From the swooping space-age shopping mall to the Z-shaped school with a running track through it, here are the buildings that Zaha Hadid will be remembered for
‘Queen of the curve’ Zaha Hadid dies aged 65 from heart attack
Vitra fire station, Weil am Rhein (1994)
Hadid’s first completed project – a complex construction of tilted and clashing planes – looks very different from her later, organic designs. “A clear demonstration of the rhetorical power of architecture – and the possibility of achieving impressive effects with modest means,” said the Architectural Review, admiring the “gestural, pointy porch that yells ‘Emergency!’” Its daring geometries proved too much for the firemen, who moved out, leaving the building to become an events space.
Phaeno science centre, Wolfsburg (2005)
The Phaeno science centre “condenses a lot of the things that have been in my work for a long, long time”, Hadid said, while a critic described it as “an astonishing, exhilarating concrete and steel vortex of a building – somewhere you go to experience the operatic power of space”. Raised on fat concrete cones, it is a cathedral of jagged angles, looming curves, fractured planes and daring protrusions, its 154 metre length seeming to hover in the air.
Bridge Pavilion, Zaragoza (2008)
Inspired by gladioli and the waterway beneath it, Hadid’s first completed bridge throws 280 metres of fibre-glass reinforced concrete across the river Ebro. Half pedestrian walkway, half exhibition area, the covered structure was built to link the La Almozara neighbourhood to the site of the 2008 Zaragoza Expo. “A magnificent and truly ennobling way to cross a river on foot,” was the Guardian’s verdict.
Evelyn Grace Academy, London (2008)
This £36m Z-shaped school in Brixton, south London – with a running track tunnelling right through it and out the other side – beat another hot favourite to win the Stirling Prize. Given that the hot favourite was the Olympic velodrome, this was the year when Hadid – whose office was a former school – finally felt she was being acknowledged in Britain.
London aquatics centre, Stratford (2012)
The “most jaw-dropping municipal swimming pool in the world”, according to the Guardian. Originally built for the 2012 Olympics at a cost of £269m, this cathedral-like space seats houses two 50-metre pools and seats for 2,500 spectators. Its wave of a roof rests on just three concrete supports, and huge windows let the light flood in.
Heydar Aliyev cultural center, Baku (2012)
All swooping curves and flowing space, this 619,000-square-foot complex in the capital of Azerbaijan won the London Design Museum award in 2014; one judge called it “as pure and sexy as Marilyn’s blown skirt”. The softly folded roof shelters a museum, an auditorium and a multi-purpose hall. Reports put the cost at $250m. Human rights groups have criticised the project for seeing families forcibly evicted from their homes on the site.
THE US ECONOMY IS SUFFERING FROM LOW DEMAND
We have concluded that demand matters for productivity growth and that increasing demand is key to restarting growth across advanced economies, write James Manyika, Jaana Remes, and Jan Mischke in Harvard Business Review.
A little over a century ago, Henry Ford doubled the minimum pay of his workers to $5 a day. When other employers followed suit, it became clear that Ford had sparked a chain reaction. Higher pay throughout the industry helped lead to more sales, creating a virtuous cycle of growth and prosperity. Could we be at another Henry Ford moment?
Some major companies have announced plans to boost employee pay. Target raised its minimum wage to $11 this past fall and committed to $15 by 2020. More recently, Walmart announced plans to match that increase to $11. In banking, Wells Fargo and Fifth Third Bancorp also announced pay increases for minimum wage employees.
These pay increases have occurred against a backdrop of weak economic growth and rising income inequality. Economic growth has been stuck in low gear for almost a decade now, averaging around 2% a year since 2010 while productivity growth, the key to increasing living standards, has been languishing near historic lows since the financial crisis. But more recently there has been a glimmer of hope. After stagnating for years, wages have begun picking up slightly, as has productivity growth, while corporate profits remain near record highs.
Are these recent wage increases merely necessary in light of a tightening labor market, or could they start a broader trend that may change our economic growth trajectory?
After a year-long analysis of seven developed countries and six sectors, we have concluded that demand matters for productivity growth and that increasing demand is key to restarting growth across advanced economies.
The impact of demand on productivity growth is often underappreciated. Looking closer at the period following the financial crisis, 2010 to 2014, we find that weak demand played a key role in the recent productivity growth decline to historic lows. In fact, about half of the slowdown in productivity growth — from an average of 2.4% in the United States and Western Europe in 2000 to 2004 to 0.5% a decade later — was due to weak demand and uncertainty.
For example, in the mid-1990s to the mid-2000s, rising consumer purchasing power boosted productivity growth in both the retail and the auto sector, by encouraging a shift to higher-value goods that can be supplied at higher productivity levels. In the auto sector, as customers in the early 2000s purchased higher value-added SUVs and premium vehicles in both the United States and Germany, they spurred incremental productivity growth of 0.4 to 0.5 percentage points. Today, that trend has slowed slightly in both countries, contributing only 0.3 percentage points to productivity growth in the period 2010 to 2014.
