Tag Archives: Productivity

Updates from Siemens

Redefine the Line: How automotive trends are changing the ways we move from point A to B
By Tarun Tejpal – The automotive industry has been one of the most dynamic and exciting incubators of technological and product innovation in the modern world. A unique mix of investment, consumer interest, and industry competition has driven this dynamism with a constant search for the next feature, style, or capability to capture the public imagination. At the 1964 New York World’s Fair, General Motors (GM) hoped to capture such interest with the Firebird IV concept car. GM explained, then, that the Firebird IV “anticipates the day when the family will drive to the super-highway, turn over the car’s controls to an automatic, programmed guidance system and travel in comfort and absolute safety at more than twice the speed possible on today’s expressways.” (Gao, Hensley, & Zielke, 2014).

GM’s vision of the future was striking and exciting, but the technology did not yet exist to make it a reality. Ford took a different approach to generating buzz in the market, focusing on the present. Instead of forecasting a future of self-driving cars and super highways, Ford launched a car for “young America out to have a good time”: the Mustang (Gao et al., 2014). It engaged the new generation by providing both transportation and personal expression in a stylish, highly configurable, and inexpensive package. Ford estimated it would sell 100,000 Mustangs, but one year after the launch it had sold over 400,000 (Gao et al., 2014).

Vehicles are now a central feature of everyday life. Since 1964, global vehicle sales have grown by nearly 3 percent on average each year, nearly double the rate of population growth, resulting in one billion vehicles on the road today (Gao et al., 2014).

However, large-scale trends, such as a surging Chinese automotive market, electrification, and urbanization, are beginning to affect the form and function of vehicles and personal mobility systems. more>

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Updates from McKinsey

How to restart your stalled digital transformation
Most digital initiatives sputter before they take full effect. A new survey finds that organizations stand a good chance of recovering lost momentum because slowdowns typically happen for reasons within their control.
McKinsey – At organizations pursuing digital transformations, more than seven in ten survey respondents say the progress of these efforts has slowed or stalled at some point. In the latest McKinsey Global Survey on the topic, we set out to understand what organizations can do to prevent burnout or to restart their engines if burnout occurs during these transformations, which previous research has found have a lower success rate than do more traditional transformations. The good news is that in most cases, organizations can prevent or overcome a loss of momentum.

More than 60 percent of respondents who report stalled digital transformations attribute the problem to factors that—with the right discipline and focus—organizations can control in the near term to medium term. This finding runs counter to widespread assumptions that external pressures, such as market disruptions or regulatory changes, pose the biggest threats to digital initiatives. More commonly reported sources of derailed progress include resourcing issues, lack of clarity or alignment on a company’s digital strategy, and poor quality of the digital strategy to begin with.

If a digital transformation stalls, the results suggest that organizations can regain momentum by implementing rigorous change-management and internal-communications programs and clarifying the transformation’s projected impact, which can help build alignment and commitment. For scaling digital programs beyond the pilot phase—the first stumbling block in a transformation’s execution—clarity on the time frame and expected economic impact is important, as is partnering with operations. Should an intervention be needed to reenergize a transformation, having the CEO step in appears to be advantageous. Further lessons come from respondents at companies that avoid stalling in the first place. They often say their organizations maintain momentum by obtaining strong alignment and strategic clarity before a transformation gets under way. more>

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The future will be shaped by what global productivity growth does next

By Warwick J. McKibbin and Adam Triggs – Productivity growth is a shadow of its former self. It’s one-tenth of what it was 40 years ago in advanced economies, and even emerging economies are struggling to replicate the growth of the past. As the fundamental driver of long-run living standards, weak productivity growth is a serious problem. Lower living standards, bigger budget deficits, fewer jobs, lower wages, and higher inequality await if things don’t improve.

What is most striking about this period of low productivity is that it coincides with enormous advances in technology. An extra 3.5 billion people have gained access to the internet. The processing power of computers has increased exponentially while their cost and size have plummeted. Smartphones have multiplied, and online businesses have flourished. Email, GPS and advanced software have become widespread. The sharing economy is unlocking the full potential of idle cars and empty rooms and houses. Information and communication technologies (ICT) and artificial intelligence (AI) have reshaped many industries. The accumulated history of human knowledge is now at our fingertips.

