I believe the notion of  a next generation of productivity is about to ramp…sharing again

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In a recent post, I focused on a series of emerging shifts and the transformation pillars that enable a re-imagined future. In this post, I will dive into one of those pillars: next generation productivity. According to Wikipedia, productivity is an average measure of the efficiency of production. It can be expressed as the ratio of output to inputs used in the production process. In a recent Citi Report, they describe the significant slowing of labor productivity growth, which drives a focus on next generation gains. But In spite of technological progress and innovation, measured productivity growth is low by historical comparison. They cite these  growth statistics across advanced economies.

A Productivity Wall

Economist and advisor Jeremy Rifkin links the slowing of growth to our reliance on a second industrial revolution platform whose productivity peaked 20 years ago. Rifkin, who is well-known for his views on a Third Industrial Revolution, speaks to the fact that aggregate efficiency – the ratio of actual work to useful work – peaked in the early 1990s. His numbers indicate that Japan leads the world in aggregate efficiency at 20 percent, followed by Germany at 18 percent and the U.S. at 14 percent. Those numbers have not moved since the early 1990s. Rifkin believes that 2008 – known as the year that launched the Great Recession – will also get credit for starting the long sunset of the Second Industrial Revolution. A sunset that he sees occurring over the next 30 to 40 years.

Debates continue as to why productivity has stalled for 25 years, with a productivity paradox that sees increased innovation in the digital age, with no equivalent increase in productivity. The Citi report referenced above speaks to a belief by some economists that the low-hanging fruit of innovation has been picked, and the benefits of previous general purpose technology platforms (GPTs) have been exhausted. They add that recent innovations are much less significant than innovations of the past. The tenor of this argument is negative in its outlook, as this group sees little growth ahead. But another group sees things quite differently.

Breaking through the Wall

Andrew McAfee, the co-author of The Second Machine Age believes we are heading towards a period of profound growth and prosperity. He and Erik Brynjolfsson reject the low hanging fruit argument. They also focus on general purpose technology, and place information and communications technology (ICT) squarely in that category. They see exponential progression, digital, and combinatorial innovation as the foundation for future growth. A common theme across all of these sources is that the last 40 years of ICT have led us to this point – the launching pad for a much different future. I like how it comes together in Rifkin’s view of a third industrial revolution platform. The digitization of communication, energy, transport, and logistics at a level where society can manage power, move economic activity, and improve aggregate efficiency.

The Internet of Things is foundational, and Rifkin’s studies show that an IoT-based platform could move aggregate efficiency upwards to 40 percent over the next 25 years. Connectivity across this system makes productivity so extreme that it takes aggregate efficiency up and the marginal costs down towards zero. This video on Transforming the World provides a deeper look into this point of view. 

The Productivity Lag

As we shift to this emerging platform, we are likely to experience a productivity lag. History has shown that a lag exists between the introduction of general purpose technology and its main effect. The first industrial revolution was launched by the steam engine, putting growth on a sharp trajectory for two hundred years. This trajectory was extended by the second industrial revolution, as electricity, the internal combustion engine, and indoor plumbing were introduced between 1870 and 1900. But it took 100 years for second industrial revolution innovation to have their main effect, at which time growth stalled and began to decline (around 1970). What explains this productivity lag? Here again there is a convergence of thinking across these various sources: it is possible that technological change at this scale requires adaptation (skills, structure, organization, processes, etc.) to translate into meaningful increases in actual productivity. This adaptation takes both time and resources. Let’s look at a great example.

It took over thirty years to fully realize the productivity gains enabled by electrification. Mr. McAfee explains how the factory floor was organized around a large central axle tied to the steam engine, and machines had to be located around the axle. When electric motors replaced the steam engine, they simply kept the existing floor layout and delivered no performance improvement – until about 30 years later. When the original managers retired and were replaced by a new generation of managers, factories were organized around the natural workflow of materials. There are similarities between this period and what we are experiencing today. The graph below compares the relative contribution to labor productivity of electrification beginning in 1890 and information technology beginning in 1970.

Similar to the electrification story, The Second Machine Age authors remind us that in the 1990s it required complementary investments in organizational capital and new processes for IT related innovations to deliver productivity gains. Large enterprise-wide IT systems made possible a wave of business process redesign. A study by the authors showed that it takes an average of 5 to 7 years before full productivity benefits of computers are visible in the productivity of the firms making the investments. 

But are the Stories Really the Same?

