Billionaires reveal their secrets

An interesting piece by Jade Scipioni in a CNBC news piece ‘Beyond the Valley’

There are some 2,600 billionaires in the world — and more than two-thirds are self-made

A few have of the latter have shared lessons on life and how they found success

Warren Buffett, worth some $80 billion – Invest in yourself:

  • By far the best investment you can make is in yourself: 
    • The best way to do that is by first learning to communicate better, both in writing and in person, as it will increase your value by at least 50%
    • If you can’t communicate to somebody, it’s like winking at a girl in the dark – nothing happens
    • You have to be able to get forth your ideas
  • Start taking care of your body and your mind when you are still young:
    • You get exactly one mind and one body in this world, and you can’t start taking care of it when you’re 50
    • By that time, you’ll rust it out, if you haven’t done anything – so it’s just hugely important
    • And if you invest in yourself, nobody can take it away from you
  • If you get to be 65 or more, and the people you want to love you actually do love you, you’re a success

Jeff Bezos, worth some $111 billion – Change your mind:

  • Bezos started building Amazon by selling books out of his Seattle garage in 1994
  • It is crucial to be open and willing to change your mind.
  • They have the same data set that they had at the beginning, but they wake up and reanalyse things all the time and they come to a new conclusion and then they change their mind
  • People who typically win in life have worked hard to recognise what beliefs or biases they hold and actively try to look for evidence that disconfirms them
  • This allows you and your business to be more creative, flexible and ultimately more successful

Bill Gates, worth some $113 billion – Surround yourself with the right people

  • A lot could go to one’s head when you have tens of billions in the bank
  • Gates stays humble by doing normal things like washing the dishes after dinner each night and driving his kids to school in the morning
  • He also surrounds himself with people who keep his ego in check, including his wife, Melinda, his three children and his best friend, fellow billionaire Warren Buffett.
  • If I come back and I look like I’m all puffed up, they cut me down to size a little bit

Jack Ma, worth $46 billion – Anybody can be successful if you try hard

  • Jack Ma grew up in China and was rejected from 30 jobs before being introduced to the internet in 1995
  • With no marketing or legal skills, knowledge of technology or money, he started the Alibaba e-commerce group in his apartment
  • We had almost nothing, but we believed in the future,” Ma said
  • The three keys to success are to think differently, never give up and use the skills that you have currently
  • If everybody agrees, then there is no opportunity – to be successful it’s essential to think about things that no one is thinking about yet
  • Ma was also rejected by Harvard (he applied 10 times) and says that you can’t let rejection stop you
  • Of course, you are not happy when people say ‘no’ – so have a good sleep, wake up and try again
  • And use what skills you have – in his case he was good at customer service
  • “I only know about people”
  • “When you spend time on the people you serve, when they’re happy — you win!”

AI promises huge productivity gains for financial services

In an article by Donna FuscaldoArtificial intelligence) will bring lots of gains to the financial services industry, whether it’s through automating processes or adding more convenience for their customers.
But now we can quantify just how big of an enhancement AI will have on the bottom line for financial services companies around the globe. According to consulting firm Accenture it’s $140 billion. That’s in productivity gains and cost savings by 2025, all because of artificial intelligence and augmented technology.

Accenture recently studied the changing face of the workforce as disruptive technologies become more prevalent in companies around the world. The consulting firm found around 50% of tasks in the financial services industry could be augmented with technology by 2025, which will result in a big increase in productivity – for example:

  • AI could aid financial advisors in making real-time stock picks
  • Or help loan underwriters better gauge the risk of borrowers
  • Or it could enable banks to offer customised products based on an individual’s personal finance habits


Banks are expected to generate $59 billion in productivity gains by augmenting skills with technology while insurance companies can expect to generate $37 billion in gains and capital markets companies are forecast to realize $21 billion in productivity increases.

While financial services companies have already seen big boosts in productivity and efficiency thanks to automating data entry, processing, and account reconciliation there’s room to do more. Accenture said anywhere from 7% to 10% of tasks within banks, insurers, and capital market firms could be automated savings banks $12 billion, insurers $7 billion and investment firms $4 billion.
With all this augmenting and automating going on it also means the face of financial services firms’ workforce has to change. As it stands there’s a dearth of workers skilled in these advanced technologies making it hard to find talent. As more companies embrace AI, data analytics and machine learning, it’s only going to get tougher to find top talent.
At the same time, many companies lack a clear plan to prepare their workforce for roles in which technology and humans work side by side. Without those transformations, companies will never achieve the billions of dollars in productivity gains that Accenture says is available to them.

“There’s a new era ahead for financial firms that see the value of combining human ingenuity and personal touch with technology efficiency and precision to create new sources of growth,” said Cathinka Wahlstrom, who leads Accenture’s Financial Services practice in North America when announcing the research results. “This isn’t about cutting costs to improve the bottom line, it’s about embracing technology to transform the workforce.”

The scarcity of workers who possess data analytics, cybersecurity, and AI skills can’t be met by recruiting more people. It has to be solved by reskilling existing employees so they can deliver value to the enterprise almost immediately, argues Accenture. By automating some job functions the employee can be redirected to focus on high-value work whether that’s building customer relationships or coming up with new products or services. It’s not that computers will replace workers, it’s that computers will work alongside them.

“Traditionally companies have said OK we will recruit more people but what we’re saying in this report is you can’t just go get more people. There aren’t enough people with the skills,” said Bridie Fanning, Accenture’s talent & organisation practice lead for financial services.  “They are much better off if they reskill their people and get them the training they need.”

2020 foresight for fossil-free energy

A report by Kelsey Warner in The National says that, over the next 10 years, the Middle East’s biggest export could become the sun, not oil, thanks to new technology that turns solar power into fuel

A new Bill Gates-backed clean energy company, Heliogen, based in Lancaster, California, has concentrated solar energy to exceed 1,500°C – at that temperature, they can split water molecules to make 100% fossil-free fuels such as hydrogen

And in addition to creating green fuel, the technology can also replace fossil fuels in the production of cement, steel and petrochemicals, dramatically reducing greenhouse gas emissions

“I’m so excited that it’s actually possible,” Bill Gross, founder and chief executive of Heliogen, told The National

“The decade of the 2020s is going to be a decade where we make or break it”

Although concentrated solar power has been used before, it has never reached the temperature required to make cement or steel – indeed, cement alone accounts for 7% of global carbon dioxide emissions, according to the International Energy Agency

The task ahead is convincing industrial energy producers to replace their old methods with this new alternative – and high on the list is the Middle East

Gross said: “They have the money, the land, the sun, and the will – they also talk of their vision for how they want to transform their economy – they will still be making fuel, but it will be fuel that didn’t come from digging – it will be fuel that came out of the air, from water and air”

Gross calculates that Saudi Arabia could fully replace its oil exports with green solar-generated hydrogen if it commits just 4% of its land – some 1,000 square kilometres – and invests $400 billion in developing a concentrated solar park.

The fact that Heliogen has solid financial backing from Bill Gates means they can potentially survive the so-called valley of death period between having a technical prototype and a system that is commercially ready for the market

Nevertheless, Gross says: “We’re picking the first customer now – it’s probably going to be a mining or minerals company in the Mojave Desert [in California] where I can show it on a big enough scale that Saudi Arabia can copy”

“Accelerating clean energy innovation needs to be a priority” says Espen Mehlum, head of energy at the World Economic Forum – “Clean-tech development is too slow and many technologies are needed to meet the global climate targets”

Gross echoes that sentiment: “It makes me more optimistic because I feel there is a technological solution to greenhouse gas emissions” – “It makes me nervous that we won’t adopt it fast enough”

The Heliogen team is made up of 20 scientists and engineers, mainly from Caltech and MIT (Massachusetts Institute of Technology), who have been working for several years to combine mechanical engineering with massive strides in computer science and computing power

Heliogen uses computer software to align a large array of mirrors extremely accurately to reflect sunlight on to a single target – the amount of computing power needed to assess and capture the maximum amount of solar energy possible in real-time was not commercially feasible five years ago – but now it is

According to Gross: “This is so big I can’t do it all myself”

“I just want to show people there’s a way – I hope people steal this idea”

Wasted time at school

Government sanctioned waste has a lot to answer for

Ministers might bang on about the importance of productivity improvement but their thinking seems restricted to vital investment in infrastructure, R&D and skills training

Drive around any town mid-afternoon and see streams of kids walking home from school – and wonder what they do when they get back home, often to an empty home – homework, maybe, but not for long – or play some records, but again not for long

In fact, many change into casual clothes and go out again to meet their chums, play games or hang around on street corners

They’ve got bags of stored-up energy which needs to be released – they seek some fun, excitement even – many channel this energy into positive activities – however, some get up to mischief, join gangs and indulge in petty crime or worse, not least because they’re bored and have nothing else to do

Meanwhile, at the same time, all their expensive school facilities lie empty – available but unused – for example, playing areas/ fields for different sports and kids to compete against each other or other schools , gymnasiums for exercise and fitness training, rooms and instruments for kids to learn to play chess, the piano or guitar , or form pop bands, orchestras or choirs

Overall, costs are not reduced by tipping the kids out onto the streets at 2-3 p.m. – their grey cells may be too tired to absorb more prescribed knowledge by then but why not keep them back until much later (6 p.m. say) and convert the school into something akin to a youth club after their lessons have finished – in their free time, most kids prefer to be with chums their own age anyway

And this could be done without asking current teachers to work longer hours – old boys and girls who had recently left the school could be recruited as relatively inexpensive teachers’ assistants to lead/ supervise/ referee/ train groups of the kids using all the school’s facilities – this would be a formalised work experience for them

Huge benefits to society as a whole would accrue if such a simple policy was adopted, including:

  • Expensive child-care costs for many families would be decimated at a stroke
  • Many more parents, especially those with valuable experience, would be released to join the national labour force – currently, there’s a looming shortage in all developed nations
  • Kids would enjoy a broader education by learning stuff outside the narrow curriculum
  • Kids would also be better prepared for competing in the big wide world after leaving school
  • Petty crime would fall
  • Many kids would be deterred from lives of crime
  • Fewer kids would drift into using or selling drugs, not least because ‘county lines’ recruitment would become more difficult

Indeed, years ago, youth clubs took on much of this role, but far too many of them have since been disbanded, for one reason or another

So one has to ask why the government does not implement such changes – the penalty costs of the current waste of existing school facilities must surely be in the £ billions

It’s yet another open goal for ministers to consider when chasing national productivity improvement




Productivity crisis fixed?

