Category Archives: Research

Manager and machine: The new leadership equation

McKinsey & Company | By Martin Dewhurst and Paul Willmott | Sep 2014

Man vs machine - Manager and machine: The new leadership equationAs artificial intelligence takes hold, what will it take to be an effective executive?

What would it take for algorithms to take over the C-suite? And what will be senior leaders’ most important contributions if they do? Our answers to these admittedly speculative questions rest on our work with senior leaders in a range of industries, particularly those on the vanguard of the big data and advanced-analytics revolution. We have also worked extensively alongside executives who have been experimenting most actively with opening up their companies and decision-making processes through crowdsourcing and social platforms within and across organizational boundaries.

See:  The Enterprise Automation Imperative—Why Modern Societies Will Need All the Productivity They Can Get

Our argument is simple: the advances of brilliant machines will astound us, but they will transform the lives of senior executives only if managerial advances enable them to. There’s still a great deal of work to be done to create data sets worthy of the most intelligent machines and their burgeoning decision-making potential. On top of that, there’s a need for senior leaders to “let go” in ways that run counter to a century of organizational development.

The contrast with the command-and-control era—when holding information close was a source of power, and information moved in one direction only, up the corporate hierarchy—could not be starker. Uncomfortable as this new world may be, the costs of the status quo are large and growing: information hoarders will slow the pace of their organizations and forsake the power of artificial intelligence while competitors exploit it.

The Human Edge

If senior leaders successfully fuel the insights of increasingly brilliant machines and devolve decision-making authority up and down the line, what will be left for top management to do?

Asking questions:  Asking the right questions of the right people at the right times is a skill set computers lack and may never acquire. Algorithms and artificial intelligence may broaden this kind of analytical complexity beyond the financial world, to a whole new set of decision areas—again placing a premium on the tough questions senior leaders can ask. Penetrating this new world of analytical complexity is likely to be difficult, and an increasingly important role for senior executives may be establishing a set of small, often improvisatory, experiments to get a better handle on the implications of emerging insights and decision rules, as well as their own managerial styles.

Attacking Exceptions:  Senior leaders will have to draw on a mixture of insight—examining exceptions to see if they require interventions, such as new credit limits for a big customer or an opportunity to start bundling a new service with an existing product—and inspiration, as leaders galvanize the organization to respond quickly and work in new ways. Exceptions may pave the way for innovation too, something we already see as leading-edge retailers and financial-services firms mine large sets of customer data.

Tolerating ambiguity:  While algorithms and supercomputers are designed to seek answers, they are likely to be most definitive on relatively small questions. The bigger and broader the inquiry, the more likely that human synthesis will be central to problem solving, because machines, though they learn rapidly, provide many pieces without assembling the puzzle. That process of assembly and synthesis can be messy and slow, placing a fresh premium on the senior leaders’ ability to tolerate ambiguity.

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Employing ‘soft’ skills:  Humans have and will continue to have a strong comparative advantage when it comes to inspiring the troops, empathizing with customers, developing talent, and the like. Sometimes, machines will provide invaluable input, as Laszlo Bock at Google has famously shown in a wide range of human-resource data-analytics efforts. But translating this insight into messages that resonate with organizations will require a human touch. No computer will ever manage by walking around. And no effective executive will try to galvanize action by saying, “we’re doing this because an algorithm told us to.”

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NCFA Jan 2018 resize - Manager and machine: The new leadership equation The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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FT Partners Report (Jan 2020): The Rise of Challenger Banks: Are the Apps Taking Over?

FT Partners | Jan 2020

FTP rise of challenger banks research - Manager and machine: The new leadership equationExecutive Summary:

The banking sector is experiencing a major shift globally, as Challenger Banks are becoming increasingly formidable competitors to traditional banks and have begun to capture significant market share. Furthermore, the lines between banks and other consumer financial services providers are blurring, with several alternative lenders and robo-advisors beginning to offer banking products to their customers. E-commerce / internet giants are also jumping into the fray with Google and Amazon, among others, beginning to offer banking products. In response to the emergence of Challenger Banks, a number of incumbent banks have launched their own FinTech brands, and traditional financial institutions will likely turn to FinTech solution providers in order to defend their turfs.

