Irving Wladawsky-Berger

Rethinking Digital Strategy for the Post-Pandemic Era

“One year into the COVID-19 crisis, our newest McKinsey Global Survey on digital strategy indicates that the pandemic has increased the pace of business and that technology capabilities will be critical to companies’ COVID-19 exit strategies as well as to what comes next,” said a recent McKinsey report, The new digital edge: Rethinking strategy for the postpandemic era. The survey was conducted online in January of 2021, and received responses from over 1,100 C-level executives, business unit heads and senior managers from different industries, functions, company sizes and regions.

The survey’s overriding finding is that the pandemic has sped up the adoption of digital technologies by several years. “The imperative for a strategic approach to technology is universal, yet some companies are already leading the pack; their responses show that better overall technology capabilities, talent, leadership, and resources (what we call a company’s technology endowment) are linked to better economic outcomes. At the same time, the results confirm that many organizations could be missing opportunities to invest in the areas of their business models that are most at risk of digital disruption.”

The technology endowments of the top-decile economic performers include cloud adoption and infrastructure, both public and private; a common source of data across the organization; a modern architecture for technology elements; sufficient cybersecurity to mitigate current risks and threats; prioritization of tech resources to the most strategically important efforts; increased investment in talent; filling key technology roles with high-quality individuals; increased R&D spending; and creation of new partnership.

Realizing the Economic Promise of Predictive Analytics

Wikipedia defines predictive analytics as a set of statistical techniques, - such as data mining, business analytics, and machine learning, - “that analyze current and historical facts to make predictions about future or otherwise unknown events.” Increasingly powerful and inexpensive computing technologies, new algorithms and models, and huge amounts of data on almost any subject have led to major advances in predictive analytics over the past two decades.

“Worldwide revenue for ‘big data’ and business analytics solutions is forecasted to reach $274.3 billion by 2022,” wrote economists Erik Brynjolfsson, Wang Jin, and Kristina McElheran in The Power of Prediction, a research article published earlier this year. In principle, such widespread use of predictive analytics should have a positive impact of the performance of firms. “However, these investments have yet to yield productivity gains in the aggregate,” said the authors. “At the firm level, managers struggle to close the gap between the promise of predictive analytics and its performance. These concerns have been difficult to tackle empirically due to the rate of technological change and, ironically, a dearth of data.”

To address these concerns, the authors launched a research study in collaboration with the US Census Bureau to collect information on the use of predictive analytics in a representative sample of the US manufacturing industry, - an industry that’s historically been an early adopter of leading-edge technologies.

Why Do We Work So Damn Much?

A few weeks ago, I listened to a very interesting podcast, Why Do We Work So Damn Much?, where podcast host, NY Times columnist Ezra Klein, interviewed anthropologist James Suzman. Suzman has devoted almost thirty years to studying and writing about the Ju’hoansi and other bushmen from the Kalahari Basin, who are among the world’s few remaining hunter-gatherer societies. He recently published Work: A Deep History from the Stone Age to the Age of Robots, a book about his research.

Modern humans emerged in Africa between 200,000 and 300,000 years ago. Our homo sapiens ancestors were hunter-gatherers for most of those years, collecting wild plants and hunting wild animals. Starting around 12,000 years ago, the agricultural revolution introduced the domestication of plants and animals, leading many hunter-gatherer groups to establish agricultural communities and villages.

The vast majority of hunter-gatherers disappeared a long time ago, but a few groups remain in isolated sections of Africa, Australia, the Amazon rainforest and the Arctic. Anthropologists have been studying these remaining hunter-gatherers to learn how they’ve been able to survive so much longer than other human groups, as well as to understand the behaviors and cultures that modern humans may have inherited from our closest ancestors.

Revitalizing US Manufacturing

“The COVID-19 pandemic has underscored manufacturing’s role in providing products that are critical to health, safety, national security, and the continuity of multiple industries,” said McKinsey in a recent discussion paper, Building a More Competitive US Manufacturing Sector. “It has also revealed the extent to which global supply chains are exposed to shocks and disruptions. All of this has occurred at a moment when new technologies, process innovations, and demand growth are reshaping the sector worldwide. The United States can seize on these developments to make its own manufacturing sector more competitive.”

Manufacturing jobs helped build the US middle class after WWII. In the 1950s, it accounted for roughly 30% of employment and close to 30% of GDP. But manufacturing has significantly declined in the intervening decades, now comprising only 8% of the workforce and 11% of GDP. Manufacturing growth has particularly slowed down over the past 30 years, from 4.9% in the 1990s to 1.4% in each of the past two decades.

Despite its dramatic decline, manufacturing continues to have a disproportionate impact on the US economy, accounting for 35% of productivity growth, 55% of patents, 70% of R&D spending, and 60% of exports. According to McKinsey, these outsize economic contributions uniquely position manufacturing to strengthen the US recovery over the long term.

The Evolution of Shopping in the Digital Economy

Earlier this year, The Economist published a special report on The Future of Shopping, with nine articles on the subject. In its overview article, The Economist argued that “a new species of shopper is emerging: less centered on America, more intent on ensuring that what they buy reflects what they believe, and technologically dexterous. This latest incarnation of the global consumer looks likely to change how capitalism works - for the better.”

Three major changes are transforming the world of retailing. First, Western Europe and North America are no longer the biggest retail markets; nor do they epitomize the leading edge of retail as has long been the case, with innovations like the department store, the mall, catalogue shopping, and e-commerce. Shoppers are increasingly Asian. “Last year China and America were almost neck-and-neck as the world’s biggest retail markets. China’s two biggest online marketplaces, Alibaba’s Taobao and Tmall, both do more third-party business than Amazon.” And Asia’s shoppers are now at the frontier of retail, with innovations like livestreaming e-commerce.

A second change is that, beyond low prices, younger shoppers are increasingly influenced by their social, ethical, and political values when making buying decisions. They’re selecting  which brands to engage with based on their social values like environmental credentials and workplace environment. Well managed firms work hard to establish the kind of positive reputation that attracts people to want to be associated with the brand and its products and services. This is particularly important in our Internet age, which enables a company’s actions to be instantly communicated to all. “One way that capitalism adapts to society’s changing preferences is through government regulation and laws, which voters influence, at least in democracies. But the dynamic response of companies to the signals that consumers send is a force for change, too,” and the reason firms spend considerable time, energy and funds nurturing their brands.

The final big change is the increasingly digitalization of the economy. The explosive growth of mobile devices means that a company can be engaged with its customers not only when they’re shopping online, but wherever they are, - at home, at work, or in a store. “More accurate and voluminous data about shopping patterns are breaking down the decades-long relationship between mass consumption and mass production. In its place is a more varied world in which the shopper can decide whether to buy online or in store, whether to shop via platforms or from individual brands, and whether to accept targeted ads or not.”

The Coming Era of Productivity Growth

“The last 15 years have been tough times for many Americans, but there are now encouraging signs of a turnaround,” wrote economists Erik Brynjolfsson and Georgios Petropoulos in The Coming Productivity Boom, a recent opinion article in the MIT Technology Review. “Productivity growth, a key driver for higher living standards, averaged only 1.3% since 2006, less than half the rate of the previous decade. But on June 3, the US Bureau of Labor Statistics reported that US labour productivity increased by 5.4% in the first quarter of 2021. What’s better, there’s reason to believe that this is not just a blip, but rather a harbinger of better times ahead: a productivity surge that will match or surpass the boom times of the 1990s.”

After growing at an average annual rate of around 2.8% between 1947 and 1973, US productivity has significantly slowed down, except for the Internet-driven productivity boost between 1996 and 2004. Despite the relentless advances of digital technologies over the past 15 years, - from smartphones and broadband wireless to cloud computing and machine learning, - productivity has only grown at an anemic 1.3%, between 2006 and 2019. Most OECD countries have seen similar slowdowns.

What accounts for this puzzling so-called productivity paradox and when might it finally end? Over the past several years, Brynjolfsson and his various collaborators have explored this question, first at MIT where he was faculty director of the Initiative on the Digital Economy, and since 2020 at Stanford, where he’s Director of the Stanford Digital Economy Lab. Brynjolfsson discussed alternative explanations for the paradox at a recent MIT conference.