The Times has announced a project to be run by the strangely named ‘Be the Business’, a government sponsored initiative aimed at solving the productivity crisis said to be afflicting the nation

100 big companies, including Amazon, Aviva, BAE systems, British Land, Cisco, Google and Rolls Royce, ‘will promise to boost UK productivity by encouraging greater adoption of tech skills among their suppliers and offering mentor programmes for managers’

The rationale for this venture seems to be as follows, with our first reactions attached:

  • Current ONS statistics on GDP and national productivity are accurate and useful – they’re not – such stats prompt no action by individual businesses and are meaningless to individual citizens – and some say they’re ‘dangerously misleading’ for government ministers when policy-making
  • ‘Economic growth across the country is stalling’ says Charlie Mayfield, also boss of the the retailer John Lewis, much in the news recently for underperforming – actually, current mis-measurement of GDP is such that the UK may even be performing well – nobody truly knows!
  • ‘Productivity has barely improved over the last decade’ so the impact on the economy and our standard of living has been ‘severe’ –  whilst a social inequality gap still exists in the UK, the rich v poor ratio has continued to fall dramatically – most now have an acceptable standard of living and have moved on to seeking a better quality of life – national measures need to recognise this change
  • Small firms and the self-employed form the UK’s ‘long-tail’ of poor performers – the implication is that all big firms in any sector are best performers employing best managers who use best methods – this was not my experience and is clearly not so
  • If the ‘long tail’ acquire more tech skills and mentoring from the big boys (their customers) quantum leaps in productivity and revenue/ profits/ tax-take will result – many of the big boys fail to make big improvements when trying latest fads (aka tech skills?) such as Lean or Agile – they ignore the huge benefits on offer from truly putting their customers first, identifying and cutting causes of waste and making better use of existing resources –  and such actions don’t need any outside support (from consultants or the big boys’ surplus managers) or ‘best practice’ transfers, just internal enthusiasm and common-sense


All up, we hope we’re wrong about this latest venture – indeed, we hope it makes a big quantifiable difference for many people and businesses in the near future

At present, however, it seems to be yet another initiative that enjoys an initial fanfare of publicity and hope but lacks the beef to follow



More recognition of ‘consumer surpli’

A splendid article by Diane Coyle, Professor of Public Policy at the University of Cambridge and contributor to, has just been posted by the East African Business Week – it’s entitledRethinking Productivity’ and helps explain much of the current productivity puzzle supposedly afflicting many developed nations, including the UK

The word “productivity” typically calls to mind industrial assembly lines pumping out cars or washing machines, breakfast cereal or shoes.

The word may also conjure images of crops being harvested, livestock being butchered, or houses being built. It is less likely to elicit thoughts of haircuts, streaming television, or mortgages.

Yet nowadays, it is largely these kinds of intangible goods and services that define economies.

Many economists equate “total factor productivity” with technological progress. Northwestern University’s Robert Gordon, for example, predicts that productivity growth will continue to slow – as it has done in most developed economies since the mid-2000s –because today’s digital innovations are, in his view, less transformative than earlier advances like the flush toilet, radio, and the internal combustion engine.

But, today, about four out of every five dollars spent in the leading OECD economies purchase services or intangible goods.

This “dematerialisation” of economies – which I observed in the 1990s, and which figures like digital economy expert Andrew McAfee have lately been exploring – is complicating our understanding of productivity.

In fact, in much of today’s global economy, even the production of tangible goods is shaped by a growing number of intangible factors.

As Seth Lloyd of the Santa Fe Institute has pointed out, a farmer hedging against bad weather or disease now operates largely in the realm of ideas.

Whereas in the past, farmers would “insure” against the failure of one type of crop by planting others or raising livestock – that is, through physical diversification – today they do so largely by applying agricultural science, like testing soil and assessing climate conditions, or even by participating in options markets.

Such intangibles – in addition to new technologies, such as irrigation – produce the discrepancies McAfee observes in crop tonnage produced from the same amounts of inputs.

Still, when it comes to agriculture, the end result is easily quantifiable. That is not the case for many other modern productivity-boosting innovations.

In a recent presentation, Leonard Nakamura of the Federal Reserve Bank of Philadelphia offered several examples, including energy-efficient buildings, lane-keep-assist and parking sensors in automobiles, and GPS navigation.

Innovations in health-care treatment also qualify. For example, using the cancer drug Avastin to treat macular degeneration is far less expensive than using Lucentis, one of the drugs originally approved for that purpose.

In theory, the effects of some of these innovations on productivity could be quantified through quality-adjusted pricing. Cars with sensors that facilitate parking and improve road safety might be discounted, resulting in a higher “real” measured output for cars.

But, in practice, such adjustments pose a significant statistical challenge, owing to the pervasiveness of the underlying technologies. Consider GPS navigation: how do you quality-adjust for the use of apps like Waze or Google Maps?

When it comes to medical, legal, and other professional services, quantifying productivity is even trickier. One approach focuses on outcomes – say, a longer career (thanks to better health care) or higher profits (thanks to management consultants).

But these improvements cannot be traced back to a single factor. Doctors and hospitals are essential to extend people’s healthy lives, but so are living conditions, diet and exercise, social connections, and even having a pet. Luck – for example, not being exposed to a disease outbreak – also plays a role.

Some of my University of Cambridge colleagues are working to deepen our understanding of these dynamics by examining the connections between social capital and productivity.

This approach – which reflects a shift toward a broader view of productivity – is a step in the right direction.

This conclusion seems to be borne out by history. As Corinna Schlombs of the Rochester Institute of Technology shows in her new book ‘Productivity Machines’, in the twentieth century, one of the key differences between the approach of American industrialists and productivity experts and that of their European counterparts was that the latter were more likely to view productivity in purely technical terms.

After World War II, during the Marshall Plan era, Americans showed visiting European workers and industrialists new ways to organise production. (The assembly line is as much an idea as a technology.)

Moreover, they touted America’s more egalitarian social dynamics, including its public school system and broad civic involvement. The recognition that “soft” innovations were at least as important as “hard” technologies, Schlombs suggests, was the decisive factor behind America’s superior productivity.

So perhaps today’s pervasive productivity slowdown should not be blamed solely on an unsupportive macroeconomic environment, let alone on inadequate technological innovation. (Software engineers and biomedical researchers would scoff at the latter notion.) Social and cultural contexts that are fragmented, unequal, or otherwise problematic may also be playing a role.


Wasting time is not wasted time

Rest periods, R & R, tea breaks, lunch breaks and most meetings – call them what you will – are essential for brawn workers’ muscles to recover – they couldn’t work at full speed for a solid eight hours – just as Usain Bolt couldn’t run full pelt over 400 metres compared with 100 metres

But times have changed – brawnwork no longer dominates the world of work – brainwork has taken over, at least in developed nations

However, brainworkers also need rest breaks, so their brain cells can recover, be re-energised and think creatively

For them, it’s not time inputs and tasks completed versus target that matter – it’s results – results in meeting customers’ needs well, whether those customers are external and paying for the services offered or internal, further down the line, and needing their outputs RFT (Right First Time) so they can complete their work too

Brawnworkers are never expected to be able to work flat out for the whole eight hours of their shift – the same applies to brainworkers, only even more so – if in any doubt,  remember how exhausted you felt after concentrating for just three hours trying to complete an  exam paper

However, one forever reads of organisations forbidding their employees to use their iPhones whilst at work – we say let them – allow them to use Facebook or Whatsapp for as long as they like, chit-chatting to their chums – it helps resuscitate their grey cells

Indeed, let them spend their time at work however they want – even offering them the options of working flexi-time or from home part-time

But let them know they are  accountable for the results their customers, and so you, expect

More often than not, managers are surprised by the increases in productivity and morale that follow


National inputs also ‘seriously flawed’

Official measures of GDP are said to be ‘seriously flawed’

Now, a report by the OECD (Organisation for Economic Co-operation and Development) and the Centre for Cities think tank claims ‘millions more people are unemployed than official statistics suggest’

Worse still: “The joblessness rate could be three times higher than thought” because some three million people who are able and keen to work are being excluded from the register by being classified as economically inactive i.e. not in work, nor looking for work

The official unemployment rate     =      Total number of people out of work

Total economically active population

Given the current official UK unemployment total is at an apparent record low of 1.3 million (4.6%), then adding  another 3 miilion somewhat spoils this government claim, increasing the unemployment rate to 13.2%

The report thus calls on the government to increase investment in skills for people who have been out of the labour market for a long time – albeit without saying by how much and in what skills

In response, the ONS (Office for National Statistics) which produces the official unemployment statistics said:

  • Its headline figures are based on internationally agreed definitions
  • If they were widened, it would stop being a measure of spare employment capacity (i.e. precisely what the 3m are)



  • With the above huge discrepancy bewteen the official and actual unemployed figures, one can only wonder about the validity of the ONS’s official national (labour) input and so productivity statistics produced each quarter
  • National GDP output measurement is already said to be ‘seriously flawed’
  • Now, the same seems to apply to national labour inputs


At last, official recognition of the ‘GDP gap’

Yian Mui reports on CNBC that the US Federal Reserve wants to know what the internet is worth to you.

He says the answer could help the central bank solve one of the most puzzling paradoxes of the modern economy: The current expansion is the longest in history, yet productivity gains are weak and GDP growth, while steady, is far from stellar.

In a speech this week, Fed Chairman Jerome Powell raised the possibility that the problem is with the data itself. GDP measures the value of products and services that are bought and sold. But many of the greatest technological innovations of the internet age are free. Search engines, e-mail, GPS, even Facebook — the official economic statistics are not designed to capture the benefits they generate for businesses and consumers.

“Good decisions require good data, but the data in hand are seldom as good as we would like,” Powell said.

Instead, Powell cited recent work by MIT economist Erik Brynjolfsson, one of the leading academics on the intersection of technology and the economy. In a paper with Avinash Collis of the National Bureau of Economic Research and Felix Eggers of the University of Groningen in the Netherlands, the authors conducted massive surveys to estimate the monetary value that users place on the tools of modern life.