Robert Solow famously remarked that “you can see the computer age everywhere but in the productivity statistics.” Economists have put forward a variety of explanations for the so-called “Solow paradox,” each of which implies a radically different path for productivity growth in the future. Our chapter in the just-published book “Growth in a Time of Change” models each of these possible scenarios to explore what the world might look like depending on who turns out to be correct.

Let’s start with the optimists. Some economists, like the 2018 Nobel Laureate William Nordhaus and Iraj Saniee and his co-authors at Nokia Bell Labs, point to historical data showing long lag times between technological advances and increases in productivity. For these economists, a big surge in productivity is just around the corner.

If the optimists are correct and global productivity growth takes off rapidly, many of the world’s problems go away. Investment, wages, and employment rise sharply. GDP increases and inequality declines. While all sectors experience an investment boom, the durable goods sector experiences the largest increase. The sharp increase in investment sees an increased demand for investment goods, particularly durable manufactured goods and the energy and mining resources required to produce them. Countries that export durable manufactured goods (such as Germany) and energy and mining resources (such as Australia) benefit significantly. Secular stagnation becomes a thing of the past.

But new challenges emerge. The global economy is a closed system, so the resources to finance this boom in investment and production must come from somewhere: either from increased government savings or from reductions in current consumption. If governments don’t act, or if financial market rigidities prevent access to global capital markets, consumption can fall. The shock also triggers transitions that require the redeployment of labor and capital from declining sectors to booming ones. Rigid labor markets and oligopolistic product markets hamper this adjustment. Thus, the full benefits of the boom can be squandered, and its benefits may be short-lived and distributed more unequally between capital and labor.

Now consider the pessimists. Some economists, notably Northwestern University’s Robert Gordon, argue that the technological advances in recent decades won’t deliver the sort of productivity increases that we saw from the inventions of the last century. Facebook and Netflix are great, but they are no match for electricity and indoor plumbing. more>

Why hiring the ‘best’ people produces the least creative results

By Scott E Page – The complexity of modern problems often precludes any one person from fully understanding them. Factors contributing to rising obesity levels, for example, include transportation systems and infrastructure, media, convenience foods, changing social norms, human biology and psychological factors.

Designing an aircraft carrier, to take another example, requires knowledge of nuclear engineering, naval architecture, metallurgy, hydrodynamics, information systems, military protocols, the exercise of modern warfare and, given the long building time, the ability to predict trends in weapon systems.

The multidimensional or layered character of complex problems also undermines the principle of meritocracy: the idea that the ‘best person’ should be hired. There is no best person. When putting together an oncological research team, a biotech company such as Gilead or Genentech would not construct a multiple-choice test and hire the top scorers, or hire people whose resumes score highest according to some performance criteria. Instead, they would seek diversity. They would build a team of people who bring diverse knowledge bases, tools and analytic skills. That team would more likely than not include mathematicians (though not logicians such as Griffeath). And the mathematicians would likely study dynamical systems and differential equations.

Believers in a meritocracy might grant that teams ought to be diverse but then argue that meritocratic principles should apply within each category. Thus the team should consist of the ‘best’ mathematicians, the ‘best’ oncologists, and the ‘best’ biostatisticians from within the pool.

That position suffers from a similar flaw. Even with a knowledge domain, no test or criteria applied to individuals will produce the best team. Each of these domains possesses such depth and breadth, that no test can exist.

Consider the field of neuroscience. Upwards of 50,000 papers were published last year covering various techniques, domains of inquiry and levels of analysis, ranging from molecules and synapses up through networks of neurons. Given that complexity, any attempt to rank a collection of neuroscientists from best to worst, as if they were competitors in the 50-metre butterfly, must fail.

What could be true is that given a specific task and the composition of a particular team, one scientist would be more likely to contribute than another. Optimal hiring depends on context. Optimal teams will be diverse.

Yet the fallacy of meritocracy persists. Corporations, non-profits, governments, universities and even preschools test, score and hire the ‘best’. This all but guarantees not creating the best team.

Ranking people by common criteria produces homogeneity. And when biases creep in, it results in people who look like those making the decisions. That’s not likely to lead to breakthroughs. more>

Updates from ITU

How Mexico seeks to connect its rural citizens better: Arturo Robles
ITU News – In Mexico, 95.23 per cent of the population have a mobile-cellular subscription and 65.77 per cent of the population use the internet, according to ITU statistics.

Connecting the remaining population to the power of the internet, however, has been a challenge as many of the people who remain offline live in very isolated rural areas.

