GDP – Consumer Surpli

Consumer surplus is defined as the difference between the highest price a consumer would have been willing to pay and the price actually paid

It’s the unquantified value customers obtain from tangible stuff they buy – such benefits include taking less time or effort to do things, obtaining more fun and pleasure from life, having more social contacts with friends and family – all things people want, all demand growth areas, but all difficult if not impossible to measure

Nowadays, statistics on tangible outputs, GDP and national productivity levels seem to be flat-lining as we simply replace stuff, once worn out or used up, rather than add to it as in the past as more of our needs were met – and much of it, thanks to productivity improvement, would be available at lower unit prices (thus lowering GDP) if it did not incorporate significant quality and design improvements

For example:

  • In 1985, about 100,000 wealthy families were willing to pay over $1,000 for a set of the Encyclopedia Britannica – some would have paid more if they had to – others would have bought if the price had been a lot less
  • To calculate GDP, government statisticians looked at the market value of actual sales and multiplied the average price by the number of units sold – $100m say
  • Nowadays, Britannica sells about 50,000 online subscriptions at $75 each – a total of less than $4m
  • So the contribution to GDP from Britannica has dropped by 97%
  • But we are better off, not worse off
  • Thanks to the internet, Wikipedia and many other sources of specialised knowledge, the cost of such information consumption has fallen to near zero
  • We’re getting a lot more and paying a lot less

A similar story can be told for many other modern goods and services e.g. phones, GPS, voice recorders, digital watches, portable music players, video cameras

But economists and national statisticians can’t cope with this consumer surplus – they use measures better suited to the 20th century tangible world, not the new 21st century intangible world

As Matt Hancock, ex Bank of England economist and now UK Health Secretary, suggests, the growth of free apps is benefiting consumers but potentially dampening economic figures: “I don’t think economics has caught up with the impact of zero marginal cost production (digital copies) or products that are free”

Indeed, we believe consumer surpli may well represent a vast black hole in the GDP universe and may well explain much if not all of the so-called ‘productivity puzzle’ currently afflicting most developed nations

As Milton Friedman once famously claimed: “There is no such thing as a free lunch” – consumers always pay, somehow – they have to offer something of value in return for any freebie they get – and freebie services have proliferated over the last decade

Freebie services are used to trap people into revealing private data about themselves and their buying interests, preferences and search criteria – data which is then sold on to a wide variety of suppliers enabling them to focus their marketing and selling efforts on people most likely to buy from them, thus maximising their ‘hit rates’ – so the more attractive a freebie service can be, the more people will sign on to it and divulge their data, making the service even more valuable

Freebie services are thus carrots, modern ‘hidden persuaders’, clever marketing ploys predominantly peddled by IT entrepreneurs – during the past decade alone we’ve enjoyed an increasing variety of them via the iPhone, Uber,  Airbnb and Amazon plus Google, Facebook, Twitter and WhatsApp – and the value of those services to their customers, if counted somehow, would surely have increased national GDP and so productivity levels well beyond those officially announced – perhaps even making up the claimed big differences (18% in the UK) between actual current GDP levels and trend levels

No wonder Professor Hal Varian, chief economist at Google says: “GDP has a very hard time with free”

And Professor Erik Brynjolfsson agrees: “They (freebies) add a lot of consumer welfare but do not show up in GDP”

To underline his view, Erik determined the value offered by many digital services which go unrecorded by GDP:

  • He paid people to stop using freebie services and worked out a ‘reservation price’ for each one – an estimate of hidden GDP
  • He found the average user:
    • Would drop Twitter for nothing
    • Valued Facebook at £85 a month
    • Wanted £470 per month to give up WhatsApp, commenting “I run my life around it – I wouldn’t be able to go to any parties on Saturdays – I wouldn’t be able to contact my babysitter”
  • He concluded that: “Some of these services have become almost indispensable”

Clearly, the actual value of this consumer surplus varies per person as each of us usually has a different maximum we will pay for anything – hence it is nigh impossible to measure it for any nation as a whole

That said, some expert has already claimed that Whatsapp alone would add 3.74% to the Dutch GDP if 10 million of the country’s 17 million people used it (n.b. another statistic that gains credibility because nobody can disprove it)

Conclusions::

  • GDP only records transactions at market prices – it’s completely silent on what we might be getting free
  • Volume of sales may have peaked but value of benefits is forever rising
  • G7 economies are currently undergoing radical changes through digitisation but economists and their performance measures are not keeping pace – they focus on tangibles that dominated growth over the last century but this new century is increasingly concerned with intangibles
  • Some new measures are needed for national productivity, prosperity and well-being

Small Businesses measure up differently

Michelle Ovens campaigns for the UK’s 5.5 million SBs in the ‘Small Business’ publication

She notes that small businesses are responding to this time of change and uncertainty with Brexit by keeping faith in the community values that make them the backbone of the UK economy.

She asks: “Perhaps we have been looking at small businesses through the wrong lens? Perhaps there is more to success than traditional measures of productivity, and more to business than the EU?”

The UK’s GDP per hour worked is around £50m less than the EU’s two major powerhouses, France and Germany – so what is it about UK workers and business that means we don’t measure up when the UK seems to be a thriving, digitised, successful economy?

The UK comprises a huge variety of business models and structures, with 99% defined as “small”, over 60% of private sector employment being via these businesses and some £2 trillion of revenues generated – clearly, they have a huge impact – nevertheless. they are forever being told their impact could be bigger if only they improved their productivity levels.

But when one asks small business owners what is important to them, productivity is not a factor – even profit is not considered as important as creating a living for others – it is a far cry from the ‘greed is good’ days of the 1980s.

Small businesses are putting people and communities first – they are looking to create ‘Good Work’, to foster supportive environments and meaningful working lives for their staff and wider stakeholders – there’s a shift to more flexibility in work, more giving back to the community, and a continued focus on the role of the business in the wider society and economy.

This is not all out of altruism – towns such as Grimsby in Lincolnshire, Holywell in Flintshire, and Frome in Somerset are being rebuilt around thriving small businesses – reducing local employment, increasing house prices, and even increasing local school standards.

The heroes of this small business revolution care less that both they and their employees make less money than their German counterparts, and more that the people in their community have jobs in the first place, and an improved quality of life:

  • Almost three-quarters of small businesses have or would consider keeping on a member of staff even if they did not economically need them anymore
  • There is a recognition of the importance of that job to that person, of that person to the wider community, and of the impact of losing employment
  • This speaks to better mental health, better social mobility and can even impact physical health outcomes.

What would be seen as bad for productivity is almost priceless to the person who keeps their job even when times are tough – hence, staff are appreciating the benefits of working for a small business on a much broader set of criteria than just paying the minimum wage, especially covering the longevity and stability of the work they provide.

Small businesses are thus creating better communities, appreciating their employees as people rather than merely a means to profit, and their communities are appreciating them in return.

Michelle concludes: “It’s now time that the wider world of stakeholders – particularly big business, local and national government, and charities – start to realise the critical and valuable role these businesses play, and reward them for it; not hold them to a set of metrics that simply do not apply”

AI, the future of work and inequality

An excellent article follows, by Daniele Tavani, Colorado State University, USA – reprinted in full

One of the most spectacular facts of the last two centuries of economic history is the exponential growth in GDP per capita in most of the world. Figure 1 shows the rise (and the difference) in living standards for five countries since 1000 AD.

Artificial intelligence, the future of work, and inequality
Figure 1: Gross Domestic Product in five countries, 1000-2015. Source: The CORE-Econ Project. Credit: Colorado State University

This economic progress, unprecedented in human history, would be impossible without major breakthroughs in technology. The economic historian Joel Mokyr has argued that the Enlightenment in Britain brought new ways to transfer scientific discoveries into practical tools for engineers and artisans. The steam engine, electricity, sanitation are examples of technological discoveries that propelled the engine of economic growth, increasing standards of living across the planet.

At the outset of the Industrial Revolution, the Luddite movement rose out of fear of labour displacement in the British textile sector. Famously, the Luddite protesters destroyed the very machines they were using at work, in order to preserve their role as active members of society. Their reasoning was that if automation could double, triple, or quadruple a worker’s output, the economy would need half, a third, a quarter of the current workforce. The Luddite movement was eventually suppressed by military force in 1816, but history has proven them partly correct.

Humans do work shorter hours today than in the 19th century, as shown in Figure 3.

Artificial intelligence, the future of work, and inequality
Figure 2: Luddite protest. Credit: WikiCommons

Many Silicon Valley executives like the Tesla CEO Elon Musk believe that we are on the verge of a new technological revolution that will see Artificial Intelligence (AI) automating a majority of tasks that are currently performed by humans. Just as horses were displaced by motor vehicles, truck drivers may soon be replaced by self-driving vehicles.

Factories producing components for personal computers and tablets are also becoming highly automated. The BBC reports that FoxConn has replaced 60,000 of its workers with robots. An Oxford University study claims that 47% of US jobs could be lost to automation, along with 69% of jobs in India, 77% in China, and 57% worldwide. Machine learning enables robots to make decisions based on a vast amount of data on (sometimes very difficult) decision-making by highly-skilled humans.

Should we then fear that the forthcoming AI Revolution will force humanity to completely rethink the current organisation of our lives?

One of the most important economic thinkers of all time, John Maynard Keynes, wrote in his 1930 essay “The Economic Possibilities for our Grandchildren” that by the 21st century we could fulfill our needs and wants with a 15 hours workweek and devote the rest of our lives to non-monetary pursuits. Fast-forward to 2014, when the late physicist Stephen Hawking told the BBC that “artificial intelligence could spell the end of the human race.”

Artificial intelligence, the future of work, and inequality
Figure 3: Annual hours worked, 1870-2010. Credit: The Maddison Project 2013

Should we see AI as liberating or as a destructive force?

Economists have debated the effect of technology and automation on jobs for a long time. The first set of questions regards labour displacement and whether there is any future for work at all. The second set of questions has to do with how automation impacts income and wealth inequality. On the one hand, if the ownership of robots is concentrated in the hands of a few—let’s call them the 1%—and a majority of jobs disappears for the 99%, it will exacerbate inequality, which is already on the rise (see Figure 4). On the other hand, technological change is also creating polarisation in the labor market among the 99%. According to the MIT economist David Autor, between 1989 and 2007 job creation has occurred mostly in low-paying and high-paying jobs, while middle-class jobs were affected by job destruction on net.

It is true that automation displaces workers in some sectors, but workers relocate to other sectors over time. Historical examples in advanced economies like the US are the transition from rural agriculture to urban manufacturing during the first half of the 20th century, and from manufacturing to services in more recent times.

The net effect on jobs does not seem to lend support to Hawking and Musk’s gloomy predictions. This is even more true if one considers another beneficial effect of technological change: everyday objects like dishwashers, vacuum cleaners, washers, and dryers, reduced the burden of housekeeping and freed up time for women to seek employment. Indeed, the labor force participation rate was 67% in 2000, compared to 59% in 1948. The increases in labor productivity brought about by technological change spill over into higher wages for workers

Artificial intelligence, the future of work, and inequality
Figure 4: Top 1% Fiscal Income share, US, 1913-2015. Credit: World Inequality Database

This is not to say that technological change has no costs for society. The transition from agriculture to manufacturing took time, and in the short run produced economic anxiety, unemployment, and poverty among former agricultural workers. The same applies to the transition to a service economy, although there are some troubling peculiarities about the latter process. The transition to manufacturing was associated with higher wages and employment protection through union membership. The transition to services not so much: low-skill service workers tend to be paid less than workers of similar skills in manufacturing, and service workers are in general not unionised: consequently, they do not take advantage of the benefits of collective bargaining in terms of wages.

Another cause of concern is that automation and technological change is characterised by increasing returns: doubling the scale of production enables production at more than twice the output at the initial scale. Increasing returns lower the cost of production as the scale of a firm expands, which leads to firm concentration toward few, large firms with lots of market power. And it is not by chance that the most visible hi-tech industries, such as Apple, Amazon, Google, and Microsoft are all basically monopolies.

The decline of manufacturing employment and the increasing concentration of the US corporate sector are two reasons why average wages have not kept up with the increase in labor productivity over the last 40 years. An average 2015 worker is almost 2.4 times more productive than an average 1948 worker, but her wage is only 110% higher. Wages were growing on par with labour productivity up to the 1970s; starting in the 1980s, productivity has been growing at a much faster pace. The process of job polarisation has fed into this pattern, determining rising employment in low-paying sectors and high-paying sectors, at the expense of good middle-class jobs.

Although it is possible that AI is completely different from the technological advances of the past, we should be sceptical that automation will mean the end of work. Jobs—or even specific tasks—will be displaced, but workers will relocate to different jobs or take up different tasks. For low- and medium-skill workers, it is likely that the relocation will occur in jobs of lower quality, meaning either lower pay, or fewer benefits, or a combination of both. Workers who possess skills that are complementary to new technologies, on the other hand, will benefit from the advent of automation by reaping most of the productivity increases in the form of higher wages. And the very few CEOs of successful tech companies will see their incomes skyrocket.

Hence, citizens and policymakers concerned with the rise of automation should focus on its effects on inequality. During the 1980s economists have embraced supply-side views that inequality is beneficial for growth, but recent academic research has shown that the opposite is true. The work by economists Thomas Piketty, Emmanuel Saez, and Gabriel Zucman has suggested that high marginal tax rates on top incomes—that is, tax rates levied on every dollar earned above a certain, typically very high threshold—would go a long way in reducing inequality without distorting the individual incentives to work hard. Indeed, the US economy grew fastest between 1950 and 1970, when the top marginal tax rate was well above 70%. The corresponding tax revenues could be used to provide unemployment compensation or foster the provision of public goods such as education and training for workers to relocate when their jobs are automated.

Ethical capitalism

We have waxed long and hard on these pages about CEOs acting like pigs at the trough, robbing their businesses, the golden geese that should be improving the lot of all in society, by paying themselves huge unjustified pay and bonuses and maximising their share prices (and hence their shareholdings) whilst paying their employees the bare minimum and investing little for growth

At the same time, we’ve often applauded the John Lewis retail chain, in particular Spedan Lewis, founder of the company – his aim was: “Solely to make the world happier and a bit more decent” – JL now has 400 shops and 83,900 employees, called partners, who share profits made in an annual bonus scheme – this has obviously increased employee motivation levels, improved their attitude towards colleagues and customers and been a significant factor in their success

Now, another splendid example has hit the headlines

Julian Richer founded his eponymous TV and hi-fi chain Richer Sounds in 1978 – the company has a gross turnover of about £200m, is worth £9.2m and has 522 employees:

  • He is to give control of the company to an employee trust i.e. a 60% share of his company
  • And a further £3.5m as a cash bonus so each employee will receive £1,000 for each year of service – an average of £8,000 each
  • And all this on top of giving 15% of profits to charity

Apparently, Richer regularly monitors his employees’ morale by asking them for their ratings from one to ten – he also calls anybody suffering a bereavement or health treatment – and 70% of his employees use his 12 holiday homes at least once a year, funded (he says) by ‘reduced internal theft’

Overall, he says: “Companies should be encouraged, not forced, to act in a similar way”

Richer explains: “I am increasingly angered by what I see elsewhere – disreputable people running their companies in a way that involves taking as much as they can from society and then sneaking their profits out of the country”

The Times says:

  • “Richer’s decision shows a laudable commitment to the company’s employees and an acute understanding of how capitalism rests on public-spiritedness rather than avarice
  • Companies have more obligations than the enrichment of their shareholders, and acknowledging this can be a route to business success
  • The good company owes profits to its shareholders, secure jobs for its employees, good products or services to consumers, and an obligation to society – it’s how the market economy can serve the many, not the few
  • There are a mere 350 employee-owned businesses in the UK – aligning the interests of employees and owners is good for business by stimulating productivity”

Conclusions:

  • Nowadays, many bosses are more concerned with feathering their own nests than building their own companies for the benefit of all – they display what Prime Minister Ted Heath called ‘the unacceptable face of capitalism‘ – how do they get away with it? – “Because they can” according to President Barack O’Bama
  • Richer’s whole attitude towards his employees is key to his own financial success – he not only ups their pay and ownership status but treats them as equals and shows genuine concern for their welfare, both at work and at home – no wonder Archie Norman consulted him when boss of ASDA and is doing the same now he’s boss of M&S
  • Too few managers realise the potential lying dormant within their teams, not least because of them
  • Some believe most teams could perform at least 30% better if only their bosses thought and acted like Spedan Lewis and Julian Richer

Where measuring engagement goes wrong

An article by Peter Cappelli and Liat Eldor in the Harvard Business Review is reproduced below close to its entirety

Surveys to assess how engaged workers are in their jobs are highly popular among employers, who hope the results will help them improve employee productivity and creativity and reduce turnover – but consultants and academics have long differed in their conclusions about how much can be inferred from the results of these surveys

Based on our own work as academics, we caution business leaders implementing such surveys – they may not tell you much about your employees that you can do anything about

One reason for this is that there is no universal definition of “engagement” as it applies to workers – another is that while engagement has been shown to have some ties to employee performance (e.g., absenteeism, turnover, performance appraisal scores, self-reports of performance), those ties account for a small amount of the variation in individuals’ performance

Typically, companies are interested in employee motivation when they conduct engagement surveys – the more motivated workers are, the higher their level of performance will be, the thinking goes

We do know that employees tend to be more motivated and engaged when they feel their jobs are crucial to their employer’s success or contribute to society, when their leaders support them, and when they can try new things – but changing those factors and, in doing so, increasing engagement and motivation — is devilishly difficult to do

Before canvassing employees on engagement, business leaders should understand the surveys’ shortcomings, clarify what they want to accomplish, and explore whether they might be better off with alternatives

Surveys that gauge workers’ satisfaction with specific factors such as pay, benefits, and work schedules, for example, or that evaluate how they are being managed by their immediate superiors, might be more useful in reducing turnover

THE ORIGINS OF ENGAGEMENT SURVEYS

The current surveys sent out by human resources departments have their roots in the morale surveys conducted by the U.S. military during World War I – “morale survey” was a catchall term for evaluations covering a wide range of topics, but the military was especially interested in the troops’ willingness to fight

After the war, many of the experts who had conducted the morale surveys moved into the private sector and created organisations to apply the lessons from military psychology to employees

The popularity of these kinds of surveys among employers grew in the 1930s, when companies such as Sears, Roebuck used them to figure out how to fight off unions – this explains the initial focus on whether workers were satisfied with factors like pay and supervision – if companies were aware that their workers were dissatisfied, and knew why, they could address the problems before unions had a chance to step in

The Big Idea

By the 1950s, major corporations’ worries about unionisation had waned, as companies either succumbed to unions or were able to keep them out

HR departments kept the surveys alive to ask workers about issues in HR’s purview, such as satisfaction with pay, benefits, and work schedules, which can indicate whether employees will leave for new jobs

The notion that satisfied workers are productive workers made surveys even more popular, until more sophisticated analyses starting in the 1980s found that satisfaction did not predict much about job performance

These findings, combined with a new field of research, caused employers to embrace the idea that measuring worker engagement, rather than satisfaction, could tell them something about how hard their employees were working

The concept of engagement came out of the academic research of William Kahn, a Boston University psychologist interested in examining the degree to which individuals brought their “full selves” and energy to their jobs

The idea advanced with the identification of employee burnout as an issue — the finding that work performance suffered when employees were psychologically and emotionally exhausted from their work experience – if lack of energy was a bad thing, then the opposite (engagement) should be a good thing, posited Wilmar Schaufeli of Utrecht University and his colleagues

A number of contemporary definitions of engagement tap into employee commitment (Do I care about my employer’s interests?) and motivation (Am I actively trying to advance those interests?)