The results?

  • The median user would need about $48 to give up Facebook for one month
  • The median price of giving up video streaming services like YouTube for a year is $1,173
  • To stop using search engines, consumers would need a median $17,530, making it the most valuable digital service.


The authors also conducted more limited surveys with students in Europe on other popular platforms:

  • One month of Snapchat was valued at about 2.17 euros
  • LinkedIn was just 1.52 euros
  • WhatsApp would require a whopping 536 euros
  • Twitter, however, was valued at zero euros

“Over time, we’re spending more and more of our waking hours interacting with the internet or using those services on our mobile phones,” Brynjolfsson told CNBC – “A bigger share of our economy is being missed by GDP.”

Brynjolfsson is advocating an entirely new measure of economic health that calculates benefit rather than output. He calls it GDP-B and estimates that the welfare gains from Facebook alone would have added 0.05 to 0.11 percentage points to its annual growth.

“What we really care about if we want to know how well off people are is the consumer surplus — how much benefit you get — not how much you actually pay,” Brynjolfsson said.

Inside the Fed, a separate effort is underway to value the digital economy.

Powell also highlighted research by David Byrne and Carol Corrado that uses the volume of data transmitted through broadband, cable and WiFi to estimate the value of online products and services. Their analysis shows that GDP would have been half a percentage point higher over a decade if the full scope of the digital economy had been incorporated.

“The highly visible innovations in consumer content delivery raises the question of whether existing national accounts are missing consequential growth in output and income associated with content delivered to consumers via their use of digital platforms,” the authors say in their paper.

Powell delivered his speech at an annual convention of economists, where the theme was integrating old and new economies. At one point, Powell even waxed philosophical.

“How should we value the luxury of never needing to ask for directions?” he asked. “Or the peace and tranquility afforded by speedy resolution of those contentious arguments over the trivia of the moment?”

The answers to those questions may not be far off.


  • Given we’ve been banging on about this significant GDP gap for quite some time, how satisfying to find that the big boys not only have recognised it but also seem to be doing something about it
  • Sadly, however, national economic policies will continue to be decided using the current dismal measures which only relate to the old materialist/ tangible world – so those policies may, or may not, be the right ones for the new material plus mental world we now live in

New UK ‘Productivity Institute’

Productivity of UK businesses is set to be supercharged with £88 million in new government investment announced the Department for Business, Energy & Industrial Strategy:

  • £88 million new government investment to help close the productivity gap between UK and major world economies and turbocharge British businesses
  • investment will help power the next generation supercomputers which could improve business efficiencies, including providing up-to-the-minute weather forecasts
  • funding will help kickstart the UK’s largest and most ambitious productivity institute, helping examine how to boost productivity levels across the country

Levels of productivity across certain sectors in UK manufacturing, like aerospace, are among the highest in Europe, but overall UK productivity still lags behind major global economies and certain sectors, including chemicals and textiles, find it harder to grow.

By adopting new technologies and more efficient business practices, the productivity of businesses, particularly small ones, could be increased. This will help them to scale up and expand into new markets – boosting competition and ultimately benefiting consumers with lower prices or better quality products and services.

£43 million in government investment will support top researchers and analysts to explore how to turbocharge UK productivity levels through a new ambitious productivity institute; tackling barriers such as productivity imbalances between sectors and regions, poor management practices and skills investment.

Experts will work closely with businesses to power the UK towards a more competitive and resilient economy, as well as the public sector and policymakers, aiming to deliver benefits for both businesses and consumers. Increased productivity can drive up wages, lower prices of products and improve working conditions.

The announcement comes as ministers visit new infrastructure projects across the country to highlight government investment in connectivity. Infrastructure is one of the 5 foundations of productivity highlighted in the Industrial Strategy and the Prime Minister has been clear that this government will level up infrastructure across the country with new road and rail investment and full fibre broadband.

Business Secretary Andrea Leadsom said:

  • Productivity matters – if we produce more, we can earn more, as individuals and as a society.
  • Today’s investment will allow us to develop pioneering software to harness the power of supercomputers and create a state-of-the-art Productivity Institute.

A further £45 million will be specifically invested by the government into the development of cutting-edge supercomputer software, set to transform whole sectors from agriculture and advanced aerospace to Formula One and pharmaceuticals with hyper-accurate weather predictions – helping them plan come rain or shine and in turn boost their productivity.

Involving the Met Office, this radical development could mean businesses will receive up-to-the-minute weather forecasts, so they are not ‘caught in the rain’ and can focus on delivering their products and services effectively and efficiently. This knowledge could help farmers protect crops for consistent food supplies, help airports keep flights running – and businesses can foresee the impact on infrastructure that cause downtime like flooding, for example.

With the potential to provide more accurate predictions, supercomputers are helping businesses plan methodically. Research software engineers and scientists will work together to futureproof the UK against the fast-moving changes in supercomputer designs, pushing the boundaries of science and preventing compatibility issues or lags – which could pose a threat to disciplines such as weather and climate prediction, to complex aircraft design and drug development.

Named ‘ExCALIBUR’, the project will ensure the UK can meet the scientific and engineering challenges of the future with maximum efficiency and safeguard future industry productivity.

Met Office Director of Meteorological Science, Simon Vosper, said: “The ExCALIBUR project will establish a national capability in scientific computer software that mirror the real world, accelerating advances in a wide range of important areas that rely on cutting edge computer technology: from climate prediction to drug research and nuclear fusion”.

Professor Jennifer Rubin, Executive Chair of ESRC (Economic and Social Research Council), said:

  • Raising productivity is arguably the greatest economic challenge of our time, and is needed to increase wages and living standards, and to ensure benefits can be spread across sectors and regions.
  • This significant investment in understanding what will drive improvements in productivity is an important opportunity for research to make a contribution to improving quality of life and economic performance.

The £88 million funding forms part of the government’s Strategic Priorities Fund (SPF), and follows the government reaffirming its commitment to invest at least 2.4% of GDP in R&D by 2027. The government has made making boosting productivity and increasing earning power a priority – making the most of untapped potential right across the UK.


1. About the Strategic Priorities Fund:

  • the SPF supports high quality multidisciplinary research and development priorities
  • this is the second wave of funding
  • the SPF Wave 2 total programme funding allocation is £496.8 million


2. About the programmes:

  • Transforming Productivity: National Institute of Excellence (ESRC)
  • ESRC with Innovate UK HMT, BEIS, DWP and MHCLG
  • Funding requested: £42.2 million over 6 years.


Location(s): This funding is to create an institute that creates a national capability for productivity.

HEIs, Institutes, PSREs will be able to bid for funding.

The location of the Institute and any partners will be announced following a competitive process.

This SPF will invest in an ambitious, strategically driven, world class institute to provide a systematic understanding of what is required to solve the UK’s productivity challenges.

The institute will provide a convening hub for wider research as well as undertaking its own research, bespoke analysis and evaluations.

The Institute will also design and test interventions: translating findings and scaling-up solutions in collaboration with business and policy-makers.

The institute will be driven by high profile leaders; combining permanent academic researchers and analysts with seconded world-leading experts, drawing in outstanding fellows from relevant research, public and private sector organisations with an interest in understanding and improving productivity.

The project will be delivered with £30 million funding for the Productivity Institute and £11 million for open research calls.

Fast-moving advances in supercomputer architectures will render current scientific simulation codes redundant. This poses a significant threat across a range of disciplines from weather and climate prediction, through complex aircraft design and drug development, to frontier science fields including cosmology. The UK must harness the power of those advances in architecture to meet the scientific and engineering challenges facing society and mitigate the risk of this threat.

Present approaches to scientific computing are not adequate to that task.

ExCALIBUR will design cutting-edge algorithms and software for the efficient solution of scientific problems on future generation supercomputers.  A multidisciplinary cohort of research software engineers and scientists will work together to future-proof the UK against the fast-moving changes in supercomputer designs.

This will be delivered through knowledge integration activity between software engineers (£0.75 million), a scoping workshop to establish high priority use cases which will be developed through a mixture of open calls, commissioned research and single tenders (£5-7 million each), a second wave of use cases (~£2 million each), funding for disciplines with emerging requirements for high-performance algorithms (£3 million), cross-cutting research activities to drive impact (£10 million) and capital funds to develop proof-of-concept systems with new computer architectures in partnership with industry (£4.5 million).


  • We have been banging on for decades about the need for a well-funded UKPC (UK Productivity Centre), albeit independent of government, not reliant on funds from it – and run by people with a track record of success with major productivity improvement and drawn from board rooms, trade unions and academia
  • The above announcement started off well but increasingly lost me as management-speak took over
  • It’s also seemingly driven by the belief that UK productivity levels are dire compared to other G7 nations – i.e. a belief that UK official statistics are accurate when they’re woefully not
  • Last, it’s unclear just how the above institute might interact with the existing PLG (Productivity Leadership Group), PIN (Productivity Insights Network) and other well-meaning national initiatives to improve productivity
  • Hopefully it will morph into a phoenix UKPC
  • We shall see

Productivity stagnant despite global stimulus

Mark John reports that economies around the world have failed to boost productivity levels despite $10 trillion of central bank stimulus unleashed since the global financial crisis of a decade ago, according to the WEF (World Economic Forum) think tank.

Productivity, a measure of an economy’s ability to generate growth, has become of a matter of increasing concern among policy-makers around the world as headline growth rates remain weak and fears emerge of a new economic slow-down.

Publishing its annual index of competitiveness based on an aggregate of some 103 indicators (so it will be anyone’s guess which have the most impact!) the WEF urged countries to use fiscal policy and other incentives to boost research and development, workforce skills and infrastructure.

“What is of greatest concern today is the reduced ability of governments and central banks to use monetary policy to stimulate economic growth,” WEF managing board member and report author Saadia Zahidi said –

“This makes it all the more important that competitiveness-enhancing policies are adopted that are able to boost productivity, encourage social mobility and reduce income inequality,” she added.

The WEF, which hosts the annual Davos meeting of business and political leaders, compiles its index by aggregating findings from its own surveys and other sources such as the World Bank and United Nations bodies.

