Perception vs. Reality: Immersive Technologies

Christopher Koch and Kai Goerlich

01Perception:
Immersive experiences are scripted productions.

Reality:

Credit: The Void VR

Early versions of immersive technologies, which include augmented reality (AR) and virtual reality (VR), resemble their video game forebears in that they are essentially journeys of discovery through different stages of preprogrammed experiences. We can scale virtual cliffs and mountains while riding a roller coaster or stumble over park benches in pursuit of Pokémon Go characters. However, as immersive technologies become imbued with machine learning and AI, digital experiences will become increasingly multisensory, making them more convincingly “real.” For example, Fast Company reports that surgeons can now practice a procedure using VR with a stylus that simulates the feel of operating on an open knee joint. The AR and VR of the future will gather information from the surrounding physical environment and instantly pass it back to an AI for analysis in order to derive unique, in-the-moment responses to our actions.

 

02Perception:
You need bulky equipment.

Reality:

Credit: Eter

We won’t be wearing those silly goggles forever. As the sensors that pick up data from our movements and speech become smaller, they will be easier to embed in everything. Imagine being in a factory in which every object has a visual overlay that lets you drill into information about that object, handle a digital version of it, or control it remotely. Today, firefighters can wear a smart helmet from Qwake Tech that combines AR technology with a thermal imaging camera. The device outlines the edges of objects (such as doors and stairs) and highlights sources of high heat, enabling firefighters to move through buildings more quickly. Companies including BMW are experimenting with advanced gesture recognition technology that would enable users to control devices without having to touch them. You might soon be able to launch a video chat by waving your hand.

 

03Perception:
A physical presence is required.

Reality:

Credit: vTime

For now. But before long, you’ll be able to create a VR avatar that looks like you, that sounds like you, and that can meet with your colleagues’ VR avatars in a realistic virtual space. The technology will likely require a brain-computer interface such as a headset or a brain-implanted chip. Neurable has a prototype software platform to power headset sensors that let users maneuver in VR video games using only their thoughts. Given sufficient computing power and a smart enough AI, you may one day be able to program your VR avatar to participate in a virtual meeting, tour the digital twin of a factory, or attend a keynote speech as your proxy and (theoretically) do a good enough job that your colleagues would never guess it wasn’t actually you. That will raise questions about how to tell if an avatar is being controlled live by a human or operated by a bot—and whether to require the differences be obvious. D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

How To Cope With Decision Fatigue

Lauren Pytel

Decision fatigue refers to the deteriorating quality of decisions as one is forced to engage in more and more decision-making. If you’ve ever planned an event, redesigned a home or purchased a new car, you probably remember the exhaustion and indifference that eventually resulted from being faced with so many choices.

Many companies put managers at risk of decision fatigue by creating performance management, compensation, staffing and development processes that require evaluating multiple people on multiple factors in a short period of time. For example, annual talent or compensation reviews where managers are required to make significant and critical decisions about multiple employees in less than four weeks, while also performing their full-time job.

Decision fatigue can lead to impulsive and irrational decision-making that can impact the accuracy of critical decisions related to employee promotion, staffing and compensation. Research shows that when our brains are tired, we tend to use mental short-cuts or heuristics to make decisions, rather than engage in effortful thought about a choice’s pros and cons. While heuristics can save decision-makers time and energy, they can also prove highly problematic for talent management decisions for several reasons.

Overly simplified decision-making

Fatigued managers may choose to pay everyone the same amount because it’s quick and easy, rather than critically evaluate whether some employees warrant greater levels of investment given their past contributions and future potential. Heuristics can result in biased decision-making. For example, people exhibit the ‘familiarity heuristic’ or ‘similarity heuristic’ when their decision-making reflects a bias for familiarity over novelty. This suggests that employees who were promoted by a manager in the past could be favored over employees who were not, or that employees who are demographically similar to a manager might be favored over employees who are not. This bias could have disastrous consequences for underrepresented demographic groups.

It would be difficult to completely eliminate decision fatigue as a risk, but there are things your organization can do to mitigate its negative effects:

Conduct calibration talent reviews

Calibration sessions can reduce individual manager decision fatigue, but only if they are conducted the right way. One of the most compelling reasons to hold calibration sessions is that the conversations they promote provide managers with a deeper understanding of the unique skills and capabilities their employees have to offer. But this only works if you provide adequate time to discuss employees. Including too many employees or failing to dedicate enough time to talk about the employees in a session defeats their purpose. In fact, when designed ineffectively, calibration reviews can actually make decision fatigue more likely as people may rush through evaluating employees so they can end the meeting on time.

Two additional calibration session best practices can also help mitigate the effects of decision fatigue. First, include a diverse group of raters with a variety of viewpoints and perspectives. Research suggests that group members can act as a ‘check & balance’ system against individuals’ biases, but only if all group members do not exhibit the same bias. Intentionally including raters who are not like other members of the rater group can help ensure that biases are detected and resolved before they affect decision-making. Second, randomize the order of evaluation.

Having to evaluate a large number of employees in a small period of time may, in some cases, be unavoidable. In such cases, it is useful to randomize the order in which employees are evaluated. Research has shown that the order in which individuals are assessed can influence how they are assessed. Rather than using some arbitrary criteria like an employee’s last name or their manager to order assessment, create a standardized process for defining assessment order that can be used across the organization.

Encourage managers to engage in continuous feedback

Managers can simplify the number of critical decisions during annual reviews by engaging in continuous dialogue with employees about their performance, progress and expectations throughout the year. Addressing these topics in small chunks can help reduce the burden of decision-making in terms of both the number of decisions that must be made as well as their level of criticality.