THE PROBLEMS WITH ENGAGEMENT

One problem that companies often stumble over when using engagement measures is that different definitions of the term abound – the European version, for example, associated with Schaufeli, emphasizes the idea of “vigour,” and there are an array of others

Consultants also tend to use different definitions from their competitors, which contributes to the confusion:

  • Gallup Consulting, for instance, says that engagement is pride, passion, and enthusiasm for work
  • Willis Towers Watson defines it as “employees’ willingness and ability to contribute to company success.”
  • One of the most widely cited pieces of engagement literature defines it differently still, as “the individual’s involvement and satisfaction with as well as enthusiasm for work”

The predicament is when an employer wants to find out, say, how hard employees are working, and the engagement survey it uses measures something else, such as pride in one’s job or ability to contribute

A second major problem with engagement surveys is that many employees don’t respond to them because they don’t believe management will do anything with the answers

A recent survey found that 70% of employees do not respond to surveys and nearly 30% of them think they are useless – and anecdotal evidence suggests that the pervasiveness of those sentiments hasn’t changed since then

When we survey employees, we are signaling that we care about what they think and that we are going to actually do something with their answers – if we don’t really care, and our employees know this, because they didn’t see any changes after the last survey was conducted, an additional survey will only increase worker alienation

Finally, many employers are interested in the idea of engagement because they believe it tells them something about job performance and, in particular, whether people are working hard – but job performance and other employee behaviours are influenced by many factors that most engagement surveys can’t take into account, including the tasks people are given, which sometimes change daily; what their supervisors are doing; what is going on with their project or the company; and so on – in addition, many factors outside the job affect an individual’s performance, such as ill health or family problems

The results also vary depending on what a business does – engagement has been shown to be far greater in organisations with a clear social mission, such as saving children’s lives, than in those that lack one, like investment banking

Given all this, the hope that we can predict someone’s future job performance with accuracy based on any self-reported statement about that person’s current mental state is unrealistic

Consequently, employers should rethink their survey strategies and make sure they are using the type of survey that can give them the best information for achieving their goals

WHAT YOU SHOULD DO INSTEAD

Before conducting an employee survey, figure out what you actually want to know:

  • If you want to find out whether employees think your compensation and benefit policies are fair, ask them that question directly
  • If you are concerned about who might quit, ask about that directly as well
  • If you want to know how employees are performing their jobs, you can survey them on their perspective (or, better yet, ask their supervisors – we believe their assessments are better indicators of job performance than the self-reports from individuals about their motivation levels)

You can also learn a lot simply by asking employees open-ended questions such as “What would you change about your job and how you are managed?” and by having meaningful conversations with supervisors about what prevents them from getting more work done

You are likely to learn more about how to improve performance from these kinds of questions than from surveys about engagement

So, if you are truly interested in your employees’ motivation and commitment and decide to conduct engagement surveys, just be sure to keep their limitations in mind:

  • Once you have the scores, be realistic about the meaning of the results
  • You shouldn’t expect your workers’ engagement to be anywhere near 100% – few people are completely focused on their work even when they are at the office
  • Engagement scores are also reasonably stable over time – employees who are highly engaged tend to stay that way
  • The same holds true for those who are not
  • Don’t expect that a new compensation system or a culture change initiative is going to result in higher engagement scores

Second, remember that engagement scores measure the perceptions of a group of employees, but this does not address causation – and while some surveys try to ask employees directly why they are disengaged, this is often difficult for workers to self-diagnose

The best approach is to ask employees directly about factors that research has shown matter to engagement:

  • Employees want to have a sense of purpose in their work and to feel that their role is meaningful to the organization’s success
  • They want leaders who lead by example, who are supportive, who set clear goals, and who give regular, meaningful feedback
  • They want a safe environment where they can take risks and try new things

Are they seeing that at work?

Finally, do something about the results – improve the factors employees report are lacking

Engagement scores, for all their prominence in HR and media circles, are ultimately about something both remarkably simple and also difficult to do successfully – doing a good job of managing your employees every single day

Economists’ information gap

Robert Samuelson, an economic journalist writing in the Washington Post, says: “Many economists often don’t know what’s going on”

How refreshing to read this breeze of commonsense after being buffeted by gales of expert opinion and advice from the government and its agencies, economic think-tanks or the media

The following is a precis of his article

The most intriguing thing we have learned about economists in recent decades is that they don’t know nearly as much as they thought they knew

Their forecasts are usually badly wrong:

  • They don’t see major turning-points coming in the economy, at least not until afterwards
  • They can’t explain the current growth in jobs, nor how long it will last
  • They missed the long term decline in interest rates – and can’t fully explain it
  • They did not predict double-digit inflation many years back – worse still, they advocated policies which kindled it – and they’re now baffled by current inflation remaining low
  • They were completely surprised by the recent 2008-09 financial crisis – “Why did nobody notice it coming?” Queen Elizabeth famously asked
  • And, over the last 50 years and more, they have consistently failed to forecast correctly any major shift in productivity growth, whether up or down

Samuelson concludes: “There is an ignorance gap between what economists know and what we need to know which is huge”

The cause of the ignorance gap is the very complexity and obscurity of a $20 trillion economy (United States) or an $85 trillion economy (World) – it’s changing in detailed and often-unanticipated ways – and we humans, including economists, have never been very good at predicting the future

Most economists may be extremely smart and well-informed – many are also public-spirited and generous with their time – they elevate the level of public discussion

But many exaggerate what they know and how much they can influence the economy, not least to gain and retain political relevance and power – the result is often disappointment, with government performance falling short of promises

Samuelson suggests: “A little more humility might be in order”

We say: “Better basic data on the economy would do better”

21C to be greatest century in history

According to Ian King, banyanhill.com, we were promised flying cars by now but got Facebooknot to mention Google, Twitter and Skype

He admits Facebook has its uses but the utopian future expected has yet to arrive – all these new technologies have not yet led to widespread prosperity

In 1930, John Maynard Keynes predicted we would be working 15-hour weeks around now – the impact of the Industrial Revolution led to a sharp decline in average weekly hours – new machinery powered by technologies such as electricity and the internal combustion engine allowed workers to produce more with less human input

Weekly U.S. Manufacturing Hours 1940-2010

Keynes expected this trend to continue with the rise of new technologies – however, the last 50-plus years have bucked that trend – the steady decline of weekly hours flat-lined during the Great Depression and has continued to do so ever since

Despite recent technological innovations, workforce productivity hasn’t rapidly improved yet their productivity determines the average standard of living, including their work hours input

Indeed, in the last 100 years, there has been only one big wave of productivity improvement and that occurred in the first half of the 20th century – it had taken a few decades before the breakthroughs of the Industrial Revolution translated into major productivity improvement:

  • The first automobile patent was awarded to Karl Benz in 1886, but it was decades before Henry Ford mass-produced the Model T
  • Thomas Edison produced the first light bulb in 1879, yet 50 years later only half the homes in the United States had electricity
  • Both thus started slowly at first, but then suddenly became part of everyday life, ushering in many other developments like the dishwasher and washing machine which freed us from the toils of home labour

Now, we are about to hit a tipping point with the Information Technology Revolution:

  • The internet has followed a similar trajectory as electricity
  • It’s been around for three decades
  • It’s only been used to search a giant database
  • That’s about to change

Within the next decade, nearly everyone on planet Earth will have internet access, putting the world’s information in the palms of their hands

Billions of devices will collect and transmit the world’s information over high-speed 5G networks, launching new disruptive trends into the 21st century viz:

  • Blockchains will create new financial networks, as users can own something of digital value that can no longer be duplicated
  • Robo-taxis will use artificial intelligence to shuttle kids safely to soccer practice
  • Robo-trucks will ship goods cheaply around the country, bringing manufacturing back
  • City traffic, congestion and parking will become a thing of the past
  • The world’s best surgeons will be robots
  • (And the above are just some of the tangible benefits possible – there’s a host of more valuable mental benefits in the offing)

King concludes: “It will be like the Roaring ’20s again — a decade of increased productivity and prosperity”

GDP – Flaws

At present, GDP is universally taken to be not just a measure of national output but also shorthand for national well-being

Richard Tomkin, assistant director of the ONS (Office for National Statistics), which collects all the base data, says: “GDP is used as an all-encompassing proxy for people’s living standards although never designed for this”

Essentially, GDP growth is determined by just two factors – population and productivity growth and as nations become developed economies, so their populations tend to stop growing  – this means they then become totally dependent on productivity improvement if their children are to even equal what their parents achieved, never mind do better as was expected in the olden days

Why so:

  • Because, when productivity is improved, unit costs and real prices usually fall, including when unit quality improves
  • So if more people don’t buy more, GDP will fall 
  • So, for GDP to rise, we need to consume more existing stuff and/ or new stuff on offer
  • But there comes a time when most of us don’t want more existing stuff on offer – we have enough and only replace worn out stuff
  • So, for GDP to grow Then GDP will slowly fall as populations peak – as they always do as nations develop/ mature and birth rates fall to below replacement levels
  • And this will increase as our values change from material to mental stuff

So, just as birth rates fall the more developed a nation becomes, so GDP will also fall

And if and when GDP stalls, as now, central bankers can consider national capacity to be fully utilised and so expect prices to rise as demand exceeds supply – given this would lead to inflation rising above target, currently 2% per annum, they raise interest rates to deflate such extra demand – the result is borrowers, especially those with mortgages, suffer, sometimes harshly

But what if those GDP measures were flawed – what if central bankers and government ministers were being misled by them?

Indeed, it was the late Robert Kennedy who said: “GDP measures everything except that which makes life worthwhile”

We agree, and question why GDP is even used by anyone, especially our leaders deciding policies affecting everyone – claiming it’s the only measure they have is not good enough, just as a flawed ‘fix’ on a chart can lead a ship to steer confidently onto rocks

So why is GDP well past its usefulness date:

  • First, it does not measure everything:
    • Much countable economic activity is not counted
    • More is deemed uncountable
    • Much is spent on failure and putting things right, examples being repairing or replacing shoddy goods, repeat visits to doctors or hospitals to be cured or dealing with youth suicides, exam failures or litter louts and fly-tipping
    • Much that enables people to live lives that are meaningful and satisfying goes uncounted – worthwhile modern living is much more than just consuming goods and services

 

Governor of the Bank of Canada, Stephen Poloz, agrees – he doubts the appropriateness of GDP and whether we are accurately measuring economic activity in the digital age, saying:

  • “Traditional measures were developed to measure the manufacturing-based economy of old – to count the number of widgets produced in a factory by the workers employed there
  • But the economy has become a very different animal, dominated by services, and those services are hard to measure and properly value – digital services in particular”

 

The overriding concerns now are whether the gains from technology are being fully captured by GDP statistics – whether the apparent decline in advanced country national productivity levels over the last decade or so is because of slow economic growth or other valuable activity is being overlooked

At present, we guestimate the composition of any developed economy’s GDP to be as follows:

 

                                    COUNTABLES       UNCOUNTABLES                           

COUNTED                 A =  50%                      B = 20%

                                    ________________________________________                        

UNCOUNTED          C = 15%                      D = 15%           

 

A. Counted Countables (50% – trend flat):

  • Private sector goods and services all have a selling price – customers assess the VFM on offer, some buy – those sales are counted, albeit some are fraught with errors
  • Public sector services usually don’t have a price – input costs are thus assumed to be equivalent to notional output prices paid and so the value obtained by tax-payers – N.B. if one pours extra tax-payers’ money into such services, GDP rises so the economy and national productivity appear to improve when the opposite may be the case
  • Professor Hal Varian, Chief Economist at Google commented on the impact of technological progress in this quadrant:
    • “In 2000, there were 80bn photos taken worldwide – now, it’s about 1,600bn i.e. 20 times as many
    • The cost of each photo, the film, developing and printing was about 50p each – now it’s effectively zero, resulting in a decline in GDP but a huge increase in enjoyment”
    • Thus, if technological creative destruction keeps reducing unit costs of existing stuff, even if it keeps increasing the quality and so value offered, overall GDP will be reduced
    • Equally, if technology keeps replacing much existing stuff – for example, smart phones replacing files, letter paper, envelopes, postage stamps, diaries, watches, atlases, cameras, video-recorders as well as old phone, then GDP again will fall
    • Hence, for GDP to grow, nations must either sell more volume of existing stuff at existing or higher prices and/ or sell new stuff as well
  • Brent Moulton, formerly of the US Bureau of Economic Analysis which collects US GDP data, has two further concerns:
    • How to account for the effects of innovation on new products and quality changes
    • How to measure price changes – how much of any change in the sales of a particular good or service is due to price inflation and how much due to changes in real output, either the quantity or quality of that good or service
  • Conclusion – The scope to under or double-count in this quadrant is considerable, especially when outsourcing abroad or several suppliers are involved for the one product – it’s not just assumptions, estimates and forecast errors that muddy these waters

 

B. Counted Uncountables (20% of GDP –  trend flat):

  • There are a few significant but uncountable private sectors where the ONS  estimates their GDP value, including:
    • Drug dealing – apparently worth some £4.4bn to GDP
    • Prostitution – which clocks some £5.3 bn
  • Apparently some ONS investigator, maybe team, was able to establish that the average price of a prostitute in the UK was, at the time, £67, but sadly gives no more detail
  • And then they ask us to believe their official GDP statistics are accurate to within 0.1%

 

C. Uncounted Countables (15% of GDP –  trend rising)

  • New 21st century economy activities, including:
    • Millions of us now use our computers and mobile phones to complete clerical activities once done by secretaries, typing pools, bank and insurance clerks, even stockbrokers – what once cost money and counted for GDP is now done for free and doesn’t count
    • Many organisations get their customers to do, for free, much of the admin paperwork once done by paid staff e.g. HMRC and tax returns, supermarkets and self-server checkouts
    • Much R&D investment is made hoping to find new products and services for later years – GDP measures only the R&D costs and any revenue obtained from products and services this year
  • Long standing ‘white economy’ activities, including:
    • Housework – cleaning, cooking, DIY, gardening
      • The ONS says the value of unpaid housework is £1.25 trillion p.a.
      • This is bigger than the output of the non-financial sector and equivalent to some 2/3 of total UK GDP
    • Hobbies, arts, music
    • Charity work e.g. RNLI lifeboatmen
    • Most child and elderly care
    • Ferrying family members to/ from school, shops, friends, healthcare
    • The unregistered unemployed earning a few bob
  • ‘Black economy’ activities, including:
    • Moonlighting
    • Working for cash
    • Crime – fraud, muggings, black markets
    • Tax avoidance
    • Hidden incomes

 

D. Uncounted Uncountables (15% of GDP –  trend rising):

  • Environmental benefits:
    • Costs to ensure the sustainability of the environment – not having to later repair damage done now e.g. from pollution, global warming, atomic waste, less bees for pollination
    • Free enjoyment of the countryside, seaside, fresh air, clean seawater, diversity of flora and fauna
    • More trees, less flooding – introduction of beavers on floodplains
    • Better infrastructure e.g. transport convenience and speed, broadband capacity
  • Physical benefits:
    • Longer lives
    • Healthier lives
    • More caring/ altruism/ concern for others
  • Mental benefits – aka ‘consumer surpli’:
    • More/ better leisure/ pleasure – more choice, better quality
    • Less tedium/ slog doing boring work
    • More contentment if not happiness
    • Better educated/ more skilled
    • Better informed, and quicker, so can make better decisions
    • Better/ quicker diagnoses of illnesses
    • Better/ quicker searches of legal precedents before court cases
    • More social connectivity
    • More working from home – less stress, less wasted commuting time

 

Given the above, one is minded of what the famous economist Joseph Stiglitz said: “What we measure affects what we do, and if our measurements are flawed, decisions may be distorted”

The good news is this may all give cause for optimism – people may be much better off now than official statistics would indicate

Indeed Charlie Bean, economist and ex Deputy Governor of the BoE (Bank of England) sides with us by saying: “The UK economy may be growing 0.75% per annum faster than official figures say”

CONCLUSIONS

  • Developed G7 nations continue to count GDP using flawed old-world measures of physical/ tangible goods and services – they also make huge assumptions about the value of public services offered – at the same time they miss many other equally valued outputs or outcomes producing  intangible benefits which make peoples’ lives worth living
  • The result is GDP, and thus national productivity figures, can be dangerously misleading, especially to governments who determine economic policies and tax regimes based on them

_________________________________________________________________________________________________

Points made by Philip Aldrick in The Times

  • Not everything that can be counted counts – and not everything that counts can be counted
  • We count what we measure
  • We never know all, usually don’t know much, and probably get most of that wrong
  • All leaders need good measures first to establish their current position, where problems and opportunities lie and what policies work
  • Take productivity – which drives real wages, living standards and even life expectancy (show how):
    • Conventional wisdom has it that higher productivity regions are skewed towards higher productivity industries, such as finance and manufacturing
    • But London and the South East are more productive, regardless of industry
    • According to Rob Kent-Smith, the ONS’s deputy director for national accounts, the important factors are ownership structure, whether a company trades internationally and its age
    • Dig deeper, and clusters explain much (see ????) – where like-minded businesses and suppliers locate next to each other, spreading good/ best practices back and forth, and enriching each other with ideas
      • Raise the standard of an area and higher-skilled workers will come
      • Seed new creative industry clusters outside London
      • Andy Haldane says the government needs to invest in the poorest regions and ‘lean against market forces which will only widen regional differences’
      • Throw taxpayers money at risky bets rather than sure things
  • (Dangerously) the numbers we do count end up taking on a hallowed importance – such as GDP, which does not reflect people’s lived experience
    • (Note the nonsense now being spouted about huge differences between UK regions)
    • According to Darren Morgan, director of economic statistics development at the ONS (no less): “GDP is not even the best gauge of living standards – average incomes after housing costs would be better (I agree), and those too vary by region
  • Some official has established that happiness is lowest in London, the richest UK region, and highest in Northern Ireland, one of the poorest

 

 

Current NHS productivity measurement

The University of York’s Centre for Health Economics confidently announced that, despite the government making drastic cuts: “Hard working NHS staff are providing 16.5% more care per £ than they did 10 years before whilst national productivity has only grown by 6.7% over the same period

In particular, they claim that:

  • NHS outputs have continuously increased since they began measuring some 12 years before
  • 5.2 million more patients received planned or emergency hospital treatments over that period – an increase of 42%
  • Outpatient activity shot up by 131% with over 60 million more attendances

The ONS – Office for National Statistics – also joined in the applause with: “NHS England productivity grew by 3% over the last year which was more than treble the 0.8% achieved by the whole UK economy”

Apparently, the NHS has delivered over £6 billion of quality and cost improvements in the last year alone – action taken including:

  • Introducing a cost-per-hour cap on employing agency staff
  • Curbing prescription of medicines that have little or no benefit
  • Stopping routine commissioning of procedures where less invasive, safer treatments were available and just as effective

(Ed: £6bn is an impressive figure, if true, given total annual NHS spend is some £100bn – but, rather than stop there, ask how much more could have been saved)

Unsurprisingly, Simon Stevens, CEO of NHS England, has been quick to say the above findings are proof that: “Taxpayers’ investment in our NHS is money well spent”

Professor John Appleby, chief economist at the Nuffield Trust think tank adds his pennyworth, saying: “This certainly gives the lie to the idea that the health service is some form of backwater of inefficiency missing out on progress – it appears quite the opposite”

So, given this fanfare of good news, one has to ask why Prime Minister Theresa May rains on it all by requiring Simon: “To tackle waste, reduce bureaucracy and eliminate unacceptable variation within the NHS”

And how can the IEA – Institute of Economic Affairs – brand the NHS: “The most overrated and inefficient service in the world”

Both sides can’t be right

We suspect their opposite views depend on the base data they’re using – one might use some bits of the overall jig-saw, the other quite different bits

Whatever the reason, the NHS and associated think tanks seem to focus on patient volumes treated (outputs) and input resource costs – and less so on quality and service levels offered patients, especially the extra costs, wasted time and suffering many patients endure because of NHS system failings