Highlighting some of the trends captured by the report, the WEF noted in particular that technological innovation was racing ahead of workforce skills in many countries and urged governments to focus on labor and education policies.

Citing the threat of rising protectionism, the OECD (Organisation for Economic Cooperation and Development) said last month the global economy could be entering a new, lasting low-growth phase – it estimated global growth this year of 2.9%, the lowest since the 2008-09 crisis.


  • The WEF is the self-appointed world leading economic think tank 
  • Nevertheless, they continue with their blinkered view that economic performance can only be measured from the suppliers’ perspective, clocking up their tangible outputs and inputs – the old material world dominated by the agricultural and manufacturing sectors
  • It seems the apparent failure of $10 trillion stimulus to boost apparent productivity levels causes none of them to stop and think: “Are we looking at the right picture nowadays?”
  • Imagine if they realised the economic world is at a watershed, moving from a material to mental world – a world where service sectors now dominate developed economies – a world where productivity at organisation and national level should be measured by how well one meets customers’ needs (material and mental) whilst minimising all costly inputs, not just labour
  • Then, they might find that output/ demand for material stuff has indeed started to level off as many people in the developed world consider they have ‘enough’, no matter how much stimulus is being pumped in – but demand for more new mental stuff is growing rapidly so, overall, demand is growing apace
  • It’s just that the WEF, with its 103 indicators, plus all other economists/ experts it seems, plus all their governments, don’t seem to haven’t spotted this
  • So the policies needed to boost productivity for the benefit of all are unlikely to be the policies currently followed
  • ‘What larks’! 

A National ‘Balanced Scorecard’

All nations – governments and their electorates – need a National Balanced SCorecard (NBSC) of performance measures – a set of cardinals they each can monitor which covers all important factors affecting their standard of living (SoL) and quality of lives (QoL)

The  NBSC would be a mix of measures – some absolute, some subjective – much as medal winners at the Olympics are determined either by being clearly longer/ faster/ higher or in the view of expert  judges in  their discipline e.g. gymnastics, boxing, synchronised swimming or diving

At present, government ministers have to navigate their economies based on just two bald statistics – GDP and national (labour) productivity, produced just quarterly

But no skipper, navigating his boat through dangerous waters, would rely on such a paucity of measures to decide a safe course and speed – to be in good control, he would use a set of measures – not too many or he might get confused, not too few or he might miss something important – and no crew would be happy if they knew their skipper relied on so little whilst ignoring them completely

Back on land, the same thinking applies – people want to know whether factors important to their lives are getting better or worse,  whether they’re getting good value for their taxes paid, whether their government and its managers are doing a good job and spending their money wisely

Sadly, lack of transparency at national level prevails:

  • The ONS (Office for National Statistics) produce the above two statistics – but even they are said to be ‘seriously flawed’
  • And, whilst the OBR (Office for Budget Responsibility) checks government budgets and borrowing, it does little on  how they spend the money – hence, there’s little to prevent the government spending what it wants, where it wants, perhaps unwisely
  • Overall, there’s no regular national performance scorecard issued – electorates have to suffice with a few select crumbs of information once every four or five years when general elections are held, but they are invariably biassed, not balanced – for the rest of the time, the electorates’ views are (seemingly) mostly ignored


So what factors need to be covered by an NBSC recognising that there are two distinct economic worlds out there, working in parallel?

If in any doubt, ponder why 86% of Americans already feel ‘what matters in life matters more than more stuff’ – the two are:

  • An old world of tangibles satisfying our material and physical needs
  • A new world of intangibles satisfying our mental needs


THE MATERIAL WORLD – for tangibles

  • Prosperity:
    • Current measure = GDP/ capita
    • It counts revenue, whether profitable or not, and ignores the value of fixed and current national assets
    • It’s therefore a flawed, useless measure – something better is needed
  • National output (versus income?):
    • Current measure = GDP
    • GDP is known to be seriously flawed – much national effort is uncounted or miscounted – much is estimated and so prone to error
    • Something better is needed, which includes a credible assessment of the intangible value people now get from much that is offered them
  • National inputs:
    • Current measure = Labour hours or numbers
      • Need to account for skills and experience inputs too
      • And need them broken down by sector
    • Re labour inputs, also need:
      • Average hours worked per annum
      • Average wage/ employment cost per sector
      • % unemployed
    • Capex is also ignored – it needs to be broken down by spend on:
      • Plant/ equipment – (% GDP)
      • R&D
      • Infrastructure
      • Energy supply
  • National productivity:
    • Current measure = GDP/ Labour hours or numbers input
    • This gives only part of the picture
    • It ignores the ever-increasing value of capital input
  • Poverty v Inequality index
    • Measures of both are needed
  • Housing index:
    • A measure is needed reflecting shortages and building rates


THE MENTAL WORLD – for intangibles

  • National Health index – NHI – covering:
    • Length and quality of lives
    • Quality of healthcare experienced from NHS
  • National Knowledge Index – NKI – covering:
    • Overall education levels attained
    • Quality of education experienced
    • Investment in R&D, IP, patents, broadband infrastructure
    • Accumulated knowledge, skills and experience
  • National Crime index – NCI – covering feelings of safety and security re:
    • Defence
    • Terrorism
    • Effectiveness of police/ prison/ legal systems
  • Establishment and institutional index – covering:
    • ‘Faith in Government’
    • The degree of trust affecting transactions and the provision of public goods
  • Environment index – covering:
    • The positive value of renewable resources provided by nature e.g. clean air, mountains, moorlands, open seas – the natural environment:
      • Currently fresh water and air are either cheap, or free – but we cannot live without either
      • What if they were priced with the underlying value to each of us
      • Compare water to a diamond – a lump of carbon only, and no life saver
      • For years, too much money has chased too few assets
      • So prices alone do not paint the full picture
    • The penalty costs of modern day polluters – greenhouse gas emissions, plastic rubbish in the oceans, kids ignored when young so they become criminals – who currently pay nothing towards future clean-up costs – or those destroying habitats which prevent flooding, absorb/capture carbon dioxide or provide recreation


A set of measures covering the above factors would force ministers to ‘do something’ where action was needed most – they’d be well aware of the biggest issues affecting their electorates, whether things were getting better or worse, where they needed to ‘do something’ fast

And the electorate would be able to monitor their progress


  • The principal aim of any government should be to grow the national wealth pie first (the Tories’ main aim?), then distribute it more equitably and improve public services (the Labour party’s main aim?) so all enjoy better lives than before
  • At present, most electorates have far too little information on how well their governments are spending their tax money – worse, most of the information they do get is ‘seriously flawed’ so big improvements are needed there straightaway
  • The proposed NBSC should be devised and collected by an independent survey organisation – Ipsos Mori for example
  • The problem will be government inertia if and when it comes to commissioning such an agency to collect and publish their findings for all to see – a ‘can of worms’ may then be opened for any sitting government
  • And there lies the rub!

Beware ‘snooptech’

Ben Gallagher, co-founder of B+A, a management consultancy, raised an interesting slant on new digital possibilities

‘Snooptech’, as the Telegraph reported recently, is a £2.7billion industry

The increasing sophistication of digital tools, as well as the continued stagnancy of productivity in the UK, has created a market for technology whose sole purpose is to allow companies to watch their staff and track their movements

These tools promise an alarming degree of scrutiny: there are tools which let companies record and monitor calls, emails, even keystrokes – while they might be created or used with the aim of increasing productivity, there are arguments that highlight that the unintended negative consequences of such a move might far outweigh the benefits.

First, these practices raise questions about ownership – if a business is recording everything its staff does, then in effect it is claiming the right to possess that information – and yet, at best obscured with legal language and buried deep in an employment contract, the terms of this arrangement are unlikely to be clear to the member of staff in question – the standard by which staff are being held is therefore an invisible one, and if this were not bad enough for the average employee, it’s especially concerning for creatives, who may not realise that even their half-formed ideas or earliest creative expressions, possibly not even committed to paper, could belong to someone else.

Trust is granular – it’s made up of a multitude of small acts that build up over time – this is a process that you can’t force or hasten, and it’s a natural outcome in a business that hires carefully and gives its workers autonomy within their respective roles

Of course, identifying the ‘right’ level of autonomy is a never-ending project, involving setting boundaries and then enabling team members to grow to fill them until the right relationship is reached – but business culture is like that — complex, fluid and naturally evolving in certain conditions – its intricacy and difficulty in building is proportionate to its importance

Healthy workplace cultures are also diverse – only by bringing together people with different ways of seeing, doing and being can you have the creative tension needed to arrive at new ideas – and with diversity in people comes diversity in how, where and when they are most effective – one person’s five minutes at the coffee machine is different to another’s – it’s there, while having a conversation with a colleague, that a lightbulb might go off in one person’s head – for another, that five minutes supplies the time away from the screen they need to come back to their work with renewed enthusiasm and determination

The risk with productivity tracking is that it won’t allow for personalisation of metrics – to track everyone according to the same or similar standards is to ignore the valuable differences between team members — in essence, the individuality of each person you have taken time and effort to employ – you could quickly find yourself one step removed from commodifying staff entirely, treating them like machines whose behaviour is managed with homogenised guidelines that reflect the predictable middle ground for all, rather than the brilliance of each

Finally, ‘Snooptech’ implies a number of more general qualities which should be considered catastrophic for a business in the long term, and undesirable in any person, group or institution

By defining ‘optimal’ workplace behaviour, a business assumes perfect knowledge – it’s a fundamentally close-minded approach, suggesting that the business already has the information it needs to govern the working lives of its workforce in the best possible way

There’s a real arrogance, even delusion in this – it implies that each person couldn’t possibly know which ways of working are best for them, and that there is nothing to gain by empowering them to work in that way. – but it also closes the door on creativity, which by definition is a venturing-out into the unknown – new ideas give vitality to businesses without them, they grow stale.

If the goal of all this is truly to improve efficiency, then the businesses that have embraced ‘snooptech’ suffer from short-sightedness – in the long term, there is no way that a business can thrive in a culture of paranoia such as that brought about by the enthusiastic use of workplace surveillance

Ultimately, and as many highly successful businesses are starting to recognise, those who are given permission to manage their time and their energy, to form relationships with their co-workers, and to express themselves creatively enjoy their work and work harder as a result – they work because they’re engaged, but they also work for those around them – it sometimes seems that in our relentless march to productivity, productivity, productivity, we’re actually heading in the wrong direction.


