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Tomorrow's Economy

Value creation in the data-driven economy

17 May 2018
Authors
Paul Hofeinz
Author
Sergei Bachlakov / Shutterstock.com

It has been understood for centuries that society and the economy are linked. The ‘base’, as Karl Marx described it in his seminal depiction, provides a foundation for the ‘superstructure’ that sits on top of it (Marx 2014). But what happens when the base shifts? What occurs when the material foundation of the economy – the ‘means of production’, as Marx would have it – begins to change profoundly? Is the right policy response still to seize the ‘commanding heights’? Or is it rather time to start retooling that society to sit more comfortably on top of an economy where the fundamental underlying value arises from completely unforeseen new processes and wealth is being created in a fundamentally different way?

I believe something like that is happening now, even if analysts sometimes struggle to cast the challenge in a way that sheds more light on the future being born than the past being left behind. The question policymakers face is not so much how to keep industry from disappearing, though this discussion is perennial and appeals can be found in most major political platforms at every major election. It is also a point of reference and a too-obvious-to-be-questioned explanation within the communities that have been devastated by industry’s disappearance.1 The issue is how do we prepare for and legislate for an economy where the social order will face a radically different set of challenges – problems that will themselves need to be mitigated with a radically different set of policies (Hofheinz 2017). The social structure has shifted already. In the old days men ran the world, but now there is more access, more opportunity. Is that a good thing? It depends on where you sit. But for the vast majority of people – particularly women, immigrants and, yes, the world’s poor – this is a very good thing indeed (Sachs 2005).

So what, then, are the fundamental shifts?

The economy has become dematerialised

First and foremost, the economy has become dematerialised (Haskel and Westlake 2017). It is no longer about making and shipping goods. It has become about producing and selling services (OECD 2017). Advanced manufacturers – at least the ones who understand the shift – are reacting cleverly and responding flexibly. Rolls-Royce, for one, no longer sells airplane engines. Instead, it sells guaranteed ‘aviation hours’ to the world’s airplane manufacturers – and monitors the engines it leases with advanced analytics (Dinges et al. 2015). This is not a unique development. Companies worldwide are starting to see the goods they make as part of a larger set of services to offer. And those services, in turn, can be parsed, outsourced and spread around the world in unique combinations that make us a truly global economy, despite what the Brexiteers will tell you (Hofheinz and Mandel 2015). There is no ‘little England’ any more. The economy is truly global.

Improvement in life expectancy

Life expectancy has improved dramatically, with a consequent shift in the way public resources are spent and a major impact on the labour inputs available to the economy worldwide (Sachs 2005). Here, in ‘industrial Europe’, life expectancy has risen to 77.9 years for men and 83.3 years for women, up from a frighteningly low 25 years as recently as 200 years ago.2 With improvements in lifelong healthcare and decreases in crippling infant mortality, the size of families has consequently also shifted, falling from an average of around 10 in Europe 200 years ago to 2.3 today (interestingly, almost two-thirds of European families are now one- or two-person households).3

This latter point is a radical shift as well: mothers are no longer stuck at home, essentially running small child-rearing businesses that would have defied the management capabilities of the men who deserted them each day for the factory floor. And the true revolution in our time is that the phenomenon is no longer limited to the developed world (Sachs 2005). With the notable exception of Africa, life expectancy has also risen dramatically in the developing world, an achievement that is not coincidentally contemporaneous with the rise of globalisation. This has brought literally billions of hardworking, relatively cheap and often extremely talented people into the global workforce.

Improvement in access to education

Access to education has improved dramatically. Literacy rates are rising around the world and, guess what?, some of those who might not have learned to read in previous generations are fast becoming the world’s best engineers. Five years ago, Massachusetts Institute of Technology agreed to let external students who followed a sophomore-level circuits and electronics course on the Institute’s popular massive open online course (MOOC) to sit the final exam. The result was an explosion of good results. One of the recipients was Battushig Myanganbayar, a 15-year-old Mongolian boy, who earned a perfect score from his desktop in Ulan Bator.4 More than 58 million people have participated in MOOCs since their advent some five years ago. Some of them are now covering Master’s degree-level material.5

Shift in the economic ‘base’

