Absolute returns

So much capital is misallocated these days, and that continues to drive down trend GDP growth – the term misallocated capital is used by economists to describe capital that is deployed without having any impact on productivity – it’s capital that is deployed unproductively

Niels Jensen of Absolute Return Partners wrote about The Productivity Conundrum and listed five reasons why productivity growth continues to be lacklustre despite all the benefits we reap every day from the digital revolution:

1. Ageing of society at large, as older workers are less productive than their younger peers

2. The rising cost of servicing the elderly in society

3. Excessive indebtedness in all economic sectors and the rising cost of servicing that debt

4. The rising cost of producing the energy we need to spin the wheels every day

5. The fact that the savings freed up by the digital revolution have not been re-invested in reskilling the workers affected to a higher level but have instead been pocketed by capital owners

Reasons 2-4 all have to do with the rising amount of capital being deployed unproductively – capital that could, and should, have been used to enhance productivity

Niels then reminds us of the most fundamental equation in economic theory:

∆GDP = ∆Workforce + ∆Productivity

And given ∆Workforce will turn negative in many developed countries in the years to come, robust productivity growth is pivotal to future economic growth

However, since WW2, the US economy has only enjoyed two long-lasting periods of productivity growth in excess of 2% per annum (the same is true for most of the rest of the developed world):

  • The first unfolded from the mid-1950s to the mid-1960s – Eisenhower had returned from the war in Europe and told Congress about a German phenomenon called autobahns, which allowed Hitler to move his army swiftly around – Congress subsequently decided to establish the interstate highway system – at about the same time, commercial aviation took off and the two new modes of transportation had a meaningful impact on labour productivity over the subsequent 10 years or so
  • The second wave occurred in the early years of the digital revolution – the internet had just been rolled out, and that had a similar impact on productivity

Now, as we are entering the second stage of the digital revolution (advanced robotics, AI, etc.), Niels believes a declining workforce will most likely lead to depressingly low GDP growth

He then cites a paper called Negative Productivity Agents by J.P. Morgan Asset and Wealth Management which deals exclusively with the main negative factors that are holding US GDP growth back viz:

1. A massive war machine

Some wars that the US military has been involved in have improved prosperity whereas others have not – either way, the US war machine is very expensive to run – it siphons capital away from productivity-enhancing investment opportunities like education and infrastructure

2. An inferior infrastructure

Governments all over the world are determined to electrify virtually all heating and transportation as the fight against global warming continues – however, electrification of everything will only work if you have a reliable electricity grid, and the US grid is near the bottom of the international league table for reliability – significant investment to upgrade the grid will therefore have to be sanctioned before the US economy can take full advantage

3. Behavioural quirks

J.P. Morgan says the number of Americans killed by firearms in the last 50 years, including suicides, is more than 1.5 million which equates to more than 30,000 gun-related deaths every year – and the trend for this number is upward – the US is quite simply in a league of its own when it comes to gun ownership and gun-related deaths – hence, it spends a vast amount of money dealing with gun violence, money that could be spent on educating youngsters instead

4. Out-of-control healthcare costs

Gun crime, obesity and other behavioural quirks combined with ageing of the populace at large continue to push US healthcare expenses through the roof

In fact, US public healthcare expenditures are not miles away from the cost of providing public healthcare in Western Europe – it is the US healthcare model, based on private care paid for by insurance companies, that is the culprit

5. A “dysfunctional” legal system

The last negative factor is the excessive level of corporate litigation costs in the US when compared to other OECD countries

Excessive litigation costs siphon capital away from potential productivity-enhancing corporate investments which could benefit all – instead, the money is spent on protecting corporates from ridiculous lawsuits

Productivity versus regulation

Niels quotes Dietmar Meyersiek for concluding that superior economic growth was very much affiliated with greater economic freedom i.e. productivity could be dramatically affected by the extent of regulation

Meyersiek had based his conclusions on work conducted by the Heritage Foundation which defined economic freedom as business, trade and investment freedom, financial and fiscal freedom, size of government, monetary freedom, property rights, freedom from corruption and labour market flexibility