Similarly, in retail, we estimate that consumers shifting to higher-value goods, for example higher-value wines or premium yogurts, contributed 45% to the 1995-2000 retail productivity acceleration in the United States. This subsequently waned, dragging down productivity growth.
To put it simply, when consumers have more to spend, they buy more sophisticated things. That’s good not just for consumers and producers, but for the overall economy, because making more sophisticated, higher-value things makes everyone involve more productive, and therefore helps increase overall standards of living.
In addition, we found two other ways weak demand hurt productivity growth in the aftermath of the financial crisis: a reduction in economies of scale and weak investment.
First, the economies of scale effect. In finance, productivity growth declined particularly in the United States, United Kingdom, and Spain due to contractions in lending volumes that banks were unable to fully offset with staff cuts due to the need for fixed labor (for example to support branch networks and IT infrastructure or to deal with existing loans and bad debt). The utilities sector, which has seen flattening demand growth due to both energy efficiency policies as well as a decline in economic activity during the crisis, was similarly not able to downsize labor due to the need for labor to support electricity distribution and the grid infrastructure, and here, too, productivity growth fell.
Second, the effect of weak investment. We have found from our global surveys of businesses that almost half of companies that are increasing their investment budgets are doing so because of an increase in demand. Demand is the single most important factor driving corporate investment decisions. Investment, in turn, is critical for productivity growth, as it equips workers with more – and with more recent and innovative – equipment, software, and structures. But we have seen capital intensity growth fall to the lowest levels in post-WWII history. Weaker demand leads to weaker investment and creates a vicious cycle for productivity and income growth.
Of course, the financial crisis is long since over, and the economy has recovered, at least by some measures. So what’s to worry about? Won’t demand return to pre-recession levels, and thereby increase productivity?
Unfortunately, there is reason to believe that some of the drags on demand for goods and services may be more structural than crises-related. Slowing population growth means less rapid expansion of the pool of consumers. And rising income inequality is shifting purchasing power from those most likely to spend to those more likely to save. This is reflected in slowing growth expectations in many markets. For example, across our sectors and countries studied, in the decade from 1995 to 2004, growth in demand for goods and services averaged 4.6%, slowed to 2.3% in 2010 to 2014, and is forecast to slightly increase to 2.8% in 2014 to 2020.
Today, there is concern about where the next wave of growth will come from. Some prominent economists worry that we may be stuck in a vicious cycle of economic underperformance for some time. Our analyses strongly suggest that supporting sustained demand growth needs to be part of the answer. Demand may deserve attention to help boost productivity growth not only during the recovery from the financial crisis but also in terms of longer-term structural leakages and their impact on productivity. Suitable tools for this longer-term situation include: focusing on productive investment as a fiscal priority, growing the purchasing power of low-income consumers with the highest propensity to consume, unlocking private business and residential investment, and supporting worker training and transition programs to ensure that periods of transition do not disrupt incomes.
Companies play a key role in promoting growth through investment and innovation as well as supporting their workforce through training programs. Yet companies may also want to consider the words of Ford when he said: “The owner, the employees, and the buying public are all one and the same, and unless an industry can so manage itself as to keep wages high and prices low it destroys itself, for otherwise it limits the number of its customers. One’s own employees ought to be one’s own best customers.” While this is certainly not true for individual companies, it is true for the broader economy, and we might be at a rare point where the representatives of employees and employers alike share a common interest in healthy wage growth.
Source: Harvard Business Review.
AUTOMATION WILL MAKE LIFELONG LEARNING A NECESSARY PART OF WORK
Shifts in skills are not new: we have seen such a shift from physical to cognitive tasks, and more recently to digital skills. But the coming shift in workforce skills could be massive in scale, write Jacques Bughin, Susan Lund, and Eric Hazin in Harvard Business Review.
President Emmanuel Macron together with many Silicon Valley CEOs will kick off the VivaTech conference in Paris this week with the aim of showcasing the “good” side of technology. Our research highlights some of those benefits, especially the productivity growth and performance gains that automation and artificial intelligence can bring to the economy — and to society more broadly, if these technologies are used to tackle major issues such as fighting disease and tackling climate change. But we also note some critical challenges that need to be overcome. Foremost among them: a massive shift in the skills that we will need in the workplace in the future.
To see just how big those shifts could be, our latest research analyzed skill requirements for individual work activities in more than 800 occupations to examine the number of hours that the workforce spends on 25 core skills today. We then estimated the extent to which these skill requirements could change by 2030, as automation and artificial technologies are deployed in the workplace, and backed up our findings with a detailed survey of more than 3,000 business leaders in seven countries, who largely confirmed our quantitative findings. We grouped the 25 skills into five categories: physical and manual (which is the largest category today), basic cognitive, higher cognitive, social and emotional, and technological skills (today’s smallest category).
The findings highlight the major challenge confronting our workforces, our economies, and the well-being of our societies. Among other priorities, they show the urgency of putting in place large-scale retraining initiatives for a majority of workers who will be affected by automation — initiatives that are sorely lacking today.