All of this is possible because of a dramatic shift in the economic ‘base’, to use the Marxist term. The internet made possible instantaneous, zero marginal cost communication – at the local as well as the global level (see Soete this volume). This has been an enormously empowering and disruptive influence – not just on politics, but on the social order that prevailed in some places for centuries. But it has other, more deep-seated, implications. Put simply, it has turned data into the economy’s newest, most valuable vital asset (OECD 2015). Policymakers have struggled to find a suitable metaphor; data is the new economy’s most important ‘commodity’, ‘currency’ and ‘infrastructure’, to use just three of the concepts to which it is most often (and somewhat misleadingly) compared. But data is really something else entirely. Data is data. Its use has its own logic, and its own requirements (Hofheinz and Osimo 2017). In a nutshell, data is how global businesses communicate across the vast spaces they now occupy. And it is the crucial raw material from which those companies – as well as governments and individuals – will come to new insights, develop and deliver new services and derive vital conclusions.

Everywhere you see the economy shifting. Financial service companies now derive more value from their ability to collect and learn from the data they gather than they do from the margins on routine financial transactions. Once obscure internet platforms have grown to be enormous global businesses, often offering excellent services for free in return for nothing more than the right to track how you use it. And now artificial intelligence (see Petropoulos this volume) is poised to take it to a higher level, holding out the possibility of automating more and more tasks with the knowledge internet platforms gain from the data we feed them (Hofheinz 2016).

Implications for industry

So what, then, are the implications for industry? First and foremost, industry in the developed world ignores these trends at its peril (OECD 2017). Companies like Germany’s vast Mittelstand (see Rahner and Schönstein this volume) are particularly affected. The world is big, hyper-competitive and horizontally connected. There is little nostalgia. Price is king, though quality can still command a premium, but it is important that that premium remains affordable and within reach. The developed world is both challenge and opportunity. It is a challenge because developing-world products and manufacturing techniques have risen so dramatically and remain relatively cheap. It is an opportunity because that rise gives developed-world manufacturers bigger and bigger markets to sell into.

The larger question is not can and will industry adapt – contrary to its reputation, European industry is more competitive than we give it credit for.6 Rather, it is how we will deal with the dramatic social and political disruption that this brave new world gives rise to. First is rising inequality.7 While global income disparities are falling, demonstrable and quantifiably rising inequality is the unwanted side effect at ‘the local level’ – which is how we now refer to the nation state in a sign of how much change these times have already brought. Put simply, the spread of digital technologies and the concurrent rise of the global economy created winners and losers. If enough of the losers feel the game is rigged against them – and many have come to that conclusion – the result will be a nasty form of protest politics, which threatens the prosperity on which so many countries and societies are based (Clinton 2017). Policy does make a difference. And decisions to dismantle democracy – as the Polish government is doing – or drop out of important global trade flows – as the British have foolishly decided to do – will be felt directly, and sooner than you think. The Roman empire did collapse, though few at the time of Julius Caesar’s putsch could have foreseen the dark age that was to come.

There is something new, something truly ahistorical, about what is happening in the economy right now. It is the unforeseen shift in the way value is created (Hofheinz and Osimo 2017). More than is commonly perceived, the industrial economy was built on a model of strong property rights (including intellectual property) and the associated concept of individual accumulation of wealth.8 It started with the great move towards enclosures in the 16th century – an effort to clear farmers from previously common land so that that land could be developed privately (until that time, the prevailing social order had been common, based mostly on unwritten feudal rights and duties, which tied owners and peasants together in patterns of shared responsibility for each other). But the trend continued with the rise of factories and the scientific and industrial explosion of the 18th and 19th centuries. This development was driven not by ever larger markets but by stronger – and more easily enforced – property rights than had existed before. Most notable was patents – a legal monopoly on innovation, which made science and scientific discovery extremely lucrative. But the notion of ‘trademark’ meant that companies could organise at scale. And accumulated capital – the ultimate private property – could be invested and reinvested. A strong legal environment with easily enforceable property rights allowed the returns to be reasonably assumed, accurately calculated and ultimately quite lucrative. The history of roughly 500 years can be summed up in these words: by and large it worked.

But the digital economy – with its heavy reliance on speed, flexibility and economies of scale – is pushing us towards a new, radically different logic. At the heart of the problem is data, a new kind of economic input, which not coincidentally has already become the new economy’s most precious. Put simply, data is not worth much to the individuals who own or create it.9 Data becomes valuable when it is combined. This is how we will find cures for cancer. This is how we will improve traffic in our cities. This is the area where large, industrial-scale services will be delivered with a level of personalised service that would have been unthinkable in the old days. And it is how the next, most advanced, innovation in our economy will be calculated and created.