The Post-Pandemic Future of Work: An Optimistic Outlook

“The COVID-19 pandemic-induced lockdowns and related global recession of 2020 have created a highly uncertain outlook for the labour market … millions of workers have experienced changes which have profoundly transformed their lives within and beyond work, their well-being and their productivity,” said the World Economic Forum (WEF) in The Future of Jobs Report 2020, published in October, 2020. “Comparing the impact of the Global Financial Crisis of 2008 on individuals with lower education levels to the impact of the COVID-19 crisis, the impact today is far more significant and more likely to deepen existing inequalities.”

The Economist  was considerably more optimistic in a special report on The Future of Work in its April 10 issue, which included several articles on the subject. “A jobs rebound, shifting politics and technological change could bring a golden age for labour in rich countries,” said the overview article. “It might seem premature to predict a wonderful world of work only a year on from a labour-market catastrophe. But America is showing how rapidly jobs can come back as the virus recedes. In the spring of 2020 the country’s unemployment rate was nearly 15%. Now it is already just 6% after a year containing five of the ten best months for hiring in history.”

The key reason for The Economist’s optimistic outlook is that as labor markets recovers, two deeper shifts are unfolding: a political environment which is becoming friendlier to workers than it’s been in decades; and an accelerated digital economy which promises to bring about faster productivity growth. Let me briefly summarize each of these two shifts.

The Three Types of AI: Artificial, Authentic, and Augmented Intelligence

“The history of work - particularly since the Industrial Revolution - is the history of people outsourcing their labor to machines,” notes a recent article in the Harvard Business Review, - AI Should Augment Human Intelligence, Not Replace It, - by National University of Singapore professor David De Cremer and chess grandmaster Garry Kasparov. “While that began with rote, repetitive physical tasks like weaving, machines have evolved to the point where they can now do what we might think of as complex cognitive work, such as math equations, recognizing language and speech, and writing. Machines thus seem ready to replicate the work of our minds, and not just our bodies.”

Throughout the Industrial Revolution there were periodic panics about the impact of automation on jobs, going back to the so-called Luddites, - textile workers who in the 1810s smashed the new machines that were threatening their jobs. Automation does indeed substitute for labor. However, automation also complements labor, raising economic outputs in ways that often lead to more long-run employment, not less.

Most jobs involve a number of tasks or processes. Some of these tasks are more routine in nature, while others require judgement, social skills and other human capabilities. The more routine, rules-based the task, the more amenable it is to automation. But just because some of the tasks have been automated, does not imply that the whole job has disappeared. To the contrary, automating the more routine parts of a job will often increase the productivity and quality of workers by complementing their skills with machines and computers, as well as enabling them to focus on those aspect of the job that most need their attention.

The Transformation of Logistics in the Retail Industry

In the spring of 2018, MIT launched the Work of the Future Task Force to understand the impact of our increasingly intelligent machines on the future of work, and how to best harness these technological innovations for social benefit. The MIT-wide task force released its findings and recommendations in a November, 2020 report, - Building Better Jobs in an Age of Intelligent Machines.

In addition to the task force report, the Work of the Future initiative has published a number of working papers and research briefs on related topics. I’d like to now discuss one of those briefs, The Future of Work in Logistics by Arshia Mehta and Frank Levy, which explored the transformation of the retail industry since the advent of e-commerce in the 1990s. The brief is a very interesting case study of the evolution of the retail industry over the past few decades.

“Twenty years ago, U.S. distribution networks were built to deliver products in bulk to retail stores,” wrote the authors. “Today, large parts of distribution networks are built to deliver individual items to home residences. The shift has been driven by technology, working through e-commerce, and recently reinforced by the COVID-19 pandemic.”

A Biological Framework for the Study of Labor Market Resilience

I recently read Universal Resilience Patterns in Labor Markets, - an article published earlier this year in Nature Communications by members of MIT Connection Science and the Max Planck Institute for Human Development. The article analyzed the resilience of labor markets in US cities using a framework inspired by biological ecosystems.

Biological principles have long been an inspiration for the study of sociotechnical systems, - that is, systems that deal not only with complex technologies and infrastructures, but also with the even more complex issues associated with human and organizational behaviors, such as firms, industries, economies, and cities. For example, a 2016 Harvard Business Review article, The Biology of Corporate Survival, applied evolutionary biology principles to analyze why businesses are disappearing faster than ever before.

“[T]he typical study of urban labor at equilibrium obfuscates responses to out- of-equilibrium disruptions,” notes the Nature article. “Cities are the innovation centers of the US economy, but technological disruptions can exclude workers and inhibit a middle class. Therefore, urban policy must promote the jobs and skills that increase worker pay, create employment, and foster economic resilience.”

Business and Technology Predictions for 2021 and Beyond

Earlier this year, I attended Predictions 21, an online event organized by Forrester Research to help companies understand the key business and technology dynamics that will shape 2021 and beyond. “Faced with the pandemic, firms did things that once seemed impossible - sometimes overnight,” said the accompanying event guide. “Under the relentless pressure of new customer realities, the future came into focus: The value of your company depends on how customer-obsessed, resilient, creative, and adaptive you are in jumping to the next growth curve in your industry. … 2021 will be the year that every company - not just the 15% of firms that were already digitally savvy - doubles down on technology-fueled experiences, operations, products, and ecosystems.”

The past year has been truly chaotic. How can firms formulate their strategies for the next few years in such an uncertain environment? But, as former US president Dwight Eisenhower famously said when he was Commander of Allied Forces in WWII: “In preparing for battle I have always found that plans are useless but planning is indispensable.” In other words, you must carefully assess the various directions in a highly uncertain future while being ready to flexibly adjust to changing circumstances.

Much has been written about the post-pandemic new normal. There are multiple opinions on a number of areas, such as cities, globalization, supply chains, and labor markets. But, just about everyone predicts an increasingly digital post-pandemic new normal. “The COVID-19 crisis seemingly provides a sudden glimpse into a future world, one in which digital has become central to every interaction,” said McKinsey in an April, 2020 article. “The adoption of new technological behaviours in response to the pandemic, from video-conferencing to online shopping, means usage has already reached levels that were not expected for many more years,” noted The Economist several months later.

In addition to the online webinar, Predictions 21 includes a number of related articles and videos. Let me summarize a few of Forrester’s key predictions.

The Urgent Need for Wide-Scale Upskilling

Few topics are as important as the future of work in our 21st century digital economy. In the spring of 2018 MIT President Rafael Reif commissioned a task force on the Work of the Future to address whether our rapidly advancing technologies will not only raise economic output and the wealth of nations, but enable people to attain higher living standards and better working conditions. After working across MIT for over two and a half years, the task force released its final report in November, 2020.

“Amidst a technological ecosystem delivering rising productivity, and an economy generating plenty of jobs (at least until the COVID-19 crisis), we found a labor market in which the fruits are so unequally distributed, so skewed towards the top, that the majority of workers have tasted only a tiny morsel of a vast harvest,” was the overriding conclusion of the task fore. But, it further argued that with better policies in place, more people could enjoy good careers even as new technologies transform the very nature of work.

Similar conclusions were reached by Upskilling for Share Prosperity, a report published in January, 2021 by the World Economic Forum (WEF) in collaboration with PwC. “Millions of people are already being left behind because of volatile market conditions, the effects of COVID-19, or because they work in industries that are being replaced by new sectors,” said the report… There is an enormous opportunity to reconfigure the world of work at this critical juncture and embark on an upskilling revolution that will give people across the world the ability to participate fully in the future of work, whatever that might be.”

The Post-Pandemic Outlook for Technology, Jobs, and Skills

“The COVID-19 pandemic-induced lockdowns and related global recession of 2020 have created a highly uncertain outlook for the labour market,” said the World Economic Forum (WEF) in The Future of Jobs Report 2020. The pandemic has caused labor markets to change significantly faster than previously expected. What used to be considered the future of work has already arrived. As McKinsey noted in a May, 2020 article: “we have vaulted five years forward in consumer and business digital adoption in a matter of around eight weeks.”

The WEF report aims to shed light on the post-pandemic outlook for technology adoption, jobs and skills over the next five years, including detailed quantitative profiles on 15 industry sectors and 26 advanced and emerging countries. The report is based on a survey of senior executives from nearly 300 global companies which collectively employ 8 million workers. The survey asked 49 questions on the outlook for their companies’ workforce through 2025, including major trends affecting the labor market, the technologies their companies are adopting, the expected evolution of jobs and skills, their training and reskilling programs, and the near-term impact of the pandemic on their workforce.