 

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NCFA Jan 2018 resize - Manager and machine: The new leadership equation The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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Securities Exchange Commission’s Advocate for Small Business Capital Formation – Annual Report 2019

SEC | Martha Millar | Jan 8, 2020

capital raising volume in private and public markets - Manager and machine: The new leadership equationAnnual 2019 Report to Congress

The Office prepares an annual report to Congress summarizing its activities in supporting small businesses and their investors during the immediately preceding fiscal year. The report provides statistical information and analyses of the issues on which the Office has worked, information on steps that the Office has taken to improve small business services, and a summary of the most serious issues encountered by small businesses and their investors, including any unique issues encountered by minority-owned small businesses, women-owned small businesses, and small businesses affected by natural disasters. The FY2019 annual report was delivered on December 19, 2019.

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NCFA Jan 2018 resize - Manager and machine: The new leadership equation The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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The Psychological Price of Entrepreneurship

Inc. | By Jessica Bruder | Jan 7, 2020

price of entrepreneurship 1 - Manager and machine: The new leadership equationNo one said building a company is easy. But it's time to be honest about how brutal it really is -- and the price so many founders secretly pay.

Editor's Note: This article won an award in the Magazine Personal Service category in the 2014 Annual Awards Contest of the Deadline Club, the New York City chapter of the Society of Professional Journalists.

By all counts and measures, Bradley Smith is an unequivocal business success. He's CEO of Rescue One Financial, an Irvine, California-based financial services company that had sales of nearly $32 million last year. Smith's company has grown some 1,400 percent in the last three years, landing it at No. 310 on this year's Inc. 500. So you might never guess that just five years ago, Smith was on the brink of financial ruin--and mental collapse.

See: Debt vs. Equity Financing: Pros And Cons For Entrepreneurs

Back in 2008, Smith was working long hours counseling nervous clients about getting out of debt. But his calm demeanor masked a secret: He shared their fears. Like them, Smith was sinking deeper and deeper into debt. He had driven himself far into the red starting--of all things--a debt-settlement company.

"I was hearing how depressed and strung out my clients were, but in the back of my mind I was thinking to myself, I've got twice as much debt as you do," Smith recalls.

He had cashed in his 401(k) and maxed out a $60,000 line of credit. He had sold the Rolex he bought with his first-ever paycheck during an earlier career as a stockbroker. And he had humbled himself before his father--the man who raised him on maxims such as "money doesn't grow on trees" and "never do business with family"--by asking for $10,000, which he received at 5 percent interest after signing a promissory note.

Smith projected optimism to his co-founders and 10 employees, but his nerves were shot.

"My wife and I would share a bottle of $5 wine for dinner and just kind of look at each other," Smith says. "We knew we were close to the edge." Then the pressure got worse: The couple learned they were expecting their first child. "There were sleepless nights, staring at the ceiling," Smith recalls. "I'd wake up at 4 in the morning with my mind racing, thinking about this and that, not being able to shut it off, wondering, When is this thing going to turn?"

After eight months of constant anxiety, Smith's company finally began making money.

Successful entrepreneurs achieve hero status in our culture. We idolize the Mark Zuckerbergs and the Elon Musks. And we celebrate the blazingly fast growth of the Inc. 500 companies. But many of those entrepreneurs, like Smith, harbor secret demons: Before they made it big, they struggled through moments of near-debilitating anxiety and despair--times when it seemed everything might crumble.

Until recently, admitting such sentiments was taboo. Rather than showing vulnerability, business leaders have practiced what social psychiatrists call impression management--also known as "fake it till you make it." Toby Thomas, CEO of EnSite Solutions (No. 188 on the Inc. 500), explains the phenomenon with his favorite analogy: a man riding a lion.

"People look at him and think, This guy's really got it together! He's brave!" says Thomas. "And the man riding the lion is thinking, How the hell did I get on a lion, and how do I keep from getting eaten?"