Shifts in skills are not new: we have seen such a shift from physical to cognitive tasks, and more recently to digital skills. But the coming shift in workforce skills could be massive in scale. To give a sense of magnitude: more than one in three workers may need to adapt their skills’ mix by 2030, which is more than double the number who could be displaced by automation under some of our adoption scenarios — and lifelong learning of new skills will be essential for all. With the advent of AI, basic cognitive skills, such as reading and basic numeracy, will not suffice for many jobs, while demand for advanced technological skills, such as coding and programming, will rise, by 55% in 2030, according to our analysis.
The need for social and emotional skills including initiative taking and leadership will also rise sharply, by 24%, and among higher cognitive skills, creativity and complex information and problem solving will also become significantly more important. These are often seen as “soft” skills that schools and education systems in general are not set up to impart. Yet in a more automated future, when machines are capable of taking on many more rote tasks, these skills will become increasingly important — precisely because machines are still far from able to provide expertise and coaching, or manage complex relationships.
While many people fear that automation will reduce the number of jobs for humans, we note that the diffusion of AI will take time. The need for basic cognitive skills as well as physical and manual skills will not disappear. In fact, physical and manual skills will remain the largest skill category in many countries by hours worked, but with different importance across countries. In France and the United Kingdom, for example, manual skills will be overtaken by demand for social and emotional skills, while in Germany, higher cognitive skills will become preeminent. These country differences are the result of different industry mixes in each country, which in turn affect the automation potential of economies and the future skills mix. While we based our estimates on the automation potential of sectors and countries today, this could change depending on the pace and enthusiasm with which AI is adopted in companies, sectors, and countries. Already, it is clear that China is moving rapidly to become a leading AI player, and Asia as a whole is ahead of Europe in the volume of AI investment.
We see retraining (or “reskilling” as some like to call it), as the imperative of the coming decade. It is a challenge not just for companies, which are on the front lines, but also for educational institutions, industry and labor groups, philanthropists, and of course, policy makers, who will need to find new ways to incentivize investments in human capital.
For companies, these shifts are part of the larger automation challenge that will require a thorough rethink of how work is organized within firms — including what the strategic workforce needs are likely to be, and how to set about achieving them. In our research, we find some examples of companies that are focusing on retraining, either in-house — for example, Germany’s SAP — or by working with outside educational institutions, as AT&T is doing. Overall, our survey suggests that European firms are more likely to fill future staffing needs in the new automation era by focusing on retraining, while US firms are more open to new hiring. The starting point for all of this will be a mindset change, with companies seeking to measure future success by their ability to provide continuous learning options to employees.
The skill shift is not only a challenge, it is an opportunity. If companies and societies are able to equip workers with the new skills that are needed, the upside will be considerable, in terms of higher productivity growth, rising wages, and increased prosperity. M. Macron’s point about technology being a force for good will become a self-fulfilling prophecy. Conversely, a failure to address these shifting skill demands could exacerbate income polarization and stoke political and social tensions. The stakes are high, but we can already see the outlines of what needs to be done — and we have a little time to work on solutions.
Source: Harvard Business Review
WHY AI ISN’T THE DEATH OF JOBS
Companies using AI to innovate are more likely to increase employment, writes Jacques Bughin in MIT Sloan Management Review.
When pundits talk about the impact that artificial intelligence (AI) will have on the labor market, the outlook is usually bleak, with the loss of many jobs to machines as the dominant theme. But that’s just part of the story — a probable outcome for companies that use AI only to increase efficiency. As it turns out, companies using AI to also drive innovation are more likely to increase head count than reduce it.
That’s what my colleagues and I recently learned through the McKinsey Global Institute’s broad-based research initiative aimed at understanding the spread of AI in economies, sectors, and companies.1 We polled 20,000 AI-aware C-level executives in 10 countries to compile a sample of more than 3,000 companies (mostly large), identified distinct clusters within that pool, and ran a variety of scenarios on those clusters to project the effects of AI on employment, revenue, and profitability.
This research and analysis suggest that although AI will probably lead to less overall full-time-equivalent employment by 2030, it won’t inevitably lead to massive unemployment. One major reason for this prediction is because early, innovation-focused adopters are positioning themselves for growth, which tends to stimulate employment. (See “How AI-Based Innovations Drive Employment.”)
Here’s how we expect things to play out in the five clusters of companies we examined.
Enthusiastic innovators, or pioneering companies that make early investments in AI and embrace the disruption it can create in the quest for advantage, adopt a full range of AI technologies and use them to bolster innovation and efficiency. These companies are analogous to what sociologist and communication theorist Everett Rogers called “early adopters” back when he coined the term — they’re intrinsically motivated to use new technology to shape and open markets.2 While this approach is potentially complex in the short term, our analysis shows that by 2030, the profitability of enthusiastic innovators will grow 8% faster than that of the average company on an annual basis, their revenue will grow 4% faster, and their head count will rise 2.2% faster.
Source: MIT Sloan Management