“The global shift to a future of work is defined by an ever-expanding cohort of new technologies, by new sectors and markets, by global economic systems that are more interconnected than in any other point in history, and by information that travels fast and spreads wide. … As a new global recession brought on by the COVID-19 health pandemic impacts economies and labour markets, millions of workers have experienced changes which have profoundly transformed their lives within and beyond work, their well-being and their productivity. One of the defining features of these changes is their asymmetric nature - impacting already disadvantaged populations with greater ferocity and velocity.”

The Changing Nature of the Liberal Arts in the Digital Economy

What is meant by the liberal arts? Here is a succinct dictionary definition: “The academic course of instruction intended to provide general knowledge and usually comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects.” And, here is a more thorough explanation: “A liberal arts education is by nature broad and diverse, rather than narrow and specialized…  [it] is not intended to train you for a specific job, though it does prepare you for the world of work by providing you with an invaluable set of employability skills, including the ability to think for yourself, the skills to communicate effectively, and the capacity for lifelong learning.”

Over the past few decades, business, engineering, and other professions not previously associated with the liberal arts have embraced a number of its attributes. A few years ago, for example, I came across an article about the efforts of Roger Martin to transform business education. At the time, Martin was the Dean of the Rotman School of Management at the University of Toronto. He had long been advocating “that students needed to learn how to think critically and creatively every bit as much as they needed to learn finance or accounting. More specifically, they needed to learn how to approach problems from many perspectives and to combine various approaches to find innovative solutions.” Such a transformation would require business schools to move into territory more traditionally associated with the liberal arts.

Similarly, in a 2006 report, the National Academy of Engineering called for reforming engineering education. “New graduates were technically well prepared but lacked the professional skills for success in a competitive, innovative, global marketplace. Employers complained that new hires had poor communication and teamwork skills and did not appreciate the social and nontechnical influences on engineering solutions and quality processes.”

A few years ago, USC’s Annenberg School of Communications and Journalism conducted a study to better understand the key competencies companies were looking for. Future leaders, the study found, must be strong in quantitative, technical and business skills. But to advance in their careers, they also need to be good strategic thinkers and must have strong social and communications skills. Companies were looking for so called T-shaped professionals who combine deep quantitative, technical, problem solving hard skills with broad multidisciplinary, communications, and social soft skills that enable them to collaborate with experts in other fields.

AI Is Mostly About Business Value, Not Technology

A few months ago, Babson College professor Tom Davenport convened a virtual meeting of chief data and analytic officers (CDAO) from a variety of industries to discuss how to best achieve a return on investments (ROI) in AI. “We wanted to learn to what degree these senior leaders shared our perspective that AI faces an important economic return issue, and what, if anything, their companies were doing to address it.”  Many participants said that a decent ROI remains a critical issue for AI projects.

Davenport has long been analyzing how companies should build up their AI capabilities to achieve their business objectives.  For example, in a 2018 Harvard Business Review article he co-authored, Davenport advised companies to build their AI capabilities through the lens of business opportunities, rather than technology.  As has been generally the case with new technologies, highly ambitious, multi-year moon shot projects are less likely to be successful than low-hanging-fruit projects.  Business process automation is one of the least expensive and easiest capability to implement, since companies have long been engaged with enhancing and automating their business processes.

The following year, Davenport talked about the state of AI in the enterprise at the annual conference of MIT’s Initiative on the Digital Economy  His talk was based on recent surveys by Deloitte of executives in US-based companies who were involved in AI projects.  The surveys found that 20-30% of enterprises were early adopters, having implemented at least one AI prototype or production application; most of the projects were in pilots with relatively few already in production; simple projects prevailed over more ambitious and complex ones; and implementation, integration, data issues and talent topped the list of challenges faced by these early adopters.

Is Work-from-Anywhere Here to Stay?

Remote work has been around for a few decades, but took off in the mid-late 1990s with the explosive growth of the Internet.  There were predictions that the Internet would lead to the decline of cities, because technology was making location less relevant to our work and personal lives.  Why would anyone choose to live in an expensive, stressful metropolitan area and endure a long daily commute?  However, instead of declining, superstar cities continued to attract talented, ambitious knowledge workers, and to generate the greatest levels of economy activity and innovation.

But, even before the pandemic, “a movement was brewing within knowledge-work organizations,” wrote Harvard professor Prithwiray (Raj) Choudhury in a recent Harvard Business Review article, Our Work-from-Anywhere Future.  “Personal technology and digital connectivity had advanced so far and so fast that people had begun to ask, ‘Do we really need to be together, in an office, to do our work?’”

“We got our answer during the pandemic lockdowns.  We learned that a great many of us don’t in fact need to be colocated with colleagues on-site to do our jobs.  Individuals, teams, entire workforces, can perform well while being entirely distributed - and they have.  So now we face new questions: Are all-remote or majority-remote organizations the future of knowledge work?  Is work from anywhere (WFA) here to stay?”

The Surprising Power of Business Experimentation

We’ve long associated innovation breakthroughs with science and technology coming out of R&D labs, e.g., the transistor, penicillin, DNA sequencing, TCP/IP protocols, and so on.   Such major lab-based breakthroughs are at one end of the innovation spectrum.  At the other end are market-facing innovations, whose purpose is to create appealing and intuitive user experiences, new business models, and compelling market-based strategies.

Lab-based innovations were generally born when scientists, mathematicians or engineers developed new theories, technologies, algorithms or programs in an R&D lab.  Over time, often years, the innovations found their way to the marketplace.  Since technology and markets advanced at a relatively slow pace, there was little pressure to reduce the transition times from lab to market.  This was the prevailing innovation model through most of the 20th century.

It all started to change in the 1980s as the rate and pace of technology advances significantly accelerated.  The hand-offs and elapsed times to take an innovation from lab to market were no longer competitive, especially with products based on fast changing digital technologies.  Start-up companies significantly shortened the time-to-market for new products and services, putting huge pressure on companies still operating under the old rules.

These competitive pressures, were further exacerbated by the explosive growth of the Internet in the 1990s, as I personally learned when becoming general manager of the newly established IBM Internet Division in December of 1995.  A lot was starting to happen around the Internet, but it was not clear where things were heading, and in particular what the implications would be to the world of business.  With the Internet, there was no one technology or product you could work on in the labs that would make you a success in the marketplace.  This time around, the strategy itself had to come from the marketplace, not the labs.

Embracing the Internet turned out to be much more than a technology change.  It had a very big impact on the overall culture of IBM and many other companies, paving the way for a more outside-in approach to innovation based on continuous marketplace experimentation. 

In his 2020 book Experimentation Works: The Surprising Power of Business Experiments, Harvard professor Stefan Thomke explains the major changes that’ve been taking place in innovation and experimentation over the past 20 - 25 years.

The Intangible Asset Revolution

“Take all the physical assets owned by all the companies in the S&P 500, all the cars and office buildings and factories and merchandise, then sell them all at cost in one giant sale, and they would generate a net sum that doesn’t even come out to 20% of the index’s $28 trillion value,” said Epic S&P 500 Rally Is Powered by Assets You Can’t See or Touch, an article in Bloomberg published on October 21, 2020, -  a day when intangible assets made up more than 84% of the S&P value.

“The rise of intangibles helps explain why many American workers have recently had it so rough, with wages stagnating and benefits disappearing,” adds the article.  And, given our increasingly digital post-pandemic new normal, we can expect the share of intangibles to go higher, “a source of deep concern for those who worry about things like employment and inequality.”

Intangible assets are easier to define as the opposite of tangible assets.  Tangible assets are generally physical in nature, including vehicles, land, plants, equipment, and furniture, but they also include financial assets like stocks, bonds, account receivables, and cash which have a concrete contractual value.   On the other hand, intangible assets are neither physical nor have a concretely specified financial value.  Intangibles include patents, copyrights, trademarks, goodwill, brand value, human capital, R&D, software, and data.  Despite having no physical existence, intangibles have a monetary value since they represent potential revenue, but that value must be established based on accounting principles.  And, unlike tangible assets, intangibles are difficult to value and insure.