Not everyone who walks through darkness makes it out. In January, well-known founder Jody Sherman, 47, of the e-commerce site Ecomom took his own life. His death shook the start-up community. It also reignited a discussion about entrepreneurship and mental health that began two years earlier after the suicide of Ilya Zhitomirskiy, the 22-year-old co-founder of Diaspora, a social networking site.

See: The Average Cost of Health Insurance

Lately, more entrepreneurs have begun speaking out about their internal struggles in an attempt to combat the stigma on depression and anxiety that makes it hard for sufferers to seek help. In a deeply personal post called "When Death Feels Like a Good Option," Ben Huh, the CEO of the Cheezburger Network humor websites, wrote about his suicidal thoughts following a failed startup in 2001. Sean Percival, a former MySpace vice president and co-founder of the children's clothing startup Wittlebee, penned a piece called "When It's Not All Good, Ask for Help" on his website. "I was to the edge and back a few times this past year with my business and own depression," he wrote. "If you're about to lose it, please contact me." (Percival now urges distressed entrepreneurs to seek professional help: Call the National Suicide Prevention Lifeline at 1-800-273-8255.)

Brad Feld, a managing director of the Foundry Group, started blogging in October about his latest episode of depression. The problem wasn't new--the prominent venture capitalist had struggled with mood disorders throughout his adult life--and he didn't expect much of a response. But then came the emails. Hundreds of them. Many were from entrepreneurs who had also wrestled with anxiety and despair. (For more of Feld's thoughts on depression, see his column, "Surviving the Dark Nights of the Soul," in Inc.'s July/August issue.) "If you saw the list of names, it would surprise you a great deal," says Feld. "They are very successful people, very visible, very charismatic--yet they've struggled with this silently. There's a sense that they can't talk about it, that it's a weakness or a shame or something. They feel like they're hiding, which makes the whole thing worse."

See: Why Older Entrepreneurs Have the Edge

Entrepreneurs often juggle many roles and face countless setbacks--lost customers, disputes with partners, increased competition, staffing problems--all while struggling to make payroll. "There are traumatic events all the way along the line," says psychiatrist and former entrepreneur Michael A. Freeman, who is researching mental health and entrepreneurship.

Complicating matters, new entrepreneurs often make themselves less resilient by neglecting their health. They eat too much or too little. They don't get enough sleep. They fail to exercise. "You can get into a startup mode, where you push yourself and abuse your body," Freeman says. "That can trigger mood vulnerability."

So it should come as little surprise that entrepreneurs experience more anxiety than employees. In the latest Gallup-Healthways Well-Being Index, 34 percent of entrepreneurs--4 percentage points more than other workers--reported they were worried. And 45 percent of entrepreneurs said they were stressed, 3 percentage points more than other workers.

But it may be more than a stressful job that pushes some founders over the edge. According to researchers, many entrepreneurs share innate character traits that make them more vulnerable to mood swings. "People who are on the energetic, motivated, and creative side are both more likely to be entrepreneurial and more likely to have strong emotional states," says Freeman. Those states may include depression, despair, hopelessness, worthlessness, loss of motivation, and suicidal thinking.

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NCFA Jan 2018 resize - Manager and machine: The new leadership equation The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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Executive Perspectives on Top Risks 2020

Protivity | Dec 12, 2019

Executive perspectives on top risks 2020 - Manager and machine: The new leadership equationA constantly evolving geopolitical landscape that is trending toward nationalism, an ever-present concern over cyber threats, increasing market disruptions caused by “born digital” organizations and the rise of artificial intelligence (AI)-enabled technologies, and the effects of tightening labor markets are just a handful of concerns voiced by organizational leaders around the globe. Add to these the devastating impact of hurricanes and other natural disasters, continued apprehension over interest rates, uncertainty in war-torn regions of the world, polarization of political viewpoints, the ease with which information can go viral via social media and other digital platforms, and ongoing negotiations to settle Brexit.

See:  Navigating the Great Reset: Fintech in Canada in 2020

These are but a few of the many drivers of uncertainty affecting the 2020 global business outlook. Concerns that foretell a rapidly changing business environment and the potential for unwelcome surprises vividly illustrate the reality that organizations of all types face risks that can either disrupt their business model over time or damage brand image and reputation almost overnight. Insufficient focus on and attention to the web of complex enterprise wide risk events of varying velocity, persistence and severity are likely to threaten an entity’s brand, reputation, business model and, in some instances, its very survival.