Clearly, despite the above negative factors, the US is still a very free economy so it’s no surprise to see them topping this chart

The chart also suggests there are probably even more negative factors in Europe than in the US

Niels raises just one, for example – in 2009, the EU Parliament passed a new law regulating the shape of bananas – such laws are not just silly, they offer nothing in terms of consumer protection – they also add to the costs of the corporate sector – hence, they impact productivity negatively

Even worse, Niels concludes, they turn many people against the EU

A toast to bananas

AI increases productivity

By 2021, artificial intelligence (AI) will allow the rate of innovation of Filipino companies to increase by 1.7 times, and nearly double employee productivity gains in the Philippines, according to a study titled Future Ready Business: Assessing Asia Pacific’s Growth Potential Through AI

The study made by Microsoft and IDC (International Data Corp.) surveyed 109 business leaders and 100 workers in the Philippines

An article in The Manila Times which reported on the results is reproduced below as it will be of great interest to many businesses in many other nations, East and West

While close to 90% of business leaders polled agreed that AI is instrumental for their organisation’s competitiveness, only 45% of organisations in the Philippines have embarked on their AI journeys – yet those companies that have adopted AI expect it to increase their competitiveness by 1.5 times in 2021

“AI is the defining technology of our time that significantly accelerates business transformation, enables innovation, boosts employee productivity and ensures further growth – economies and businesses that have yet to embark on their AI journey run a real risk of missing out on the competitive benefits that are enjoyed by leaders” said Ricky Kapur, Microsoft Asia Pacific’s Enterprise and Partners Group general manager.

Why adopt AI?

For organisations that have implemented AI initiatives, the top five business drivers to adopt the technology were, in priority order:

  • Better customer engagements (27%)
  • Accelerated innovation (24%)
  • Higher competitiveness (16%)
  • More productive employees (10%)
  • Higher margins (8%)

“Last year, organisations that have adopted AI saw tangible improvements in those areas in the range of 22% to 44%” said Randy Roberts, IDC Philippines head of operations

“They forecast further improvements of at least 1.5 times in the three-year horizon, with the biggest jump expected in higher margins, accelerated innovation, and more productive employees”

The study evaluated six dimensions critical to ensuring the success of a nation’s AI journey – data, strategy, investments, culture, capabilities and infrastructure – it uncovered that the Philippines needs to focus on improving all areas, particularly its investments and data to accelerate its AI journey

“The Philippines needs to substantially improve its readiness – organisations’ leaders should make AI a core part of their strategy and continuously invest in this transformative technology for the long-term success, sometimes without immediate returns” Roberts said

Business leaders who are adopting AI face three top challenges:

  • Lack of thought leadership and commitment to invest in AI
  • Lack of skills, resources, and continuous learning programmes
  • Lack of advanced analytics or adequate infrastructure and tools to develop actionable insights

The study showed that, to move ahead on their AI journeys, businesses have to create the right organisational culture – a significant proportion of business leaders and more than half of workers surveyed believe that cultural traits that support AI journeys, such as risk-taking, proactive innovation, as well as cross-function partnerships among teams, are not pervasive today

“Overall, workers in the Philippines are more sceptical than business leaders about the cultural readiness of their organisations” said Roberts.

The study also found that business leaders and workers in the Philippines hold positive viewpoints about AI’s impact on the future of jobs – the majority (74%) believe that AI will either help to do their existing jobs better or reduce repetitive tasks

Kapur said: “Microsoft’s vision for AI is first and foremost about people – AI technology cannot progress without them – this means that millions will need to transform themselves into skilled workers as well as learners that an AI future needs – it is heartening to see that 88% of businesses prioritise skilling and reskilling of workers in the future – they plan to invest as much, or even more, in human capital than in new technology”

“The jobs of today will not be the jobs of tomorrow, and we have already seen demand for software engineering roles expand rapidly beyond just the tech sector – however, building an AI-ready workforce does not necessarily mean an acute need for technological skills”

The top future skills required by business leaders in the Philippines include digital skills, IT and programming skills, adaptability and continuous learning, as well as analytical skills