BoE powerless in UK productivity crisis

Tim Wallace in the Daily Telegraph reports Mark Carney, Governor of the BoE – Bank of England – saying: “Britain’s economy has a new, lower speed limit”

Growth can only get to even modest levels before inflation takes off whereupon ‘we must ease our foot off the accelerator’

Ben Broadbent, one of Carney’s deputies, claims: “Productivity growth has slowed in just about every advanced economy, but it has been more severe in this country than in others”

Apparently, poor investment and poor productivity growth is ‘ the biggest part of the story’ – oh, and Brexit has had an impact too

As we all know, the BoE has few clubs in its bag – bank rate manipulation is one used to drive the economy further and get it out of trouble

For the past decade, extremely low interest rates have been used to prop up demand – it keeps mortgage bills down, encourages savers to spend rather than earn measly returns – and, theoretically, businesses can fund investments more cheaply

But it has failed with business investment

Carney says we had much spare capacity in the past so lack of investment didn’t have much impact on the ‘speed limit’ of the economy

But now, labour supply and capacity is near its limit – production capacity also – so productive investment is certainly needed

One’s left hoping for the best and keeping one’s fingers crossed

After all, what are central bankers paid for?

Three Factors Of Successful Companies

Kweilin Ellingrud, a senior partner at McKinsey & Co, contributed the following interesting article to Forbes magazine


It’s been 12 years since the last recession, when the World Bank estimates that global GDP fell by 1.7%. But some companies were better prepared than others: their revenues didn’t fall as far and, as the recession ended, they recovered more quickly than their peers. Looking at what these organisations did differently, and learning lessons from their experiences can help leaders prepare for the unexpected—whatever the source of turbulence.

According to a recent study of more than 1,000 large, publicly-traded companies, three factors made the biggest difference before, during, and after the downturn:

  • Increasing productivity levels—and, crucially, making the improvements stick
  • Improving balance sheets through a combination of decreasing debt and cutting operating costs
  • Being smart with M&A activity—both in divesting underperforming businesses and in buying promising ones from other companies


The combination allowed some businesses not only to boost earnings by an average of 10% in the darkest year of 2009, but also to build on that advantage over the coming decade. This is what we mean by “resilience”: a company’s ability to generate an economic profit through cyclical and structural changes in supply and demand, balanced on twin pillars of flexibility and productivity. After 10 years, total return to shareholders for this resilient group had outperformed their non-resilient competitors by about 150%.

Given the volatility of the current economic environment, achieving resilience will require a new, flexible approach to operations. This approach applies next-generation levers such as digitisation, analytics, and automation, and integrates them to cut across silos and sustain the impact. The result helps businesses respond not only to the fast pace of change but also to an ageing workforce, increasingly regionalised value chains and rising consumer demand for fast delivery and mass customisation. Together, these forces make adaptability and responsiveness more valuable than ever before.

During previous downturns, resilient companies drove higher productivity to help protect margins. In our new digital age, digital and analytics tools allow organisations to dial production levels up or down to match demand, building a new and important factor of flexibility. It requires a focus on the success measures that really matter—defining what it means to win the day at the individual, team, business unit, and company levels. It also requires a management system that works across all levels of the organisation, empowering the employees closest to the work to inform the development of digital processes—and aligning incentives accordingly.

Companies can increase their readiness for the unexpected by making structural, strategic, and operating decisions that improve performance. Even in good economic times these are helpful actions to take, as they ensure an organisation is ready, whatever storms may come their way.

The auto industry’s performance is a good demonstration of the effect of different levels of preparedness for a downtown. During the 2007 recession globally, vehicle production dropped by nearly 16% in 2008 and 2009, and in North America vehicle production dropped by over 43%. It was not just auto manufacturers who suffered in terms of profitability, the whole value chain was impacted—several major auto OEMs and up to half of all North American auto suppliers were in severe financial distress. Bankruptcies spiked, and government support was critical to helping the industry recover.

In recent times automakers around the world have been significantly reducing their operating costs and increasing flexibility. Organisations that take actions such as these will be better positioned to cope with economically challenging times in the future.

Companies should act now, when the economy is stronger, so that they can adjust quickly to a changing environment. Automation, digitisation, and analytics are changing industries faster than ever before, and the pace of change is only accelerating. And with political flux and trade disputes on the rise, economic disruption becomes more a question of “when” than “if.”

What was “good enough” five or ten years ago will no longer do. To pivot in time, businesses need to be lighter on their feet and quicker in their reflexes. By understanding where your operations are rigid or slow today, you can take practical steps to become more resilient tomorrow—and perform much better over time

Organisation productivity measurement

Professor Jillian MacBryde from the University of Strathclyde says: “When manufacturers talk about productivity, they’re not talking about the same thing as the economists and politicians – they’re not even talking about the same thing when you go from company to company”

Such is the current fog enshrouding the productivity of UK businesses

The set of performance measures managers need depends on the level they’re’re at – organisation, process or task level – each set should cover the following areas and be focused on the few important areas under their control viz:

  • Financial results
  • Customers’ ratings on what’s offered them
  • Productivity levels
  • Team motivation levels
  • Corporate knowledge levels – within heads and files


Sadly, most managers, whatever their level, don’t have such a comprehensive set – many of their performance jig-saw pieces are missing, often leaving them dangerously exposed – they might have 100% of the financial information they need, many even too much, but only some 20% of the rest 

Hence, when it comes to productivity and measurement of whether they’re getting the most out of assets in their charge, most lack anything useful

But, if they don’t measure their productivity levels, they’ll be very lucky to improve them – it’s a major reason why the UK is said to suffer a long tail of under-performing businesses in most sectors, public and private

So what are the most important measures – the cardinals?

    • Cardinals = Revenue,  Costs and  % Profitability per product
    • Comments:
      • The great Arnold Weinstock of GEC fame used six financial measures:
        • RoCE = % Profits/ Capital Employed (CE) = Capital productivity
        • RoS = % Profits/ Sales = Sales productivity
        • Asset turn = Sales/ Assets (CE) = Capital productivity
        • Stockturn = Total cost of sales/ Total stock value = Sales productivity
        • Sales/ Employee cost = Labour productivity 
        • Profit/ Employee cost = Labour productivity


  • CUSTOMER RATINGS = Effectiveness
    • Cardinals = Rating of Price, Quality and Service levels received
    • Comments:
      • At organisation level, it’s vital that senior managers regularly monitor external customers’ ratings of the price, quality and service levels offered them – NOT what they think of what they offer them – many are surprised by the results – too many simply rely on skimpy analyses of customer complaints, warranty claims and/ or replacements needed
      • At process/ task levels, some end up serving external customers – most have internal customers who also need to be satisfied – they’re the guys next down the line to whom they pass work, and those guys don’t want to receive shoddy work which causes them problems and delay – hence, measures and systems should be in place to prevent such events regularly happening


  • PRODUCTIVITY of costly input resources
    • Cardinals = Productivity & Waste levels of costly resources i.e. Labour, Materials, Capital
    • Comments:
      • At organisation level, the productivity ratios = Total output/ Total input – but this is meaningless given many different outputs and inputs can be involved
      • Even partial productivity ratios – one type of output/ one type of input  e.g. cars/ man hour – are less than useful when output involves many different models of car and most production is achieved by robots, machines (i.e. capex), not humans
      • Efficiency, another productivity measure = How well total capacity is used = Actual net volume output/ Maximum output possible – this lets managers know their % scope to improve – but few know the capacity of a whole organisation, especially when they comprise many different inputs and outputs, entry and exit points – hence, this measure is only useful at process or task levels
      • Waste of outputs and inputs usually incurs huge but unrealised cost penalties
        • Output waste has four possible causes – each one can severely reduce gross output volume:
          • % rejects v regulations
          • % rejects v specifications
          • % rework v specifications
          • % returns from customers
        • Inputs waste = % actual gross input used/ minimum needed:
          • A% = % Available for work versus labour absent/ material stock-outs/ machines broken down
          • U% = % Utilised on productive work versus idle or wasting time
          • E% = % Efficiency when working, perhaps working slowly, below expectations


  • MOTIVATION of teams
    • Cardinal = A motivation index derived from surveying 10 factors most important to the team
    • Comments:
      • An organisations is a ‘team of teams’
      • The mood of those teams can have a major impact on customer satisfaction and productivity levels
      • Hence, managers should regularly monitor the mood of their team and act when necessary and not just occasionally notice high absenteeism or sickness rates
      • Organisation-wide employee surveys should identify where specific problems may lie – and, once held, employees expect the results to be fed back to them, and action to be taken if necessary


    • Cardinal = An index combining subjective assessments of important knowledge held ‘in heads’ or ‘in files’ which is readily available to the team 
    • Comments:
      • Corporate knowledge covers that needed to ‘keep the show on the road’ and also come up with new ideas for better ways of doing things
      • The availability, utilisation and efficiency of this vital input resource has become increasingly important to most organisations
      • Nevertheless, unlike other costly input resources, most managers have no measures to control it and so have to rely on gut-feel alone
      • Hence recruitment and training efforts are starved of knowing where serious gaps arise



  • Most managers, whatever their level, find it difficult to distil the few cardinal performance measures they need from the blizzards out there available to them
  • This is one big reason why there remains enormous potential to make big productivity improvements in all sectors, public and private – even in so-called vanguard or beacon organisations
  • Managers should stop using dubious measures simply because there’s no others available
  • Instead, they should find measures which put them in good control – otherwise, they’ll continue to be flying blind with inevitable results

Mentalism overtaking Materialism

According to official statistics, the GDPs of all G7 developed nations have been trending flat, even downward, over the last decade and more

The big question is whether, at the turn of the century, the G7 reached a watershed between their old 20th century materialist economies and the new 21st century mentalist economies – the former focused on the production of tangible stuff, the improvement of our SoL (Standard of Living) and the minimising of the negatives of life – the latter focuses on intangibles, the creation of stuff which improves our QoL (Quality of Living) and maximises the positives of our life