Leaders of organizations in virtually every industry, size of organization and geographic location are reminded all too frequently that they operate in what appears to many to be an increasingly risky global landscape. Boards of directors and executive management teams cannot afford to manage risks casually on a reactive basis, especially considering the rapid pace of disruptive innovation and technological developments in an ever-advancing digital world.

Protiviti and NC State University’s ERM Initiative are pleased to provide this report focusing on the top risks currently on the minds of global boards of directors and executives. This report contains results from our eighth annual risk survey of directors and executives worldwide to obtain their views on the extent to which a broad collection of risks is likely to affect their organizations over the next year.

Our respondent group, comprised primarily of board members and C-suite executives from all major regions of the world, provided their perspectives about the potential impact in 2020 of 30 specific risks across three dimensions:1•Macroeconomic risks likely to affect their organization’s growth opportunities•Strategic risks the organization faces that may affect the validity of its strategy for pursuing growth opportunities.  Operational risks that might affect key operations of the organization in executing its strategy.

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In presenting the results of our research, we begin with a brief description of our methodology and an executive summary of the results. Following this introduction, we discuss the overall risk concerns for 2020, including how they have changed from 2019 and 2018, followed by a review of results by size of organization and type of executive position, as well as a breakdown by industry, geographic location, type of ownership structure (i.e., public company, privately held, not-for-profit and government), and companies with rated debt outstanding. We conclude with a discussion of plans among organizations to improve their capabilities for managing risk and a call to action offering executives and directors diagnostic questions to consider when evaluating risk assessment and risk management processes.

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NCFA Jan 2018 resize - Manager and machine: The new leadership equation The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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The Enterprise Automation Imperative—Why Modern Societies Will Need All the Productivity They Can Get

ITIF | Robert D. Atkinson and David Moschella | November 12, 2019

tech handshake - Manager and machine: The new leadership equationContrary to common belief, enterprise automation is not a cause for alarm, but instead a societal imperative. Modern nations will need all the productivity they can get to address today’s ever-more-resource-constrained challenges.

Key Takeways

  • Increased automation can significantly boost societal productivity, which would help address challenges such as wage growth, aging populations, rising health-care costs, environmental restorations, global competitiveness, and public sector debt.
  • The EU and U.S. economies are in a productivity slump, which is one of the reasons wage and GDP growth have stagnated, making it increasingly difficult for governments and residents to meet their civic and financial obligations.
  • Productivity increases in the EU and the U.S. would reshore work, make the costs of aging populations affordable, boost wages and living standards, reduce debt-to-GDP levels, and free up human capital and other resources for new societal tasks.
  • Large enterprises—both public and private—must drive automation and its ensuing productivity gains, because many of today’s most promising digital initiatives can only be brought to fruition by large organizations and the sectors they serve.
  • Public policies should support the transformation of large enterprises and their associated industries and ecosystems by ensuring laws, rules, regulations, incentives, political attitudes, and worker skills do not impede needed changes.

Introduction and Overview

Despite vocal claims to the contrary, automating a large portion of today’s U.S. and EU economies remains one of the most important technology opportunities of the 2020s. Increased automation—with its ability to significantly boost societal productivity—is needed to help modern nations address seemingly intractable challenges such as sluggish wage growth, aging populations, rising health care costs, environmental restorations, global competitiveness, and often-worrisome levels of public sector debt. Advances in public and private sector productivity are also needed to free up human capacity, talent, and ingenuity so the workforces of the future can more fully focus on the exciting possibilities of the Information Age.

See:  ‘Underwhelming’ financial services sector contributes to lagging productivity: report

Much of this automation must be led by large public and private sector enterprises because so many of today’s most promising digital initiatives—including smart cities and grids, precision agriculture and medicine, shared ledgers, autonomous vehicles, robotics, machine learning, and artificial intelligence (AI)—can only be brought to fruition by large organizations and the sectors they serve. While easy-to-use services designed for consumers have dominated digital innovation thus far, global technology leadership will increasingly depend on complex changes in the ways many traditional enterprises and industries work.

