This article is taken from two sources: the Economist and Forbes. The Economist argues that data is the new oil. Forbes argues that it is not. For the original Economist article, click here. For the original Forbes article, click here.

The world’s most valuable resource is no longer oil.

It is data.

(by the Economist)

A new commodity spawns a lucrative, fast-growing industry, prompting antitrust regulators to step in to restrain those who control its flow. A century ago, the resource in question was oil. Now similar concerns are being raised by the giants that deal in data, the oil of the digital era. These titans—Alphabet (Google’s parent company), Amazon, Apple, Facebook and Microsoft—look unstoppable. They are the five most valuable listed firms in the world. Their profits are surging: they collectively racked up over $25bn in net profit in the first quarter of 2017. Amazon captures half of all dollars spent online in America. Google and Facebook accounted for almost all the revenue growth in digital advertising in America last year.

Such dominance has prompted calls for the tech giants to be broken up, as Standard Oil was in the early 20th century. The Economist has argued against such drastic action in the past. Size alone is not a crime. The giants’ success has benefited consumers. Few want to live without Google’s search engine, Amazon’s one-day delivery or Facebook’s newsfeed. Nor do these firms raise the alarm when standard antitrust tests are applied. Far from gouging consumers, many of their services are free (users pay, in effect, by handing over yet more data). Take account of offline rivals, and their market shares look less worrying. And the emergence of upstarts like Snapchat suggests that new entrants can still make waves.

But there is cause for concern. Internet companies’ control of data gives them enormous power. Old ways of thinking about competition, devised in the era of oil, look outdated in what has come to be called the “data economy” (see Briefing). A new approach is needed.

Quantity has a quality on its own

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.

Who ya gonna call, trustbusters?

The nature of data makes the antitrust remedies of the past less useful. Breaking up a firm like Google into five Googlets would not stop network effects from reasserting themselves: in time, one of them would become dominant again. A radical rethink is required—and as the outlines of a new approach start to become apparent, two ideas stand out.

The first is that antitrust authorities need to move from the industrial era into the 21st century. When considering a merger, for example, they have traditionally used size to determine when to intervene. They now need to take into account the extent of firms’ data assets when assessing the impact of deals. The purchase price could also be a signal that an incumbent is buying a nascent threat. On these measures, Facebook’s willingness to pay so much for WhatsApp, which had no revenue to speak of, would have raised red flags. Trustbusters must also become more data-savvy in their analysis of market dynamics, for example by using simulations to hunt for algorithms colluding over prices or to determine how best to promote competition (see Free exchange).

The second principle is to loosen the grip that providers of online services have over data and give more control to those who supply them. More transparency would help: companies could be forced to reveal to consumers what information they hold and how much money they make from it. Governments could encourage the emergence of new services by opening up more of their own data vaults or managing crucial parts of the data economy as public infrastructure, as India does with its digital-identity system, Aadhaar. They could also mandate the sharing of certain kinds of data, with users’ consent—an approach Europe is taking in financial services by requiring banks to make customers’ data accessible to third parties.

Rebooting antitrust for the information age will not be easy. It will entail new risks: more data sharing, for instance, could threaten privacy. But if governments don’t want a data economy dominated by a few giants, they will need to act soon.

Here’s why data is not the new oil

(by Forbes)

It’s a claim you’ve probably heard multiple times – “Data is the new oil!”

Now it’s true, that in some ways, the analogy fits – it’s easy to draw parallels due to the way information (data) is used to power much of the transformative technology we see today – artificial intelligence, automation and advanced, predictive analytics.

However, in many ways, it’s also lazy and inaccurate – and while it’s handy as a marketing shorthand (because it gets across the fact that data is a valuable commodity with many different uses across many applications) it’s also potentially problematic. The concept is usually credited to Clive Humby, the British mathematician who established Tesco’s Clubcard loyalty program. Humby highlighted the fact that, although inherently valuable, data needs processing, just as oil needs refining before its true value can be unlocked.

However, data also has many other properties which cause the analogy to break down on more detailed inspection.

For a start, while oil is a finite resource, data is effectively infinitely durable and reusable. This means that treating it like oil – hoarding it and storing it in siloes, has little benefit and reduces its usefulness. Nevertheless, due to the conception that it is similar to oil (scarce), this is often what is done with it. Oil requires huge amounts of resources (including oil itself) to be transported to where it is needed. Data, on the other hand, can be replicated indefinitely and moved around the world at the speed of light, at very low cost, through fiber optic networks.

Data also becomes more useful the more it is used, rather than its energy being lost as heat or light, or permanently converted into another form such as plastic, as when oil is used. Once processed, data often reveals further applications. For example, medical data collected from patients can help a doctor diagnose and treat an individual patient. After that, it can be anonymized and fed into machine learning systems to generate broader insights that can benefit many, many more.

Treating data like oil – using it once then assuming its usefulness has been depleted and disposing of it – would certainly be a mistake. As the world’s oil reserves dwindle, extracting it becomes increasingly difficult and expensive. Conversely, data is becoming increasingly available as computer technology advances, more of our business and leisure activity moves online, and sensors become more sophisticated.

Data – particularly Big Data – also has far more variety than oil. The crude oil which is drilled from the ground is processed in a variety of ways into many different products of course, but in its raw state, it is all the same. Data can represent words, pictures, sounds, ideas, facts, measurements, statistics or anything else which can be processed by computers into strings of 1s and 0s that make up digital information.

Of course, data, like oil is a source of power. And those who control it (think of Amazon, Alibaba, Facebook or Google) are establishing themselves as masters of the universe, just as oil barons did 100 years ago. This has even led some to suggest that the data-mining giants have a responsibility to ensure that their resources are put to work for the benefit of humanity as a whole, rather than simply being allowed to enrich themselves. Unlike oil drilling, however, data mining does not intrinsically involve causing damage to the natural environment and exploitation of finite natural resources (apart from the electricity used to run the system).

Unregulated data-mining causes a whole different set of problems – privacy issues as well as the imbalance of power which is caused by information being in the hands of the few, rather than the many. Treating or thinking about data like oil only serves to encourage this dichotomy between the haves and the have-nots in the digital age.

In fact, if we are going to think about data as a power source or fuel, then it would make more sense to consider its similarities with renewable sources like the sun, wind and tides. There is an abundance of it – more than we can ever use – and rather than fencing it off and reducing the supply, we should think about how we can make it more widely available to everyone.

Data – in the quantities it is available today – is, in fact, an entirely new commodity, and the rules around how it is stored, treated and used are still being written. Comparing it to existing, old world resources makes for nice snappy soundbites but, apart from conveying the idea that it is valuable, is largely a meaningless exercise. Data will hopefully also cause less disruption and destruction of life on our planet than we have done with oil, over the last century

It’s far more productive to consider how data is different – the myriad of ways it can be captured, used and reused, and in doing so, generate value and benefits to humans that will help us tackle big issues from education to healthcare, from reducing hunger to fighting climate change.