For example, where’s measurement of the following:

  • Attendances (aka episodes) may indeed be going up but how many are repeat visits by the same patient for the same one health problem which was not dealt with right first time
  • How much of this failure demand is caused by the NHS themselves whilst patients are being treated for something else e.g. catching MRSA whilst an in-patient, or HIV/ hepatitis C when injected with infected blood
  • Waiting times are getting longer, forcing many patients to suffer longer as most cannot afford to ‘go private’ at great expense – how often does the same NHS doctor offer the treatment needed on a private basis and nigh immediately, even using NHS facilities

And, when patient queues lengthen, loud cries are always heard for ‘more funding for more input resources’ – last time, the beleagured Theresa immediately leapt in with an extra £20 bn (of our taxes), not least to garner votes at the next general election and outflank Corbyn

Nobody questions the body of senior health managers and experts who assume existing NHS methods are fine so it must be extra resources that are needed – ask front-line staff, however, and a different view emerges

It’s well-known that internal methods/ systems determine most (over 90% according to guru Dr Deming) of the productivity level of any organisation i.e. NOT employee numbers, engagement or incentivising them to work harder

Of course, the piecemeal action being taken, such as above, is most welcome – sadly, however, one never reads about any root-and-branch review of the whole NHS process, from GP gatekeepers through in-and-out patient services at hospitals and then on to social care services – nobody seems to quantify the waste and bottlenecks at each stage, nor identify ways to improve the entire patient flow

This is not to downplay the fact that the NHS has been a great success story – indeed, survey after survey show the vast majority of patients are more than satisfied with the service they receive despite managers having to cope with a constant diet of political reforms and ministerial micro-meddling – nor is it to deny that most staff work hard and long hours despite recent pay freezes and Brexit creating staff supply problems

But the rosy picture of the NHS painted by the University of York is misleading – their cherry-picking of what data does exist is not what hard-pressed tax-payers want to hear

Instead, a comprehensive ‘balanced scorecard’ of performance measures should be agreed by both NHS patients/ tax-payers and ministers/ managers which quantifies those KRAs – Key Result Areas – where the NHS is performing well or not, and where most scope for improvement lies

At present, big improvements that should be staring them in the face are going unseen

_____________________________________________________

P.S. No sooner had we posted the above than Matt Hancock, UK Secretary of Health launched a new TPA – Tax Payers’ Alliance – report claiming the NHS could save £12.5bn in annual staff time, allowing staff ‘much more time to do the vital things they love’ – and a further £5.9bn in the social care sector

Their secret is increased use of automation – the use of technology to improve the methods and systems used by all NHS staff, help them address shortages and free professionals from repetitive tasks – technology which addresses the areas of biggest improvement potential that we outline above

Hancock explains: “Automation and innovation are changing the way we live our lives – they can transform the way we deliver public services for decades to come – it’s critical for all of us that we seize the opportunities of the future and ensure modern technology benefits staff, patients and our country as a whole”

“Big productivity gains are made when technology is embraced”

Dr Simon Wallace, Chief Clinical Officer at Nuance Communications adds that:

  • “The NHS must encourage a culture shift to ensure technology is properly used to boost efficiency, improve patient care and reduce stress and burnout seen across the healthcare profession”
  • “Technologies like cloud computing are enabling inter-operability, resulting in increased data sharing across Trusts and more complete patient records, whilst AI should reduce the burden of administration and support clinical decision-making”

Is everything preordained?

According to ‘The Science of Fate’ by Cambridge scientist Hannah Critchlow, your future may be more predictable than you think

Everything about you is fated, from your love or hate of garlic, your academic success, your expanding waistline or the cancer that will eventually kill you

Everything is determined by your genes and environment

If you’re fat, that’s not down to your lack of willpower – Hannah says we’re predisposed to overeat for evolutionary reasons when we would guzzle what few calories ever came available – it’s mostly a genetic lottery which determines whether you’re fat or thin – hence, it’s almost impossible for many active fat people to keep a healthy BMI

Environment factors also come into play, examples given being:

  • Kids raised on healthy foods by pious middle-class parents are more likely to eat healthily as adults
  • If mothers eat caraway seeds whilst breast-feeding, their kids will seek out that taste thereafter
  • Kids of parents who starved during WW2 are programmed to hoard calories
  • Mice who are presented with the smell of cherries while simultaneously receiving an electric shock give birth to offspring who are terrified by the smell (vital cruelty to advance science?)

Hence, the idea that we have any conscious control over our lives may be an illusion

Our consciousness is simply superimposed on top of the automatic machinery of our brains – we luxuriate in the illusion of power while unseen subordinates quietly get on with the business of actually running things

Another neuroscientist colleague adds: “I don’t believe in free will – everything is caused by something prior – for example, scientists can forecast the course of human conversations with great accuracy because much of what we say is constrained by our relationship with the person we’re talking to, our background, our social expectations and the rules of language”

Hannah concludes that we’re nothing more than fleshy robots, not least because:

  • There are some genes linked to impulsivity and sensation seeking, even influencing when you will lose your virginity
  • Others which determine whether you will turn out to be liberal, with a greater tolerance for the unknown, or conservative and so more sensitive to perceiving threat

Overall, Hannah says the brain is nothing more than an ‘electro-chemical circuit board’

James Marriott, reviewing Hannah’s book in The Times, admits this view may disturb many who thought they were ‘magnificent, rational beings driven by their indomitable wills’

Leonardo paints knowledge path

According to The 50th Law by 50 Cent and Robert Greene, knowledge in the mid-fifteenth century had hardened into rigid compartments viz:

  • Philosophy and scholasticism
  • The Arts
  • Science
  • The Occult – dark knowledge

Leonardo da Vinci was then a youth, the illegitimate son of a notary so lacking the usual formal education – hence his mind was freed from all the prejudices and rigid categories of thinking that prevailed at the time

He started as an apprentice to great artists, learning the craft of drawing and painting – knowledge in one field however simply opened up in him an insatiable hunger to learn something else in a related field:

  • Painting led to design in general
  • This led to architecture
  • Then on to engineering, making war machines
  • Animals and motion mechanics
  • Birds and aerodynamics
  • The anatomy of animals and humans
  • The relationship between emotions and physiology
  • And on and on – even to the occult

He recognised no boundaries between them – he sought the connections between all of them – in effect, he was the first real Renaissance man

Sadly, today, knowledge has regressed and hardened into rigid categories with intellectuals shut off in various ghettos:

  • Intelligent people are defined by how deeply they immerse themselves in one field of study – their views becoming more and more myopic
  • After school we are all encouraged to specialise – to learn one subject well and stick to it – we strangle ourselves with the narrowness of our interests – polymaths are the white crows of our time

Instead, we should follow Leonardo’s example and develop a new body of knowledge – one where what matters most are the connections between things, not what separates them

All the greatest innovations in history come from an openness to discovery, one idea leading to another, sometimes from quite unrelated fields

We need to encourage and develop Leonardo’s insatiable hunger for knowledge by widening our fields of study and observation, and letting ourselves be carried along by what we discover – that way leads to unexpected ideas, new practices, novel opportunities – whole new and better ways of doing things, to benefit all

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’

Productive recidivists

Over 70% of offenders re-offend within one year!

Why is this?

Most prisoners are locked up for most of the day and not treated well by the officers which surely makes them worse than they were at the start, not better – in these Universities of Crime, they learn to despise authority, not learn a trade for when they’re released and that there’s better ways of living

According to Rod Aldridge, founder of Capita:

  • 66% of people going to prison have no job
  • 75% of people leaving prison have no job to go to
  • And 30% of them don’t even have a place to live

It’s not rocket science to see that, if they have no job, no job experience and nowhere to live, they have a major incentive to go back to offending – what options do they have?

As a result, some enlightened UK companies have set up schemes to train and employ offenders and thus give them a second chance – and they’ve found only 7% of those that take this opportunity re-offend, a huge benefit to society at large

Many other benefits also accrue to the employer organisations involved – Adrienne Selko has just reported in Industry Week about the same initiative taken in the USA

Nehemiah Manufacturing’s workforce comprises former felons, returning citizens as they are called, who are creating great results for the company

Richard Palmer, president of the company, wanted to provide jobs for people in Cincinnati who were unable to find them – the company’s mission is to rebuild the city of Cincinnati by giving people jobs and a “renewed hope for the future”

When he opened the doors, one of the first people who came to him looking for a job was a former felon – Palmer hired him immediately – it worked out so well that currently 90% of his workforce comprises returning citizens – and one important way they show they are welcome is to stop asking them about their past – they delay criminal background checks until later so that potential candidates are not immediately dismissed.

Palmer says: “The loyalty of these workers and their productivity is just amazing – it’s been a great business decision with a high rate of retention, which is especially important given the labour shortage:

  • They’re some of the hardest working people we’ve ever seen
  • In proving themselves, these employees become fiercely loyal, insistent on high quality, positive teamers who help each other, hard chargers who self-sacrifice for the success of all”

Offering second chance opportunities to returning citizens has now been going on for years in the USA – and with almost 700,000 people released from prison each year, it’s a very large pool of workers to fish in

Conclusions:

  • Clearly the upsides here are significant not only for employers and returning citizens involved but also society in general
  • The downside concern is the relatively small % of ‘no-hoper’ felons who have a long record of stealing or worse – if this is not known upfront, they may well abuse such altruism and spoil matters for all others

Catching the right fish

With globalisation, all organisations can fish for new recruits in the one big pond

But the most successful anglers are they who hire on merit, not in their own image, according to Tomas Chamorro-Premuzic, a professor of business psychology at Columbia University in his book Why Do So Many Incompetent Men Become Leaders

An article by Rosamund Urwin in The Times goes on to quote Tomas saying bosses need “data-driven assessment i.e. CVs, psychological tests and analysis of past performance” to identify potential winners who might be humble and understated in interviews compared with other self-aggrandising applicants

At present, most organisations tend to haul on-board the wrong candidates and then promote them up corporate ladders:

  • “Boss interviewers are not great at judging competence and can be unaware of interviewees’ limitations
  • Many can charm people initially but don’t make good bosses, being more prone to bullying and harassment, and resistant to negative feedback
  • They blame others for their mistakes and take credit for others’ achievements”

Hence survey after survey show a majority of employees believe they have a bad manager

Tomas says: “People get rewarded for sucking up when leadership should be about managing down – turning a bunch of people into a high-performing team – but bosses don’t care about people development, they’re more focused on politics and, sadly, this works for them”

One major hurdle, according to Tomas, is that most people think a good leader is overconfident, narcissistic, inspirational, even bullying – citing Steve Jobs and Philip Green as examples – when the qualities that make a great leader are humility, integrity and competence – virtues (he believes) which are more readily found in women like Angela Merkel – they lead in a more transformational way, are less likely to be absentee leaders and have more emotional intelligence

Tomas’s concludes with: “The people who are best at something tend to be very self-critical”

Customer measures needed

Once, supply of most goods and services people wanted to buy was limited – suppliers thus had the whip-hand – for example, Ford could offer their ‘Model T’ cars using the strap line “any colour so long as it’s black”

Those days are long gone

Mid 20’th century and on, competition between suppliers started to become serious – first nationally, then globally – seeing profits being made by a few vanguard suppliers, others quickly moved in to their markets, some with new and better ways to do things and offerings for customers

The result of all this competition between suppliers is that customers now determine what and how much they sell (except when the supplier is a public sector monopoly offering an essential service the public cannot do without)

Initially, price was their main criteria for making their buying decisions – but, in the 70s/ 80s, quality and then service levels offered soon grew to be equally as important to most customers

Value for money was what most sought – if the price was high, quality and service levels were expected to be high – pay for a five star hotel and expect Savoy or Ritz standards, for example – pay for a one star B&B and expect a good night’s sleep, clean linen and a tasty ‘full English’ breakfast – both would be deemed ‘good value for money’

Hence, all suppliers, given the star rating they target, need to know what rating their customers give to the price charged versus the quality and service levels received – and, if the quality and service levels are below ‘top box’, they should seek to identify those specific criteria (used by customers, not assumed by suppliers) where they’re judged not to have performed well – and put them right quickly before their sales suffer badly

And the only way suppliers can do this is by conducting regular surveys of a sample of their customers whilst being wary of the many pitfalls connected with doing this

Last, a new major buying criteria has recently become important to many customers, inevitably attracting yet another TLA (Three Letter Acronym) – this time it’s CSR (Corporate Social Responsibility)

More and more customers will avoid suppliers who apparently show no concern for human or animal welfare, dodge paying fair taxes, damage the environment or sell products which are bad for their customers in order to feather their own nests

To counter this possibility, some companies now make ‘ethical statements’ in their annual accounts – and Big Four accountancies such as PWC and KPMG now claim they can measure corporate reputations enabling them to identify where they’re wanting

P.S. There are many other more detailed customer measures possible (e.g. sales or profit per customer, % repeat business) but they all depend on a supplier getting the above cardinals right in the first place

Customers don’t measure up

Supplier organisations have two sorts of customers – external and internal:

  • External customers pay for the goods or services private or public sector organisations offer them – it’s their money alone which keeps businesses in business and public services alive, and pays every employee and shareholders dividends – they decide whether or not to buy or use products or services based on price, quality and service levels offered them
  • Internal customers are fellow-workers further ‘down-the-line’ who depend on you to supply them with raw materials, semi-finished goods or paperwork so they can complete their work – they want to be passed stuff which is ‘right-first-time, not faulty or late causing them extra work and delays which also increases costs

Given such importance, one would expect all organisations to closely monitor how satisfied their customers were with what they were being offered – but most don’t know such important details

Instead, they rely on measures of sales volume, value and trends plus their own internal views on how good they are – if they’re not negative, they assume all things must be hunky dory – hence, many are surprised when existing customers become ex-customers

To be fair:

  • Some survey their customers’ satisfaction levels, albeit most do this badly – too infrequent or too often, thus irritating customers – sample sizes and/ or methods used are unrepresentative or inadequate – hence, they rarely identify important areas where they’re going wrong
  • Some analyse customer complaints, returns and warranty claims but they’re usually half-hearted and little effort is put into making amends, thus missing a golden opportunity to convert unhappy customers into repeat sales – they can also suffer a double whammy here as unhappy customers usually tell more people about their bad experiences than happy ones do about theirs, so more potential sales are lost
  • Some count customer footfall and monitor their average total purchases

However, most organisations have no good idea what their customers really think about what is offered them

In addition, most don’t fully understand the nature of the demand for their services – they assume all demand is equally valuable

But much demand (e.g. output units, episodes, incidents) is repeat demand for the same good or service simply because the original demand was not met ‘right first time’ – goods or services provided were flawed in some way requiring extra costly time to put things right whilst earning no extra revenue or funding e.g. units having to be replaced or patients catching MRSA whilst a patient in hospital

In many organisations, such failure demand can be over 50% of their total, but few know it – and even fewer believe it when told

And the cost of such failure demand to the customers is never considered – e.g. the cost of their wasting time, suffering longer, having to cope with broken down units or making repeat visits to hospital for the convenience of consultants, not them

Conclusions:

  • The business mantra, nowadays is “Put Customers First”
  • Such words are easy to say, and even easier to ignore
  • What most organisations actually do is put themselves first – they look inwards, not outwards – and they see only what they want to see
  • Hence it’s no surprise when experts claim there to be a long long tail of underperforming organisations in ALL sectors

Waste murders productivity

Whilst few managers measure productivity well, even fewer measure their waste of outputs and costly inputs

Waste arises both internally and externally:

  • Internal waste = When things are not done RFT (Right First Time) and work is rejected or has to be reworked
  • External waste = When things are delivered to customers either not as ordered or not to their satisfaction, so extra costs are incurred for no extra revenue e.g. replacing returns, making second deliveries, dealing with customers more than once to sort out their problems/ queries, patients catching MRSA whilst in hospital being treated

Such waste can be hugely costly viz:

  • Analyse customer demand, especially on service organisations and one can find at least 50% and up to 90% of all customers’ contacts are repeats because their queries were not dealt with right first time
  • To save money, eight London hospitals outsourced thousands of letters to India to be typed from dictaphones, but it didn’t go too well:
    • ‘Eustachian tube malfunction’ became ‘Euston Station Tube malfunction’
    • ‘Below-knee amputation’ became ‘baloney amputation’
    • ‘Phlebitis, left leg’ became ‘flea bite his left leg

The result of such waste is lost sales, extra input resource costs and/ or investment in additional output capacity well before needed

So what are the key measures of waste needed:

  • A% = % Availability of an input resource e.g. % labour not off sick and available for work, % materials in stock, % plant ready to go
  • U% = % Utilisation of said resource e.g. % of total time when at work spent productively rather than sat idle or attending a pointless meeting, say
  • E% = % Efficiency e.g. % actual total good output produced (after rejects, rework or replacements) versus the maximum possible – its capacity – e.g. how fast or slow it worked

The waste multiplier then comes into play viz:

AUE% = % Total net output/ Maximum output possible


It usually gives most managers some very unwelcome surprises – for example:

  • If labour A% was 90%, U% 80% and E% 70%, then the multiplier AUE% would be a mere 50%
  • And if a machine A% was 95%, U% 40% and E% 80%, then the multiplier would be a miserable 30%

In both cases, which are optimistic for many organisations, managers would surely be prompted not only ‘to do something’ but also have a steer on where best to act for biggest effect

But most managers do not have this information – they don’t realise such lost potential is typical, not unusual

In the NHS, for example, managers forever say: “Everyone is working hard and long hours so more cannot be done unless we get more resources” – so the government finds billions more to fund these extra resources, otherwise votes will be lost – taxpayers thus have to pay many more taxes than needed – meanwhile ministers and their advisers dabble with more NHS reforms without understanding what’s really needed or possible

And all because they lack basic measures of the waste of existing resources

Current productivity fog

All managers need to get the most out of all costly input resources they employ:

  1. In the private sector, to beat their competition in meeting customers’ needs whilst minimising unit costs and maximising sales and profit margins
  2. In the public sector, to optimise the number and quality of services on offer

However, most managers do not measure productivity well – they have plenty of financial productivity measures, perhaps too many, but little else – the result is most of them are far from getting the most out of their existing input resources

Why so – why should simple ratios of outputs over inputs not be found everywhere?