Consider how outputs and inputs have changed over this period


The problem here is our official bean-counters have no appropriate measures for the new mentalism world and continue to collect statistics appropriate only to the old materialist world – one where GDP either clocked the private sector’s output of tangible stuff which had a price, or the public sector’s costs which were assumed to be the value of their output

Manufacturing dominated economies (80% plus) for most of the 20th century and output value was relatively easy to count – GDP totals were thus assumed to paint a reasonably accurate picture of the state of entire developed economies 

However, by the end of the 20th century, major changes had occurred – manufacturing’s share of developed economies fell to around 20% and has continued to trend downwards – at the same time, ‘relatively-difficult-to-measure’ service sectors grew to over 80%

Now we’re well into the new 21st century – instead of just buying stuff which helps remove the chores of life and makes our lives more comfortable, many of us now have ‘enough‘ – we don’t need another car, house or pair of shoes – we just replace them when worn out – there’s nothing fundamentally new to buy to add to them now most have an iPhone – so we’ve moved on to seek ‘higher level’ things which we enjoy doing such as socialising with friends and family, playing games and sports, developing hobbies or being entertained

The problem is such latter ‘higher things’, whilst valued highly by us are often available for free and hence are not clocked by the official GDP bean-counters

Inevitably, some geek has come up with a new collective noun for all this new stuff – consumer surpli – aka unmeasurable intangibles i.e. the extras, including freebies, on offer to customers by the likes of Google, Skype and Facebook to attract valuable personal preference information from us which they sell on to companies seeking to target those of us most likely to buy from them – and such consumer surpli comprise an ever-increasing proportion of the value created by national economies but are also totally missed by their GDP numbers

The same change in values has already occurred with private businesses – if in any doubt, note how the most valuable companies nowadays are ones which are tangibles poor Coca Cola, Apple or Google for example – overall, some 80% of stock market values are now based on intangible assets, so the financial markets and investors are already up to speed

Sadly, at present, we’re stuck with official GDP data which presents a gloomy failing picture for most developed nations – in particular:

  • We knew the base data was already seriously flawed, being so full of errors, assumptions and forecasts – now we know much that we value is being ignored
  • We also know G7 experts, economists and media all announce there is a productivity puzzle because their GDP and productivity (GDP/ Labour) growth has apparently stalled over the last decade or so
  • And yet government ministers are reliant on these statistics to decide their economic policies and different ways to tax us
  • The consumer surplus is the biggest economic elephant in their room


G7 bean-counters thus must at least recognise the failings of their current measures and gear up for these fundamental economic changes


And it’s not just outputs where big changes have occurred

Once, most people went to work for the pay alone – work was a chore they had to do, something they would not do if not paid – and most work was brawnwork, few opportunities were available for brainwork

Now, already, quite the reverse applies – most brawnwork that was dirty, dangerous, dull or repetitive has been automated with robots, AI  or computer software – most has been replaced by more interesting jobs involving considerable, if not total, brainwork:

  • Brawnwork required numbers of workers ‘clocking-in’ for numbers of hours on the factory floor or in the office – such numbers were easily countable and thus controllable by local managers 
  • Brainwork is different, and far less controllable – it requires individuals to produce results by deadlines – it requires problem solving, creativity, analysis skills and decisiveness – it thus requires individuals who are well trained but also motivated, ’employee engagement’ being the buzzword for the latter


Indeed, modern managers have become increasingly concerned to maximise employee engagement to boost overall productivity levels – they do this also to maximise staff retention, especially of staff they cannot afford to lose, and so minimise the extra costs of recruitment, training and short term work disruption

Essentially, this means:

  • Re job design – they seek to inject more interest, variety, control and responsibility into jobs – to make them seem more like hobbies, something they’d want to do for no pay, and even work endlessly at – even get people to look forward to Monday mornings, not dread them
  • Re individuals – they show genuine interest in their staff, talking face-to-face with them often – they also train them not only so they are more efficient at their work but become more promotable and can climb ladders


We’re not there yet – the following describes the current situation in most organisations:

  • Being seen in the office working long hours is deemed essential for holding on to a job – input hours still rate more than results achieved with most managers – presenteeism still outweighs individual productivity 
  • Over 90% would not do their job if they were not paid
  • Most don’t enjoy what they do and would resign immediately if they won the lottery
  • Most don’t rate their immediate boss
  • Most would love to run their own business and be their own boss


But changes to working conditions are increasingly being made or considered, including the following: 

  • Flexi-time working, working from home, four day working weeks
  • Dress-down days
  • Gig work – zero hours contracts (some people prefer this, some do not)
  • Appointing mentors
  • Free healthcare insurance, gyms, yoga classes, massage parlours
  • Office games rooms, nap rooms, healthy lunches


Such changes all have a part to play but more radical change is needed, addressing the following issues:

  • How to make jobs become paid hobbies – just as many footballers would continue to play, even if not paid
  • How to allow people to work from wherever they want, whenever they want
  • How to let people feel they are their own boss 
  • How to make work feel like being a member of a social club – a place to meet and chat with lots of different like-minded chums



  • G7 economies are changing big-time at present but official statisticians are not noticing
  • Hence, official ‘doom and gloom’ economic pictures do not paint the real world out there
  • Modern managers can no longer manage their troops using old ‘command and control’ methods – they must ensure their troops enjoy their work if they are to get the best results out of them 

A new ISC rides to the rescue

Puzzle no more about dormant national productivity – the cavalry have arrived in the form of Andy Haldane, chief economist of the BoE (Bank of England) who is to chair the government’s new ISC – Industrial Strategy Council – it’s another quango of sorts for a select few of our great and good to deal with a nagging problem that nobody seems able to resolve

Despite most experts bemoaning the UK’s lack of significant productivity improvement over the last decade, Andy claims: “The UK’s macroeconomic performance has improved dramatically since 1992 when the UK was forced out of the EU’s ERM (Exchange Rate Mechanism)” – furthermore: “The UK is now, arguably, an established Premier League team”

Then another surprise

Apparently this is  all due to “inflation targeting” by his chums at the BoE rather than the government’s efforts which: “Frequently adopted and abandoned different industrial strategies as well as other schemes to raise Britain’s productivity”

Note the role of UK managers at the coal-face merit no mention yet it is they (in our view) who determine some 80% of national productivity levels achieved – Governments can only influence the other 20% by complementing the private sector via their taxation policies and investment in education, healthcare, low-income housing, R&D and infrastructure

Why such influence by organisation level managers?

Because workers in all sectors, public or private, soon settle down to a rate of work they’re comfortable with whatever the systems and processes they’re required to follow – and it’s those systems and processes that determine most of the productivity levels achieved, both at organisation and hence national level – indeed, the famous management guru Dr Edwards Deming went so far as to claim it was systems which determined as much as 94% of an organisation’s productivity level – and the people with the power over and sole responsibility for those systems and processes are organisation managers, not their employees

Undeterred,  Andy goes on to say the ISC will provide: “An independent body to evaluate progress and develop appropriate measures of success” which suggests he has doubts about the current official data available (we wish him well)

However, to kick off his ISC reign, Andy tells us he has identified three productivity gaps facing the UK – sadly,  they’re all based on the rich, albeit flawed, trove of national statistics available to him – viz:

  • Inequality between the country’s highest and lowest performing areas/ regions
  • Lower labour productivity than other large rich countries
  • A slowdown in productivity growth since the 2008 financial crisis


Such claims may or may not be true to a greater or lesser extent – the data on which they’re based is so full of errors, forecasts and assumptions that we’re not talking here about 1% or even 5% error margins – our guestimate is it’s more likely to be in the 30% to 50% range

And if that were not bad enough, what would Andy and his new colleagues be prompted to recommend to whom on the basis of such claims – by the sound of it, he’d be focussing on possible changes to Government policies whilst continuing his successful BoE action, and thus restricting himself and his council to a mere 20% of the problem causes

One can only hope that the value of the ISC will itself be determined by some significant improvement in some acceptably accurate measures of national productivity – and disbanded if found to be yet another ‘kicking the can down the road’ initiative


Beware all economist geeks bearing their advice and solutions

Currently, we are very cynical about Andy’s prospects with the ISC

At work but not working

According to the CEBR (Centre for Ecoomics and Business Research) UK businesses don’t know how to maximise their human capital despite the vast majority being ‘concerned’ or more about their people productivity – indeed, a survey they conducted found that:

    • Some two thirds have not looked at ways to boost employee well-being and so motivation levels
    • Some 60% have not looked at improving business processes and decision-making
    • Some 70% have not invested in technology to automate repetitive tasks


But, important as such initiatives are, a bigger source of ‘human capital improvement’ they should all address is the huge waste of employee time when at work – plenty of studies show that, most of the time, people are busy at work but ‘are they productive during that time?’

At present, most managers still equate long hours at work with dedication, commitment and loyalty

This is why, in the early days of Microsoft, Bill Gates memorised employee license plates: “I knew everyone’s licence plates so I could look out in the parking lot and see when people came in, and when they left”

But this attitude is ineffective nowadays, as Gates soon realised – what matters is results, not hours worked

This particularly applies to brainworkers as they steadily replace brawnworkers in workplaces – the former are people who have to use their brains more than their hands to complete their work – people whose outputs and results are less easily countable and often subjectively measured

Brainworkers can look extremely busy when they’re actually unproductive

Indeed, one recent study claims most employees only work about three hours a day – they fill the rest of the time following Parkinson’s Law and surfing, chatting or complaining about being overloaded whilst accomplishing very little – they’re at work but not working

Hence, the increasing calls for most to work only six hours a day or four days a week – or flexitime working, often from home – all  in the expectation of producing much the same if not more and better output

The problem with this is most managers would feel a loss of control over their charges – they find hours input are easily countable and so controllable,  whilst results are less so – hence many managers stick with their old ‘command and control’ ways and manage by time inputs mainly

Fortunately, more enlightened managers recognise their need to move with the times – actions they are taking include:

  • Hiring people they can trust – then trusting them – and this is usually reciprocated
  • Setting expectations and targets for each of the people in their charge – expectations of each team member include not only deliverables on time and of acceptable quality but also coming up with new improvement ideas and helping each other
  • Letting their people decide when they work, where – they know they will be judged on what they get done so they plan accordingly but this allows them to manage their work/ life balance requirements better – an important motivation factor nowadays
  • Not endlessly contacting individuals when not in the office, unless absolutely essential – most problems/ thoughts can wait until tomorrow or later


Better results inevitably follow – and all started by the manager managing differently


Further UK education needs

“The new prime minister will have to rise to the skills and productivity challenge, and make sure that everyone, no matter where they come from, can get a chance to have a great job”, says Anne Milton, UK Minister for Skills and Apprenticeships

The following is an article she wrote in FEWeek

I want the next prime minister to make sure the work on technical and vocational education continues to be a priority and that we build on what we have already achieved.