At present, the demand for these skills is higher than the existing supply

New technology needs new models

According to the WEF – World Economic Forum – manufacturing executives today are confronted with an enormous variety of promising new technologies, ranging from artificial intelligence to connected machinery to 3D printing, all of them offering some combination of cost savings, quality improvements and increased flexibility

They then say it’s tempting to think that a manufacturer could modernise itself simply by replacing its old processes with new ones that feature these technologies – but the historical record suggests that isn’t enough

N.B. The following text reproduces most of the interesting detail in a recent WEF article

ELECTRIFICATION

For an analogy, consider the late 19th century when managers rushed to electrify their factories – electrification seemed an obvious productivity boost but it failed to produce any notable gains for more than three decades – just before 1920, that began to change; gains from electrification accelerated, and it accounted for half of all productivity growth in manufacturing during the 1920s

The Stanford economist Paul David found that managers at first simply overlaid “one technical system upon a preexisting stratum” – factories of the late 19th century used “group drive” systems, with a waterwheel or steam engine driving large groups of machines through systems of pulleys and belts – in the first wave of electrification, managers simply replaced the old power sources with new electric motors, which continued to drive large groups of machines through these pulley systems – they enjoyed modest cost savings on fuel as well as slightly improved control, but their factories continued to function exactly as before

A new generation of factories in the early 20th century began to use electrification differently – rather than instal centralised motors that drove machines through rotating shafts, they began to use “unit drive”, in which a single electric motor is installed in every machine, driving it independently – the advantages of electrification turned out to be profound in ways that early electrifiers hadn’t imagined

Because group-drive shafts lost energy to friction quickly over distance, early factories were arranged around the transmission of power rather than the flow of labour and goods – they needed to be compact to keep machines close to power sources, and any reorganisation was a cumbersome process

By contrast, the 1920s and 1930s saw the birth of factories without group-drive shafts bolted to their ceilings – factories could be bright, airy facilities with efficient single-floor layouts that could be rearranged quickly in response to market demands – electrification thus changed manufacturing, but only after managers became willing to redesign their entire businesses around the fundamental capabilities of electric machinery

COMPUTERS

Computers have since become another example – it seemed obvious that they should boost productivity, but those gains didn’t materialise at first

In the 1960s and 70s, businesses simply moved individual functions like payroll, inventory management and invoicing to computers, treating them more like glorified databases and printers – this led to some modest efficiency improvements, but no more – the real gains would be realised not from saving a little money on record-keeping and printing but by reorganising entire companies and industries around computers – indeed, from the mid-1990s onwards, we’ve seen the rise of an entire generation of valuable companies that invented new, fundamentally digital business models around computers and networking

Today’s manufacturers are in a position similar to that of the semi-digitised businesses in the early 1990s – individual technological solutions are available for a wide range of problems that manufacturers experience:

  • Artificial intelligence can save worker costs on tasks like quality assurance
  • Connected machinery can reduce downtime by warning of maintenance needs in advance
  • 3D printing offers rapid prototyping, flexible production, and savings on small- and medium-run manufacturing

Manufacturers that adopt these technologies without a plan for reinvention will earn only incremental improvements and fail to realise the full value of such new technologies

Ways to reimagine manufacturing

Manufacturers should look to early successful examples of digital factories driving changes in products and business models

These include:

Mass customization, in which products are designed and fabricated around individual consumers – first applications have emerged in high-value fields such as medical devices – decreasing costs for digital fabrication technologies promise to bring mass customisation to lower-value products, including consumer electronics, apparel and athletic equipment

Example: Align Technology has treated more than 5 million orthodontic patients with its Invisalign dental aligners – they begin with a 3D scan of a patient’s mouth and continue with a 3D printing-based manufacturing process

Continuous product development, in which physical products are constantly refined in order to offer improvements or address new markets – the flexibility of digital manufacturing reduces product-development and retooling costs and makes continuous product development possible.