And this has huge implications: society and the economy around it have a huge incentive to share their data with each other, putting it in larger and larger pools where the lucrative insights and brilliant innovations of the next phase of human history will come. We all have a very strong incentive to contribute to good economic outcomes. In the past, that meant being good consumers, holding down jobs and paying our taxes. It still means all of those things. But now it means pooling our data – the information about how we live, work, drive and play – so that new and more original insights can be generated. And as those insights are derived collectively, we have a strong incentive to make sure that the benefits are shared and apportioned collectively as well.

This is the true revolution. It won’t be industrial. It won’t even be digital. It will be social and political. And it will speak not just to the way we share wealth but also to the way we generate it. We stand on the cusp of an important decision: will we find and develop the social innovation needed to make the digital revolution a win-win-win for all? Or will we regress into our most atavistic politics, attacking and killing a system that has delivered uneven results, preferring to blind our neighbour’s cows rather than giving sight to our own?

Sharing more in the data-driven economy

And success is not guaranteed. The current wave of ‘post-truth’ politics is a dangerous lurch backwards. Rather than fixing a broken system, voters are choosing to smash the system itself. There are many reasons for this – including the fact that the pillars supporting that system have been poorly explained and were never widely understood. Many of the ideas floating around today – like universal basic income – are primitive, and would lead to poor social results if implemented. But they point in the right direction, and show that – in a crude way – people are thinking more or less correctly about the kind of change their future will require. One way or the other, the rise of a data-driven economy means that we will share more, which has implications on two levels: we will share more data about ourselves – with improved social outcomes that will be common and collective, and we need to find ways of sharing the wealth created in that process more equitably as well.

Use new systems to share data

Advanced economies need new systems for sharing data. Today, the area is blocked, still functioning under the old paradigm of individual property rights. Companies are hoarding data – sometimes even buying up other companies only for the data they own (Hofheinz and Osimo 2017). This is a fool’s errand. Recent practice tells us that the average machine-learning trained machine will need as many as 10,000 to 100,000 times more data than single human workers will generate during the course of their professional life (Cutler 2017). This is well beyond the capacity of any one company to attain or provide. If the data economy is to be a success, we need common pools of data – a ‘data commons’, in other words, though this concept is still in its infancy (Hofheinz and Osimo 2017; OECD 2015). Under that scenario, companies will base their competition on the services they offer, drawing insight from common pools of data to which all will have access.

Make data pools common

If the data pools are common, the results should be more broadly socialised as well. Some of this will happen naturally. Cures for cancer will have broad and evident advances for all – though it will be important, when these advances come, to make sure that they are widely available. Improved traffic management in cities is a huge advantage to everyone as well, and data and the data-driven economy will play more than a small role here. The advent of ride-sharing technology like Uber will make the ownership of cars less necessary and the cities much cleaner.

Keep global trade flows open

Global trade flows should be kept open. The challenge of managing the global economy within our own society should not become an excuse for shutting down the global economy itself. We need to find ways to preserve the benefits. There needs to be more concrete, credible and robust policymaking to take care of communities that have thus far been left behind.10

Fight the precariousness of the data economy

The data economy is inherently precarious, but the effort to fight that precariousness should take the form of greater state-led social protection rather than greater requirements for social commitments from private-sector companies. The European social model grew up around a fairly simple concept – the best way to ensure social peace was to get companies to pay for it. The result is the highest non-wage labour costs in the world, a situation which is itself contributing to a hollowing out of good jobs in Europe, pricing them rather directly out of the market. This needs to stop. The global economy is too competitive – and European workers too expensive – to continue adding costs in the way we have added them over the years.

More recently, the most successful social-policy initiatives have had a common theme – freeing up companies to compete by taking the social burden onto the state. Towards that end, the best and most illustrative policy is still Denmark’s ‘flexicurity’ model (Baily and Kirkegaard 2004, see Ilsøe this volume). It increased benefits to workers and lowered the direct requirement on companies to provide them. Legal severance was shortened to one week, for example. But the result was an explosion of new jobs, driving unemployment to 2.4%, down from the 12.4% that the government of Poul Nyrup Rasmussen inherited from his predecessor (Hendeliowitz 2008).