There is a risk society will turn away from automation at the very moment it is most needed.

Unfortunately, today’s automation debate is focused almost entirely on the potential downsides. From both the left and the right, we are constantly warned that new technologies—particularly AI and robotics—will destroy tens of millions of jobs, and even diminish human worth. This paper disagrees with these now widely shared perspectives. Although technology innovations will require, as they always have, difficult worker transitions, forecasts of massive job losses have been proven wrong ever since the dawn of Industrial Revolution. Today’s labor and skills shortages—and aging populations—suggest the doomsayers are well along the path to being wrong again. While we could just dismiss the hype and say, “Here we go again,” there remains the risk of society turning away from automation at the very moment it is most needed.

Of course, new technologies are not an instant cure-all. We have heard many times how, for example, e-health, e-government, and self-driving cars were just around the corner, only for reality to prove otherwise. But while the skeptics can make their case—and it is true there will be no quick fixes—two things make us optimistic over the longer term. First, today’s automation technologies are almost uncannily well suited to meet the societal challenges listed above. This means that to bet against advanced automation is to bet against the future of digital technology itself—and this has generally been a losing wager. Second, we can already see that China, without the same constraints many Western economies face, is committed to establishing its own highly automated society, albeit not always in a manner more democratic nations would prefer.

See:  Three Big Things: The Most Important Forces Shaping the World

Importantly, we want to state from the outset that we are not saying that increasing productivity is the only way public policy should respond to these challenges. Far from it. Clearly, much can be done to reduce income inequality, shrink the pay gap between CEOs and workers, close international and other tax loopholes, ease employment transitions, make U.S. health care more portable and affordable, and address similar concerns. However, as these are not technology policy issues per se, they are largely outside the scope of this paper. More fundamentally, without higher levels of productivity, we believe these efforts will likely fall short of meeting the societal challenges we have identified.

To inform both industry executives and technology policymakers about today’s productivity challenge, ITIF and the Leading Edge Forum have launched a new research initiative. This initial paper argues that, contrary to common belief, enterprise automation is now a societal imperative—and modern nations will need all the productivity they can get to address today’s ever-more-resource-constrained challenges. It further argues that without greater enterprise urgency, a significant public policy boost, and the requisite societal skills and support, Western competitiveness will likely suffer.

The paper begins with a discussion of the current trends in productivity and automation. It then shows why increasing public and private sector automation will be essential to Europe and the United States if they are to meet their financial and demographic challenges. We end on an optimistic note by explaining why fears of an increasingly jobless future are still largely unfounded. There’s a great deal of work that needs to be done.

What Do We Mean by Productivity?

To understand what productivity is, it is worth noting what it is not. Productivity is not a measure of how much an economy is producing. In other words, total output (gross domestic product) is not a measure of productivity. Nor is productivity a measure of how many hours people work. Rather, in its simplest form, productivity is a measure of economic output per unit of input (i.e., it is an efficiency measure). The unit of input can be labor hours (labor productivity) or all production factors, including labor, machines, and energy (total-factor productivity). The former is the easiest to understand: If a hairdresser previously cut 10 people’s hair in 8 hours, but now cuts 12 people’s hair in the same amount of time because of better technology (e.g., more efficient clippers), then the hairdresser has increased their productivity by 20 percent.

See:  [Report] A New North Star: Canadian Competitiveness in an Intangibles Economy

Productivity can increase in a number of ways.1 One is for workers to work harder and faster. But this comes at the cost of worker satisfaction and, in some cases, safety, so such gains can be offset by “losses.” This is why increased productivity and overall economic growth are not the same thing. One proven way to raise productivity is to help people work more efficiently by reorganizing work processes or using better technology. For example, self-service elevators eliminated the need for elevator operators, just as automatic teller machines reduced the need for human bank tellers to handle many routine transactions.2

Productivity is often confused with innovation and competitiveness.  As noted, productivity is the ratio of output to input, while innovation means developing an improved product (a good or service), production process, marketing method, or organizational model—or making a similar change. The distinction between “product” and “process” innovation is important because product innovation usually affects the output side of productivity, while process innovation affects the input. Similarly, competitiveness mostly relates to the relative strength of a region’s or nation’s “traded sectors,” i.e., those sectors wherein output is also sold outside that region or nation.