Survey after survey produce the same results – managers think productivity is too difficult to measure, not a boardroom issue, not the main determinant of their financial success, relevant only to the shop-floor or someone else’s problem

At the same time, leading management organisations and business schools ignore the subject – there’s no productivity headings or focus on their websites, nor any courses offered on it either – a sure indicator of the true importance they attach to the subject

So, given this paucity of measures and lack of interest at the top, is it any wonder that current productivity growth in most organisations and nations is (apparently) flat-lining

A big change in management attitudes is urgently needed

And, for this to happen, six major failings with existing productivity measures need to be addressed:

  1. A partial, not total, productivity picture painted:
  • Valued outputs nowadays are not just sales volumes (cars or insurance policies, say) but quality and service level outcomes for customers that go with those sales – yet performance measures that cover the latter are as rare as hens’ teeth
  • Wasted outputs i.e. repairs or replacements for no extra revenue, say – are often included in total output figures
  • Costly inputs include labour, materials, capex and IT systems – however, labour volumes (hours or FTEs) are the only ones measured – labour quality (i.e. skills, experience, education levels, qualifications) can make a big difference to productivity levels but is ignored
  • Wasted inputs – the time and resources spent on work which was not right first time, say, are usually submerged in total input figures
  • Hence, most productivity measures quoted can be seriously flawed and offer only a fraction of the ‘big performance picture’ needed – as a result, many productivity problems and improvement opportunities pass by unseen

2. A lack of useful benchmarks:

  • External best practice information is usually only sought by better private sector companies – and rarely by any public sector unit, even though such information should be in the public domain and readily available to them
  • However, caution is needed before copying another firm’s best practices – there will always be differences preventing exact copying but knowing others do things differently with better results should make managers ask whether they could be doing as well
  • Most organisations have no idea what their overall output capacity is because of the variety of goods and/ or services they offer – this means they don’t know how much more they could do with the resources they’ve already got – as a result, many invest big money in extra capacity well before needed

3. A lack of regular, timely measures:

  • Important performance information is often produced quarterly yet a manager may need it weekly, say, for her to take appropriate action in good time

4. Few clear links down/ up to lower/ higher levels of management:

  • Managers cannot drill down their set of measures to identify problem causes – nor up and across to those of others and check on the impact of any proposed changes
  • Different management levels often use quite different performance measures, so they don’t talk the same language, so they don’t understand each others’ problems
  • There should be just one set of performance measures linking all managers to all levels

5. Too short a time horizon often used:

  • Some companies have to invest heavily upfront (e.g. oil wells, coal mines), make big money with stuff that’s easy to extract, then less and less per barrel or ton as extraction becomes more difficult until all peters out
  • In such cases, whole-life productivity measures are needed

6. Too much aggregation destroys value of information:

  • One cannot mix quite different outputs, or inputs, to calculate overall productivity levels unless they’re converted into cash
  • This aggregation problem increases the higher one goes in any organisation
  • It’s worse still at national level where official productivity measures have been described as ‘pointless and unusable’ – they spread misinformation, not knowledge

Conclusions:

  • Overall, productivity must be measured well if it is to be managed well
  • At present, few managers do this well – most are ‘flying blind’ and so not in good control
  • Managers need to make their decisions based on good performance data, not opinions
  • It’s at organisation level where most (80%?) national productivity improvement potential lies – and it’s managers, not workers, at that level who have the power to make the improvements necessary
  • But, to do this, they first need to know where, when and how to act

NHS targets have had their day

Lord Prior of Brampton is reported by The Times as saying: “NHS staff suffer from learned helplessness in a dysfunctional system”

So what prompted this mystifying statement?

A&E units are currently reporting their worst numbers of patients waiting longer than four hours, many on trolleys as no beds were available – the NHS Confederation of Managers says the system is “buckling under the strain of rising patient numbers”

Prior claims this is because targets, competition and a reliance on inspectors have led to a ‘disjointed system and demoralised staff’ – breaking up the NHS into autonomous hospitals has made ‘ driving an integrated strategy across the service almost impossible – you could not have designed something that had at its heart more dysfunction’

Chaotic organisation and overuse of targets has led to ‘a disempowered culture, a learned helplessness culture, a top-down looking upwards culture, a very hierarchical culture’ – targets which once worked well when waiting times were unacceptable ‘have had their day’

At present, hospital bosses are under such enormous pressure to hit their targets that there is now ‘widespread gaming of the system’ – frantic efforts are made to get patients out after three hours and 55 minutes waiting, but care stops once the target is missed

Hence, Prior seeks ways to address these cultural issues and bring back the vocation he remembers doctors and nurses once had viz:

  • Junior doctors would say ‘at the end of our day when we’re about to go home, we’d always walk back to A&E to lend a hand if there was a problem – now we go home’
  • When GPs and nurses qualified for their maximum pension, most would stay on for at least another two years – now they simply say: “I’m going”

The issue is how to regain that engaged spirit ‘which would take care of so many of the NHS’s other problems’

But Taj Hassan, president of the Royal College of Emergency Medicine, offers a cautionary note – “If policymakers and governments choose to scrap these targets, they must be held accountable for any impact on patient safety and the added risk of harm or avoidable death”

Conclusions:

Targets still have a role to play in the NHS – the issue is not whether they’re needed (some are, some are not) but how the important few are used

A wholesale NHS management culture change is indeed needed – targets should never be imposed from ‘on-high’ and managers told to ‘get on with it (or else)’ – they need to agree their targets first, taking account of the resources available to them, and then be left alone to figure out how best to meet them – words like challenge, reward, empowerment and accountability should replace the current central control, hit-squads, penalties and micro-meddling that many hospital bosses fear at present

Zipf’s Law

Zipf’s law is a mysterious, empirical law – it’s also linked to Pareto’s rule:

  • It suggests limits on the size of companies and their share of markets
  • According to Annalee Newitz, the editor of i09, in 1949 linguist George Zipf noticed that people used a very small number of words most of the time – we minimise what we need to convey our messages
  • In particular, Zipf found that a pattern emerges – the most popular word is used twice as often as the second most popular, three times as often as the third, and so on
  • A mere 135 words cover 50% of all the words we ever use on a regular basis
  • The most popular three words are:
    • The = 7% of occurrences
    • And = 3.5%
    • Of = 2.3%
  • Zipf’s law must surely offer a clue as to how Alan Turing and his Bletchley Park team were able to break the Enigma code – although I’m guessing here
  • Zipf then found his law also applied elsewhere:
    • To income and wealth distributions in any given country, where the richest have twice as much money as the next, and so on – much as Pareto observed many years before him
    • To the size of cities, where the city with the largest population in any country is generally twice as large as the next biggest, etc. – this only applies where cities are economically integrated, with common language, laws and institutions, as in any nation – it does not apply to any group of nations like the EU
    • To the size of firms in any sector – the biggest firm is twice the size of the next one, three times the size of the next, and so on – hence, it’s inevitable to end up with a group of Big 4, 5 or 6 companies in any sector
  • Other interesting applications include:
    • Books borrowed from libraries
    • Web sites visited
    • Earthquake sizes
  • Quite why the pattern is followed so closely is not understood
  • However, it offers useful predictability for economists and businessmen alike

Wealth gains and distribution

US Fed Chairman Jerome Powell believes our two greatest challenges for the next decade are ‘the widening wealth gap and sluggish productivity’

But Lawrence Fuller, in an article for Seeking Alpha, claims the Fed’s attempts to create a wealth effect by inflating the value of financial assets has mostly benefited the top 10%, and even more so, the top 1% of the population

New found wealth has not trickled down to the middle classes in the form of wage gains – according to data from the Congressional Budget Office, income gains since 1980 are as follows:

  • 242% – Top 1%
  • 79% – Next 19%
  • 78% – Middle 60%
  • 46% – Bottom 20%

Given the above, one might have thought a surge in investment in plant, equipment and employees would follow

Not so

Instead, corporations have returned capital to shareholders via stock buybacks and dividends – some even took advantage of very low interest rates to borrow capital to fund them

This simply filled the pockets of managers and shareholders but did little for productivity improvement and employees’ wages and their quality of living – it also reduced the latter’s demand for more goods and services and so the revenue and earnings of those same corporations

Hence the wealth moat between the very wealthy and the rest has been widening over the last few decades

However, Fuller expects ‘wealth disparity and income inequality to revert to the mean’ over the coming decade:

  • Current trends are not sustainable 
  • Economies should work for everyone
  • Strong headwinds are expected as capital shifts from the ownership to working class

“Our economy cannot be considered healthy when 40% of adults can’t come up with $400 in the case of an emergency”

4 day weeks to boost productivity

new report by Autonomy – a thinktank focusing on the future of work – argues that a shorter working week should be a central pillar of our economic future.

They say calls for a shorter working week have gathered pace in recent years, with the TUC, the Green partylarge and small unions and now the shadow chancellor, John McDonnelljoining the chorus.

Why so?

Because we are working longer days but for stagnant wages and receding state pensions – and some of the most productive economies in the world work far fewer hours collectively than the average UK worker.

They say productivity relies not just on the sheer number of hours put in but on the wellbeing of the workforce – as well as investment in labour-saving technology.

At present, they claim heavy workloads, work-related stress and anxiety are costing millions each year, with one in four sick days being lost as a direct result of workload pressures – shorter working weeks and greater worker control over working time would mean fewer sick absences, fewer in-work accidents and higher motivation on the job – all of which would be good for business too.

Hence the Wellcome Trust has just announced plans to trial a four-day week without a loss in pay this year, possibly making it the largest company to do so anywhere.

In this same vein, at the recent World Economic Forum (WEF) in Davos, Gitura Mwaura says the world was urged to embrace the four-day working week, busting the notion that long working hours lead to more productivity – a shorter working week not only improves productivity by some 20% but has an overall effect on the well-being and work satisfaction of employees

Examples put forward include:

  • South Korea which ranks near the bottom of OECD (Organisation for Economic Co-operation and Development) countries for labour productivity despite having a culture of working very long hours
  • Greece which has one of the longest working weeks but comes out bottom in the OECD’s measure of GDP per hour worked
  • And Japan which also has a culture of long working hours but emerges bottom of any G7 productivity list – hence, they are now deliberately cutting down on working hours, including overtime, to alter this position

However, other studies show there to be no correlation between long working hours and productivity — Germany is said to be more productive but works fewer hours on average than the UK

And in Sweden the WEF observes that “although employees report an improved quality of life, with less stress and more time to spend with their families, it can also be an expensive experiment for some businesses which have to hire extra workers to make up for the shortfall in hours”

Aidan Harper, the Autonomy report’s editor, concludes:

  • The past century has shown us that automation technologies have more often than not been introduced by employers as a way of simply maximising productivity without sharing the surplus time and/ or the profits with employees
  • The proceeds of automation should be shared evenly — in the form of a working time reduction
  • Machines should liberate us from work, not subject us to ever-increasing inequality
  • But few suggest workers should enjoy any of the benefits

This mindset clearly cannot continue

Companies would do well to consider a report by Minda Zetlin, co-author of The Geek, in an article for Inc. magazine on a company moving to a much shorter working week

Could you run your company just as well if employees worked a five-hour workday instead of an eightt-hour one?

If Australian financial services company Collins SBA is anything to go by, you probably could. And you’d benefit from better work-life balance, higher employee morale, and improved recruiting and retention. Your staff would take fewer sick days, and productivity would likely rise.

It may all sound too good to be true, but Collins SBA has been offering its 35 employees the opportunity to quit work between 1 and 2 p.m. for two years now, and it’s been a resounding success, managing director Jonathan Elliot told TNW. The shortened workday came about because the company, like all companies, was struggling to recruit the talent it needed in a very tight labor market. At the same time, Collins’s wife became ill with cancer. She needed surgery and chemotherapy and went through a long recovery process. The couple also had a 6-month-old daughter, which meant that Elliot needed to spend much more time at home taking care of them both than he ever had before.

He learned to be incredibly efficient. He stopped spending time chit-chatting with colleagues at work. He cut out unnecessary meetings. “I just focused on work and got home in time to look after my family,” he said. 

When his wife got better, Elliot was free to go back to working longer hours. That’s when it struck him that he didn’t really need to. By working shorter hours more efficiently and cutting out meetings and lunches, he’d been able to get the same amount of work done that he’d previously been doing during a full workday. And so, partly inspired by Tower Paddle Boards, which cut its workday to five hours without sacrificing any productivity, Elliot pitched his colleagues and shareholders on trying out the new schedule throughout the company. They agreed.

Elliot didn’t simply declare that everyone could now work five-hour days. The new workday came with a few new rules. First, employees must arrive between 8 and 9 a.m. if they want to leave between 1 and 2. Second, their work responsibilities remain the same, and they must get their work done, even if it takes more than five hours. Third, unless specifically approved, they can’t have any personal appointments during their workday. And finally–of course–they shouldn’t go out for coffee or lunch. Instead, Collins SBA provides coffee and healthy snacks in the office. The company also now holds no one-hour meetings unless there’s absolutely no choice. And all employees have gotten training to help them manage their email more efficiently.

Can Collins SBA employees really get done in five hours everything that they were previously doing in eight? Well, no. Most employees have some workdays that last five hours and others that last six or seven, Elliot told TNW. But they don’t often work 40-hour weeks, or even 38 hours as specified in their contracts. In the end, what Collins SBA offers employees is really a flexible work schedule and the opportunity to leave work after five hours if they’ve finished their tasks for the day. In essence, it’s a powerful motivator to be more efficient, and to home in on the 20 percent of effort that yields 80 percent of results, as the Pareto Principle says. There has also been a 12 percent reduction in sick leave.

Not everyone loves the new schedule. Some employees left because of it. Elliot says the idea has proven surprisingly polarizing. And while most clients have supported the idea, a few have blamed the shorter workday when they were unhappy over other issues. However, this didn’t happen until the change had been widely reported in the press–before that, clients hadn’t noticed it. That in itself proves the new workday is a success, Elliot said. “If we can implement this covertly, we are doing it right.”

As you might expect, those same press accounts caught the attention of prospective employees. Elliot says the company’s candidate pool is bigger than it was, and some candidates are contacting the company to inquire about working there even when they weren’t responding to a specific ad for a job.

It’s also helping the company screen out some candidates who would likely make unproductive employees. “If a job candidate brings up our five-hour workday very early on, that’s a red flag,” Elliot says.

Productivity tops Brexit

An article by Peter Barker, Gui Tao and Xinhua – www.xinhuanet.com

Improving productivity, instead of the Brexit issue, is the primary task facing the British economy at the moment, says renowned British economist Jim O’Neill

“The UK being in or out of the EU (European Union) is not the most important thing facing our economic future, and I strongly believe that,” O’Neill, chairman of Chatham House think tank in London, told Xinhua in a recent exclusive interview

For O’Neill, Brexit is very much a short-term problem and he has a longer vision when he looks at economic issues. “Doing something about our productivity performance and our geographic inequality and our inter-generational inequality, these things are way more important (than Brexit),” he says

Britain has suffered a slump in its productivity growth since the financial crisis – (according to official, albeit highly suspect, national data) this slowdown has been more dramatic than that of any major Western economy, with annual growth in productivity falling from an average annual rate of about 2.3 percent before the financial crisis to 0.4 percent in the past decade

“So, even a hard Brexit, which would be very bad at first, isn’t as important as those things. The contradictory part is — why the hell would we deliberately make our productivity challenge even worse by choosing to have no trade arrangements with the single biggest economic trading zone in the world?”

“It doesn’t really make a lot of sense.”

CHALLENGE TO INDUSTRY

O’Neill cited his own industry of finance and the successful industry of auto assembly as areas where the economy could suffer after Brexit because there could be greater friction and costs to both trade and imports, which would eat into businesses’ profit margins.

In 2017, the British auto industry built 1.3 million cars for export, accounting for 12.8 percent of total British exports, according to motor industry statistics.

“The auto industry, which in modern Britain is arguably the most successful of any traditional industry, produces more cars today than 40 years ago — it would be decimated under World Trade Organization (WTO) rules,” O’Neill says

“Some of the world’s most productive auto plants are in the UK, and if we go out under WTO rules they won’t stay that way because the profit margins are too thin — I’m sure there are many other industries where that’s true.”

“My old industry of finance would have some interesting challenges,” O’Neill adds, and challenges the idea that Britain could leave the EU with a managed no-deal.

ISSUES OF GLOBALIZATION, LEFT-BEHIND PEOPLE

“There are a lot of people in the Western world who don’t believe, because of the circumstances they’ve lived in, that the past 30 years have helped them at all,” O’Neill says

“When our Chancellor of the Exchequer often says ‘we didn’t vote to make ourselves poorer,’ actually a lot of people that are poor in the UK might have voted to make themselves poorer, because they want to shake up the system.”

“They don’t really understand the degree of sacrifice they might make, but they don’t mind sacrificing growth in the UK, because they’ve not benefited from (it) anyhow,” he added.

“There’s a commonality with this (thinking) in the U.S., there’s some commonality of it in many parts of Europe, and it is clear that — as fantastic as globalization has been for China and for many other places, and for the elite world that I’ve lived through — there’s a lot of lower-income, working people that have not benefited much from the past 30 years, and it’s easy to blame globalization.”

P.S. Sadly, the powerhouse thinker Lord Jim ignores the fact that many Brexiteers voted to leave, not from a misunderstanding of the economic/ productivity implications as trotted out above but for:

  • Control – over immigration
  • Control – over the laws we live and work by
  • Control – over who rules us – better our second rate Brits than third rate unknown foreigners with Germany driving them from the back seat
  • Control – over who we can trade with, worldwide, and how

And as for making no sense ‘having no trade arrangements with the EU’:

  • The EU market is stagnating whilst the rest of the world (RoW) is growing, rapidly is many parts – however, the UK is currently not allowed to address RoW markets separately
  • The UK exports less than 10% of its GDP to the EU, not 50% say, so it will not be catastrophic, overall, if this % is dented – and as the EU exports more to the UK than we do to them, self-interest on both sides will ensure most of this trade will continue somehow
  • In the short term, there may be import supply problems for some sectors – but that may well encourage many UK start-ups to replace some of these imports  and so be good for us in the long term
  • The EU is essentially a ‘rich members club’ which insulates itself from RoW competition by a mix of tariffs and trade agreements so members become richer still – such protectionism is not only bad for EU (and UK) productivity but also morally abhorrent for putting up barriers to other nations, especially poorer nations, seeking to better themselves and so widening, not closing, prosperity gaps

Clusters need roads

An article by Maria Machancoses,  a director at Midlands Connectvestment, is fully reproduced below

For centuries, good roads have influenced the way we live, work and trade

As a nation that makes over 80% of journeys by road, and whose population is forecast to grow to 75m by 2050, investing in our ageing infrastructure is rightly at the top of the agenda.

Rather than developing proposals in isolation, roads investment is now recognised as a boost to productivity and a catalyst for regeneration.

With this in mind, economic road corridor approaches to investment, new central government spending pots and continual digital innovation are set to take centre stage

Economic corridors – Clusters

The need for the UK to forge a new place for itself in a post-Brexit world and strengthen both domestic and global market access has seen the re-emergence of the corridor approach to economic development.

While corridor-led schemes are prevailing in places like Singapore, India, China and Pakistan, ground-breaking strategic proposals are also being proposed here in the UK. They take encouragement from the continued success of the M4 corridor’s so-called ‘Silicon Alley’, the largest tech cluster in the UK outside London, turning over £10bn each year.

Plans for a London-Stansted-Cambridge corridor, a Cambridge-Milton Keynes-Oxford trade highway and Midlands Connect’s own calls for urgent, co-ordinated development along the length of the A46 are all emblematic of this trend.

By linking economic centres to each other and the rest of the UK, corridor development schemes widen access to labour pools, boost business productivity and increase the reliability and resilience of the network.

Promoting nationwide connectivity and collaboration is essential if we’re to address regional inequalities and rebalance our national economy.

Hence a Major Road Network (MRN) should be formally established by the government, following an indicative funding commitment of up to £3.5bn from 2020-2025.

Creating an additional tier of roads between the Strategic Road Network, managed and maintained by Highways England, and local authority roads, Midlands Connect and other sub-national transport bodies have called for greater influence over where this pot of money is spent, to ensure it draws on regional expertise and prioritises schemes with the highest potential for economic growth.

However, MRN funding pales into relative insignificance when compared to the second Road Investment Strategy pot – RIS2 – which is worth over £25bn. Where, when and how this will be allocated to both the delivery of regional priorities and the development of new projects, could be the most important event of the near future

Digital infrastructure

It is increasingly clear that we cannot address the mobility challenges of the future with construction alone. The greater availability of data provides us with new opportunities to better use our existing infrastructure and build networks fit for the future.

The increased uptake of electric vehicles (EVs) and roll-out of 5G networks will change the way we plan, develop and improve road networks in the coming year and beyond.

EVs aside, expect to see an acceleration in the testing of connected and autonomous vehicles and HGV platooning as 5G connectivity and the internet of things continue to revolutionise the way we travel.

As well as incorporating traditional charging points infrastructure into transport plans, we will also see further consideration of more radical technologies such as electric charging lanes, which are already in use in Sweden.

The future of our road infrastructure is inexorably linked to economic regeneration, emerging technologies and new government funding strategies.