According to a 2019 research report by the Ponemon Institute, the value of intangible assets has truly exploded over the past several decades, right along with our increasingly digital economy.  In 1975, the overall value of the S&P 500 was $715 billion, of which 17% was intangible.  In 1985, out of a total value of $1.5 trillion, 32%, or around one third was intangible.  By 1995, the percentages had switched, with intangibles now being 68% of $4.6 trillion.  Intangible values continued to climb to 80% out of $11.6 trillion in 2005; and to 84% of $25 trillion in 2018.

Trends That Will Likely Shape a Highly Uncertain Year

A few weeks ago The Economist published The World in 2021, it’s 35th annual look at the economic, political, social and cultural trends that will likely shape the coming year.  Overall, 2021 will be a year of unusual uncertainty given the still ongoing pandemic, the uneven economic recovery, and the turbulent political environment in the US, Britain, and a number of other countries.  “The great prize on offer is the chance of bringing the coronavirus pandemic under control,” wrote the issue’s editor Tom Sandage.  “But in the meantime risks abound, to health, economic vitality and social stability.”

The World in 2021 highlights ten specific trends.  Let me focus my discussion on three of them.

The Evolution of American Capitalism - Tweaks, Reforms, or Wholesale Change?

“American capitalism has evolved time and again, and we may be poised for another such shift,” said a recent McKinsey article, Rethinking the future of American capitalism, by James Manyika, Gary Pinkus, and Monique Tuin.  “Capitalism has contributed to significant gains in economic growth and prosperity throughout its history.  But at a time of growing public discontent about rising inequality, heightened competition from economies with different models, and existential threats including from climate change, capitalism in its current form - and American capitalism in particular - may face its most serious test.”

Adam Smith, the 18th century Scottish philosopher and economist, is generally considered the father of free-market, free-trade capitalism.  Smith is most famous for The Wealth of Nations, published in 1776 and generally regarded as the first work of modern economics.  He’s also well known for his famous metaphor of the invisible hand - “the free market, while appearing chaotic and unrestrained, is actually guided to produce the right results by this so-called invisible hand.”

Smith believed in a balanced approach to capitalism.  On one side is the fierce competition and self-interest inherent in open, free markets.  On the other, - as he wrote in The Theory of Moral Sentiments, - is the sympathy and community support that’s required to achieve beneficial results in well functioning, stable societies.

How Covid Is Reordering the Global Economy

The October 10 issue of The Economist includes a special report on the impact of covid-19 on the global economy, with eight article on the subject.  “The pandemic has caused the world’s economies to diverge,” notes the issue’s overview article.  “But its long-term impact will be even more far-reaching… huge gaps between the performance of countries are opening up - which could yet recast the world’s economic order.”

According to the OECD, whereas China’s economy is expected to be 10% larger by the end of 2021 than it was in pre-pandemic 2019, the US economy will be essentially the same size, while the economies of the Euro area, the UK, Japan and South Korea will see a decline by the end of 2021 compared to their pre-pandemic levels.

“The covid-19 pandemic will accelerate change in the world economy,” says The Economist.  It’s becoming increasingly clear that “the pandemic will lead to immense structural changes in the global economy: less globalized, more digitized, and less equal.”  Supply chains will bring production closer to home to cut risks.  Office workers will continue to work from their homes for at least part of the week.  Lower paid urban service workers will face unemployment and need to find new jobs.  The gulf between Wall Street and Main Street will widen.  “The challenge for democratic governments will be to adapt to all these changes while maintaining popular consent for their policies and for free markets.”

Let me discuss the three key areas where The Economist expects long-lasting changes: globalization, digitization and inequality.

How to Emerge Stronger in the Post-Pandemic New Normal

“What now?,” asked a recent McKinsey article on the implications of Covid for business.  “Over the past six months, they have reorganized supply chains, set up remote operations, and made tough financial decisions.  But without a COVID-19 vaccine yet available, not much feels different, and the summer pause hasn’t done much to relieve fatigue.”

“One priority, then, is to reenergize the organization - to act rather than react.  Even as the COVID-19 crisis continues to create a world of uncertainty, the goal must be to rebuild for the longer term.  Companies that are strong and resilient will be better placed to survive and prosper.  Those are qualities that can’t be taken for granted; they need to be cultivated.” 

But, how can a company, - regardless of size or industry, - formulate a rebuilding strategy for the longer term in such an uncertain environment?  As former president Dwight Eisenhower famously said when he was the overall Commander of Allied Forces in WWII: “In preparing for battle I have always found that plans are useless but planning is indispensable.”  In other words, rather than doing so on-the-fly, planning during highly uncertain times requires that companies thoroughly map out their rebuilding strategy, and quickly and flexibly react to the continuing changing circumstances.

Building Better Jobs in an Age of Intelligent Machines

On November 18, the MIT Task Force on the Work of the Future released its final report, The Work of the Future: Building Better Jobs in an Age of Intelligent Machines.  The Task Force was commissioned in the spring of 2018 by MIT President Rafael Reif to address what may well be the most critical question of the digital economy: as emerging technologies raise aggregate economic output and the wealth of nations, will they also enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity?  An interim report was released in September, 2019.

“Amidst a technological ecosystem delivering rising productivity, and an economy generating plenty of jobs (at least until the COVID-19 crisis), we found a labor market in which the fruits are so unequally distributed, so skewed towards the top, that the majority of workers have tasted only a tiny morsel of a vast harvest,” is the Task Force overriding conclusion.  Yet, it argues that with better policies in place, more people could enjoy good careers even as new technologies transform the very nature of work.

AI Technologies Are Fundamentally Changing How Work Gets Done

After decades of promise and hype, artificial intelligence is finally becoming one of the most important technologies of our era.  AI technologies, like machine learning, are clearly having a major impact on the very nature of work.  But, how can we best quantify their impact on the actual evolution of jobs?

The best approach for exploring the relationship between technology and jobs is to look at the individual tasks that comprise a job.  Most jobs involve a number of tasks.  Some of these tasks are relatively routine and based on well-understood rules, while others require judgement, social skills and other human capabilities.  The more routine and rules-based the task, the more amenable it is to automation. 

However just because some of its component tasks have been automated, does not imply that the whole job has disappeared.  To the contrary, automating the more routine parts of a job will often increase the productivity and quality of workers by complementing their skills with technologies and tools, thus enabling them to focus on those aspect of the job that most need their attention.  While automation  substitutes for labor, automation also complements labor, increasing productivity and other economic outputs in ways that often raise the demand for and earnings of workers.

“The emergence of artificial intelligence (AI) and machine learning (ML) poses a new set of opportunities - and challenges - for work and workers,” said The Future of Work: How New Technologies Are Transforming Tasks, a research report released last Fall by the MIT-IBM Watson AI Lab.  “The tasks that can be done by machine learning are much broader in scope than previous generations of technology have made possible.  The expanded scope will change the value employers place on tasks, and the types of skills most in demand.”

America’s Obsession with Economic Efficiency

The belief that efficiency is fundamental to competitive advantage has turned management into a science, whose objective is the elimination of waste, - whether of time, materials, or capital, - wrote Roger Martin in “The High Price of Efficiency,” a January 2019 article in the Harvard Business Review.  Martin is professor and former dean of the Rotman School of Management at the University of Toronto, as well as a prolific writer.

“Why would we not want managers to strive for an ever-more-efficient use of resources?,” asked Martin.  Of course we do.  But, an excessive focus on efficiency can produce startlingly negative effects.  To counterbalance such potential negative effects, companies should pay just as much attention to a less appreciated source of competitive advantage: resilience,  - “the ability to recover from difficulties - to spring back into shape after a shock,” he presciently added a year before the advent of Covid-19.

In his recently published book, When More Is Not Better: Overcoming America's Obsession with Economic Efficiency, Martin expanded on his HBR article, arguing that an excessive focus on efficiency is not only detrimental to business but constitutes a serious threat to America’s democratic capitalism.  “Throughout the first nearly two and a half centuries of America’s existence as a sovereign state, most citizens experienced an advance in their economic status in the overwhelming majority of those years.  Based on that trend, Americans have, unsurprisingly, used their votes throughout the years to support and perpetuate capitalism as America’s economic system.  But that consistent economic advance has stalled, and has been for a longer period than ever before in American history.”

The book is based on a six-year project on the future of America’s democratic capitalism by the Martin Prosperity Institute.  The project conducted in-depth interviews with a wide variety of Americans to understand what they thought about the directions of the country.  It excluded people in the top 10% of the income distributions, focusing instead on the vast majority of the populations, which includes people with household incomes ranging from $25,000 to $110,000 with a median of $75,000.