But thanks to successful connections with K-band satellites, commercial satellite operators are now finding profitable and feasible opportunities to provide connectivity in these remote villages, says Arturo Robles, Commissioner of Mexico’s Federal Institute of Telecommunications (IFT).

During an interview with ITU at the World Radiocommunication Conference 2019 (WRC-19) in Sharm El-Sheikh, Egypt, Mr. Robles also shared his hope that innovative services could help provide affordable rural connectivity solutions. more>

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Updates from McKinsey

Why your next transformation should be ‘all in’
By Chris Bradley, Marc de Jong, and Wesley Walden – Business transformation programs have long focused on productivity improvement—taking a “better, faster, cheaper” approach to how the company works. And for good reason: disciplined efforts can boost productivity as well as accountability, transparency, execution, and the pace of decision making. When it comes to delivering fast results to the bottom line, it’s a proven recipe that works.

The problem is, it’s no longer enough. Digitization, advanced technologies, and other forms of tech-enabled disruption are upending industry after industry, pressuring incumbent companies not only to scratch out stronger financial returns but also to remake who and what they are as organizations.

Doing the first is hard enough. Tackling the second—changing what your company is and does—requires understanding where the value is shifting in your industry (and in others), spotting opportunities in the inflection points, and taking purposeful actions to seize them. The prospect of doing both jobs at once is sobering.

How realistic is it to think your company can pull it off? The good news is that our research demonstrates it’s entirely possible for organizations to ramp up their bottom-line performance even as they secure game-changing portfolio wins that redefine what a company is and does. What’s more, “all-in” transformations that focus on the organization’s performance and portfolio appear to load the dice in favor of transformational results. By developing these two complementary sets of muscles, companies can aspire to flex them in a coordinated way, using performance improvements to carry them to the next set of portfolio moves, which in turn creates momentum propelling the company to the next level.

If you want to see where you’re going, it’s best to start with a point of reference. Our choice, the power curve of economic profit, came out of a multiyear research effort that sought to establish empirical benchmarks for what really makes for success in strategy. To create Exhibit 1, we plotted the economic profit (the total profit after subtracting the cost of capital) earned by the world’s 2,393 largest nonfinancial companies from 2010 to 2014.

The result shows a power curve that is extremely steep at both ends and flat in the middle. The average company in the middle three quintiles earned less than $50 million in economic profit. Meanwhile, those in the top quintile earned 30 times more than the average firm in our sample, capturing nearly 90 percent of all the economic profit created, or an average of $1.4 billion annually. more>

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Updates from Siemens

The best reason to adopt cloud innovation software
By Blake Snodgrass – The decision on cloud timing varies based on each company’s scenario. The first step in the transition is to understand what your company’s goals are in the first place. The change driver may be reaching the limits of an existing solution, requiring new capabilities to support digital transformation, consolidating acquisitions, or choosing to modernize IT infrastructure. The impetus for moving to the cloud helps set the right objectives.

The cloud should not be the driver, in the same way that the goal of a software implementation should never be to “go live” with the software. There has to be some tangible business value. For product innovation and engineering software, what better reason could there be than to improve product innovation and engineering performance? The cloud is a means to an end. The real value is helping manufacturers improve the pace and level of innovation.

Improving product innovation and engineering is the bread and butter of CAD, CAE, PLM, and other engineering solutions. These solutions help provide the capabilities engineers and designers need to innovate efficiently. They offer collaboration capabilities that enable product development teams to work together so they can move faster and avoid introducing errors from disjointed processes. They also help coordinate processes and manage product development projects to ensure that projects are executed effectively.

Perhaps that’s old school, and clearly, on-premise solutions can deliver most of these benefits. But the cloud offers some special help here, as well. Today’s engineering teams are working with increased complexity and disruption, adopting new materials, systems-oriented designs, advanced manufacturing methods, and more. To remain efficient, they need to not only innovate their products – they need to innovate their innovation and engineering processes.

How does the cloud help? Traditional software deployments lock in processes and capabilities until the next upgrade cycle. With the cloud, innovations, functionality, and techniques developed by the software vendor can be made available on an ongoing basis. Access to new features allows engineering teams to take advantage of new software capabilities faster. more>

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Updates from McKinsey

How to develop soft skills
As today’s skill shift accelerates, it is essential that organizations enhance and expand development initiatives for business longevity.
By Julie Avrane-Chopard, Jaime Potter, and David Muhlmann – As automation and artificial intelligence dramatically change the nature of work, employees must fine tune the social and emotional abilities machines cannot master. To encourage this behavior, employers must adjust the ways they assess, educate, train and reward their workforce on soft skills such as collaboration, communication and critical thinking.

