Data is the new oil

In my opinion, data is the new oil as it decouples human productivity from fossil fuel. Indeed, data is the new oil is a vivid depiction of data's potential in replacing fossil fuel as human's main production means. Fossil fuel has been the main driver of human's industrial productivity leapfrog in 20th century. Fossil fuel powers up combustion engine and accelerates the advancement of mechanical engineering. However, in the era of machine learning, data will gradually replace fossil fuel as the main driver of industrial productivity with its capability to train autonomous electric vehicles, robotic automation processes, smart devices, and various professional services that involve high level of repetitive work routine. Besides, big data trained prescriptive analytic applications also enable the effective acquisition and efficient deployment of alternative energy to non fossil fuel powered vehicles and machines and therefore further reduce human's dependency on fossil fuel.

Reference:

1) OpenMind - Data: The Lever to Promote Innovation in the EU

Source: https://www.bbvaopenmind.com/en/technology/digital-world/data-the-lever-to-promote-innovation-in-the-eu/

[Excerpt] If we do a #10yearchallenge on how stock markets have evolved from 2008 to 2018 it is apparent that in the global ranking of corporations based on market capitalization, oil companies – which led the trading floor rankings for decades – have been replaced by so-called digital natives. Yet another symptom of the wager the new economy is making on companies with the best capabilities to process data as raw materials and transform them into useful and actionable information. [/Excerpt]

2) The Economist - The world’s most valuable resource is no longer oil, but data

Source: https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data

[Excerpt] What has changed? Smartphones and the internet have made data abundant, ubiquitous and far more valuable. Whether you are going for a run, watching TV or even just sitting in traffic, virtually every activity creates a digital trace—more raw material for the data distilleries. As devices from watches to cars connect to the internet, the volume is increasing: some estimate that a self-driving car will generate 100 gigabytes per second. Meanwhile, artificial-intelligence (AI) techniques such as machine learning extract more value from data. Algorithms can predict when a customer is ready to buy, a jet-engine needs servicing or a person is at risk of a disease. Industrial giants such as GE and Siemens now sell themselves as data firms.

This abundance of data changes the nature of competition. Technology giants have always benefited from network effects: the more users Facebook signs up, the more attractive signing up becomes for others. With data there are extra network effects. By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on. The more data Tesla gathers from its self-driving cars, the better it can make them at driving themselves—part of the reason the firm, which sold only 25,000 cars in the first quarter, is now worth more than GM, which sold 2.3m. Vast pools of data can thus act as protective moats.

Access to data also protects companies from rivals in another way. The case for being sanguine about competition in the tech industry rests on the potential for incumbents to be blindsided by a startup in a garage or an unexpected technological shift. But both are less likely in the data age. The giants’ surveillance systems span the entire economy: Google can see what people search for, Facebook what they share, Amazon what they buy. They own app stores and operating systems, and rent out computing power to startups. They have a “God’s eye view” of activities in their own markets and beyond. They can see when a new product or service gains traction, allowing them to copy it or simply buy the upstart before it becomes too great a threat. Many think Facebook’s $22bn purchase in 2014 of WhatsApp, a messaging app with fewer than 60 employees, falls into this category of “shoot-out acquisitions” that eliminate potential rivals. By providing barriers to entry and early-warning systems, data can stifle competition. [/Excerpt]