The Social Network Is the Computer

“Human beings have always been a social species,” writes MIT professor Sinan Aral in the opening paragraph of The Hype Machine, his recently published book.  “We’ve been communicating, cooperating, and coordinating with one another since we were hunting and gathering.”  Our increasingly complex social interactions have been the critical factor in the exponential increase of human cranial capacity over the past few million years.  “But today something is different.  Over the last decade, we’ve doused our kindling fire of human interaction with high-­octane gasoline.  We’ve constructed an expansive, multifaceted machine that spans the globe and conducts the flow of information, opinions, and behaviors through society.”

Professor Aral has been studying social media since its beginning in the early 2000s, when it was driven by the idealistic vision of connecting the world and providing free access to information.  The Hype Machine is what he now calls our global social media ecosystem.  This ecosystem has been designed to stimulate and manipulate the human psyche, “to draw us in and persuade us to change how we shop, vote, and exercise, and even who we love.”  His book nicely explains how the social media industrial complex works, how it affects us, and what we can do to help achieve its original vision while avoiding its later perils.  Let me discuss a few of its key points.

How Will the Pandemic Reshape Labor Markets?

“The COVID crisis appears poised to reshape labor markets along at least four axes: telepresence, urban de-densification, employment concentration in large firms, and general automation forcing,” wrote MIT’s David Autor and Elisabeth Reynolds in a July essay on The Nature of Work After the COVID Crisis.   “Although these changes will have long-run efficiency benefits, they will exacerbate economic pain in the short and medium terms for the least economically secure workers in our economy, particularly those in the rapidly growing but never-highly-paid personal services sector.”

Autor and Reynolds are cochairs of the ongoing MIT Work of the Future task force, whose interim report was published in the (pre-Covid) Fall of 2019.  The report’s overriding conclusion was that the likelihood that AI and automation will wipe out major workforce sectors in the near future was exaggerated.  However, there were very important reasons for concern, in particular, the rising polarization of employment and wage distribution over the past few decades which has disproportionately benefited high-skilled professionals. Our most critical challenge, said the report, isn’t necessarily a lack of jobs, but the low quality of jobs and viable careers available to many workers, particularly those without college degrees.

“Despite our concerns about the distributional consequences of advancing technologies, until the COVID crisis began, we were sanguine about the prospects for ongoing employment growth, even in the face of lackluster wage growth,” said the authors in their July essay.  “In the fall of 2019 we wrote, ‘We anticipate that in the next two decades industrialized countries will have more job openings than workers to fill them, and that robotics and automation will play an increasingly crucial role in closing these gaps’. The COVID crisis has upended our confidence in that prediction - not merely because COVID has generated mass unemployment in the short term, which it has, but also because the postcrisis trajectory now worries us.”

Reconnecting Society and Reopening the Economy

A few months ago, MIT Connection Science held it’s annual Sponsors’ Meeting online.  The virtual meeting included a number of very interesting presentations.  Given its continuing importance, I want to focus my discussion on “Reconnecting Society After a Pandemic,” a talk given by visiting professor Esteban Moro. 

Moro started his presentation by showing a slide from this article.  The slide illustrates that if we had done nothing, or just relied on soft mitigation and herd immunity to contain the spread of the Covid-19 virus, the number of cases and deaths would have gone up very rapidly, - overwhelming healthcare systems around the world.  Instead, many national and state governments adopted two distinct sets of actions, the hammer and the dance.

The hammer is the somewhat draconian social distancing policies aimed at containing the spread of the virus, especially in regions like the New York metro area where the number of cases were escalating at a very rapid pace.  The dance starts once the spread of the virus has been brought under reasonable control, - albeit at the price of large economic costs and societal disruption.  The dance is the longer term effort to keep the virus contained until there’s an effective vaccine while reopening the economy and bringing life as close to normal as possible.

Are We Becoming a Decadent, Stagnating Society?

Earlier this year I read a very interesting essay, “The Age of Decadence”, by NY Times columnist Ross Douthat.  The essay is adapted from his recently published book The Decadent Society - How We Became the Victims of Our Own Success.  This long essay covers a lot of ground, from technology and innovation to politics and religion.  The essay was published in early February, before Covid-19 spread across the US.  I’ll discuss the original essay, but I do wonder how it would have been modified to reflect the impact of the pandemic.

“The real story of the West in the 21st century is one of stalemate and stagnation,” wrote Douthat.  “Everyone knows that we live in a time of constant acceleration, of vertiginous change, of transformation or looming disaster everywhere you look.  Partisans are girding for civil war, robots are coming for our jobs, and the news feels like a multicar pileup every time you fire up Twitter.  Our pessimists see crises everywhere; our optimists insist that we’re just anxious because the world is changing faster than our primitive ape-brains can process.” 

“But what if the feeling of acceleration is an illusion, conjured by our expectations of perpetual progress and exaggerated by the distorting filter of the internet?,” he asked.  What if we really inhabit an era in which repetition is more the norm than invention; in which new developments in science and technology consistently undercover; in which we’re comfortably aging, “no longer optimistic about the future… [while] growing old unhappily together.”  What if  “Our civilization has entered into decadence.”

The Long-Term Impact of Early-Career Setbacks

Fail fast, fail often is one of Silicon Valley’s best known mantras.  Is there something to this belief that if you’re not failing fast and often you may be stuck in a stagnating endeavor?  After all, social scientists have their own Matthew Effect, - i.e., the rich get richer and the famous get more famous, - as evidenced in our age of rising economic inequality and superstar dynamics.

In early March, - just before Covid-19 brought normal life to a screeching halt, - I attended a very interesting seminar by Northwestern professor Dashun Wang.  Over the past several years, professor Wang, along with various collaborators, has been investigating the impact of early-career setbacks on the future careers of scientists.

“Setbacks are an integral part of a scientific career, yet little is known about their long-term effects,” notes a recent article he co-authored in Nature Communications.  “Despite the ubiquitous nature of failures, it remains unclear if a setback in an early career may augment or hamper an individual’s future career impact.”  The Matthew Effect would suggest that early-career success is an important determinant of a successful scientific career.  On the other hand, early setbacks could well be a marker for future achievement, teaching young scientists, entrepreneurs, artists, etc, valuable lessons that they wouldn’t have otherwise learned, i.e., what doesn’t kill you makes you stronger.  Which is the most likely scenario?

Scenario Planning - Formulating Strategy in the Face of High Uncertainty

“How can we formulate strategy in the face of uncertainty?,” asks Learning from the Future, a recent Harvard Business Review article by Peter Scoblic, in its opening sentence.  Answering this question has never felt more urgent as leaders prepare for the future.  “Even before the Covid-19 crisis, rapid technological change, growing economic interdependence, and mounting political instability had conspired to make the future increasingly murky.”  Uncertainty was already all-encompassing.

“And then the pandemic hit.”

When the present resembles the past, we can calculate the probability of future outcomes by analyzing past historical data.  That’s how insurance companies accurately predict the life expectancy of different people based on age, gender, general health, behavioral traits like smoking and drinking, etc.  But the situation is very different when the present doesn’t resemble the past.  “Uncertainty stems from our inability to compare the present to anything we’ve previously experienced.  When situations lack analogies to the past, we have trouble envisioning how they will play out in the future.”

Military strategists first developed scenario planning in the 1950s to help them envision the impact of a nuclear war between the US and the Soviet Union, - something that was clearly way beyond anyone’s experience.  The object of scenario planning is to assemble all known facts, trends, and other information and use them to create a number of alternative stories rich in detail, typically three or four, about plausible future outcomes along with the development paths and key events that led to such outcomes.  Altogether, the scenarios should span the scope of possible futures, although the actual future will likely include events from each scenario.

Remote Work is Surprisingly Productive, But For Many… Something Is Missing

What If Working From Home Goes on … Forever?, asks science and technology journalist Clive Thompson in the title of his June 9 NY Times Magazine article.  “The coronavirus crisis is forcing white-collar America to reconsider nearly every aspect of office life.  Some practices now seem to be wastes of time, happily discarded; others seem to be unexpectedly crucial, and impossible to replicate online.  For workers wondering right now if they’re ever going back to the office, the most honest answer is this: Even if they do, the office might never be the same.”