To be sure, these three factors can be closely related. For example, effective innovation can improve productivity and competitiveness. Consider how faster computer chips boost the productivity of the companies and people using devices with those chips—while also helping the chip manufacturers become more globally competitive. Likewise, productivity growth, especially in traded industries such as automobiles, can make nations more competitive by enabling their companies to sell in global markets at lower prices. But each of the three terms is distinct in important ways. For example, rising productivity does not make a nation more competitive when other nations are increasing their productivity even faster.

In most countries, policymakers prioritize competitiveness first, innovation second, and productivity last, if at all. But in modern economies, productivity is typically the most important driver of economic well-being. This is not just because the majority of jobs in most economies are in “non-traded sectors,” wherein the benefits of productivity gains go more directly to workers and domestic consumers. It’s also because these same gains often spread to traded industries because the companies that compete in traded sectors also tend to be heavy consumers of health care, transportation, telecommunications, and many other non-traded services.

See:  Competition Bureau’s call for intel on anti-competitive conduct in digital economy raises eyebrows

Finally, there are two related measures of productivity: labor productivity and total factor productivity. Labor productivity is just as it sounds: the output of workers divided by the number of hours of work. Total factor productivity is a broader measure of the productivity of all factors of production, including workers, energy, and machines. For example, an economy might increase labor productivity by adding more machines, but total factor productivity could go up or down depending on whether the machines’ output is worth the costs. This means total factor productivity is ultimately the more comprehensive measure, although it’s often considerably more difficult to quantify. Even more confounding to the productivity-measurement community is the fact that digital technology is often a major driver of both cost cutting and value creation, as well as labor and factor productivity—and the resulting competitiveness—all at the same time.

Today’s Worrisome Productivity Slowdown

The EU and U.S. economies are in need of a productivity “booster shot” of the kind they experienced in the 1950s and early 1960s with electromechanical and materials innovations (steel, chemicals, plastics, etc.), and again in the 1990s with information and communications technology (ICT) innovations (personal computing, the Internet, broadband, etc.). Indeed, both economies are now in a productivity slump. Labor productivity—all the goods and services a country produces per hour of work—inched up in the United States at just 1.2 percent per year between 2008 and 2017. That is half the rate of the prior 13 years. Similarly, since the financial crisis, labor productivity in the 28 EU member states has grown at just 0.7 percent annually.3 While there is some debate about whether the productivity slowdown is real or simply reflects measurement challenges, the body of evidence suggests the slowdown is not just a measurement effect.4

The EU and U.S. economies need a productivity “booster shot” of the kind they experienced in the 1950s and early 1960s with electromechanical and materials innovations, and again in the 1990s with ICT innovations.

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As will be discussed throughout this paper, this slowdown in productivity is one of the key reasons wage and gross domestic product (GDP) growth have stagnated in both regions, making it increasingly difficult for governments and residents to meet their civic and financial obligations. Too often, the result has been ever-rising public and private sector debt. And even with this borrowing, many nations and individuals feel increasingly squeezed in terms of both their time and finances.

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NCFA Jan 2018 resize - Manager and machine: The new leadership equation The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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Global AI Survey: AI proves its worth, but few scale impact

McKinsey & Company | Nov 2019

Global AI survey - Manager and machine: The new leadership equationMost companies report measurable benefits from AI where it has been deployed; however, much work remains to scale impact, manage risks, and retrain the workforce. A group of high performers shows the way.

Adoption of artificial intelligence (AI) continues to increase, and the technology is generating returns. 1 The findings of the latest McKinsey Global Survey on the subject show a nearly 25 percent year-over-year increase in the use of AI 2 in standard business processes, with a sizable jump from the past year in companies using AI across multiple areas of their business. 3 A majority of executives whose companies have adopted AI report that it has provided an uptick in revenue in the business areas where it is used, and 44 percent say AI has reduced costs.