As corridor approaches pave the way for enhanced inter-regional and international connectivity, the UK is well placed to become a more balanced, productive and innovative society

Current knowledge levels

Many, perhaps most, developed nation companies are brainwork companies nowadays i.e. at least 33% of their employees have degrees or equivalent

Clearly, all top jobs require best brains/ problem solvers – there’s little routine work for them – it’s their ideas, decisions, tactics and plans, actions and people skills that are needed most

But the same logic now applies to the majority of workforces – most jobs require more brain than brawnpower – in addition, they increasingly require an interaction with and use of ICT systems for them to do their jobs well

This means perhaps less than 20% of all jobs require mostly brawnpower – simple instructions must be followed – little knowledge/ skills/ experience and so training or experience is needed

Hence, some 80% of any developed nation’s workforce relies on brainpower and considerable training to do their jobs well

But training in what?

At present all UK kids are forced to go to primary and then secondary schools to learn the same range of basic subjects up to age 15:

  • Many then leave either to earn a living or attend some apprenticeship course – the former usually find employment opportunities and pay levels for the unskilled are meagre, the latter are (currently) limited in choice and made to feel second-rate versus any degree course
  • Most that stay on to their sixth form have to choose between studying arts or sciences, but not both
  • And most that go on to university have to further specialise, their choice of subjects usually made on the basis of what they like and/ or are ‘good at’
  • Throughout this whole process, ‘careers advisers’ might get involved but, in my experience, their inputs are either useless or worse
  • Nor do the kids get any significant nudges from either government or industry when choosing what to study

The end result is UK kids emerge into the world of work having cost a fortune being educated, whatever the level, but not knowing much of what they need to know

Is it any wonder businesses forever complain of a mismatch between skills available to them and those they need?

And that’s not the only problem nowadays – whilst many UK universities are ranked among the best in the world, there has been a huge expansion in their total number – this has led to a dilution of degree standards which is infecting the whole tertiary system viz:

  • Given students are universities’ customers, many choose where to apply (if not a top university) partly based on the likelihood of being marked well – hence most universities now award first or 2.1 degrees to well over 50% of their customers
  • Many lowly-ranked UK universities are struggling to attract sufficient numbers of students – aka income – to cover their costs and so are lowering their entry standards, even greatly increasing unconditional offers to poorly performing applicants, which has obvious knock-on effects later on

The inevitable result is that many employers are now strongly biassed towards graduates from the ‘top ten’ or Russell Group universities – hence a first from a tin-pot university may only lead to a life of shelf stacking

A major sieving of the long tail of UK universities is thus needed, and soon, before too many kids rack up too much student loan debt and have their dreams shattered

What’s needed is a raft of technical apprentice colleges, but call them something grand to stop people looking down on them – as per MIT (Massachusetts Institute of Technology) offering courses up to Bachelor and Master degree level in skills not only business but the general public desperately need i.e. not only engineers and computer scientists but electricians and plumbers:

  • A start has indeed been made with many more apprenticeships on offer
  • However, in most people’s opinion, the very word ‘apprenticeship’ downgrades the value of current courses on offer versus any degree
  • And take-up of these courses has also been disappointing to date

Worst of all, there’s still no clear steerage or incentives from business or government for kids to obtain the skills the nation most needs

And the above ‘training gaps’ only relate to kids at the start of their careers – delve into the training most companies offer their employees after their start and the picture is equally pitiful:

  • Some have formalised induction programmes – most are superficial at best
  • Many view training as a few days junket at the expense of the firm, and no use to anyone afterwards
  • The more senior you are, in the West, the less the training on offer despite the rapid changes ongoing these days

Yet most staff at all levels are usually keen to upskill themselves – and they look to their employers to help them do this – however, many companies don’t recognise that employee training should be good for them too by helping their employees be more productive

Overall, companies should thus take note of surveys that show those with formalised training and workshops have at least twice the income per employee compared to the rest – they also enjoy big increases in productivity and sales whilst reducing stress and attrition

CONCLUSION

At present, there are training pot-holes all over the national road to increased productivity and prosperity – and there seems to be no concerted effort by those in power towards filling them in properly

Knowledge measures needed

Management guru Peter Drucker once said: “In the knowledge economy, everyone is a volunteer, but we have trained our managers to manage conscripts” – he might have added that managers act this way because they lack the measures and understanding needed to maximise the knowledge productivity of their teams

It’s another productivity gap afflicting most organisations and nations

Yet, according to Thomas Stewart in The Wealth of Knowledge: “Knowledge is the most important factor in production (business) and knowledge assets the most powerful producers of wealth – even your toothpaste is more the product of knowledge than any other input resource because R&D and marketing costs comprise more than 50% of its total cost”

Winning companies nowadays are not just cash-rich but corporate-knowledge-rich too – many winners are even ‘tangible-assets-poor’

Corporate knowledge (K) includes:

  • Designs, patents, formulae, copyrights, trademarks
  • Brand names
  • Customer contacts
  • Process knowhow, ‘best practice’ knowhow, learning curve experience i.e. knowing not only what works but what does not
  • People skills and experience

Corporate knowledge (K) is thus said to be the sum of everything everybody in a company knows that gives it a competitive edge (aka a large moat) – and all held either ‘in files’ or ‘in heads’

So what’s K for?

It enables organisations:

  • To invent – to add to or replace existing offerings
  • To innovate – to improve existing offerings
  • To control operations and minimise unit costs
  • To increase output volume, quality and/ or service levels

Hence it’s crazy not to be able to manage and control such a powerful and valuable input resource

To do this, managers first need some indicators which show their teams’ actual K position – at present, most have little idea of where they’re falling short, by how much or the potential they’re ignoring

The least they need are subjective assessments of the availability, utilisation and efficiency of use of the K within their walls viz:

  • KA% = K Availability % = % Actual K available/ Total K needed:
    • ‘In heads’ = % assessment of the actual skills, qualifications and experience within a team versus that needed
    • ‘In files’ = % assessment of the actual important K recorded rather than being resident solely in heads and thus liable to be lost if those heads just ‘walk out the door’ – BP (Best Practice) databases are rarely maintained yet are vital in, for example, the public sector
    • ‘Accessibility’ = An assessment of the % of K resident in heads or files which is readily accessible by others in the team
  • KU% = K Utilisation % = % K used by others/ Actual K available
    • % of K in team heads used by others – team members can be unaware of what others in-house know – they need to know who are champions in specific areas who can be spoken to – and there are few mechanisms to encourage team members to talk to each other and exchange K – some hoard specific K believing ‘knowledge is power’ but organisations need to tear down such K silos
    • % of K in team files used by others – at present, wheels keep being re-invented rather than improved upon
    • % of K outside the team but within corporate walls, whether held in heads or files, used by the team – this requires some form of taxonomy, an information classification and tagging system, to make K easily findable and facilitate sharing
  • KE% = K Efficiency % = % Operational efficiency/ Maximum 100
    • aka Kleverage = How effectively K is used
    • An overall % rating assessment of current products/ services, market share, customer satisfaction levels and key processes reflecting their scope for improvement

Such subjective measurements, if agreed by a group of internal managers rather than just the manager concerned, would not need to be deadly accurate – you don’t need to know someone’s precise weight to know if they’re fat or not

However, the K review process of peer-discussions first followed by peer-agreed results would force any manager to consider her team’s actual K position more than ever before – and thus be more likely to identify where and when big changes were needed to benefit both the team and the organisation

For example, if a team’s results were KAUE% = 80% x 50% x 70% = 28% (an indication of the waste of K ongoing) then clearly ‘something must be done’ – probably by first addressing KU% and the need to share in-house knowledge better

Aggregation hides info needed

Current measures of productivity become less and less useful the higher the level they go:

  • Aggregation increasingly blurs the performance picture
  • Apples get mixed with pears
  • Specific inputs used for specific outputs and outcomes get lost in the mix

At national level, this aggregation problem is at its worst, compounded by much output and most input being uncounted or uncountable rendering official statistics useless for managing the economy and meaningless for any manager struggling within it

At organisation level, different outputs in the private sector can be counted either separately or together if converted into cash

However, the latter is not possible in the public sector where outputs (of most services) are provided free at the point of delivery and so have no price attached – hence official statisticians employ estimates and assumptions to complete their calculations, thereby introducing considerable errors which further blur the picture

And, in all sectors, costly inputs counted are confined to volumes of labour (hours or FTE numbers being easily measurable) whilst quality of that labour (skill levels, experience, morale), raw materials, SFGs (semi-finished goods), capital investments, IT systems and corporate knowledge are all ignored

The result is most national productivity figures cannot be trusted for an ‘accurate fix’ on the current national position, nor trends being followed, nor relative productivity gaps with other nations

Dare to claim this in public and the only credible defence one hears is: “They’re the best and only measures we have”

One response heard is: “If that is so, then ignore them – better to stick your finger in the air and just hope”

We say: “Surely it is not beyond the wit of man to find a set of measures useful to those on any bridge which helps them avoid rocks ahead, take advantage of wind-shifts and compete with the rest of the fleet”

CONCLUSIONS:

  • Officials should accept that, at the macro level, it’s impossible to measure productivity in any useful way
  • What ministers at national level and managers at organisation level need is first, an alarm bell system to warn of dangers and opportunities ahead – then a framework of measures enabling them to drill down to levels where productivity measures are meaningful and useful
  • Only then, would ‘officers on watch’ have a suite of productivity measures which put them in good control for navigating their ships safely

 

UK productivity gap half-explained?

According to Philip Aldrick, Economics Editor of The Times, Britain’s dismal productivity gap with much of the developed world is due not only to lack of investment, bad management and low interest rates as previously thought

Another significant causal factor has been found

The UK’s ONS – Office for National Statistics – asked the Paris-based OECD – Organisation for Economic Cooperation and Development – to look into the consistency of national data produced by 40 different countries and they found ‘the maths used leads to misleading results’

It turns out there are differences in the adjustment of official figures used to calculate hours worked and employment levels – different countries make different adjustments for their self-employed, overseas workers, prison workers and even drug traffickers and sex workers – and for workers’ tendency to underestimate holiday time taken

For example, France marks down employees’ reported hours by nearly 20%

Hence, comparisons of national labour productivity levels – national output (GDP) divided by national hours worked – end up being ‘apples with pears’ comparisons

If the UK made the same sorts of adjustments, it is estimated their labour productivity would increase by 10%

And actual labour productivity gaps between the UK and France, Germany and the USA would be much smaller than officially thought viz:

     . 16%, not 24%, less than USA

     . 14%, not 22%, less than Germany

     . 11%, not 19%, less than France

So, whilst the finding of these errors does not explain away the apparent productivity gaps between the UK and other developed nations, nor cover the errors that abound when assembling all national productivity data, it does suggest things may not be quite as bad as once thought, at least in the UK 

So let’s leave the last words to Richard Heys, deputy chief economist at the ONS: “This research reveals some striking differences in the way different countries estimate the amount of work taking place – however, they don’t explain why productivity growth has been so stubbornly low for so long”

     . 

Work hard or work well?

Many say the secret for a good life is ‘work hard and play hard’

Leila Hock, in an article for Career Contessa, disagrees – ‘work hard’ apparently “makes my eyes roll a little”

She believes we’ve become too preoccupied with “the grind” and it’s actually bringing us down – “It has a negative effect on productivity”

When people say they’re working hard they mean they’re putting a lot of time in – this mindset is because our economies once hinged on time:

  • Workers ran machines or performed rote tasks, and those machines and tasks would give a pretty static output per hour
  • Occasionally, someone would find a way to increase output per time unit but, usually, more time spent led to more productivity

 

Nowadays, developed economies have transformed into knowledge economies, and they require brainworkers/ thinkers to produce new/ better ideas, decisions and results

The problem is that appropriate performance measures to monitor their progress at work have not been developed – instead, the old familiar industrial-age measures and thinking continue to be used for the new economies

People still tie time to the value of work, not least because measuring time is easy – it’s a number and numbers can be easily compared

Hence, when most managers see someone arriving early at the office, leaving late and responding to emails at all hours of the night, they usually think said employee is committed to her work and trying hard – why would she spend all that time that way otherwise?

What most managers need to do is start measuring the value of employees’ work – and that means truly understanding why they were hired and what they were required to produce – and it’s not just the quantity but the quality of their output that now matters

Few managers do this at present, however, not least because it would take considerable time – and as hours input wins their attention more than productive work, such an exercise is deemed ‘a waste of valuable time’

Consider also the professions that still bill clients solely by their time inputs rather than ways which reflect quantifiable results achieved – and who value their employees by the hours/ days billed regardless of the value obtained by the clients – for example:

  • Lawyers
  • Management consultants
  • Accountants
  • Marketing and PR consultants

 

Leila ends up saying that, instead of such archaic thinking, what’s needed nowadays is a focus on ‘working smarter, not harder’ for the benefit of both customers and employees

Conclusions:

  • Success is no longer determined by hard work and long hours
  • Success comes from using time productively and being effective
  • That requires a focus on what one is trying to accomplish each day and week
  • And, once completed satisfactorily at least, one should relax

All nations need a National Productivity Centre

An article by Lalin Fernandopulle in Sri Lanka’s Sunday Observer, headed ‘Productivity policy vital for economic growth’, promotes the worth of all nations having a National Productivity Organisation 

Sri Lanka is the only APO (Asian Productivity Organisation) member country which does not have an NPO (National Productivity Organisation).

Company director Sunil Wijesinghe says: “Setting up a fully-fledged stand-alone NPO is the way forward for industrial and overall economic growth in Sri Lanka”

He said their National Productivity Secretariat (NPS) is still only a unit under a Ministry while in Singapore and Malaysia they are powerful statutory bodies.

The USA was the most productive nation at the end of the World War 2 – Japan realised Asian countries lagged behind in economic growth and initiated the Asian Productivity Organisation (APO) in 1961 with Asian member countries – Sri Lanka too joined, albeit a few years later

Most other Asian countries had open economies at that time, and developed their productivity programmes fast

For example, the Japanese Government carried out a massive program to inculcate good productivity habits and promote productivity techniques and practices in the 1960s through radio and TV programmes but later it was the private sector that carried it forward through the Japanese Union of Scientists and Engineers (JUSE) and the Japan Productivity Centre for Socio Economic Development (JPC-SED).

At the start of the National Productivity decade in 1996 Sri Lanka started emulating Singapore but later the focus changed.

Singapore claims their productivity programmes have helped economic growth substantially – they had the highest patronage with former Prime Minister Lee Kuan Yew initiating the programme when the annual productivity theme was launched each year – the initial focus of the program was to make government institutions more productive.

A few Sri Lankan enterprises have adopted good productivity practices while others lag. We need a massive re-launch of productivity enhancing programmes in Sri Lanka.

Not only industrial growth but also overall economic growth can be influenced by productivity because productivity improvement techniques can be applied not only in factories but also in offices, plantations, schools, government offices and even homes

Sri Lanka lags behind in industrial growth since economic policies are not consistent – frequent policy changes wreak havoc on the strategies of private companies.

What is needed is for policy makers to prepare a comprehensive medium-term strategic economic plan, in a similar way to strategic corporate plans – Singapore prepared a Strategic Economic Plan in 1990 and stuck to it.

Thereafter we need to communicate it to the people using tried and tested change management programmes so that the population buys in to it.

The ideal would be economic policy stability even with changes of government.

During a productivity study tour to Singapore in the 1980s, and following a briefing at the then Singapore Productivity Board, one of our Sri Lankan colleagues visited the wash room and, having seen a notice there which said “20 dollar fine if you don’t flush”, came back and asked the Director conducting the briefing how they could identify who the culprit is. His response was: “How come only Sri Lankan visitors ask this question? The notice in the toilet is a mere deterrent,” he said.

He said having observed the happenings in Sri Lanka, Singaporeans believe that Sri Lankans are overly legalistic, and this hampers progress.

Today every newspaper, radio and TV channel gives pride of place to (anything other than) coverage of management, productivity, or economics

We should focus on building up our economy and improving the productivity of our enterprises

And setting up a properly resourced NPO would be a good start

N.B. The same void exists in the UK where there is no well resourced/ well-known UKPC – Why?

UK industrial strategy

The UK government’s ‘Industrial Strategy’ for making the UK more competitive and the economy better-balanced essentially involves increasing R&D investment and workers’ skills

It considers five areas for productivity improvement – Ideas, People, Infrastructure, Places and Business environment – and recognises four grand challenges:

  • Artificial intelligence and machine learning
  • Clean growth
  • Future mobility
  • Ageing society

In particular, UK Prime Minister Theresa May has since confirmed her commitment to raise R&D spending to 2.4 % of our national income – an increase of £22 bn over the next 12 years when it increased by just £6.6bn over the last 12 – her aim is to help the UK become “the ideas factory of the future”

So is the strategy working?
The biggest challenges for smaller (SME) manufacturers are poor cash flow, high energy costs, reduced margins, competition from Asia, lack of skills and an ageing workforce i.e. most not listed in the grand strategy
So what help is on offer to these vitally important SMEs?
  • The HVMC – High Value Manufacturing Catapult:
    • The HVMC is a network of seven centres who work with industries, large and small, to prove and de-risk technologies that can be adopted in their own factories to improve productivity and quality
    • It’s funded through the BEIS – Business, Energy and Industrial Strategy Department – and Innovate UK – the national innovation agency
    • It’s tasked with engaging SMEs and measuring the impact of the Catapult on improving SME competitiveness
  • The ‘Made Smarter’ programme, led by Siemens CEO  Jürgen Maier:
    • The programme facilitates the adoption of digital manufacturing technologies such as robotics and automation, augmented and virtual reality, artificial intelligence and machine learning
    • The aim is to unlock big improvements in productivity
    • The approach is to link with existing growth hubs
    • However, some say that while it may eliminate duplication, its success will depend on getting people in post who understand industrial digitalisation and the challenges of change-averse business cultures
  • And, only recently, an independent council has been set up to oversee the delivery of the ‘Industrial Strategy’, headed by Andy Haldane, chief economist at the Bank of England:
    • Haldane is not a manufacturer but qualifies, apparently, because he’s ‘familiar with monitoring government performance on key economic indicators’
    • The council will scrutinise R&D spend, seek to keep the UK economy on track and assess whether the strategy’s aims are being delivered
So the UK might be said to have a productivity plan – expert advisers are in place, universities are being encouraged to join in, professional monitors are watching key indicators, billions have been allocatedWhat could possibly go wrong?

Well quite a lot, actually

For a start, this UK plan addresses a mere 15% of its total economy i.e. the manufacturing sector alone

And David Parker, New Zealand’s Minister for Trade, might well take a different tack – he recently outlined their plan to boost productivity – ‘creating more from our resources while staying within environmental limits’ – and so lift the standard of living of all Kiwis – a suite of sector-led Industry Transformation Plans they copied from Singapore, each one unique to the sector and the actions required, including investment, innovation and skills development:

  • The key industries chosen are agritech, digital technologies, food and beverage, forestry and wood processing
  • They bring together two of NZ’s key competitive advantages – sectoral expertise and the educated workforce
  • The overriding need is to move from volume to value in these sectors
  • There has been too little investment in growing their productive enterprises for competitive advantage

Parker says:

  • “NZ is facing new challenges and opportunities due to technology – the nature of work is being profoundly affected by AI (Artificial Intelligence) and automation, but this is also creating opportunities for businesses who innovate and develop their businesses using such technology”
  • “The higher the productivity of a country, the higher the living standards that it can afford and the more options it has to choose from to improve well-being – well-being can be increased by things like quality healthcare and education, excellent roads and other infrastructure, safer communities, stronger support for people who need it and improved environmental standards”

All splendid food for thought

Financial cardinals needed

Of the many financial measures available, only three qualify as financial cardinals – the ones whose alarm bells must ring to prompt action in good time

They are total revenue, total cost and profitability

They’re ‘catch-all’ measures covering all outputs, outcomes and inputs:

  • Total revenue covers net outputs sold and outcomes the customers took into account before making their purchases
  • Total cost covers the mix of costly input resources used
  • Profitability covers how well those input resources were used – a ‘total productivity’ measure in effect

 

Trends in each one need to be regularly monitored

In the private sector, the three must be monitored together – otherwise managers might be tempted to make themselves look good by boosting one at the expense of another

For instance, senior managers have been known to buy other companies to boost their revenue and profits growth record – however, their capital employed will also have increased so profitability, not profits, may well have fallen

In the public sector, there’s only one financial cardinal – total cost

Overall, if something goes wrong, it may not show up in the financial cardinals – minor failures can be cancelled out by minor successes when results are aggregated

But, if something goes badly wrong ‘below decks’, it should be noticed not only by the manager responsible but also his peers – transparency and honesty between them all are key

And once understood, quick action will be vital – hence, financial cardinals must always be presented in good time, not months later as many are

To quote Dr Devi Shetty, chairman of the Narayana Cardiac Hospital in India: “If you get the profit and loss at the end of the month, it’s a post mortem, the patient is dead – if you get the profit and loss daily, it’s a diagnosis and you can treat”

Financial metrics are not enough

  • How do you know if an organisation has performed well?