A recent survey found that of the 56% of respondents employed pre-Covid-19, half were working from home, - 35% having recently switched to working from home, while another 15% were already doing so pre-Covid; 37% continued to commute to work, and 10% had been recently laid-off or furloughed.  The survey was  based on two separate national samples of US data, - one which gathered 25,000 responses in early April, and the second another 25,000 responses in early May.

Thompson’s article cites the experience of Accenture, which has around 500,000 employees in more than 200 cities in 120 countries.  Before the pandemic, no more than 10% worked remotely on any given day.  But, by the middle of March, nearly all were asked to work from home.  Employees adapted quickly, said Accenture’s CTO.  The volume of video calls went up by a factor of six while those of audio calls tripled.  Despite having to switch from face-to-face to audio and video interactions, overall productivity actually went up as measured by several metrics.

It’s difficult to judge whether the surge in remote work will last.  “Home life in a lockdown is much harder than usual,” notes Thompson.  “Many workers who live alone are experiencing enforced isolation as an emotional grind… Nearly every parent I spoke to had their fingers crossed that schools and day care would reopen in the fall - at which point remote work might become an option they could choose, as opposed to one they were forced to endure.  Assuming that such a day does arrive, it’s possible that quite a few may elect to continue working outside the office.”

Post-Pandemic, Is the World Likely to Become Significantly Less Flat?

“The golden age of globalisation, in 1990-2010, was something to behold,” wrote The Economist in a January, 2019 article.  “Commerce soared as the cost of shifting goods in ships and planes fell, phone calls got cheaper, tariffs were cut and the financial system liberalised.”

Thomas Friedman’s The World is Flat became an international best-seller in 2005 by nicely explaining what this new golden age of globalization was all about, including the key forces that contributed to flattening the world, - from the explosive growth of the Internet, open source software and related technologies; to the rise of outsourcing, offshoring and global supply chains.

In 2011 I attended a conference where Friedman was one of the speakers.  He said that we’ve transitioned from a connected to an increasingly hyperconnected global economy since he wrote The World is Flat in 2004.  Many of the companies and technologies that were part of every day conversations in 2011, - Facebook, Twitter, LinkedIn, smartphones, cloud computing, big data, broadband wireless Internet, - weren’t mentioned in his book because they had not yet been born or were still in their infancy.

The very nature of the global firm was transformed during these same decades.  In The Globally Integrated Enterprise, a 2006 Foreign Affairs article, then IBM CEO Sam Palmisano argued that the modern industrial corporation was now in its third stage of evolution in the way it conducted business around the world.

Why “The Techlash” Is a Threat to Growth and Progress

A few months ago, the Information Technology and Innovation Foundation (ITIF) published A Policymaker’s Guide to the “Techlash” - What It Is and Why It’s a Threat to Growth and Progress.  “Does information technology (IT) solve problems and make our lives easier, allowing us to do more with less?,” asks the ITIF report.  “Or does it introduce additional complexity to our lives, isolate us from each other, threaten privacy, destroy jobs, and generate an array of other harms?”

It wasn’t all that long ago that digital technologies and Big Tech were largely seen as catalysts for positive change: the Internet had become a global platform for collaborative innovation; social media was a liberating force, helping democratic uprisings like the Arab Spring; and the smartphone was transforming the lives of people all over the world.

But, the 2010s saw the emergence of what’s come to be called the techlash.  The Oxford English Dictionary (OED) defines techlash as “a strong and widespread negative reaction to the growing power and influence of large technology companies, particularly those based in Silicon Valley.”  The term seems to have originated in a November, 2013 article in The Economist, which said that tech elites are turning out to be some of the most ruthless capitalists around, and “will join bankers and oilmen in public demonology.”  By 2018, techlash was one of eight shortlisted entries for OED Word of the Year.

What History Tells Us About the Accelerating AI Revolution

A few weeks before our lives were turned upside down by Covid-19, I read Technology at Work v4.0, the fourth report in the Technology at Work Series developed by Citigroup in collaboration with Oxford University.  The report includes an excellent chapter on What History Tells Us About the Coming AI Revolution by Oxford professor Carl Benedikt Frey based on his 2019 book The Technology Trap.

Recent AI advances have “sparked much excitement…  yet despite this, most ordinary people don’t feel particularly optimistic about the future,” wrote Frey.  For example, a 2017 Pew Research survey found that three quarters of Americans expressed serious concerns about AI and automation, and just over a third believe that their children will be better off financially than they were.

But, in fact, serious concerns about the impact of technology are part of a historical pattern.  “Many of the trends we see today, such as the disappearance of middle-income jobs, stagnant wages and growing inequality were also features of the Industrial Revolution, which began in Britain around 1750.  This was a period of unprecedented technological change but also one of turbulent social and political change.”

The Urgent Need to Strengthen the Nation’s Resilience

Following World War II and the onset of the Cold War with the Soviet Union, the US undertook a series of measures to strengthen the resilience of the country.  These included a significant expansion of government support for scientific research in universities and R&D labs, leading to product innovations from the private sector and better weapons from the defense industry, which contributed to making the US the most prosperous and secure nation in the world.

Another important measure was the expansion of educational opportunities, like the GI Bill which offered the nation’s 16 million WWII veterans payments of tuition and living expenses to attend high school, college or vocational/technical schools.  By 1956, over 2.2 million had used the GI Bill to attend college or university, and 5.8 million had used it for some kind of job training program.

In the 1950s the government enacted the National Interstate and Defense Highways Act, which led to the construction of over 48,000 miles of the Interstate Highway System at a total price estimated at over $500 billion, - the largest public work in America .  The Act had a dual purpose: facilitating the economic growth of the country as well as supporting the country’s defense during a conventional or nuclear war should it be necessary.

And, last but far from least, in the late 1960s the government launched ARPANET, the digital infrastructure that eventually became the Internet.  ARPANET was supported by the Department of Defense to significantly enhance the resilience of the country following a nuclear attack by enabling computers to communicate with each other using a flexible packet-switching digital network.

But, this post-war focus on resilience has significantly waned over the past few decades.  Let me explain.

The 2019 Artificial Intelligence Index

AI has emerged as the defining technology of our era, as transformative over time as the steam engine, electricity, and the Internet.  While still in its early stages, AI is already reshaping the economy, society, our personal lives and the very nature of work, with much more to come as the technology and applications mature, including the scientific research necessary to anticipate and fight future pandemics.  But, what’s the current state of AI and where is it heading?

To help address these important questions, the annual Artificial Intelligence Index was created under the auspices of the Stanford Institute for Human-Centered Artificial Intelligence, - guided by a Steering Committee of experts from academia and industry, and in collaboration with a number of sponsoring partners and data contributors.  The AI Index aims to “provide unbiased, rigorous, and comprehensive data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI.”

Now in its third year, the 2019 AI Index Report was released this past December.  So was the associated 2019 AI Index Data, which includes three times as many data sets as the 2018 edition.  The report  comprises nine chapters.  Let me summarize a few of its highlights.

The Long-Term Future of Work and Education: Three Potential Scenarios

“Experts differ widely in their predictions about how technological innovation will change the labor market, but they all see a need for changes in education,” write British professors Ewart Keep and Phillip Brown in  a recently published article, Rethinking the Race Between Education and Technology.  While experts don’t generally agree on much, they’re pretty much of one mind when it comes to the growing importance of skills and education in our 21st century digital economy.

Every past technological transformation ultimately led to more jobs, higher living standards and economic growth.  But, as a number of recent studies concluded, to ensure that this will indeed be the case, our emerging knowledge economy should be accompanied by the expansion of educational opportunities for everyone.

While noting that this is the most likely scenario for the next 10 - 15 years, Keep and Brown also consider two potential longer-term scenarios.  Perhaps AI will lead to even more pervasive and fundamental transformations in the nature of work, making it difficult for even those with a college or higher education to find a good job.  Beyond that, some have suggested that in the more distant future we might see an even more radical, science-fiction-like transformation: the end of work as we’ve long known it.

The authors argue that considering such a spectrum of possibilities will help us better prepare for what’s essentially an unpredictable future.  In that spirit, their paper discusses three different labor market scenarios: labor scarcity, job scarcity, and the end of work.

The State of AI Adoption - High Performers Show the Way

For the past few years, the McKinsey Global Institute has been conducting a yearly survey to assess the state of AI adoption.  Its 2017 survey of over 3,000 AI-aware executive found that outside the technology sector, AI adoption was at an early, often experimental stage.  Only 20% of respondents used any AI-related technology in a core part to their business.  A common theme throughout the report was that the same players who were leaders in the earlier waves of digitization and analytics were the early leaders in the AI wave.