Upon deeper analysis, has information technology ushered in the same type of productivity growth as electricity and the steam engine before it? Take a look again at the slowing growth since the 1970s and you can see why people question innovation as a continued driver of growth. One view is that the internal combustion engine allowed for continued growth when it replaced the steam engine, but nothing has come since. Many have argued that information and communication technology stepped in behind the internal combustion engine. It is indeed a general purpose technology (GPT) in the same sense as the steam engine and electricity. In fact, the authors of the Second Machine Age indicate that information technology tied for second with electricity as the most commonly accepted GPT (behind the steam engine). But then how do you explain the numbers? Could it be that the building blocks born from information and communication technology were not mature enough to accelerate productivity growth? Are these building blocks now positioned to create the emerging platform that Rifkin describes? Is it a function of plugging into this new platform and adapting rapidly on the strength of exponential progression? I believe the answer to these questions is yes.

An Emerging Platform

With the building blocks in place, next generation productivity is possible. This emerging platform leverages the Internet of Things at its foundation. Riding on top are the components of the next general purpose technology platform: communications, Energy, transport, and Logistics. General Electric clearly sees the foundational nature of IoT and its impact on productivity. GE estimates that a 1% IoT enabled productivity improvement across its global manufacturing base translates to $500 million in annual savings. Worldwide, GE thinks a 1% improvement in industrial productivity could add $10 to $15 trillion to worldwide GDP over the next 15 years.

The technology that surrounds the platform and the exponential growth in computing have spawned a number of supporting forces:

• Exponential progression reduces the productivity lag
• Building blocks increase our capacity to innovate
• The Rising Billions contribute skills, capacity, ideas, innovation, insight, passion and more
• An endless supply of data fuels our ability to simulate and test
• Exponential technologies increase our capacity to automate
• Connectivity speeds idea flow 

The seeds of a next generation are therefore sewn. The power of our connectedness drives speed in the flow of ideas, allowing innovation to happen faster than it did in previous revolutions. The possibilities explode quickly as the number of valuable combinations grows, increasing our capacity to innovate and test combinations. These forces break through the productivity wall and reduce the time to realizing productivity gains. As modern day businesses are born on this emerging GPT platform, the urgency for traditional businesses to shift grows. 

An Increased Capacity to Automate

As our capacity to automate expands, that which can be automated will be automated. BCG Research Predicts that by 2025, adoption of advanced robots will boost productivity by up to 30 percent in many industries and lower total labor costs by 18 percent or more in countries such as South Korea, China, the U.S., Japan, and Germany. They see the economics for automation and robotics nearing an inflection point, where robotics adoption rates will pick up sharply. Other exponential technologies will converge in a way that automates that which we never believed possible (e.g., knowledge work, driving cars, etc.)

As technology like Blockchain, AI, and robotics mature, the realization of completely decentralized and autonomous organizations becomes viable. It is possible for the rules that drive business to be executed without a central authority, leveraging autonomous agents to enable fully automated business entities. Movement on a continuum between our current centralized, controlled structures and decentralized autonomous structures moves the productivity needle. No one can predict how far we move on that continuum – but it is safe to assume movement will occur – witness the first Unmanned Factory in China.

Measuring Growth

The last piece of the productivity puzzle is our method of measurement. It is increasingly clear that current measures are inadequate for modern economies. The democratization of production, the sharing economy, and very low marginal costs all contribute to the ineffectiveness of measures like GDP. More value takes the form of consumer surplus – the difference between what someone is willing to pay for value and what they actually pay. Today, consumer surplus is often very high relative to the price paid, but only price is counted in GDP and productivity statistics. Services with zero price (Skype, streaming, online media, Apps, etc.) add value to the economy, but not dollars to GDP.

In a recent article titled Why Every Aspect of Your Business is about to Change, the author talks about the destruction of value for incumbents and the creation of value for consumers in the form of consumer surplus. They use a powerful example to make their point: Skype generated $2 billion in 2013, but McKinsey calculates that at the same time, they transferred $37 billion away from telecom firms to consumers via free or low-cost calls. Even the innovative new company only gets a fraction of the value created (Skype: $2 Billion, Consumers $37 Billion). This creates two challenges: First, do we need to change the way we measure value? Second, how do companies monetize the newly created consumer surplus?

Next generation productivity is a critical pillar in the transformative journey of every organization, but our path forward will have unintended consequences. Is the linkage between our measurement and our well-being broken? Will we reach such an extreme level of productivity that an economic paradigm based on scarcity struggles in the aftermath? Let’s not wait thirty years for the next generation of leaders to address the many challenges that arise along the way. Let’s address this productivity wheel sooner rather than later.

 

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