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Profusion, confusion, congestion – Editorial for Challenges by Denis Kessler
November 10, 2016
Chairman & CEO of SCOR, Denis Kessler publishes an editorial piece in the French weekly Challenges, covering economic, political and financial current events in France and worldwide.
The term profusion is a relatively accurate characterisation of the network society we have become over the last 20 years. It now seems that any quantity of any type of information can be disseminated in real time. It used to be difficult, costly and time-consuming to obtain information; it is now quite the reverse. This turnaround means that we have evolved from a situation where information was dominated by demand to one where supply plays the leading role. Information germinates and proliferates in large part because the cost of disseminating it is declining exponentially, thanks to the rise in new technologies that produce, transfer and store it. The development of streaming is the most recent example. Whereas we used to have a shelf of VHS cassettes next to the TV, we can now stream nearly all films produced since the invention of the cinema. And our smartphones can store more music than a roomful of vinyl records could hold. The big data era is characterised by an unprecedented profusion of data, a veritable deluge that is flooding all organisations. Could it be drowning them?
The effects on productivity of this profusion of data are more complex than first meets the eye. General equilibrium theory says that perfect information helps markets to function optimally. As a result of technological advances, the cost of searching for information is approaching zero. All other things being equal, this should increase productivity, as we now spend less time leafing through books in libraries or coding punch cards. But we spend more time sorting and assessing information. The quantity of information has increased exponentially, but its quality has not kept pace. Sometimes the information is raw, unverified, repetitive, muddled, manipulated, false or contradictory. The number and the role of the “influencers”, who must authenticate and process information and in so doing, assume part of the responsibility for it, has diminished. The sheer quantity of information has made it difficult to elicit what is truly relevant. This process can be time-consuming and costly. This is the challenge "big data" presents. A constantly expanding choice often leads to indecision, and so profusion has led to confusion.
With a profusion of information, comparison – in particular price comparison – becomes systematic. In the short term, this is deflationary, in that this profusion reduces the margins of producers and intermediaries. In the longer term, it benefits productivity, because producers seek to reconstitute their margins by reducing costs.
Moreover, while we may have access to all this data, we do not have an infinite amount of time available to take advantage of it or analyse it. Even if you have 10,000 songs on your smartphone, you still can't listen to more than one at a time, any more than you can look at several of your 1,000 photos at once. Listening to a Beethoven symphony takes as long today as it did in the 19th century, even if you now have immediate access to all 150 recordings of it. So we have resorted to zapping, creating a regrettable form of superficiality. Quotations and other extracts are easy to find, so why bother reading the book? Productivity – production or consumption per unit of time – initially increased, but is now tending to stagnate. In other words, profusion is leading to congestion and saturation. You waste time going through your e-mails, an increasing number of which are unsolicited, just as you used to weed out the junk mail that filled your physical mailbox. Too much data is squeezing out real information and clogging up the works. With too much data to digest, we cannot manage it efficiently, i.e. we cannot use it to improve consumption and/or production.
All this brings us to a sort of paradox. Remarkable progress has clearly been made in terms of disseminating and storing information, but this does not seem so far to have stepped up the economic growth of the countries that benefit from it. So then where are all the productivity gains from this progress? Maybe we will have to wait for artificial intelligence to become widespread, and able to sort, analyse and exploit information, before we see this phenomenon contributing significantly to economic growth.