 

  • If it’s a private company, financial results will reflect customers’ valuations of what they were offered and translate them into revenue and profits

 

  • If it’s a public sector unit, the tax-paying public will judge quality and service levels received – actual costs are not their concern unless their taxes become unacceptably high – until then, they leave it to service unit managers and government ministers to manage resources needed and so costs

 

  • Currently, there’s a glut of financial measures available and, confusingly, more than one definition for some of them – they include:
    • Free Cash Flow – FCF
    • Net Assets – NA
    • Capital employed – CE
    • Return on Sales – RoS
    • Return on capital employed – RoCE
    • Asset turn
    • Added value – AV
    • Economic value added – EVA
    • Gearing
    • Working capital
    • Liquidity

 

  • The problem, as Peter Drucker once pointed out, is: “Financial accounting is an X-ray of an enterprise’s skeleton but most of the diseases we commonly die from such as heart attacks, cancer or Parkinson’s disease do not show up in a skeletal X-ray – a loss of market standing or failure to innovate does not show up in an accountant’s figures unless the damage has gone beyond repair”

 

  • Hence, financial measures have their limitations

 

  • And they don’t drive results – they’re the results of actions already taken – they show where an organisation has been, rather than where it’s going

 

  • Warren Buffett famously described them as ‘rear mirror, not windscreen’ measures

 

  • Using them alone would be like steering a boat by watching its wake and hoping there are no dangers ahead

 

  • That said, there are some financial measures which are vitally important – the financial cardinals, detailed later

Most plans go unseen or unused

The following is an extract from ‘Productivity Knowhow’

  • A good corporate plan is a punchy summary of where an organisation aims to be in five years’ time and, broadly, how it is to get there

 

  • Essentially, the plan should define the organisation’s ‘business model’ – how it will be better than its rivals and harder to copy – how it will make money

 

  • Glen Moreno, Chairman of Pearson and a director of Man Group and Fidelity, said: “A corporate plan is the reallocation of scarce capital resources towards the best opportunities for growth in earnings and returns”

 

  • Author, Stephen Covey, said: “Plans are the knowledge about what to do and why – others then have to provide the how to do and employee motivation for want to do

 

  • According to Peter Drucker, the corporate plan should provide answers to: “If we were not in this business, would we be going into it now?”

 

  • Jack Welch, when CEO of GE, said an organisation’s strategy should define the ultimate aim of: “How it intends to win in business:
    • It’s actually very straightforward
    • It’s an approximate course of action that you frequently revisit and redefine according to shifting market conditions
    • It’s about funding the big ‘aha’, setting a broad direction, putting the right people behind it and then executing with an unyielding emphasis on continual improvement
    • It’s resource allocation, given you cannot be everything to everybody, whatever your size”

 

  • Good plans are thus not long-winded glossies but short statements of broad aims and how they are to be achieved – not prescriptive in every detail – and they deliberately leave tactics to others

 

  • They’re the written equivalent of the inspirational briefings that General George Patton or Vice Admiral Horatio Nelson gave to their commanders before battle – their commanders didn’t need, or want, any more

 

  • However, many managers think their corporate plans are a waste of time and effort – an annual ritual conducted by a few senior managers whilst those who have to implement them never know much about them – and, once written, even their authors tend to ignore them

 

  • The current situation was best summarised when Roger Smith, Chairman of General Motors, said: “We got these great plans together – then we put them on the shelf and marched off to do what we would be doing anyway – it took us a little while to realise that wasn’t getting us anywhere”

The evolution and future of productivity

The Universe is some 15 billion years old, apparently – ‘Big Bang’ followed, some 10 billion years later, spawning Planet Earth – then, over the last 4.5 billion years, life appeared on Earth and a wide variety of species, both flora and fauna, eventually emerged

At first, resources needed for their survival – food or sunlight, say – were plentiful – hence numbers of species grew

But those same resources were limited so, as demand for them grew, competitive battles began

Eventual winners proved to be ones which:

  • Either had an edge over others for the resources available at the time – fauna had to be bigger, stronger, have sharper teeth/ beaks/ claws or be faster – flora had to grow taller, quicker or need less water
  • Or, lacking such an edge – extra speed or stamina for catching prey, say – had the wit to organise themselves into over-powering teams e.g. lions, wolves or hyenas hunting in packs 

The result was the strong became stronger, and more fecund, whilst the weak became weaker, with many species dying out

Eventually, a ‘balance of nature’ would be reached when the great majority of winner species had ‘enough‘ to survive – they didn’t need or want more – they preferred to spend their spare time either asleep or watching others

And this happy state would only be interrupted by the occasional asteroid hitting the planet or Krakatoa-like volcanoes erupting, either one sending so much dust into the atmosphere that it blotted out sunlight on which most of life depended

Evolutionary battles would then start up again

And so it was until ‘homo sapiens’ appeared only some 200,000 years ago – a mere blink in the annals of total Earth time (< 0.01%):

  • It took ‘man’ most of those 200,000 years to invent stone tools and the use of fire to feed, warm and protect himself better
  • Then, in only the last 10,000 years, his brainier colleagues invented farm tools, gunpowder, the abacus and paper for books to make his life easier – they also enabled him to win all his battles with other species and become ‘king of the planet’
  • From then on, he could and would take whatever resources he needed, and more, leaving all the other species to fight for what was left – his only serious battles ever since have been with his own species
  • Tribes formed villages, then towns, then cities – groups of them became nations – some nations went further and built empires
  • Battles between tribes for resources became wars between nations for power and glory as well – the result was, over just the last 2,000 years, man has slaughtered hundreds of millions of his fellow-men
  • However, over the same period, man’s inventiveness has also enabled his total population to grow exponentially and far exceed this slaughter rate
  • But this net expansion of numbers did not improve the standard of living for most – life for all but a very select few was a constant struggle – most people were serfs, poor and miserable – their average lifespan was short, health poor and creature comforts rare compared to today
  • Rumblings for big changes thus started to be heard

Then, only some 300 years ago, the productivity revolution started in the UK – followed by Belgium and Germany:

  • Newcomen and Watt’s steam engines pumped water out of coal mines to increase supply
  • The steam engine then powered Hargreaves, Arkwright and Cartwright’s  spinning jennies, frames and looms for the northern cotton and wool mills
  • Using local coal and iron ore, Bessemer’s furnaces also started the UK’s iron and steel industry which enabled ship and bridge building
  • Stephenson’s ‘rocket’ locomotives and Brunel’s railways and tunnels soon followed

And, ever since, man has continued to find ways to invent more and better stuff to make his life longer and healthier, easier and more enjoyable

The result is the human population on Earth has now grown to some seven billion souls – some experts say it will soon reach 10 million and keep on rising – others claim vital physical resources are at their limit so, if the population does keep on rising, our future will comprise nothing but wars for them or starvation from being without

Such gloomy forecasts are not new, however

Back in the 18th century, Thomas Malthus, an English cleric, announced that growth of human food production (at the time) was linear whereas population growth had become exponential so, if nothing changed, mass starvation was inevitable – in the 1970’s the learned ‘Club of Rome‘ reached much the same conclusion

Happily, Malthus had not allowed for the capacity of man to improve productivity – to get more and better out of existing, albeit limited, resources

Indeed, over the last 300 years:

  • Man has contrived to produce more and more food from existing finite land – and whilst needing less and less human effort to do so
  • He was also able to produce more and more volume of stuff to meet his basic personal needs, the first rungs on Maslow’s hierarchical ladder – many things which once were considered a luxury for a few became an affordable necessity for the many e.g. motor cars, colour TVs
  • And, with his basic needs sated, more stuff came to be offered at affordable prices which made human lives not only easier but also more enjoyable e.g. dishwashers, package holidays 
  • Now, under pressure from customers and competition, suppliers not only offer more volume of affordable stuff but better quality stuff too – e.g. cars and TV programmes  

Thus, in a mere 300 years, most human lives, at least in so-called developed nations, have been transformed from what they were over man’s first 199,700 years – it’s been truly astonishing progress

But can it continue?

Modern-day pessimists, the equivalent of Malthus, say ‘no’

The most famous of them is the respected Professor Robert Gordon of North Western University, USA – he claims that invention of GPTs (General Purpose Technologies like the steam engine, electricity or computers) has been exhausted and there will be no more

But maybe this is is a selfish and blinkered view:

  • Selfish because it ignores the plight of most of the current human population on Earth who have yet to enjoy most of the benefits of the productivity revolution
  • Blinkered because it ignores the many unknowns we have yet to know about, not to mention all the unknown unknowns

And maybe a global paradigm shift is also in the offing – one where we humans now find ourselves at a watershed, moving:

  • From an ‘old world’ focussed on producing more and better tangible stuff from limited physical resources at lower unit costs – one which seeks to improve our SoL (Standard of Living)
  • To a ‘new world’ focussed on developing more and better intangible stuff from unlimited knowledge resources, much of it offered for free – one which seeks to improve our QoL (Quality of Living)

At this juncture, productivity improvement efforts become even more important to both our SoL and QoL:

  • SoL because some five billion of the seven billion people on Earth still live relatively wretched lives and need help to catch up with the rest of us – and we better-off two billion will not be content to just stand and wait for them, forever wanting to improve our SoL further
  • QoL because the ‘new world‘ opening up before us requires a radical review of what our likely needs will be in future

So what might life be like some 20 years from now when the ‘new world’ could well have taken over?

A. SoL factors?

  • Wages will be unnecessary – a UBI (Universal Basic Income) experiment will be short-lived and found pointless:
    • All private sector goods and services will be produced by AI (Artificial Intelligence) and robots, and be free – cash will not be needed to buy or exchange them – everyone will have what they want – expensive luxuries to reward success will be passé – IP (Intellectual Property) protection and patenting for commercial gain will no longer be needed as latest and best ideas will be immediately shared with all
    • Public services will also be free – taxation to fund them will be unnecessary
  • ‘Work’ will thus cease – we’ll all do only what we want to do, for fun, not what we had to do, for money
  • Wealth, and inequality, will no longer be measured by physical possessions but mental capacity beyond that available from AI
  • ‘Old world’ poverty will disappear as everyone will have all the physical stuff they need
  • ‘New world’ poverty will never arise as everyone will be able to learn basic skills instantly, for free e.g. downloads to their brain to play the piano or speak Swahili

B. QoL factors?

  • Every single person will consider themselves, and be considered by others, to be of equal importance – life will no longer be ‘unfair’ for most
  • Class systems, royalty, aristocracy and unmerited power will have disappeared
  • Status, fame and Olympic gold medals will be confined to those with exceptional minds, not those topping promotion ladders, looking good or winning track races 
  • We’ll all have the choice to live for as long as we like, disease free, either in our physical form thanks to major medical breakthroughs or via digitally uploading ourselves to ‘clouds of the day’ 
  • We’ll fill our time:
    • Either being proactive – learning new skills, socialising with others, being altruistic or helping push out boundaries in the arts and sciences
    • Or reactive – watching our favourite sports teams or being entertained by others 

In other words, life on Earth, and any other place we’ve populated, will probably be very different to now – one where the volume and quality of outputs needed most will be information on ideas, systems and controls

And the most important input resource will be knowledge – K – either held ‘in heads’ or ‘in files’ – for example, K stored in the form of data, flow charts, formulae, reports/ articles, customer details and contacts or experience gained from successes and failures etc.

However, there is one big difference between ‘old world’ physical inputs and ‘new world’ mental inputs:

  • Labour, materials and capital are all limited, often unrenewable and all costly
  • On the other hand, K is unlimited, can grow rapidly and is mostly free for, if you and I each have a £1 coin and exchange them, we each still have £1 but if you and I each have a good idea and exchange them, we each have two good ideas

Hence, unlike physical resources, mental K resources have enormous potential to improve the SoL and QoLof every man and woman on the planet

As ever, however, man already wastes most of this potential

Consider the following three performance measures usually applied to physical resources but now to the K available within your team, organisation or nation:

  • KA% = K Availability = Amount available in-house/ Total needed = 60%
    • The actual volume ‘in heads’ is usually more than adequate for any team to complete its work well
    • However, the volume ‘in files’ is usually poor – people are reluctant to record their experiences – systems are not in place for others to find it
    • And whilst the volume available from outside and in the public domain is vast, and said to be doubling every year, it’s currently biassed by search engine algorithms and optimisers which determine what one sees on first pages – hence much valuable information can be hidden on later pages, or completely ignored
  • KU% = K Utilisation = Amount used/ Amount available in-house = 30%
    • Only a small % of the K available in-house is made use of by others because:
      • They don’t know it exists, or how to find it
      • They find it difficult to access
      • It’s kept secret by owners because ‘knowledge is power’
      • It’s of poor quality and often out-of-date 
    • Hence many people in many organisations either keep re-inventing the wheel or make no advances
  • KE% = K Efficiency = Improvements made/ expected = 20%?
    • Key outputs sought from good use of K are more and better ways to do things which improve the quality of lives – also known as Kleverage, the ability to obtain significant benefits from the K available
    • KE% is a measure of the value of actual gains made versus those expected
    • The higher this %, the more it feels like having a Thomas Edison, Albert Einstein or Alexander Fleming on board – people who turn K into gold

Overall, the above product measures the efficiency of your team’s use of the knowledge available to it viz:

KAUE% = 60% x 30% x 20% = 3.6% = Very Poor

Clearly, ways to make big improvements to KA%, KU% and KE% are needed here – and given the above numbers are optimistic for the current position in most teams, the sooner the better

Fortunately, major advances are already under way, including:

  • Taxonomy and Knowledge Management, two disciplines still in their infancy, which seek to improve the availability and utilisation of K
  • Humans have limited capacity to absorb and analyse Big Data – masses of data and information – however, AI is able to dig far deeper, wider and quicker into all K that exists, seeking patterns, correlations and solutions, many beyond human comprehension – AI already offers the potential to discover whole new and better ways of doing things, from winning games like chess and ‘Go’ through to curing health problems, creating music or saving the planet 
  • Apps, expert systems and computer models have already mushroomed on a wide spectrum of fronts, many offering better, even optimum, solutions for specific personal or business problems faced 

So, whilst we humans might well be approaching peak performance levels in our physical ‘old world’, there’s a long and steep climb ahead as a mental ‘new world’ opens up before us

At present, man is still in the foothills of the K mountain, taking his first tentative steps, yet K productivity has already become the biggest issue he faces

Unlike the ‘old world’ however, if we ever near the top of this mountain, we must expect another higher mountain to appear soon after – K2?

Our future is thus mental, infinite and very exciting

 

 

 

 

Excess regulations and legacy systems solve productivity puzzle?

Brian Caplen, editor of The Banker, says the challenges banks face with regulation and legacy IT systems hold lessons for the wider economy

He points out that ‘great minds have been pondering the productivity puzzle – so why, in a time of rapid technological change, is productivity stagnant in many advanced economies?’

The UK has particular problems related in part to the tendency of firms to hire cheaply from an EU migrant pool (one which may disappear post-Brexit) rather than invest in new equipment.

But there are two other reasons — less often cited and especially pertinent to banks — which might explain this so-called mystery.

  1. The first is regulation and compliance:
    • Banks can be forgiven for thinking that theirs is the only industry suffering from regulation overload given the slew of regulation since the financial crisis
    • But all industries are engaged in a massive regulatory push across areas ranging from data protection to employment law to health and safety
    • These require not only additional resources to implement but also take out management and employee time filling in spreadsheets in order to comply
    • Many of these new regulations have noble objectives but are a direct hit to productivity
  2. Then there are control systems run on legacy IT that also eat into productivity:
    • These typically involve purchasing and invoice systems that require numerous steps to complete and ask for multiple lines of information
    • All very nice for the data collectors but they use up lots of staff time
    • Banks again are in the frontline as they are often running these off legacy and cumbersome IT systems

 

The US administration is currently under fire for revisiting regulation and loosening it where appropriate.

In fact, a thorough cost-benefit analysis of regulation and compliance across sectors could produce better outcomes, consume fewer resources and help solve the productivity puzzle.

 

Deaf ears encore une fois

Barnes Wallis, the English scientist of ‘bouncing bomb’ fame, once said: “There is a natural opposition among men to anything they have not thought of themselves”

He might better have said ‘western men’ – ‘eastern men’ can be ‘all ears’

Once upon a time, just after WW2, three eminent American statisticians tried to convince US businesses of their radical new ways to improve productivity by reducing waste and improving output volumes and quality – ways which employed basic statistics at their heart
 
But those same US businesses chose to ignore them, preferring more obvious stuff like Work Study and O&M, then Mathematical modelling via Operations Research, then TQM for culture changes and employee engagement – and nowadays ICT systems rule the roost
 
Fed up with those deaf ears, the three statisticians – Doctors Edwards Deming, Philip Crosby and Joseph Juran – crossed the Pacific to Japan where they were listened to intently – the result was the Japanese economic miracle – a transformation over a decade from a reputation for widespread shoddy goods to one quite the opposite – and with exponential increases in profit margins and overall profitability
 
In the 80s and even 90s, the US, and West in general, could no longer ignore this huge change in their competition – they flew thousands of managers to Japan to discover their secrets – they also came back no wiser, thinking it must be something to do with culture differences and changes
 
Hence TQM (Total Quality Management) was born, and it took over a decade before most in the West realised it was not the answer – worse, it was an expensive failure given it produced few quantifiable and significant results yet cost a lot in time and effort
 
Meanwhile, productivity deaf ears continue in the West
 
Readily available common sense about productivity improvement is again being ignored whilst organisations believe it’s ICT systems plus digitisation of processes that will transform their financial accounts and improve their service levels
 
The first problem is productivity has been so downgraded in the minds of most managers that it no longer features on any boardroom agenda – some soul-searching is thus required straight-away
 
Then consider what’s on offer to organisations in the West if and when any of them do seek to improve their productivity – if only as a by-product of some other worthier aim:
  • Management organisations like the CBI and IoD offer no help via their websites and largely ignore the topic
  • UK business schools, to their everlasting shame, offer no courses on productivity improvement
  • And UK management consultancies that peddle good practical sense for big productivity improvements are as rare as hen’s teeth – but there are hundreds, including all the top ten, who do not – they prefer to address leading-edge thinking in more strategic or technical areas, which also command higher fees

And none dare offer their services to clients at a cost which includes a ‘payment by results’ element – as per investment advisers with their win/ win 2/ 20 charging formula i.e. 2% to cover their basic costs plus 20% of any resultant profits (and no recompense if any losses)

It’s another example of an ‘elite’  bubble, all thinking and speaking the same way and blotting out pesky outsiders with their differing views

 
 

What kills change?