Example: Airbus uses over 1,000 3D-printed parts in its newest airliner, the A350-1000 – most must be reconfigured whenever a modification is made to the layout of the cabin – by 3D-printing these components, Airbus avoids retooling costs and supply chain disruptions – meeting a customer demand for a new cabin configuration only requires a digital redesign

Digital supply chains, which combine digital design files with flexible, automated production facilities that are able to fabricate them – by making distributed manufacturing feasible and cutting inventory requirements, they reduce supply chain cost and risk, and make it possible to serve markets in ways that would not otherwise be feasible or cost-effective.

Example: Deutsche Bahn, the German railway operator and global logistics provider, found that 50% of the replacement parts it requires to maintain its trains can be 3D-printed – this reduces its costly inventory of spare parts, currently worth €600 million, increases dependability, and brings flexibility to the railroad’s fleet planning by making it possible to operate trains, some of which are 50 years old, without long-term support from their original manufacturers

Digital supply chains also offer a way to respond to the emerging global tariff regime: product specifications can be transmitted digitally to distributed factories, which can produce them for local markets without exposure to tariffs.

CONCLUSIONS

When new manufacturing technologies emerge, it’s easy to think about them in terms of concrete applications—the requirements they’re able to meet, the kinds of products they’re able to fabricate

But the real returns go to those who are able to build new business models that stand on top of them, and are willing to reorder entire industries around them

Puzzle – What puzzle?

“The Miracle Years Are Over – get used to It”

So announced Ruchir Sharma, a contributing opinion writer for the NEW YORK TIMES, in a well-argued article reprinted with only minor tweaks below

Across the world, economists have had to downgrade growth forecasts – but it’s not as bad as it sounds

Last year (2018) looked like the time when President Trump had delivered on his promises to strengthen the economy – his tax cuts appeared to juice growth above 3%, a pace the United States had not topped since 2005 – but the US Commerce Department has since revised 2018 growth downward to below 3%, even as forecasts for 2019 were also trending lower, toward 2%

And it’s not just an American story and Mr. Trump who won’t deliver on promises of 3, 4 or even 5% growth – across the world, economists have downgraded growth forecasts in most years since the global financial crisis of 2008:

  • Defying the hopeful projections, Japan has rarely grown faster than 1%
  • Europe has struggled to sustain growth faster than 1.5%
  • And no one quite knows how fast China is growing, but it’s clear that there, too, the economy is slowing.

So why is the dismal science suddenly guilty of issuing overly optimistic forecasts that set the whole world up for disappointment?

Economists keep basing forecasts on trends established during the postwar miracle years, when growth was boosted by expanding populations, rising productivity and exploding debt – but population and productivity growth had stagnated by 2008, and the financial crisis put a sudden end to the debt binge

The miracle is over

Politicians often promise to bring back a golden age, but serious economists also are encouraging a similar illusion – even during the Industrial Revolution, in the 19th century, the world economy rarely grew faster than 2.5% a year, until the post-World War II baby boom began to rapidly expand the labour force – after 1950, the combination of more workers and more output per worker lifted the pace of global growth to 4% – economists came to think 4% was “normal”

Yet by the last decade, the baby boom had faded out from Europe to Japan and China – even in the United States, younger and faster-growing than most developed countries, growth in the working-age population slowed to a mere 0.2% last year from 1.2% in the early 2000s – and because fewer workers correlates directly with slower growth, that decrease implied a 1-point drop in economic growth

Roughly, economists should have expected that United States economic growth would slow to 2% from 3% — and it has – this is the new normal for the American economy – stimulus measures like the Trump tax cuts can lift growth above this path, but at best temporarily, at the risk of higher deficits and debt

For political leaders, the new age of slow growth is not a problem to solve – it’s a reality they need to accept and explain to the public – especially because it’s just not that bad:

  • When populations are growing slowly, the economy doesn’t need to grow as fast to keep incomes high
  • In the United States this decade, growth in GDP per capita has slowed much more gradually than the overall economy, by half a point, to an average of 1.4%
  • Although Mr. Trump likes to boast about how well the United States is doing against developed rivals, Europe has been growing just as fast in per capita terms this decade
  • And Japan has been growing slightly faster
  • In a rich country, that is fast enough to satisfy most people
  • Indeed, surveys show that Americans have rarely been more confident about the economy.