There are other policies which have performed a similar role: Obamacare makes it easier for Americans to switch jobs because their healthcare is no longer dependent on their employer. And the French have invented important new ways of spreading access to education over a lifetime with the compte personnel d’activité (personal activity account) (Hofheinz 2017, see Weber this volume). Systems based on income tax credits, which provide incentives to work by offering top ups for those whose earnings are beneath a living wage, have proven enormously effective in the US and the UK. But these are merely the seeds of broader social changes that have yet to take hold. Put simply, in a rapidly globalising economy, it is no longer feasible to impose greater social commitments on companies in the form of requiring them to offer only full-time labour contracts or mandating expensive restructuring charges. The state must step in with a comprehensive set of policies designed to protect and empower workers in an economy based on flexibility and change. It must become the guardian of a radically rewoven social fabric. Above all new and innovative measures are needed to fight social challenges that are different from the ones that existed when the current system was conceived and implemented.

Provide greater access to education

Working life will unfold differently, too. Education is no longer something we can frontload; people will need access to it throughout their lives. Companies like General Assembly – with its short-term skills accreditation courses – and Udacity – with its ‘vocational courses for professionals’ – are showing the way. We must rethink the famous work–life balance as a triad of work–life–education balance, forever combining and recombining throughout what used to be called a person’s ‘working life’. The social system must support career patterns based on fast changing needs – that is what the world demands. And it would not require much more than a leap of imagination and a bit of education system retooling to provide it.11

A dystopian vision and its alternative

There is another future – a dystopian one – where technology becomes a weapon of oppression. The Chinese, with their Communist Party-inspired social rating system, are dangerously close to this. And the Russians have shown a flair for mainstreaming their talent for ‘disinformation’, using it to disrupt their perceived enemies effectively, with unprecedented success. The Americans under Donald Trump are not far behind. In the US, efforts to fight inequality have been pushed radically backwards: an absurdly regressive tax reform, an internet where traffic is throttled, a blind eye towards police violence and the racial prejudice that remains America’s greatest shame (see Kalleberg this volume).

We must counter this with an alternative vision. One where European industry has the tools it needs to succeed so it can continue to serve as a pillar for the world’s most advanced social system. One where society itself feels that it is part of these exciting developments, with each of us making an important contribution. This outcome is not guaranteed. But it is not out of our reach, either.

Endnotes

1 A good example of this thinking is Marianne Cooper’s very good study of family finances and risk management (Cooper 2014).

2 This is higher than in North America (where the equivalent figures are 76.9 and 81.6). The reasons for Europe’s better performance are beyond the scope of this essay, but it is a fact worth noting. The European social model is delivering longer, healthier lives (Eurostat 2017a).

3 Around 40% of Europeans died before reaching adulthood in the ‘pre-industrial era’ (Eurostat 2017b).

4 Mr Myanganbayar was one of 350 of the 120,000 students who took the exam to make a perfect score (Pappano 2013).

5 The 58 million figure is for 2016 and comes from the very helpful ‘By the Numbers: MOOCs in 2016’ (Shah 2016). See also ‘Master’s Degree is New Frontier of Study Online’ (Lewin 2013).

6 The euro area itself maintains a healthy monthly trade surplus with the rest of the world of €18.9bn, though much of that success is attributable to one country: Germany. As the global economy picked up steam, the trade balance with the rest of the world of the 28-member EU itself slid to a €0.3bn deficit in October 2017, down from a €2.4bn surplus a year before (Eurostat 2017c).

7 See World Inequality Report 2018 (World Inequality Lab 2018) and ‘Inequality is a Threat to Our Democracies’ (Wolf 2017a), a very good recent summary. The seminal work on this phenomenon is Capital in the 21st Century (Piketty 2014).

8 For a very good, early discussion of the policy implications posed by rise of intangible assets in the economy, see ‘The Challenges of the Disembodied Economy’ (Wolf 2017b).

9 The OECD tried to calculate the market value of individual data. The bottom line: the data people held about themselves was worth much less – companies were willing to pay much less for it – than the individuals themselves thought it was worth. Recent market-based transactions – such as the 2013 acquisition of Climate Corporation by Monsanto Corporation for $930 million – have demonstrated that the value of data rises considerably when it is aggregated (OECD 2015).

10 See especially the highly instructive account of a community left behind by globalisation – and the poverty of the policy response – in ‘Are We Witnessing the Strange, Lingering Death of Labour England?’ (Engel 2017).