Ken Blanchard, of ‘One Minute Manager’ fame, recently focused on why implementing change stumbles so much

He listed 13 pitfalls that stop major change in its tracks without attaching relative weightings to each one so you are left to decide your own:

  • Culture = The predominant attitudes, beliefs and behaviour patterns of the organisation:
    • The current culture is not fully understood at first
    • Any disconnect between actual values and those posted on the wall means the latter are ignored
    • Employees become cynical about leaders who say one thing and do another
    • One must determine how to leverage the current culture to support, enable and sustain the change
    • To change the culture requires leadership, measures and incentives
  • Commitment = Employees’ motivation to engage in the new behaviours required by the change:
    • Employees are far more likely to buy in to a change they’ve influenced than one imposed on them by others – their involvement may lengthen implementation but greatly increase the likelihood of success
    • Uncovering and addressing employees’ concerns about any change increases both trust and buy-in
    • Those ignored can derail all
    • “There’s no commitment without involvement”
    • So provide forums for people affected to express their views, listen to bosses, become involved, have doubts removed, not least by others converted
    • Do you want compliance or commitment?
  • Sponsorship = The senior person pushing for the change and with authority over resources needed:
    • He must live and breathe the change in behaviours needed to show he is serious
    • Actions speak louder than words
    • He must assemble a well-qualified change team
    • He must not announce visions such as “To be the leading XYZ company” when all employees know it’s unrealistic given the company is nowhere near that position and steadily falling further behind
  • Change team = They have responsibility for deciding and making the changes – leading people through them and delivering the outcomes wanted:
    • They must speak with one voice ALWAYS and resolve employees’ concerns
    • Members should include advocates for the change – people who have been part of successful projects, have the time, have respect of peers, are highly skilled, will speak the truth, can communicate – people from different areas, and represent diverse points of view
    • They must involve, not ignore, employees affected
  • Communication = Essential dialogue between changers and those affected on why the change is needed:
    • Mixed messages from sponsors, other managers and the change team give employees excuses not to change
    • Don’t focus on getting words out – also listen i.e. take employees’ words in
    • Use all types of media, often
  • Urgency = How quickly employees must change:
    • Employees must be convinced that the status quo is not a viable option – what is wrong with now
    • Present them with the facts, show the gaps between what is and what could be, and then ask them why the need to change
    • Spend lots of time with apparent losers
  • Vision = A clear and compelling picture of the future after the change:
    • Go beyond a slogan and present a clear picture of what the future could look like
    • Ensure (most) employees can see themselves benefiting in future
    • Don’t invent a vision off-site at some exec retreat
    • Involve the maximum number of employees in the visioning process to maximise the number who will want to be part of it
  • Plan = A detailed programme of actions to fully integrate changes into the organisation:
    • Don’t focus on the big picture and ignore the detail, the main stumbling blocks for change projects
    • Always try to include ‘early wins’ – build a momentum of enthusiasm or naysayers will prevail
    • Always include employees affected in the planning process, especially the resisters who will identify what could go wrong
    • “Those who plan the battle rarely battle the plan”
  • Budget = The allocation of limited resources:
    • Ensure the project has enough resources for the change to succeed
    • Don’t let he who holds the purse strings run the whole show
  • Training = All employees affected have all the new skills needed:
    • Pilot the changes first – to learn who needs what training
    • Employ trainers whom employees respect and will learn from
  • Incentives = Rewards for desired behaviours and results:
    • They must be meaningful/ relevant – and not necessarily monetary
    • They must be on offer to all, not just a few
    • Employees must not forget their other roles
  • Performance management = Goals and expectations:
    • Track outcomes expected of people – provide feedback and coaching
    • Ensure they have the time and capacity for the extras needed for the changes
    • Some people want change but are not willing to pay for it
    • HR should be the most important division – (not a dumping ground for failures)
  • Accountability = Delegation, follow-up and consequences:
    • Leaders must ‘walk the talk’
    • Avoid lots of action then no follow-up
    • Need clear measures of success for all, not just the leaders – which are  regularly reviewed

With so many important factors to consider, it makes one wonder about the chances of success for any big improvement initiatives, whether at organisation or national level

Productivity improvement must involve all employees

The following are extracts from an article in the Huffingtom Post by Mike Clancy, General secretary of Prospect – one must involve all employees, all the time, for effective productivity improvement

The appointment of the Bank of England’s Andy Haldane to lead the government’s work on productivity may herald the advent of some badly needed fresh thinking. In a forensic speech this summer Haldane explained what he sees as the root causes of our current malaise. There was a lot in the speech, but two themes stand out:

  • Lack of innovation
  • Lack of institutional economic infrastructure.

It is time to call time on this top-heavy economic model and its defenders. The belief that all wisdom in a company is contained within the boardroom is central to our productivity and wages crisis.

If we are serious about ending it, we need to shake up the power imbalance in companies, reverse the decline of collective bargaining and involve everyone, government, employers and trade unions in a national mission to raise productivity.

 

The perfect working environment?

According to an article by Michael Odell in The Times, Basecamp is a US software/ tech company that supposedly runs without the scourge of 80 hour weeks, unrealistic deadlines, weekend emails and meetings

Two American guys, Jason Fried and David Heinemeier Hansson, run Basecamp – they’re also authors of a new book called It Doesn’t have to be Crazy at Work covering their creation of a ‘calm office’ where everyone is happy and well paid, and stress doesn’t exist

The two brim over with iconoclastic views about work, including:

  • Meetings should be a last resort – pull your eight most talented people into a one-hour meeting and that’s eight hours of quality work lost
  • Sustained exhaustion is not a badge of honour, it’s a mark of stupidity
  • No-no’s re staff attendance:
    •  Are they working? – Dunno
    • Are they taking a break? – Dunno
    • Are they at lunch? – Dunno
    • Are they picking up the kids from school? – Dunno – Don’t care
  • Adopt traditional workplace titles reluctantly – there’s often a lot of bullshit around them
  • 40 hours a week is enough for anybody – workaholics who slave all hours out of loyalty to the mission are advised to “f*** the mission”
  • Staff benefits should include:
    • Pay the best rates in the US tech industry
    • Take proper holidays, not ‘fakecations’
    • While on holiday – “log out, delete the company app, go dark” and “here’s $5,000 towards your trip”
    • Only work four days a week in the summer
    • Have a paid sabbatical every three years
    • A free monthly massage at a spa
    • A free monthly fruit and veg delivery, to their homes
  • Our goal? – We have no goals:
    • No customer count goals
    • No sales goals
    • No retention goals
    • No revenue goals
    • No profitability goals (other than to be profitable)
  • People who say ‘doing nothing is not an option’ are dumb – nothing should always be on the table
  • If you’re the multi-billionaire gorilla in the room, why not pay good rates to your staff?
  • We make good money so why try to avoid taxes – why not set an example instead – it really rubs us up the wrong way when people don’t pay enough tax

 

Many of these views were prompted by a survey they conducted of 600 people, asking “who managed three to four hours effective work in a day?” – only 30 put their hands up

Such a result will come as no surprise to regular readers of our posts

And when, in 2016, Basecamp showed signs of booming sales and growth, they took action to slow things down, stopped hiring and tripled selling prices – it worked – they continue to exist but stopped growing

They say they don’t want to be the next Jeff Bezos and Amazon:

  • “I don’t want to meet the Canadian Prime Minister for lunch”
  • “Colonising space is not on my to-do list”

 

So what do they want?

“We don’t want a bigger company – and if that means leaving some money on the table, so be it”

“We love work, but we want a life too”

 

Robots at Work

The Financial Times reported on a study “Robots at Work,” written by Georg Graetz, a researcher at the Department of Economics, Uppsala University, and Guy Michaels, London School of Economics, which examines the impact of industrial robots on jobs, productivity and growth.

Industrial robots are programmable and are widely used for assembly, packaging, inspection and agricultural harvesting. In recent years, use of industrial robots has increased sharply, while the price of the robots has declined by about 80 per cent, taking into account increased quality.

A brief summary of their findings and conclusions follow – readers may disagree

Job opportunities and wages

“We can see that industrial robots increase employee wages and increase productivity and that the  of jobs for low-skilled employees, and also to some extent for the medium-skilled, decreases, while job opportunities for the highly skilled increase,” says Georg Graetz.

“Most likely the profits realised through the introduction of robots are divided among the company and its employees.” (an optimistic view)

The composition of the labour market is changing towards a higher proportion of highly educated employees while at the same time the study suggests that the total number of jobs is not affected by industrial robots.

Increased productivity

Industrial robots increased the annual growth in GNP in the countries surveyed by 0.37%, and labour productivity increased by 0.36% (unbelievable accuracy)

“This means that without industrial robots, growth in labour productivity would have been about 5% lower during the 14 years we have studied.”

The contribution of robots to the economy is comparable to the economic importance of the railways in the 19th century or the more recent contribution from ICT (Information and Communication Technology).

“In this context, it is interesting to note that industrial robots account for only 2% of capital, which is much less than technological driving forces for growth in the past.”

Of the surveyed countries, the number of robots increased most in Germany, Denmark and Italy.

Countries that had a more rapid increase in the number of robots also had a greater increase in labour productivity.

Continued increases in productivity likely

The study suggests that:

  • An increasing number of robots produces a reduced increase in productivity – that is, there is a limited potential for utilising robots in production. ( we disagree – now is take-off, not slow-down, time – and what of the impact on all other sectors?)
  • Robots will continue to contribute to an increase in growth and productivity.
  • Industrial robots are evolving and will be able to do more.
  • At the same time, new types of robots are coming, such as medical robots that can perform surgery or different types of robots for transport.
  • This development will contribute to continued growth and production increases.

 

By refreshing contrast, consider the views expressed in an article by Kweilin Ellingrud who claims to cover ‘transforming large-scale companies and workplace diversity’ viz:

  • To date, the results of integrating automation and new technology in manufacturing operations have been promising
  • Their bottom lines have been improving via higher efficiency and greater employee productivity
  • There will be more automatic real-time data feeds and data monitoring
  • For employees, the mix of their work is changing to be less repetitive and more judgement-intensive
  • In addition, new and more exciting jobs are being created, rather than merely eliminating positions
  • Workers are or will be doing less predictable physical work, data processing and information collection – and, at the other end of the spectrum, making better decisions based on data collected, more managing of others and reacting better to what customers want
  • The result is manufacturing jobs are growing at the fastest pace for two decades
  • And, over all sectors, there are now far more people than ever before employed
  • In future, there will be a lot of job transitions and retraining needed

 

Kweilin then quotes MGI (McKinsey Global Institute) projecting that:

  • About 15% of the global workforce, or 400 million people, will be displaced by 2030
  • Another 8-9% of employees will work in categories that do not yet exist today (unknown unknowns?)
  • So there will have to be significant reskilling of workers

 

Conclusion:

Kweilin and the MGI must surely trump the dismal views of Georg and Guy

Immigration pluses and minuses

  • 40% of Fortune 500 companies were founded by first or second generation immigrants, and more than half of the nation’s billion-dollar startups have an immigrant co-founder
  • According to the National Science Foundation, only 17% of US bachelor degrees are STEM (science, technology, engineering, and maths) degrees – the percentage in China topped 40%
  • The US leads the world in awarding STEM doctoral degrees, but more than a third of those degrees are awarded to foreign students
  • Twenty years ago the US share of global venture investment was 90% – that number dropped to 81% in 2006 and to 53% in 2017
  • In 2016, China was home to six of the ten largest venture capital investments in the world

 

And other countries like the UK, Singapore, France, and Canada dedicate visa regulations explicitly to attract young immigrant entrepreneurs (n.b. Claude claims)

Not to mention China which, in addition to graduating far more STEM students than the US, is also devoting vast resources to its Made in China 2025 program to surpass the US in the production of key high-tech industries.

There are claims of fiscal benefits too

Consider the following extracts from an article in Moneyweek by James Lewisohn

September’s Migration Advisory Committee report on immigration to the UK from Europe claimed that European migration into the UK has caused only small impacts to our economy compared to other events such as the post-Brexit referendum devaluation of sterling, for example.

Its main conclusion appeared to be that the many immigrants to the UK from the EU (who arrived in waves, first after we opened our borders to Eastern European states in 2004, and again during the economic crisis from 2008 onwards) have made a much more fiscally positive contribution to the UK than immigrants from elsewhere. This fitted nicely with the views of most politicians and journalists and so generated a good few headlines along the lines of “Immigration myths that fuelled Brexit blown apart” (the Independent).

But is the conclusion really so simple?

It seems not.

The Committee’s chair, LSE’s Professor Alan Manning, gave evidence to the Home Affairs Select Committee

The SNP’s Stuart McDonald asked him: “Given the research, should the conclusion just be that the best thing for the UK to do is just carry on with free movement of people from the EU?”

The answer was a surprise – “No” replied Professor Manning

He and his team had, regrettably, failed to synthesise their argument:  “It’s all in there – but not brought together in one place”

What they actually meant is “lower-skilled migrants have been fiscally-negative – they make the UK a slightly lower wage, lower productivity kind of economy – any effects that they have on innovation are not positive – and, basically, if you ask what have been the benefits of this lower-skilled migration, there isn’t very much on the positive side of the ledger”

“That doesn’t come through very much in your report”, said Mr McDonald.  And indeed, it doesn’t. But it is very very important.

If Professor Manning’s conclusion is correct, and a lot of work has gone into it, then he may just have put the UK’s 14-year debate over the EU’s bedrock principle – free movement of labour – to bed

By the time of the EU referendum, the UK had seen more EU immigration, and vastly more low-skilled immigration, than any other country – it has, for example, been the primary reason why the UK’s foreign-born population, rose from 8.6% in 2003 to 12.3% even at a time when major economies such as Germany and Italy actually saw their foreign-born populations slightly contract

If, as many have argued, that has come with huge fiscal benefits for the UK, it isn’t necessarily a bad thing. But if it has not, as seems to be the case, a more restrictive policy post Brexit might be a very good idea

It could, for example, force Britain’s employers of low-wage labour to invest in greater automation, leading to greater productivity (n.b. already happening, even in advance of Brexit) and to real wage growth

That, surely, would be a result welcomed by both sides of the Brexit debate

National distribution of wealth

An interesting, sometimes complex (at least to me), article by Laurie Macfarlane for www.opendemocracy.net follows – it amply demonstrates that totting up any figure for national wealth is not straightforward

According to a new OECD working paper, Britain is one of the wealthiest countries in the world.

Net wealth is estimated to stand at around $500,000 per household – more than double the equivalent figure in Germany, and triple that in the Netherlands. Only Luxembourg and the USA are wealthier among OECD countries.

On one level, this isn’t too surprising – Britain has long been a wealthy country.

But in recent decades Britain’s economic performance has been poor. Decades of economic mismanagement have left the UK lagging far behind other advanced economies. British workers are now (said to be) 29% less productive than workers in France, and 35% less than in Germany.

How can this discrepancy between high levels of wealth and low levels of productivity be explained?

Wealth creation and division:

If you pick up an economics textbook today, you’ll probably encounter a narrative similar to the following:

  • Wealth is created when entrepreneurs combine the factors of production – land, labour and capital – to create something more valuable than the raw inputs.
  • Some of this surplus may be saved, increasing the stock of wealth, while the rest is reinvested in the production process to create more wealth.

 

How the fruits of wealth creation should be divided between capital, land and labour has also been the subject of much debate. In 1817, the economist David Ricardo described this as “the principal problem in political economy”.

Nowadays, however, this debate attracts much less attention. That’s because modern economic theory has developed an answer to this problem, called ‘marginal productivity theory’.

This theory, developed at the end of the 19th century by the American economist John Bates Clark (author of ‘The Distribution of Wealth’), states that each factor of production is rewarded in line with its contribution to production. Marginal productivity theory describes a world where, so long as there is sufficient competition and free markets, all will receive their just rewards in relation to their true contribution to society.

There is, in Milton Friedman’s famous terms, “no such thing as a free lunch”.

Seen in this light, wealth accumulation is a positive sum game – higher levels of wealth reflect superior productive capacity, and people generally get what they deserve.

There is some truth to this, but it is only a very small part of the picture. When it comes to how wealth is created and distributed, many other forces are at work.

Wealth, property and plunder:

The measure of wealth used by the OECD is ‘mean net wealth per household’. This is the value of all of the assets in a country, minus all debts. Assets can be physical, such as buildings and machinery, financial, such as shares and bonds, or intangible, such as intellectual property rights.

But something can only become an asset once it has become property – something that can be alienated, priced, bought and sold. What is considered as property has varied across different jurisdictions and time periods, and is intimately bound up with the evolution of power and class relations.

For example, in 1770 wealth in the southern United States amounted to 600% of national income – more than double the equivalent figure in the northern United States.

This stark difference in wealth can be summed up by one word: slavery:

  • For white slave owners in the South, black slaves were physical property – commodities to be owned and traded.
  • And just like any other type of asset, slaves had a market price.
  • As the below chart shows, the appalling scale of slavery meant that enslaved people were the largest source of private wealth in the southern United States in 1770.

When the United States finally abolished slavery in 1865, people who had formerly been slaves ceased to be counted as private property. As a result, slaveowners lost what had previously been their prized possessions, and overnight over half of the wealth in the southern US essentially vanished. All of a sudden, the southern states were no longer “wealthier” than their northern neighbours.

But did the southern states really become any less wealthy in any meaningful sense?

Obviously not – the amount of labour, capital and natural resources remained the same. What changed was the rights of certain individuals to exercise an exclusive claim over these resources.

But the wealth that had been generated by slave labour did not disappear, and it wasn’t only the USA that benefited from this:

  • Many of Britain’s major cities and ports were built with money that originated in the slave trade.
  • Several major banks, including Barclays and HSBC, can trace their origins to the financing of the slave trade, or the plundering of other countries’ resources.
  • Many of Britain’s great properties, which today make up a significant proportion of household wealth, were built on the back of slave wealth.
  • Even today, many millionaires (including many politicians) can trace some of their wealth to the slave trade.

 

The lesson here is that aggregate wealth is not simply a reflection of the process of accumulation, as theory tends to imply. It is also a reflection of the boundaries of what can and cannot be alienated, priced, bought and sold, and the power dynamics that underpin them. This is not just a historical matter.

Today some goods and services are provided by private firms on a commodified basis, whereas others are provided socially as a collective good.

This can often vary significantly between countries.

Where a service is provided by private firms (for example, healthcare in the USA), shareholder claims over profits are reflected in the firm’s value – and these claims can be bought and sold, for example on the stock market. These claims are also recorded as financial wealth in the national accounts.

However, where a service is provided socially as a collective good (such as the NHS in the UK), there are no claims over profits to be owned and traded among investors. Instead, the claims over these sectors are socialised. Profits are foregone in favour of free, universal access. Because these benefits are non-monetary and accrue to everyone, they are not reflected in any asset prices and are not recorded as “wealth” in the national accounts.

A similar effect is observed with pension provision: while private pensions (funded through capital markets) are included as a component of financial wealth in the OECD’s figures, public pensions (funded from general taxation) are excluded. As a result, a country that provides generous universal public pensions will look less wealthy than a country that rely solely on private pensions, all else being equal. The way that we measure national wealth is therefore skewed towards commodification and privatisation, and against socialisation and universal provision.

Capital gains, labour losses:

The amount of wealth does not just depend on the number of assets that are accumulated – it also depends on the value of these assets. The value of assets can go up and down over time, otherwise known as capital gains and losses. The price of an asset such as a share in a company or a physical property reflects the discounted value of the expected future returns. If the expected future return on an asset is high, then it will trade at a higher price today. If the expected future return on an asset falls for whatever reason, then its price will also fall.