Significant progress has been made on our technical education reforms: the first T-levels are on track to be rolled out in 2020; the first Institutes of Technology will launch later this year; and we continue to see more people starting on apprenticeships.

I want the progress we have made to be a step change in how FE (Further Education) is viewed in this country. People are finally waking up to the need for a rebalance between FE and HE. There is much more recognition of the huge impact our further education sector plays in supporting more people to gain the skills they need to get a good job, get on the path to great careers – and for the country, boosting productivity.

This week we published the findings from our review of level 4 and 5 qualifications – or Higher Technical Qualifications – and we launched new proposals to make sure more people and employers can take advantage of them in the future.

All the evidence from our review highlights that higher technical skills (the type that many level 4 or 5 qualifications can provide) are increasingly in demand from employers, but the uptake remains worryingly low. Only 1 in 10 adults in England have studied for a qualification at this level, despite the prospect of better wages and job prospects.

The skills our economy needs now and in the future are not always aligned with the qualifications on offer and we need to make sure that we change that. Young people need to be better informed when it comes to studying for jobs and careers in key sectors such as science, technology and engineering.

Some of this is about all of us continuing to bang the drum about the benefits of technical education. We need to dispel the intellectual snobbery that still exists which dissuades some students from choosing this route in favour of a traditional academic option.

There is no overnight fix for changing the way technical and vocational education is seen by the public, but we can make sure that the qualifications and options that are available are high-quality, are valued by students, parents and employers and ultimately get more people on a path to a good, well-paid job.

That is at the heart of everything we are doing – from the introduction of new T-levels, our reforms to apprenticeships, as well as consulting on changes to post-16 qualifications at level 3 and below, and our new level 4 and 5 proposal. It is all about providing a choice of high-quality options as well as logical, clear training routes that everyone can understand.

These are once-in-a-generation reforms and while I don’t imagine that we are going to get everything right at the first time of asking, if we want to make a success of them in the long term, we need a strong sustainable and coherent technical education system. This will help unlock untapped potential and boost our economy.

The new prime minister will have to rise to this challenge if we are to have the skills we need to increase productivity and make sure that everyone, no matter where they come from can get a chance to have a great job and fulfilling life. This will be critical to the future prosperity of individuals and the country as a whole.

Conclusion: “Well said, ma’am, as far as it goes

Boeing’s MAX 737 disaster

Stan Sorscher, a former Boeing engineers and now a Labour Representative at the SPEEA (Society for Professional Engineering Employees in Aerospace) is the author of a letter, reproduced in full below, which he posted to the Seattle Times

In it he says Boeing’s cost-cutting culture is to blame for production problems with the 737 MAX and other planes:

  • “The cost-cutting culture is the opposite of a culture built on productivity, innovation, safety or quality”
  • “Boeing’s experience with cost-cutting business culture is apparent”
  • “Production problems with the 787, 747-8 and now the 737 Max have cost billions of dollars, put airline customers at risk, and tarnished decades of accumulated goodwill and brand loyalty”

It’s the first time since the grounding of the Max that a senior figure in Boeing’s engineers union has spoken – though investigations into two fatal Max crashes are incomplete, evidence of engineering errors have surfaced – errors that were not discovered in testing

Sorscher points to a major change in Boeing’s internal culture in the late 1990s – before that time, the company was focused on the performance of its products – this was the era of the bold bet on the 747 – it was also a time when a little plane called the 737 got its start, became Boeing’s best-seller and remained so over many iterations

In the 1990s, Boeing put workers at the center of its performance-driven universe – the plane of that era was the 777 – it was a time of partnership between workers and executives as they learned together how to produce the plane, and many engineers speak of this period as the most fulfilling in their professional lives

But all that changed with the 787 program in the late 1990s – Boeing reset the playing field – Washington state would have to compete with other jurisdictions, offering tax breaks to secure production lines – suppliers would have to compete with rivals around the world – and workers would discover their positions were precarious

The atmosphere inside Boeing also changed – Sorscher says Boeing engineers received clear cultural messages that identifying problems was thought of by management as making trouble – “If the message is “follow the plan” and you watch co-workers who raised an objection and the problem isn’t taken seriously or are they’re considered troublesome, then that’s a cultural message you pick up,” he said.

However, from a shareholder perspective, Boeing’s approach to its business had been wildly successful – worldwide demand for airplanes was riding a high and Boeing had diverted cash flow into dividends and share buybacks that helped boost the company’s stock – from 2000 to the present, Boeing’s stock price grew from $44 to $356 – indeed, the stock hit a peak of $440 just before the crash of an Ethiopian Airlines Max jet last March

Sorscher’s letter to the editor of The Seattle Times:

Employees come to work to do their jobs. We aren’t usually aware of workplace culture, even over the span of years.

We learn culture from our co-workers and managers when they make decisions and demonstrate problem-solving skills. Leadership messages affect thousands of decisions that add up to success or failure of the organisation.

For many years, Boeing competed with Airbus and other producers for airline customers based on performance of its products. As a recent news report put it, Boeing now competes for investors with Exxon and Apple.

Boeing rose to the top of the airplane business as an engineering company, focused on performance of its products. Boeing made bold decisions that “bet the company,” and prevailed over competitors.

In the 90s, Boeing business culture turned to employee engagement, process improvement, and productivity – adopting the “quality” business culture that made Japanese manufacturers formidable competitors.

In the late 90s Boeing’s business culture shifted again, putting cost-cutting and shareholder interests first.

Graphic by Stan Sorscher, a labor representative at the Society for Professional Engineering Employees in Aerospace (SPEEA).

Some business cultures are well-suited to commodity-like products, but are a bad fit to performance-driven products.

Ask a financial analyst, “Are airplanes commodity-like or performance-driven?”

Business instinct is to cast the question as a market transaction. Airline customers worry about price, delivery dates, training costs, spares, maintenance, and other factors, but overall, those considerations come out very close in the end.

The last major innovation in air travel was the jet engine in the 1950s. A business analyst would say the airplane business is “mature,” the products are standardised, innovation is slow, so airplanes are commodity-like.

Now ask a different question. “Are the design, development, testing, and manufacture of airplanes commodity-like or performance-driven?”

Whoa. Tough question.

Actually, making airplanes is performance-driven.

Success or failure of an airplane program turns on productivity. The first airplanes off the production line sell at a loss. Costs come down over time; the quicker the better.

If your business model emphasises productivity, employee engagement, and process improvement, costs go down faster. This was the essence of the “quality” business model Boeing followed in the mid-90s.

The 777 had the best “learning curve” in the business. On the other hand, if your industry is mature, and your products are commodity-like, business school theory says a cost-cutting model is appropriate.

Wal-Mart perfected its particular version of the cost-cutting business model. Amazon adapted that model to its industry. Boeing has adapted it to high-end manufacturing.

These companies are super-stakeholders with market power over their supply chains. The point of this business model is that the super-stakeholder extracts gains from the subordinate stakeholders for the short-term benefit of investors.

Subordinate stakeholders are made to feel precarious and at-risk.

Each supplier should see other suppliers as rivals. Similarly, each work location should know it competes on cost with rival work locations. Each state or local government should compete for incentives against rival states.

In this model, subordinate stakeholders never say no to the super-stakeholder – not workers, not suppliers, not state legislatures.

This cost-cutting culture is the opposite of a culture built on productivity, innovation, safety, or quality. A high-performance work culture requires trust, coordination, strong problem-solving, open flow of information, and commitment to the overall success of the programme.

Extra task performance measures

Some interesting ideas follow from ‘Entrepreneur Europe’ on ways to assess the performance of a team – marketing or software development, say – and keeping a finger on their pulse

Four extra performance measures are proposed:

  1. Planned-to-done ratios:
    • How well have plans been executed?
    • What % were completed satisfactorily, or better?
  2. Cycle time:
    • Work is usually completed in ‘iterative sprints’
    • Break down a project into bite-sized small-cycles and optimise each
    • The more quickly each one is done, the quicker the whole project
  3. Attendance:
    • This can make a big difference to the success of the whole project
    • Uncommitted or burnt-out team members – hence missed meetings, sick days, late arrivals – can have a serious effect on project progress and overburden others causing resentment and sometimes mental health issues
  4. Escaped defects over time:
    • Re software teams, how many bugs have been missed in a new product i.e. number of defects that affect the customer?
    • Re marketing teams, how many failed campaigns have there been, or customer complaints?
    • Is quality being sacrificed to meet deadlines – does talent need to be re-allocated?

The team leader’s job is continually to monitor his team’s productivity and connect business goals to project outcomes – and the above would help him make data-driven decisions about future tasks

Winners need stamina

A question managers often ask is “Why do so many big change projects fail?”