The results also show that a small share of companies—from a variety of sectors—are attaining outsize business results from AI, potentially widening the gap between AI power users and adoption laggards. Respondents from these high-performing companies (or AI high performers) report that they achieve greater scale and see both higher revenue increases and greater cost decreases than other companies that use AI. 4 The findings, however, provide a potential road map for laggards, showing that the AI high performers are more likely to apply core practices for using AI to drive value across the organization, mitigate risks associated with the technology, and retrain workers to prepare them for AI adoption.

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Further, our results suggest that workforce retraining will need to ramp up. While the findings indicate that AI adoption has generally had modest overall effects on organizations’ workforce size in the past year, about one-third of respondents say they expect AI adoption to lead to a decrease in their workforce in the next three years, compared with one-fifth who expect an increase, and AI high performers are doing more retraining.

Most respondents are seeing returns from AI

In this year’s survey, we asked respondents about 33 AI use cases across eight business functions, including how adoption of AI for each of these activities has affected revenue and cost in the business units where AI is used. The results suggest that AI is delivering meaningful value to companies.

Aggregating across all of the use cases, 63 percent of respondents report revenue increases from AI adoption in the business units where their companies use AI, with respondents from high performers nearly three times likelier than those from other companies to report revenue gains of more than 10 percent. Respondents are most likely to report revenue growth from AI use cases in marketing and sales, product and service development, and supply-chain management (Exhibit 1). In marketing and sales, respondents most often report revenue increases from AI use in pricing, prediction of likelihood to buy, and customer-service analytics. In product and service development, revenue-producing use cases include the creation of new AI-based products and new AI-based enhancements. And in supply-chain management, respondents often cite sales and demand forecasting and spend analytics as use cases that generate revenue.

AI adoption is increasing in nearly all industries, but capabilities vary

As in last year’s survey, we asked respondents about their companies’ use of nine AI capabilities. 5 Fifty-eight percent of respondents report that their organizations have embedded at least one AI capability into a process or product in at least one function or business unit, up from 47 percent in 2018—a sign that AI adoption in general is becoming more mainstream. What’s more, responses show an increase in the share of companies using AI in products or processes across multiple business units and functions: 30 percent of this year’s respondents report doing so, compared with 21 percent in the previous survey. While this seems to indicate that more companies are beginning to scale AI, high performers are much further along in these efforts, averaging 11 reported AI use cases across the organization versus about three among other companies.

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By sector, the results indicate increases in AI adoption in nearly every industry in the past year. Retail has seen the largest increase, with 60 percent of respondents saying their companies have embedded at least one AI capability in one or more functions or business units, a 35-percentage-point increase from 2018.

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The results show companies applying AI capabilities that help them perform the functions that create value in their industries. For example, respondents from consumer-packaged-goods companies are more likely to report using physical robotics—which can aid in assembly tasks—than most other types of capabilities. And telecom respondents report their companies using virtual agents—which can be used in customer-service applications—more than other capabilities (Exhibit 2). High-performing companies, however, are far more likely to adopt AI in business functions that this survey and past research link to greater value creation more broadly. For example, more than 80 percent of respondents from high performers say they have adopted AI in marketing and sales, compared with only one-quarter from those of other companies that use AI.

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On a regional level, the survey shows significant increases in adoption levels in developed Asia–Pacific, 6 Europe, Latin America, and North America. In Asia–Pacific and Latin America, the shares of respondents who say their companies have embedded AI across multiple functions or business units have nearly doubled since the previous survey. However, the increases put all of these regions, as well as China, at similar aggregate reported levels of adoption, suggesting that while there is considerable variation at the level of individual companies, the adoption of AI is a global phenomenon. 7

The results indicate that the pace of adoption will likely continue in the near term, with 74 percent of respondents whose companies have adopted or plan to adopt AI saying their organizations will increase their AI investment in the next three years. More than half of these respondents expect an increase of 10 percent or more. But the survey results indicate that AI high performers plan to invest more, with nearly 30 percent of respondents from these companies saying their organizations will increase investment in AI by 50 percent or more in the next three years, compared with just 9 percent of others who say the same.

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