Slower growth in the working-age population also means less competition for jobs worldwide, which goes a long way to explaining why unemployment is now at record lows not only in the United States but also in the UK, Germany and Japan – surely that’s not a bad thing

Whatever politicians tell the public, their attempts to bring back the miracle years are ill-advised – growth in the economy is driven by growth in the number of workers and in output per worker, or productivity – but since the postwar surges of 1950s and 60s, productivity growth has slowed, also defying government efforts to lift it

For a time, the global economy kept motoring along anyway, fueled by a surge in debt – in the 1980s, central banks began winning the war on inflation, which allowed them to drop interest rates sharply – lower borrowing costs unleashed a worldwide binge that saw debt surging from 100% of global GDP in the late 1980s to 300% by 2008

Then the global financial crisis hit, ruining many private borrowers and lenders, many of whom are still wary of taking on new debt – and after growing faster than the economy for three decades, debt growth in many countries, including the United States, has fallen back in line with economic growth – even China, the one major country that dodged the crisis and experienced a surge in lending after 2008, is now reluctant to build on the mountain of debt that already weighs down its economy

So the postwar miracle is over – economic growth is weighed down by the baby bust and the debt hangover – yet because economists continue to base forecasts on miracle rates of growth — 4% for the world, 3% for the United States — policymakers keep fighting to hit these targets – this is very risky

There are growing calls from economists on both the right and the left to lower interest rates, or increase government spending, to boost growth even if that risks higher inflation – at the Federal Reserve, too, there is an emerging view that letting inflation rise above 2%, long considered a red line, may not be unwise

The underlying assumption seems to be that policymakers must take action because 2% GDP growth is intolerably slow

But must they?

The confidence surveys suggest Americans are quite content with record-low unemployment, benign inflation and 1.4% growth in GDP per capita – why then the rush to pump more money into the economy which risks rekindling its debt problems and inflation?

The world does not need more debt and more inflation to counter trends of declining population growth and high indebtedness

Instead, economists need to adjust their forecasts and politicians need to rethink their polices to match this reality, because trying to recreate a bygone golden age is a shaky way to build the future

Gallup’s ‘most profound’ finding

The Wall Street Journal suggested there could be a single fix for many of the big problems that companies experience – hiring better middle managers

They based this on a Gallup study that found a company’s productivity depended on the quality of these crucial leaders – managers don’t just influence results, they explain a full 70% of the variance — something Gallup called “the single most profound, distinct and clarifying finding” in their 80-year history
 
Quint Studer, founder of his eponymous Community Institute, says: “Great middle managers are the key to creating great companies”
 
He goes on to say: “The irony is middle managers often have the smallest training budget of any group in the organisation – given their level of responsibility, their impact on organisational performance and their facing pressure from all sides (bosses, employees and customers) this makes no sense”

Hence, it’s important to hire and promote the right people for these critical positions, and to train them well

To do this, one first needs to understand exactly why middle managers are so important

Quint suggests the following reasons:

  • Managers control the culture of the company – they model the habits and patterns of behaviour expected of all employees and ensure others live up to them as well
  • They’re key to employee engagement for they determine how employees feel about their jobs – “People don’t quit the company, they quit their boss”
  • They know where performance problems are and who’s doing well
  • They have a huge impact on attracting as well as retaining talent
  • They’re responsible for bringing out the best in people – they need to inspire and nurture creativity, innovation and teamwork
  • They’re on the front line with daily processes so should know where and how things can be improved
  • They manage a multitude of tasks and projects and control whether they get done efficiently or not
  • They make change happen by moving people through the various stages
  • They determine what gets reported to senior management

In short, middle managers have hugely important and difficult jobs

Hence, all organisations should make sure they receive the resources and training they need to do them well

Sadly, at present, few organisations regularly review existing skill sets of their managers and the development needed – so it’s little wonder most employees rate their current managers as ‘bad’