11 By implication, efforts to make higher education 100% state funded, as US Senator Bernie Sanders has proposed, would be a step in the wrong direction. The crisis of rising costs for higher education is a real one. But the solution must be better, more broadly funded, higher education, with more resources, and less reliance on personal debt. Turning the state into the single payer would create the wrong incentives, and would hamstring the broader development that still needs to take place: the education system needs to be opened up. And this will require truly innovative financing models in which individual payments will surely play some part.

References

Baily, M. N. and J. F. Kirkegaard (2004), Transforming the European Economy, Washington: Peterson Institution.

Clinton, H. (2017), What Happened, New York: Simon and Schuster.

Cooper, M. (2014), Cut Adrift: Families in Insecure Times, Berkeley: University of California Press.

Dinges, V., F. Urmetzer, V. Martinez, M. Zaki, and A. Neely (2015), The Rise of Servitisation: Technologies That Will Make a Difference, Cambridge: Cambridge Service Alliance.

Engel, M. (2017), ‘Are We Witnessing the Strange, Lingering Death of Labour England?’, Financial Times, 10 February, https://www.ft.com/content/bcfe0106-edee-11e6-930f-061b01e23655.

Eurostat (2017a), Mortality and Life Expectancy Statistics, Luxembourg: Eurostat, http://ec.europa.eu/eurostat/statistics-explained/index.php/Mortality_and_life_expectancy_statistics.

Eurostat (2017b), Household Composition Statistics, Luxembourg: Eurostat, http://ec.europa.eu/eurostat/statistics-explained/index.php/Household_composition_statistics.

Eurostat (2017c), ‘Euro Area International Trade in Good Surplus €18.9 billion’, Eurostat Newsrelease Euroindicators, 15 December, http://ec.europa.eu/eurostat/documents/2995521/8541742/6-15122017-AP-EN.pdf/8eda7d75-6b12-4ed7-b6d1-f5902df6ab6d.

Haskel, J. and S. Westlake (2017), Capitalism Without Capital: the Rise of the Intangible Economy, Princeton: Princeton University Press.

Hendeliowitz, J. (2008), Danish Employment Policy: National Target Setting, Regional Performance Management and Local Deliver, Copenhagen: Danish National Labour Market Authority.

Hofheinz, P. (2016), Artificial Intelligence and Machine Learning: Challenge and Opportunity, Brussels: Lisbon Council.

Hofheinz, P. (2017), Making a Progressive Future of Work, London: Policy Network, http://www.policy-network.net/pno_detail.aspx?ID=6220&title=Making+a+progressive+future+of+work.

Hofheinz, P. and M. Mandel (2015), Uncovering the Hidden Value of Digital Trade: Towards a 21st Century Agenda of Transatlantic Prosperity, Brussels and Washington DC: Lisbon Council and Progressive Policy Institute.

Hofheinz, P. and D. Osimo (2017), Making Europe a Data Economy: a New Framework for Free Movement of Data in the Digital Age, Policy Brief, Brussels: Lisbon Council.

Lewin, T. (2013), ‘Master’s Degree is New Frontier of Study Online’, The New York Times, 7 August, http://www.nytimes.com/2013/08/18/education/masters-degree-is-new-frontier-of-study-online.html.

Marx, K. (2014), A Contribution to the Critique of Political Economy, Fairford: Echo.

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Pappano, L. (2013), ‘The Boy Genius of Ulan Bator’, The New York Times, 13 September, http://www.nytimes.com/2013/09/15/magazine/the-boy-genius-of-ulan-bator.html?pagewanted=all.

Piketty, T. (2014), Capital in the 21st Century, Cambridge, MA: Harvard University Press.

Sachs, J. D. (2005), The End of Poverty: Economic Possibilities for Our Time, London: Penguin.

Shah, D. (2016), ‘By the Numbers: MOOCs in 2016’, Class Central, 25 December, https://www.class-central.com/report/mooc-stats-2016/.

Wolf, M. (2017a), ‘Inequality is a Threat to Our Democracies’, Financial Times, 19 December, https://www.ft.com/content/47e3e014-e3ea-11e7-97e2-916d4fbac0da.

Wolf, M. (2017b), ‘The Challenges of the Disembodied Economy’, Financial Times, 28 December, https://www.ft.com/content/a01e7262-d35a-11e7-a303-9060cb1e5f44.

World Inequality Lab (2018), World Inequality Report 2018, Paris: The World Inequality Lab.

 

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