It’s not so much the steps they take – all follow much the same basic steps when under way viz:

  • Record facts
  • Examine findings
  • Develop solutions

But where most go wrong is with other steps needed before, during and after the above viz:

  • Badly set up – unclear terms of reference, unquantified targets, lack of obvious senior management support, no links to corporate plans
  • Badly manned – ‘he got us into this mess’ appointments, lack of people with past success – lack of the right skills, experience and attitude – outside consultants put in charge so only they learn ‘what does not work’
  • Badly project managed –  lack of a timetable and accountabilities, little focus on customers’ needs, deadlines allowed to drift, too little or too much time and resources made available
  • Badly implemented – employees told to implement changes without understanding why, nor what’s in it for them – little effort made to ensure changes made work well after day one

With so many pitfalls it’s little wonder so many big improvement projects stumble, even fail – each one is usually announced with considerable fanfare – but initial enthusiasm for them soon wanes, effort becomes half-hearted and any measured results are usually meagre – hence interest moves on

The same applies at national level – over the last two years the UK has set up the following grand initiatives aimed at productivity improvement:

  • PLG – Productivity Leadership Group – aka ‘Be the Business’ (someone thinks this is appropriate I assume) – led by a group of business leaders – it appears their main output will be to inspire the UK’s long tail of flagging businesses with ‘best practice’ stories – it’s now in its second year of existence, but to what quantifiable effect?
  • PIN – Productivity Insights Network – sponsored by Sheffield University and economist Jim O’Neill – no known output as yet
  • Andy Haldane, Bank of England chief economist, recently appointed to lead a new UK government drive to improve UK productivity – but given HMG can only impact maybe some 20% of national productivity via their investment in infrastructure, R&D and training, we believe Andy’s chances of quick quantifiable wins are slim

And New Zealand has announced a similar venture – some of the biggest names in New Zealand business are to form a Business Advisory Council and advise Prime Minister Jacinda Ardern on how to supercharge the New Zealand economy

The council is designed to advise the Government on how to build a productive, sustainable and inclusive economy that improves the well-being of New Zealanders

Jacinda said: “New Zealand needs a modern economy that has the investment, innovation and skills required to ensure we can all share in prosperity and opportunity in a sustainable way – to do that we need to work closely with business leaders, share ideas and consider solutions to overcoming barriers together”:

  • A mix of six women and seven men with small to large business experience, from across New Zealand, have been selected to provide advice
  • The council is expected to meet three times a year with the prime minister and her representatives
  • It will provide high-level, free and frank advice on policies that directly affect business, harness the expertise of the private sector to inform government policy and build closer relationships between government and business

“I will also be asking the council to gather advice from their peers in the domestic and international business community on some of the most important issues facing New Zealand including how we best grow and share our prosperity, support regional development, and transition to a clean, green New Zealand”

So, again, it’s a well-intentioned initiative, plus another feather-in-the-cap for those council members chosen – easy to set up and announce, easy to be seen to be ‘doing something’ about a well-known problem, easy for the government to park responsibility elsewhere, but unlikely to make any noticeable difference to the well-being of all, at least in the short term

Why so cynical?


  • The above national initiatives are a start, but improving productivity, even at organisation level, is invariably a long haul, not a quick fix
  • Once major initiatives are announced, few get down to the detail to ‘make the hard yards’ – and even fewer try to quantify what % difference they targeted or made
  • It reminds one of participating in the offshore Fastnet race – there’s much publicity and excitement at the start off Cowes as thousands of spectators watch the 200 or so boats begin their adventure – however, once past the Needles, each boat usually finds itself alone at sea with nearly 600 miles to go – whether they finish the course depends on just the skipper, crew and boat alone – there’s nobody else out there to help – and that’s when enthusiasm can fade fast
  • Everyone loves the upfront glamour of grand new initiatives – few love the hard graft that must then follow to finish the job

Turbocharging Australian productivity

Adrian Blundell-Wignall, former director of the OECD and professor at Sydney University, says:

  • “It’s not enough to tweak R&D incentives – we, Australia, need a detailed plan that will change the whole climate for smart investment and productivity growth
  • During the (recent) election, the focus was on tax cuts and “having a go”
  • The Treasurer has since talked about tax incentives for R&D
  • But improving productivity growth will need a broader framework of reforms to avoid our cloudy future”

Past government plans have resulted in the shrinkage of manufacturing in high-labour-cost economies:

  • In Australia, from around 16% of GDP in 1975 to 6% today
  • In the USA, the decline was less – 16% down to 11% of GDP

Australia made up this gap via finance and mining – and we became ‘contented and complacent’

Since China joined the WTO at the end of 2001, the commodity super-cycle pushed up the terms of trade – the real purchasing power of the income generated by domestic production was boosted by 9% of GDP, the equivalent of three full years of economic growth – the resulting feel-good factor got credit booming and house prices rising – finance and insurance now make up over 9% of GDP versus only 7% in the USA

However, mining and finance now both face headwinds:

  • In mining, China’s massive investment-focused strategy has resulted in diminishing returns – investments need to earn good returns if rising debt is to be paid for – China is on the classic path for financial crises – it suffered something of a recession in 2015, and more will follow – China is slowing structurally and diversifying its resource supply – both will hurt Australia
  • In finance, house prices and debt levels are too high and must unwind in the years to come, not least because of low interest rates.

And, outside these two industries, Australia’s labour productivity growth looks terrible – so much so that there’s a good case for excluding them from the measure:

  • Mining, because it’s so large and heavily capital intensive – relatively few people are employed there and the huge costs in equipment are someone else’s output
  • Finance, because it’s imputed from interest rate spreads

Excluding them both reveals even lower productivity growth – a meagre 0.3% p.a. over the past six years – compare that with the UK, an economy without resources, which is doing much better

So Adrian says having a plan is essential – a plan which creates an environment for more diversified and higher value-added growth covering three broad groups of firms:

  • Those with strong productivity growth accompanied by significant sales at home and in foreign markets
  • Large incumbent companies in the domestic market with negative productivity growth and weak penetration of foreign markets
  • A large number of medium-sized companies characterised by moderate growth and a domestic sales focus.

We know digitisation and technological innovations allow some firms to quickly saturate their domestic markets – however, only those that take advantage of economies of scale by expanding into foreign markets are able to remain in the strong productivity growth group

In addition:

  • Fast growers are always those firms with the highest levels of R&D expenditure
  • Mergers and acquisitions (M&A) activity are a recurrent theme in their business models

R&D innovations that drive productivity do not (outside Silicon Valley) come from small start-up companies “having a go” – R&D is a huge cost activity – in the main, it comes from larger companies with barriers to the appropriation of their IP by others, and which have access to external finance, particularly equity finance, essential for risk-taking and for entering foreign markets – their ability to restructure quickly, opening and shutting down plants via M&A, is critical – small firms lack capital and resources to carry out meaningful R&D and to launch products based on it

Overall, the “plan” should be to develop a research-and-innovation culture and policy certainty – one which recognises that better education output is central to future productivity growth – one which supports an equity culture for risk taking – so it must remove barriers to domestic and cross-border M&A

The plan must also resolve the problem that while economies of scale depend on foreign sales, tax avoidance by firms also relies on cross-border activity – IP, trademark and other earning rights should not be owned by foreign subsidiaries in tax havens

Adrian thus concludes that Australian productivity requires many hard reforms rather than just tinkering with R&D tax incentives.

Adrian Blundell-Wignall is also author of ‘Globalisation and Finance at the Crossroads’

The Secret Sauce for productivity?

Greg Hanover, CEO of Liveops Inc, claims organisations that tap into the power of the gig economy see much increased (% ?) workforce engagement and productivity

Why so?

He believes it’s because independent workers are empowered to follow their unique goals and create satisfying careers for themselves

And he’s right – it’s not only good for gig employees who prefer that way of working, it’s also good for their employers – it’s why we made good use of what we called ‘associates’ back in the 80s to man most of a consultancy division that way

Nowadays, from Uber to TaskRabbit, gig work has become ubiquitous – indeed, it’s fast becoming the dominant staffing model – for example:

  • In 2016, gig workers comprised some 34% of the U.S. labour force
  • Intuit, a financial services company, forecasts that number will reach 43% by 2020

This trend is driven in part by studies of full-time workforces which indicate that:

  • The average employee actually spends under three hours each day working productively – yet is paid for eight or more
  • Even the majority of employees themselves believe they could complete their daily workloads in only five hours
  • And, instead of working fewer hours, full-time employees are increasingly compelled to stay later and work longer – a sure-fire recipe for fatigue, burnout and chronic stress

Full-time and overtime environments thus not only generate huge waste, made worse if demand varies significantly from week to week, but often sap employees of the will to be productive – nevertheless, many organisations still choose to employ full-timers only, believing that gives them more control over their workers’ use of time, quality of work and knowledge of company secrets – they overlook the fact that gig-employees also have to be carefully selected, then trained up to company standards and need not be retained if they fail later on – and, re secrets, full-timers also can and do quit their jobs, most without any gagging constraints and often to join the competition

And they don’t fully appreciate that the on-demand gig model has big advantages:

  • It ensures 100% productivity – gig workers only get paid when they are productive
  • Gig workers, not their employers, have to manage the costs of their equipment, real estate, income taxes and insurance premiums
  • Gig workers have control over their lives and careers, and so tend to be more effective, motivated, and creative than many of their 9-to-5 counterparts

The gig economy thus promotes worker satisfaction, loyalty and productivity

By contrast, Greg goes on to say that full-timers’ engagement can vary significantly – “Even employees who love their jobs can experience low energy levels, off days and shifts when there seems to be nothing to do but wait out the clock”

However: “Independent workers seldom face the same problems – if they’re tired or bored, they can log off and come back to work when they’re ready – if motivation suddenly strikes, they can harness it immediately – if they work less than usual one week, they can make up for it another week”

Such flexibility is particularly important for creative workers (writers and designers), parents, people with disabilities, people pursuing more than one career or anyone with any obligation, interest, or lifestyle that doesn’t fit neatly into a traditionally segmented 40-hour workweek – work can happen when people are at their best, whether it’s early in the morning or later at night after the kids are put to bed – plus, on-demand work is adaptable – it can change as workers’ schedules, finances, living situations and other circumstances change

Conversely, monotony can kill engagement faster than rigid scheduling – few people thrive in settings where they are expected to do the same thing in the same way, day in and day out

Gig work can thus expose people to a wide variety of environments, processes, clients and ways of doing business – variety which not only fosters a person’s interest in their work but also increases their value for new and existing clients

When you’ve encountered more than one solution, you can choose, or create, the ideal answer for a given problem – this can save workers and organisations significant time and energy – people can take lessons learned from one gig and apply them to another – and the more opportunities someone takes on, the broader and deeper their knowledge base grows

Overall, Greg believes companies that leverage the gig economy don’t need to worry about engagement and productivity – because workers need to ensure it for themselves

We wouldn’t go quite so far – undoubtedly, partial gig employment has become an important employment model for many organisations in the 21st century – a model which is likely to become even more widespread – but it’s unlikely to fully replace the relative security of full-time employment for many years yet

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)


  • 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”


  • 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 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?)


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


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,, 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”


  • 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


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 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.


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


  • 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


  • 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


  • 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”


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”