an accurate picture of business performance. This is particularly helpful for shareholders tracking their investments. “If your company is Subway, for instance, you can get the app from Apptopia, which will immediately monitor your business,” he said. “Apptopia will monitor where and when the app was downloaded, what it is being used for, what the user purchases etc.”
At the end of the day, the Apptopia app will be able to provide information immediately. Subway will be able to see how well it is doing because the information is dynamic and real-time, as the app catches all information pertaining to the sales of Subway products. The company will be able to determine which outlet is profitable, and not have to wait for quarterly or even monthly reports. The speed with which it accesses this information makes it flexible and more capable of pivoting, and may be able to give it an edge over the competition.
Despite listing three companies dealing with natural gas, metals, and oil storage, respectively, under the Commodities segment, Dr Khoo cited the example of Cargometrics, a data analytics company that specialises in global maritime trade. Its freight optimisation and oil inventory level monitoring tracking system allows it to track oil price changes by tracking the ships’ journeys via satellite so that they always utilise their carrying capacity profitably on their outbound and inbound journeys, including trading in the commodity markets. For instance, a ship carrying oil from Copenhagen to Port Klang is empty after offloading its cargo, so it can pick up something else from ports along its return route to maximise its space and cover part of its operating costs. So successful was Cargometrics that its technology was bought over by shipping giant Maersk in 2019, just three years after making its debut.
Another successful venture, PredictWallStreet, leveraged on traders’ sentiment to identify which stock would most likely be bought by investors. Its recommendations were based on measuring interest in certain stocks through a simulated stock market game (or bourse games). The more interest in a particular stock, the more people checked and chatted about it, lengthening a ‘temperature bar’ as they did so. If the company in play was not popular, the temperature bar was shorter, indicating it was not a ‘hot’ stock. Such data is usually sold to hedge funds.
PredictWallStreet started in 1999, and sold data to its first customer in 2002, demonstrating the success of a business model built on sentiment. Some companies choose to apply technology to Health care; Evaluate is one. It has chosen specifically to apply its know-how to provide data from phase 1 and 2 clinical trials conducted in the pharmaceutical industry. This is particularly important in light of the recent pandemic, and the race to produce vaccines to save lives. For the Consumer module of the platform, Dr Khoo used the airport duty free areas to illustrate how data was applied by designers to induce travellers to spend.
Companies like Thasos design mall streams that ensure visitors spend their time looking at shops and displays, and use data gathered from cameras and other field instruments to determine optimum foot traffic flow and maximum exposure for retailers, who use the information to strategise and hone their marketing and positioning. The sixth module of Bloomberg’s alternative data platform, geopolitics, was a quick, concise overview of four industrial revolutions, and why global politics looks the way it does today. The first industrial revolution, in the 1800s, saw the majority of people using carriages, rather than walking.
Industrial technologists benefitted from the rise of engines and automation, and became very powerful. Colonisers, especially, benefitted from the industrial revolution, which was then coal-based. “The second industrial revolution, in the early 1900s, was epitomised by Henry Ford, who invented the production line,” Dr Khoo said. “This allowed mass manufacturing, which translated into mass consumerisation and the proliferation of consumer goods. Countries that were rich in resources, like the UK with its North Sea oil, became very powerful. The third industrial revolution saw the rise of the Internet and the dotcoms.”
The geo-economic powers that dominated during the industrial revolutions because of the technology they developed, continue to dominate as the world goes into the fourth industrial revolution: the rise of artificial intelligence (AI) and AI-driven automation. “A lot of geopolitical strife is rooted in the industrial revolutions,” he said. The influence of former dominant, mostly western, powers is waning with the development of different regions; other countries are more effectively learning to utilise their own resources. The ’Chip War’ between the US and China is a case in point. These uncertain, disruptive times are likely to continue, with unstructured data both feeding into, and feeding off, the unsettled environment.