Marginal productivity theory states that each factor of production will be rewarded in line with its true contribution to production. But although presented as an objective theory of distribution, marginal productivity theory has a strong normative element. It says nothing about the rules and laws that govern the ownership and use of the factors of production, which are essentially political variables:

  • For example, rules that favour capitalists and landlords over workers and tenants, such as repressive trade union legislation and weak tenants’ rights, increase returns on capital and land. All else being equal, this will translate into higher stock and property prices, which will increase measured wealth.
  • In contrast, rules that favour workers and tenants, such as minimum wage laws and rent controls, reduce returns on capital and land. This in turn will translate into lower stock and property prices, and lower paper wealth.

 

Importantly, in both scenarios the productive capacity of the economy is unchanged.

The fact that wealth would be higher in the former case, and lower in the latter case, is a result of an asymmetry between how the claims of capitalists and landlords are recorded, and how the claims of workers and tenants are recorded. While future returns to capital and land get capitalised into stock and property prices, future returns to labour – wages – do not get capitalised into asset prices. This is because, unlike physical and financial assets, people do not have an “asset price”. They cannot become property. As a result, it is possible for measured wealth to increase simply because the balance of power shifts in favour of capitalists and landowners, allowing them to claim a larger slice of the pie at the expense of workers and tenants.

To the early classical economists, this kind of wealth – attained by simply extracting value created by others ­­– was deemed to be unearned, and referred to it as ‘economic rent’.

For the most part, economists have tended to focus on the acts of saving and investment which drive the real production process. But on closer inspection, it is clear that economic rent is far from peripheral. Indeed, in many countries it has been the main story of changing wealth patterns.

To see why, let’s return to the OECD wealth statistics. Recall that net wealth per household in Britain is more than double what it is in Germany, even though Germany is (apparently) far more productive than the UK. This can partly be explained by comparing the power dynamics associated with each factor of production.

Let’s start with land:

Germany has among the strongest tenant protection laws in Europe, and many German cities also impose rent controls. This, along with a banking sector that favours real economy lending over property lending, means that Germany has not experienced the rampant house price inflation that the UK has. Remarkably, the house price-to-income ratio is lower in Germany today than it was in 1995, while in the UK it has nearly tripled over the same time period. The fact that houses are not lucrative financial assets, and renting is more secure and affordable, means that the majority of people choose to rent rather than own a home in Germany – and therefore do not own any property wealth.

In Britain, the story couldn’t be more different. Over the past five decades Britain has become a property owners’ paradise, as successive governments have sought to encourage people onto the property ladder. Taxes on land and property have been removed, and subsidies for homeownership introduced. The deregulation of the mortgage credit market in the 1980s meant that banks quickly became hooked on mortgage lending – unleashing a flood of new credit into the housing market. Rent controls were abolished, and the private rental market was deregulated. Today tenant protection is weaker than almost anywhere else in Europe. Meanwhile, the London property market has served as a laundromat for the world’s dirty money. As Donald Toon, head of the National Crime Agency, has described: “Prices are being artificially driven up by overseas criminals who want to sequester their assets here in the UK”.

The result has been an unprecedented house price boom. Since 1995, skyrocketing house prices have increased value of Britain’s housing stock by over £5 trillion – accounting for three quarters of all household wealth accumulated over the same period. While this has been great news for property owners, it has been disastrous for tenants. The driving force behind rising house prices has been rapidly escalating land prices, and we have known since the days of Adam Smith and David Ricardo that land is not a source of wealth, but of economic rent. The trillions of pounds of wealth amassed through the British housing market has mostly been gained at the expense of current and future generations who don’t own property, who will see more of their incomes eaten up by higher rents and larger mortgage payments.

So while German property owners have not benefited from skyrocketing house prices in the way that they have in Britain, the flipside is that German renters only spend 25% of their incomes on rent on average, while British renters spend 40%. The former is captured in the OECD’s measure of wealth, while the discounted value of the latter is not.

Now let’s look at capital:

In the UK and the US, the goal of the firm has traditionally been to maximise shareholder value. In Germany, however, firms are generally expected to have regard for a wider range of stakeholders, including workers. This has led to a different culture of corporate governance, and different power dynamics between capital and labour.

Large companies in Germany must have worker representatives on boards (referred to as ‘codetermination’), and they are also required to allow ‘works councils’ to represent workers in day-to-day disputes over pay and conditions. The evidence indicates that this system has led to higher wages, less short-termism, greater productivity, even higher levels of income equality.

The quid pro quo is that it also tends to result in lower capital returns for shareholders, as workers are able to claim more of the surplus. This in turn means that German firms tend to be valued less than their British counterparts on the stock market, which contributes to lower levels of financial wealth.

None of this means that Germany is poorer than Britain.

Instead, it just reflects the fact that German capitalists and landowners have less bargaining power than they do in the UK, while workers and tenants have more power.

While lower shareholder returns and house prices are reflected in the OECD’s measure of wealth, better pay and conditions and lower rents are not.

A Comment also published:

We all agree that slavery and theft are a bad idea, yet this logic is not extended to natural resources. As land is supplied for free by nature/God, when it becomes valuable, those excluded from its use suffer a loss of opportunity equal to its rental value. As we are all equally excluded, we should therefore be entitled to an equal share of the total rental value of all land.

As this does not currently happen, there is a net transfer of incomes from those that own little/no land by value, relative to the taxes they currently pay, to those whom the opposite is true.

Therefore the selling price of land is but a measure of economic injustice. If there was no net transfer, it’s selling price would be zero.

So not only does a typical working household have to pay much more to buy a house, they need to do so from a reduced disposable income.

Furthermore, as the incomes of some in society are higher than they should be, this leads to over consumption and misallocation of housing.

The housing crisis is just one symptom of economic injustice. It, along with many other issues, can in principle be easily solved by the application of a 100% tax on the rental value of land.

It just needs enough people to stand up and say so.

 

 

UK manufacturing to become ‘smarter’

The UK magazine Drives & Controls has just reported that a group of UK manufacturing business leaders and academics have joined forces with the government to create the Made Smarter Commission (MSC) which aims to make UK manufacturing “smarter”.
The inaugural meeting of the commission was chaired by Siemens CEO Professor Juergen Maier and Business Secretary Greg Clark and follows the publication of the Made Smarter Review almost a year ago.
The commission aims to drive forward digital developments to boost productivity in British manufacturing, to create more highly-skilled jobs, and to enable more efficient, cleaner production systems. It forms part of the government’s Industrial Strategy.

The commission consists of nine men and eight women from business, trade bodies and academic institutions, and includes top-level representatives from EEF, GE Digital, Renishaw, the CBI, ABB, Nestle, Rolls Royce, the TUC, and Jaguar Land Rover.

Priorities for its first meeting included discussing the pilot for adopting digital technology by manufacturers in North West England, and the Industrial Strategy Challenge Fund for digital manufacturing which aims to bring together UK researchers with business to tackle industrial and societal challenges.

The commission also discussed how the manufacturing industry can be transformed by new technologies such as 3D printing, as well as the need for stronger and more ambitious leadership.

According to Maier, the commission “promises to deliver [the Made Smarter Review’s] core recommendation of driving digitalisation across UK and invigorating industrial strategy. We need now, more than ever, to unite business, employees and government behind a strategy that boosts industrial productivity and improves living standards.

“We will build on our North West Pilot, and look at how we can scale our efforts up across the country,” he adds. “If we get this right, I believe we can kick-start a new industrial revolution, that puts digital tech at the centre of economic policy-making.”

EEF CEO Stephen Phipson describes the formation of the commission as “a bold step in harnessing the expertise right across our sector. We look forward to helping it play a key role in unleashing the potential of manufacturing as part of the fourth industrial revolution and a modern industrial strategy.”

The UK is one of the world’s ten largest manufacturing economies and the fourth-largest in the EU. In 2017, manufacturing GVA (gross value added) totalled £186bn and supported 2.7 million jobs (with estimates of 5 million across the whole of the manufacturing value chain). The sector still accounts for 48% of UK’s exports of goods and services.

Business secretary Clark predicts that the increased adoption of digital technologies “will bring enormous benefits, potentially generating £455bn over the next ten years ­– boosting productivity, creating thousands of new highly skilled jobs and enabling more efficient, cleaner production systems”.

Conclusions:

  • This is the first I’ve heard of this new MSC initiative – one wonders how it will interact with others such as the PLG and PIN
  • The MSC should be a sector specific part of an overall UK Productivity Centre (UKPC)
  • Given manufacturing now comprises only some 15% of the total UK economy, where are the comparable initiatives for the other 85%?

A short history of productivity improvement

Lydia Dishman wrote an article for Fast Company outlining steps taken over time to improve productivity – it’s not comprehensive but interesting nevertheless

According to her, there’s no definitive source for the start of productivity improvement efforts but there are historical mentions of it in Wealth of Nations by Adam Smith (1776).

Smith contended that there were two kinds of labour – productive and unproductive viz:

‘There is one sort of labour which adds to the value of the subject upon which it is bestowed; there is another which has no such effect. The former, as it produces a value, may be called productive; the latter, unproductive labour. Thus the labour of a manufacturer adds, generally, to the value of the materials which he works upon, that of his own maintenance, and of his master’s profit. The labour of a menial servant, on the contrary, adds to the value of nothing . . . A man grows rich by employing a multitude of manufacturers; he grows poor by maintaining a multitude of menial servants. The labour of the latter, however, has its value, and deserves its reward as well’.

Benjamin Franklin, a contemporary of the Scottish economist, had a simple way of assessing productivity – ‘start the day asking what good shall be done, and at the end of the day evaluate based on what was accomplished’. Lofty, to be sure, but an interesting measure nevertheless.

THE ABUSES OF LABOUR IN THE NAME OF PRODUCTIVITY

A milestone advancing  productivity occurred in the USA during the same era when Eli Whitney invented the cotton gin in 1793. This impacted the U.S. economy, particularly in Southern states where cotton was grown and picked by slaves. Of course, slave labor was free, and abuse of slaves was rampant, yet the landowners got an additional boost to their bottom lines by implementing a machine that increased their production 25-fold.

The cotton gin wasn’t the only technological advancement to grow out of the early days of the Industrial Revolution. Other machines– from steamboats to sewing machines, light bulbs to telephones – that moved production from handmade in the home to factories sprung up across the country during the late 18th and early 19th century and the frenzy with producing more goods more quickly became something of a national pastime.

Slavery was thankfully abolished after the Civil War, but low-wage factory workers (many of whom were children) continued to toil in unsafe conditions for decades, all in the name of increasing productivity. It took years, but eventually, the organisation of labour unions put measures in place to protect workers from the excesses of the push for productivity.

THE BIRTH OF  CONSULTANTS

Although the 20th century was rocked by two World Wars and the Great Depression, productivity was a focal point for manufacturing goods needed to support military efforts and later, to satisfy the demands of the growing middle class.

So it was ripe for the rise of the earliest efficiency expert, an industrial engineer from Philadelphia named Frederick Winslow Taylor. Nicknamed Speedy Taylor, he would get himself a consulting gig with a company, observe its workers, and calculate how they could do their jobs faster – and then charge a hefty sum for the report.

Peers Frank and Lillian Gilbreth were mining a similar productivity vein by dividing human action into 17 motions and then determining which was the most efficient and effective way to do any task.

From these somewhat ignominious beginnings (Taylor was believed to be a liar who fudged his numbers, and Frank was famous for saying postpartum bedrest was a waste of time–prompting Lillian to keep working after the birth of each of her 15 children) grew a sizeable industry of management consultants who aimed to tackle the productivity problem from every possible angle.

THEN CAME THE PRODUCTIVITY GURUS

Among the more recognisable players is Tom Peters, whose book In Search of Excellence chronicles the productivity practices of “America’s best-run companies.”

Michael Porter wrote Competitive Advantages, also exalting the leadership of productive management practices.

And Bill Smith, an engineer at Motorola, introduced Six Sigma in 1986 as “a disciplined, data-driven approach and methodology for eliminating defects in any process – from manufacturing to transactional, and from product to service.”

According to Six Sigma, “Productivity is much more important than revenues and profits of the organisation because profits only reflect the end result, whereas productivity reflects the increased efficiency as well as effectiveness of business policies and processes. Moreover, it enables a business to find out its strengths and weaknesses. It also lets the business easily identify threats as well as opportunities that prevail in the market as a result of competition and changes in business environment.”

THE CURRENT STATE OF PRODUCTIVITY AND WHAT’S NEXT

The thing is that in the frenzy to be more productive, we as a nation have become a little less so.

Economist Robert Gordon of Northwestern University chalks this up to the fact that we are using methods and procedures that are over a decade old. He told the Atlantic, “We had a great revolution in the 1980s and ’90s as businesses transitioned from paper, typewriters, filing cabinets to personal computers with spreadsheets, word-processing software. And then that revolution was accompanied in the 1990s by the internet, by free information through search engines, through e-commerce, and doing away with paper.” Until we start incorporating more robots and AI to take over our rote tasks, this downward trend will continue.

WORK SMARTER, NOT HARDER

The other obsession with productivity is entwined with a false belief that we need to be working all the time to be our most productive selves. And that’s simply not true.

As Leila Hock, a career coach, points out: “It’s not hard work – work is work, and yes, some work requires more brain power, but most of us smart people like that and want more of it, so let’s stop calling it hard. Let’s call it productive. Effective. Valuable. Anything that speaks to nature over quantity, because that’s what we need more of.”

So maybe Ben Franklin’s to-do list had it right all along.

Work and assess what good was accomplished that day – then the most productive day will have the most good attached to it.

A famous fire that changed workers’ rights

The following are extracts from a publication by the AFL-CIO, America’s Unions

On Saturday, March 25, 1911, a fire broke out on the top floors of the Triangle Shirtwaist factory in New York

Firefighters arrived at the scene, but their ladders weren’t tall enough to reach the upper floors of the 10-story building. Trapped inside because the owners had locked the fire escape exit doors, workers jumped to their deaths. In a half an hour, the fire was over, and 146 of the 500 workers—mostly young women—were dead.

The fire alone wasn’t what made the shirtwaist makers such a focal point for worker safety. In fact, workplace deaths weren’t uncommon then. It is estimated that more than 100 workers died every day on the job around 1911.

What it did do was bring attention to the events leading up to the fire which, after the fire, inspired hundreds of activists across the state and the nation to push for fundamental reforms.

The Life of a Shirtwaist Maker:

The shirtwaist makers, as young as age 15, worked seven days a week, from 7 a.m. to 8 p.m. with a half-hour lunch break. During the busy season, the work was nearly non-stop. They were paid about $6 per week. In some cases, they were required to use their own needles, thread, irons and occasionally their own sewing machines. The factories also were unsanitary, or as a young striker explained, “unsanitary—that’s the word that is generally used, but there ought to be a worse one used.” At the Triangle factory, women had to leave the building to use the bathroom, so management began locking the steel exit doors to prevent the “interruption of work” and only the foreman had the key.

The “shirtwaist”—a woman’s blouse—was one of the country’s first fashion statements that crossed class lines. The booming ready-made clothing industry made the stylish shirtwaist affordable even for working women. Worn with an ankle-length skirt, the shirtwaist was appropriate for any occasion—from work to play—and was more comfortable and practical than fashion that preceded it, like corsets and hoops.

Clara Lemlich:

Years before the Triangle fire, garment workers actively sought to improve their working conditions that led to the deaths at Triangle.

In 1909, as factory owners pressed shirtwaist makers to work longer hours for less money, several hundred workers went on strike.

On Nov. 22, a section (Local 25) of the International Ladies’ Garment Workers’ Union (ILGWU) convened a meeting to discuss a general strike. Thousands of workers packed the hall.

Nineteen-year-old Clara Lemlich was sitting in the crowd listening to the speakers—mostly men—caution against striking. Clara was one of the founders of Local 25, whose membership numbered only a few hundred, mostly female, shirtwaist and dressmakers. A few months earlier, hired thugs had beaten her savagely for her union involvement, breaking ribs.

When the meeting’s star attraction, the American Federation of Labor President Samuel Gompers, spoke, the crowd went wild. After he finished, Clara expected a strike vote. Instead, yet another speaker went to the podium. Tired of hearing speakers for more than two hours, Clara made her way to the stage, shouting, “I want to say a few words!” – once she got to the podium, she continued, “I have no further patience for talk as I am one of those who feels and suffers from the things pictured. I move that we go on a general strike…now!”

The audience rose to their feet and cheered, then voted for a strike.

The Uprising of 20,000:

The next morning, throughout New York’s garment district, more than 15,000 shirtwaist makers walked out.

They demanded a 20% pay raise, a 52-hour workweek and extra pay for overtime.

The local union, along with the Women’s Trade Union League, held meetings at dozens of halls to discuss plans for picketing. When picketing began the following day, more than 20,000 workers from 500 factories had walked out. More than 70 of the smaller factories agreed to the union’s demands within the first 48 hours.

Meanwhile, the fiercely anti-union owners of the Triangle factory met with owners of the 20 largest factories to form a manufacturing association. Many of the strike leaders worked there, and the Triangle owners wanted to make sure other factory owners were committed to doing whatever it took—from using physical force (by hiring thugs to beat up strikers) to political pressure (which got the police on their side)—to not back down.

Soon after, police officers began arresting strikers, and judges fined them and sentenced some to labor camps. One judge, while sentencing a picketer for “incitement,” explained, “You are striking against God and Nature, whose law is that man shall earn his bread by the sweat of his brow. You are on strike against God!”

The struggle and spirit of the women strikers caught the attention of suffragists. Wealthy progressive women like Anne Morgan (daughter of J.P. Morgan) and Alva Belmont (whose first husband was William Vanderbilt) believed that all women—rich and poor—would be treated better if women had the right to vote. Alva saw the labor uprising as an opportunity to move the women strikers’ concerns into a broader feminist struggle. She arranged huge rallies, fund-raising events and even spent nights in court paying the fines for arrested strikers.

The coalition of the wealthy suffragists and shirtwaist strikers quickly gained momentum and favorable publicity. Fifteen thousand shirtwaist makers in Philadelphia went on strike, and even replacement workers at the Triangle factory joined the strike—shutting it down.

A month into the strike, most of the small and mid-sized factories settled with the strikers, who then returned to work. The large factories, which were the holdouts, knew they had lost the war of public opinion and were finally ready to negotiate. They agreed to higher pay and shorter hours but refused even to discuss a closed shop (where factories would hire only union members and treat union and nonunion workers equally in hiring and pay decisions).

At a series of mass meetings, thousands of strikers voted unanimously to reject the factory owners’ proposal. They insisted on a closed shop provision in which all employees at a worksite were members of a union. For these young women workers, the strike had become more than taking a stand for a pay raise and reduced work hours. They wanted to create a union with real power and solidarity.

While a closed shop became standard practice in later decades, at the time, their insistence seemed radical. The issue unraveled the alliance between the union and the wealthy progressive women. But by then, only a few thousand workers were still on strike, from the largest, most unyielding companies—including Triangle.

  • In February 1910, the strike finally was settledThe few remaining factories rehired the strikers, agreed to higher wages and shorter hours and recognized the union in name only, resisting a closed shop.
  • Local 25, which prior to the strike represented only a few hundred members, now had more than 20,000.
  • However, workers at Triangle went back to work without a union agreement. Management never addressed their demands, including unlocked doors in the factory and fire escapes that functioned.

 

The Legacy of the Shirtwaist Makers:

A week after the fire, Anne Morgan and Alva Belmont hosted a meeting at the Metropolitan Opera House to demand action on fire safety, and people of all backgrounds packed the hall.

A few days later, more than 350,000 people participated in a funeral march for the Triangle dead.

Three months later, after pressure from activists, New York’s governor signed a law creating the Factory Investigating Commission, which had unprecedented powers – they first enacted laws covering fire safety, factory inspections and sanitation and employment rules for women and children – then entirely rewrote New York State’s labor laws and helped create the nation’s most sweeping worker protections.