The McKinsey 2018 survey garnered responses from over 2,000 participants from a wide range of company sizes across 10 industry sectors.  Overall, the 2018 survey found that while the business world had begun to adopt AI, few companies had in place the foundational building blocks that would help them to generate value from AI at scale.  30% were conducting AI pilots.  Nearly half, 47%, had embedded at least one AI capability in their standard business processes, but only 21% reported using AI across multiple business functions.  AI investments were still quite small, with almost 60% of respondents saying that less that one-tenth of their digital budgets went toward AI.

The most recent Global AI Survey was published in November of 2019.  McKinsey garnered responses from over 2,300 participants, nearly 80% of whose companies were using AI in some capacity.  Overall,  the survey showed that “Most companies report measurable benefits from AI where it has been deployed; however, much work remains to scale impact, manage risks, and retrain the workforce.”  AI is becoming more mainstream, with 58% of respondents using AI in at least one function, - a nearly 25% increase over the previous year; and 30% reported using AI across multiple business units, - a nearly 50% increase.

One of the survey’s major findings is that a small share of high performers, around 3% of companies using AI, are already achieving outsize business results.   High performing companies are much further along in scaling the use of AI in their organizations, with an average of 11 different use cases compared an average of 3 among the other companies.

The Puzzling Economic Impact of Transformative Technologies

“General purpose technologies (GPTs) are engines for growth,…” wrote Erik Brynjolfsson, Daniel Rock, and Chad Syverson in The Productivity J-Curve, a working paper recently published by the National Bureau of Economic Research (NBER).  “These are the defining technologies of their times and can radically change the economic environment.  They have great potential from the outset, but realizing that potential requires larger intangible and often unmeasured investments and a fundamental rethinking of the organization of production itself.”

As we’ve learned over the past two centuries, there’s generally been a significant time lag between the broad acceptance of a major new transformative technology and its ensuing impact on companies, governments and other institutions.  Even after reaching a tipping point of market acceptance, it takes considerable time, - often decades, - for these new technologies and business models to be widely embraced across economies and societies, - and for their full benefits to be realized.

In her 2002 influential book, Technological Revolutions and Financial Capital, economic historian Carlota Perez wrote that since the advent of the Industrial Revolution, we’ve had a major technological revolution every 60 years or so.  First was the age of machines and factories in the latter part of the 18th century.  This was followed by the age of steam, coal and iron in the early to mid 19th century; electricity and steel around the 1870s-1880s; and automobiles, oil and mass production in the early decades of the 20th century.  Then came the computer and communications revolution in the latter part of the 20th century, ushering the transition from the industrial economy of the past two centuries to our present digital economy.

According to Perez, the economic transformations accompanying these technologies are composed of two distinct periods, each lasting roughly 20 to 30 years.  First comes the installation period when the new technologies emerge into the marketplace, entrepreneurs launch many new startups, and venture capitalists encourage experimentation with new business models. This is then followed by the deployment period, when the now well accepted technologies and business models become the norm, leading to long-term economic and productivity growth.

The Increasing Demand for Hybrid, “T-Shaped” Workers

A recent article in The Atlantic used the USS Gabrielle Giffords to illustrate the important changes taking place in the US Navy, - and in the world of work in general.  After discussing various features of its advanced design, the article noted that the ship’s most futuristic aspect is its crew.  “It was designed to operate with a mere 40 souls on board - one-fifth the number aboard comparably sized legacy ships and a far cry from the 350 aboard a World War II destroyer.  The small size of the crew means that each sailor must be like the ship itself: a jack of many trades and not, as 240 years of tradition have prescribed, a master of just one,” noted the article.  Due to increasingly sophisticated technologies and the high cost of personnel, the USS Gabrielle Giffords is among a new class of Navy ships that’s turned away from specialists in favor of so-called hybrid sailors who are able to handle multiple tasks and rapidly acquire new skills.

The replacement of highly specialized workers with problem-solving generalists who are able to handle and quickly learn new tasks has been taking place across a wide variety of  occupations and industries.  Increased productivity and lower costs, i.e., doing more with less, are some of the reasons for this change.  But, the increased complexity of products, applications and systems, and the unanticipated problems that often follow are other important reasons.

The concept of hybrid or T-shaped workers was first introduced around 25 years ago as a metaphor to describe the kind of individuals that the Navy and many other organizations are looking for.  The vertical stroke in the letter T represents a depth of skills and expertise in one or more specific fields; the horizontal bar implies broad multidisciplinary and social skills, as well as the ability to collaborate with experts across disciplines to jointly solve complex problems.

How to Transform a “Big, Old” Company into an Agile Digital Business

“As consumers, we take digital technologies for granted…  We don’t wonder why these things are possible; we simply expect them,” said Designed for Digital a recently published book by Jeanne Ross, Cynthia Beath, and Martin Mocker in its Preface.  But, “the adoption of digital technologies in business doesn’t come as naturally,” - especially if you’re working in a big, old company.  “Inserting digital technologies to enhance operations and create new value propositions has proven extremely challenging.”

Previous research has uncovered this puzzling digital adoption discrepancy between individuals and organizations.  While in our personal lives we’ve enthusiastically embraced digital technology advances, many corporations and institutions still struggle to do so.  At a conference several years ago I learned about a so-called Sunday-night/Monday-morning syndrome, the name given to the frustration of  employees of large companies who, at home on Sunday night, have access to the latest devices and applications, but at work on Monday morning, have to use the more primitive devices and applications that their IT departments support.

A quarter century into the digital age, - as a recent McKinsey study found, - the digital maturity of traditional incumbent firms is still relatively low, - under 25% of their overall potential.  Big, established companies, in particular, have been slow to embrace digital organizational practices, - only 26% of worldwide sales are made through digital channels, 30% of internal operations have been digitally automated, and 25% of supply chains interactions have been digitized.

“If digital technologies are consistently making our consumer lives easier, why aren’t they making it easier to succeed in business?,” asks Designed for Digital.  “Why are business leaders anxious about digital disruption rather than marveling about how quickly they can provide new, exciting, and ever-improving digital solutions to their customers?”  Based on five years of research at nearly 200 large companies, - including executive interviews, surveys of business leaders, and in-depth case studies, - the authors overriding conclusion is that “Big, old companies are simply not designed for digital.”

The MIT Work of the Future Report

“The world now stands on the cusp of a technological revolution in artificial intelligence and robotics that may prove as transformative for economic growth and human potential as were electrification, mass production, and electronic telecommunications in their eras,” said the MIT Task Force on the Work of the Future in its recently released interim report.  The final report will be issued after conducting additional research over the next year.

The Task Force was convened in the spring of 2018 by MIT President Rafael Reif to address what may well be the most critical question of the digital economy: as emerging technologies raise aggregate economic output and the wealth of nations, will they also enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity?

The report’s overriding conclusion is that the likelihood that AI and automation will wipe out major workforce sectors in the near future is exaggerated.  However, we’ve already seen important reasons for concern, especially the rising polarization of employment and wage distribution over the past few decades, which has disproportionately benefited high-skilled professionals while reducing opportunities for mid- and low-skilled workers.

“[A] critical challenge is not necessarily a lack of jobs, but the low quality of many jobs and the resulting lack of viable careers for many people, particularly workers without college degrees.  With this in mind, the work of the future can be shaped beneficially by new policies, renewed support for labor, and reformed institutions, not just new technologies. Broadly, the task force concludes, capitalism in the U.S. must address the interests of workers as well as shareholders.”

How We Learned to Prosper Using Fewer Resources

“We have finally learned how to tread more lightly on our planet.  It’s about time,” writes Andrew McAfee in the Introduction to his new book, More from Less: The Surprising Story of How We Learned to Prosper Using Fewer Resources - and What Happens Next.   McAfee is Co-Director of MIT’s Initiative on the Digital Economy and a Principal Research Scientist at the MIT Sloan School of Management, as well as a prolific writer of books and articles.

“For just about all of human history our prosperity has been tightly coupled to our ability to take resources from the earth,” he adds.  “So as we became more numerous and prosperous, we inevitably took more: more minerals, more fossil fuels, more land for crops, more trees, more water, and so on.  But not anymore.  In recent years we’ve seen a different pattern emerge: the pattern of more from less.”