Soft skills, which are commonly defined as non-technical skills that enable someone to interact effectively and harmoniously with others, are vital to organizations and can impact culture, mindsets, leadership, attitudes and behaviors. These skills fall into the following categories:

  1. Advanced communication and negotiation skills
  2. Interpersonal skills and empathy
  3. Leadership and management skills
  4. Entrepreneurship and initiative-taking
  5. Adaptability and continuous learning skills
  6. Teaching and training skills

A key difference among today’s large-scale skill shift and those in the past—including the transformative transition from agriculture to manufacturing—is the urgency for workers who exhibit these capabilities.

Developing required soft skills and ensuring employees, and in turn organizations, are set up for success isn’t as simple as popping in a training video. Instead, companies must change their employees’ processes and behaviors—a much harder task.

Assessment is an important first step. Sizing the soft skill gap proves particularly challenging, since they typically lack systematic evaluation and certification mechanisms. HR departments must be equipped with a framework that codifies soft skills and defines their respective evaluation criteria.

For example, several European firms are employing “stepping stone” initiatives to build a digital platform to help workers evaluate their soft skills, know their strengths and development needs, gain access to specific trainings, and get certified.

Effective reskilling requires blended learning journeys that mix traditional learning, including training, digital courses and job aids, with nontraditional methods, such as peer coaching. One retail giant has distributed over 17,000 virtual reality headsets that immerse employees in unfamiliar situations, such as their first Black Friday sales day, and is training them in new tech, soft skills and compliance.

People naturally operate based on incentives—they do what is rewarded. To encourage people to not only begin their soft skill learning journey but to continue with it, rewards and incentives are critical. more>

Productivity Does Not Explain Wages

As long as we believe the neoclassical farce, we will know nothing about what causes prices.
By Blair Fix – Let’s start with the evidence trumpeted as proof that productivity explains wages. Looking across firms, we find that sales per worker correlates with average wages. Figure 1 shows this correlation for about 50,000 US firms over the years 1950 to 2015.

Mainstream economists take this correlation as evidence that productivity explains wages. Sales, they say, measure firms’ output. So sales per worker indicates firms’ labor productivity. Thus the evidence in Figure 1 indicates that productivity explains (much of) workers’ income. Case closed.

Yes, sales per worker correlates with average wages. No one disputes this fact. What I dispute is that this correlation says anything about productivity. The problem is simple. Sales per worker doesn’t measure productivity.

To understand the problem, let’s do some basic accounting. A firm’s sales equal the unit price of the firm’s product times the quantity of this product:

Sales = Unit Price × Unit Quantity

Dividing both sides by the number of workers gives:

Sales per Worker = Unit Price × Unit Quantity per Worker

Let’s unpack this equation. The ‘unit quantity per worker’ measures labor productivity. It tells us the firm’s output per worker. For instance, a farm might grow 10 tons of potatoes per worker. If another farm grows 15 tons of potatoes per worker, it unambiguously produces more potatoes per worker (assuming the potatoes are the same).

The problem with using sales to measure productivity is that prices get in the way. Imagine that two farms, Old McDonald’s and Spuds-R-Us, both produce 10 tons of potatoes per worker. Next, imagine that Old McDonald’s sells their potatoes for $100 per ton. Spuds-R-Us, however, sells their potatoes for $200 per ton. The result is that Spuds-R-Us has double the sales per worker as Old McDonald’s. When we equate sales with productivity, it appears that workers at Spuds-R-Us are twice as productive as workers at Old McDonald’s. But they’re not. We’ve been fooled by prices.

The solution to this problem seems simple. Rather than use sales to measure output, we should measure a firm’s output directly. Count up what the firm produces, and that’s its output. Problem solved.

So why don’t economists measure output directly? Because the restrictions needed to do so are severe. In fact, they’re so severe that they’re almost never met in the real world. more>

Updates from Adobe

December 2019 Giveaways
Adobe – Experiencing good design, illustration, photography, motion graphics, and video is like a gift—and it’s a gift that you, the creative community, give us at Adobe every day. So in return, we’re giving you gifts.

They range from Photoshop actions to lettering sets to texture packs and more. They’re all high quality, free, and copyright-free, and you can use them in any project, personal or commercial.

All we ask is that you don’t re-distribute them. more>

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