What led to the emergence of a more-from-less pattern?  The book provides a provocative answer to this question.  The most important forces responsible for the change are technological progress and capitalism.

How to Support the Widespread Adoption of AI

“Artificial intelligence is reshaping business - though not at the blistering pace many assume,” notes Building the AI-Powered Organization, an article in Harvard Business Review by McKinsey partners Tim Fountaine, Brian McCarthy, and Tamim Saleh in its opening sentence.  A number of studies agree that AI is the biggest commercial opportunity for companies and industries over the next 10-15 years.  Two recent reports by McKinsey and PwC respectively concluded that AI has the potential to incrementally increase global economic output between now and 2030 by an additional $13 to $15 trillion.

“Yet, despite the promise of AI, many organizations’ efforts with it are falling short,” adds the HBR article.  Surveys with thousands of executives, showed that most firms are only using AI in ad hoc pilots or applying it to a single business process.  Only 8% of firms are engaged in practices that support widespread adoption.

Why the slow progress?  “At the highest level, it’s a reflection of a failure to rewire the organization.  In our surveys and our work with hundreds of clients, we’ve seen that AI initiatives face formidable cultural and organizational barriers…  at most businesses that aren’t born digital, traditional mindsets and ways of working run counter to those needed for AI.”

To support the widespread adoption of AI, companies must make three fundamental shifts.

The Future of Work in the US: A Tale of Multiple Americas

The US economy looks good by almost any measure.  Unemployment is at historical low levels, forcing employers to raise wages and become more aggressive about hiring and training workers.  There are more job openings than unemployed people to fill them.  Inflation remains low.  A number of recent studies have concluded that over the next decade, our technology-based economy will create a significant number of new occupations which will more than offset declines in occupations displaced by automation.  Not only is the US economy doing well in the present, but despite our increasingly smart machines, automation fears appear to be unfounded.

Why then are so many Americans so anxious about the future?  Why do they feel left behind despite our growing economy?  Why is the country so polarized?

A recent McKinsey report, The Future of Work in America: People and place, today and tomorrow, sheds light on these very important questions.  For the past several years, McKinsey has been conducting research on the impact of automation technologies on the future of work at a national level.  This new report is radically different, based on a detail analysis of more than 3,000 US counties and over 300 cities.

Overall, the study found that while in aggregate the country is doing well, there are actually multiple Americas, each with widely different economic patterns and on sharply different trajectories, some of which are doing quite well and face an exciting future, while others are not in good shape and risk falling further behind.

The report is organized into five main sections, and includes a number of tables, graphs and maps.  Let me summarize the key findings of each of the sections.

The State of AI in the Enterprise

A few months ago, Babson College professor Tom Davenport gave a talk on the state of AI in the enterprise at the annual conference of MIT’s Initiative on the Digital Economy.  His talk was based on two recent US surveys conducted by Deloitte, the first one in 2017 followed by a second in 2018.  Davenport was a co-author of both reports.

The 2017 survey was focused on the responses of 250 US executives who were leading the applications of AI in their companies.  The larger 2018 survey reached out to 1,100 IT (46%) and line-of-business (54%) executives from US-based companies (64% at the C-level) and 10 different industries.  All of these respondents were early AI adopters compared with their counterparts in an average company, - 90% were directly involved in their company’s AI projects, and 75% said that they had an excellent understanding of AI.

Davenport started his talk by summarizing the key findings in the Deloitte surveys:

• 20-30% of enterprises are early adopters, having implemented at least one AI prototype or production application;
  
• Many projects are in pilots but some are already in production;
• Relatively simple low hanging fruit projects prevail over more ambitious and complex moon shots;
  
• Only 24% cited “reducing headcount through automation” as one of their top AI priorities;
• The great majority of respondents believe that AI leads to moderate or substantial changes in job roles and skills;
• Implementation, integration, data issues and talent top the list of challenges faced by early adopters;
  
• Further AI growth is inevitable.

The Digitalization of the American Workforce

“Over the past half century, wave after wave of digital innovation has ensured that digitalization - the diffusion of digital technologies into nearly every business and workplace and pocket - has been remaking the U.S. economy and the world of work,” said the Brookings Institution in Digitalization and the American Workforce.  The digitalization of everything has both increased the potential of individuals and societies while contributing to widespread anxiety about its impact on jobs and economic inequalities.  “And yet, for all of the evidence that big changes are underway, surprisingly little data exists to track the spread of digital adoption.”

The Brookings report quantified the spread of digitalization by analyzing the changes in the digital content of 545 occupations between 2002 and 2016 based on O*NET, the most comprehensive data on US occupations sponsored by the US Department of Labor.  O*NET includes highly detailed, task-level information on hundreds of occupations, and includes quantitative measures of knowledge requirements, skills, tools, education, training and work activities. In addition, the report collected information on the occupations’ particular industries, pay, growth rates, geographical locations and distribution across educational and demographic groups.

Each of the 545 occupations, - which encompassed 90% of the US workforce, - was assigned a digital score between 0 and 100 based on the required digital skills.  High digital occupations are those with scores over 60.  They include software developers - with a score of 91; computer system analysts - 79; and financial managers, - 61.  Medium digital occupations scored between 33 and 60, and include lawyers - 58; automative service technicians - 55; office clerks - 55; and registered nurses - 55.  Low digital occupations have a score below 33, and include security guards - 31; restaurant cooks, - 18; construction laborers - 17; and personal care aides - 14.

The (Updated) Purpose of the US Corporation

In September of 1997, the Business Roundtable (BRT), - an association of CEOs of major US companies, - issued a Statement on Corporate Governance which argued that “the paramount duty of management and of boards of directors is to the corporation’s stockholders; the interests of other stakeholders are relevant as a derivative of the duty to stockholders.”

Last week, the BRT released an updated statement on the Purpose of a Corporation which moves away from it’s previous commitment to shareholder primacy to now emphasize a “Commitment to All Stakeholders” and to “An Economy that Serves All Americans.”  This new statement, which was signed by almost 200 CEOs, now places shareholder interests on the same level as the interests of all its other stakeholders, including customers, employees, suppliers, and communities.

The recent BRT statement has received mostly positive coverage. “Top CEOs Say Companies Have Obligations to Society.  Business Roundtable urges firms to take into account employees, customers and community,” said the WSJ in its article’s headline.  Speaking of the change, Fortune noted that over the past decade “Capitalism, at least the kind practiced by large global corporations, was under assault from all sides, and CEOs were getting the message loud and clear…  Capitalism, it seemed, was desperately in need of a modifier.”  The only note of discord I came across was the response of the Council of Institutional Investors, which expressed concerns that the BRT statement “undercuts notions of managerial accountability to shareholders.”

I applaud the BRT statement.  “This is great,” I thought when first reading it, followed by “what took you so long?”  Given the suffering brought upon so many Americans by the 2008 global financial crisis, - the worst since the Great Depression, - restoring trust in business and in our capitalist economic system should have been a top priority for corporate leaders.  To help appreciate why it’s taken the BRT over a decade to affirm that companies have obligations to society, let’s take a look at the prevalent economic and political context of the past 50 years.

A Quarter Century into the Digital Age

The digital age was born around 25 years ago with the public release of the Netscape browser in 1994.  The browser made it much, much easier for the average person to access information over the Internet, sparking the explosive growth of users, websites and online applications.  This was a truly historical point, marking the transition from the industrial economy of the past couple of centuries to a new kind of digital economy.   Ever since those days, the digital age has continued to advance driven by a stream of new technologies, and business models, from smartphones and cloud to big data and machine learning.

A few months ago, the McKinsey Global Institute published Twenty-five Years of Digitization, a report offering ten insights to help business leaders navigate this still relatively new digital world.  Let me first list the ten insights, and then briefly comment on a few of them.

• Large economic potential is linked to digitization - and much of it is yet to be captured;
• Digital superstars are rising far beyond the US big four and China’s big three;
• Digital natives are calling the shots;
• Digital changes everything - even industry boundaries;
• Agile is the new way to compete;
• Playing the platform economy is an in-the-money option;
• Self-cannibalization and innovation are a necessity for digital reinvention;
• Going after the right M&A is key;
• Effective management of digital transformation is vital - but challenging; and
  
• Leveraging, and transitioning from, digital to new frontier technologies is an imperative.