Managers are faced with an enormous number of decisions each day. While some of these may be insignificant, others, such as deciding who is up for promotion or a bonus, have critical long-term consequences. It is amazing how often managers suffering from decision fatigue make these critical decisions in a way that emphasizes efficiency over quality. Ensuring that your organization’s talent review process and philosophy protects managers against experiencing decision fatigue is important, not only for your managers’ senses of well-being but for the fairness and accuracy of your talent management decisions.

For more insight on decision-making in HR, see Succession Management: Why Do We Still Fail To Get It Right?

This article originally appeared on Forbes SAPVoice.

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Lauren Pytel

About Lauren Pytel

Lauren Pytel is a human capital management researcher at SAP SuccessFactors (SAP).

Machine Learning And Medicine: Made For Each Other

John Ward

Analysts predict that artificial intelligence and machine learning will disrupt almost every industry – education, financial services, transportation, and retail among them.

But more often than not, healthcare leads their list as the top candidate.

Here are a just a few examples of how these technologies are transforming the industry.

Boosting the efficiency of clinical trials

Some sources cite that the average cost of bringing a new drug to market has increased to record levels – almost US$2 billion for the biggest companies.

McKinsey & Company believes that Big Data strategies that result in better informed decision making could optimize innovation and improve the efficiency of research and clinical trials.

A McKinsey report offers a specific example: “Smart algorithms linking laboratory and clinical data … could create automatic reports that identify related applications or compounds and raise red flags concerning safety or efficacy.”

Revolutionizing diagnosis

Early in 2017, the Stanford News reported on the university’s effort to create an artificially intelligent diagnosis algorithm for skin cancer. Stanford computer scientists trained their algorithm to visually diagnose potential cancer using a database of nearly 130,000 skin disease images.

Stanford points out that every year there are about 5.4 million new cases of skin cancer in the United States alone.

The article quotes Andre Esteva, co-lead author of a paper that appeared in Nature and a graduate student in the Thrun lab. “We made a very powerful machine learning algorithm that learns from data,” said Esteva. “Instead of writing into computer code exactly what to look for, you let the algorithm figure it out.”

The algorithm currently exists on a computer, but the team foresees making it smartphone compatible.

Streamlining business operations

The impact of “smart” data technologies on healthcare will be broad – and it won’t be restricted to clinical applications.

“My main responsibilities are to ensure the digital transformation of financial processes across McKesson,” says Shantanu Nene, the company’s director of financial planning and analytics, in a recent video filmed in part at the SAP Leonardo Live event in Chicago. McKesson Corporation, the oldest and largest healthcare company in the United States, has operations in more than 16 countries.

For Nene, this digital transformation includes machine learning. “We see machine learning as a way to adopt a more lean accounting approach at McKesson,” Nene says. “In particular, we would like to reduce the amount of manual-touch reconciliations in some of our financial processes.”

As Nene explains, analytics are core to McKesson’s operations, and the company collects and uses a lot of data to help identify industry trends and guide decision making. This includes both buying and pricing decisions. “We can now start looking at information in real time and do what-if analysis to better understand the future impact of our decision,” Nene remarks.

There are ripple effects to such determinations.

According to company sources, McKesson serves more than 50% of U.S. hospitals and delivers one-third of all medications used daily in North America.

“We conduct millions of transactions every day helping our customers improve the lives of their patients,” says Nene. “What we do can affect the entire healthcare ecosystem.”

Pairing up

Machine learning and medicine could be the perfect couple. And if so, there is a simple reality pushing these two together.

Healthcare today generates an enormous amount of data.

Writing for HealthITAnalytics.com, lead editor Jennifer Bresnik opines that machine learning, natural language processing, and artificial intelligence are becoming “foundational components” of healthcare’s efforts to keep ahead of the “data tsunami.”

“The sheer volume of available medical knowledge has long since outstripped even the most intelligent clinician,” Bresnik observes.

Learn more about how Stanford and other organizations are using AI to improve people’s lives in  More Than Noise: Digital Trends That Are Bigger Than You Think.

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Tick Tock: Start Preparing for Resource Disruption

By Maurizio Cattaneo, Joerg Ferchow, Daniel Wellers, and Christopher Koch

Businesses share something important with lions. When a lion captures and consumes its prey, only about 10% to 20% of the prey’s energy is directly transferred into the lion’s metabolism. The rest evaporates away, mostly as heat loss, according to research done in the 1940s by ecologist Raymond Lindeman.

Today, businesses do only about as well as the big cats. When you consider the energy required to manage, power, and move products and services, less than 20% goes directly into the typical product or service—what economists call aggregate efficiency (the ratio of potential work to the actual useful work that gets embedded into a product or service at the expense of the energy lost in moving products and services through all of the steps of their value chains). Aggregate efficiency is a key factor in determining productivity.

After making steady gains during much of the 20th century, businesses’ aggregate energy efficiency peaked in the 1980s and then stalled. Japan, home of the world’s most energy-efficient economy, has been skating along at or near 20% ever since. The U.S. economy, meanwhile, topped out at about 13% aggregate efficiency in the 1990s, according to research.

Why does this matter? Jeremy Rifkin says he knows why. Rifkin is an economic and social theorist, author, consultant, and lecturer at the Wharton School’s Executive Education program who believes that economies experience major increases in growth and productivity only when big shifts occur in three integrated infrastructure segments around the same time: communications, energy, and transportation.

But it’s only a matter of time before information technology blows all three wide open, says Rifkin. He envisions a new economic infrastructure based on digital integration of communications, energy, and transportation, riding atop an Internet of Things (IoT) platform that incorporates Big Data, analytics, and artificial intelligence. This platform will disrupt the world economy and bring dramatic levels of efficiency and productivity to businesses that take advantage of it, he says.

Some economists consider Rifkin’s ideas controversial. And his vision of a new economic platform may be problematic—at least globally. It will require massive investments and unusually high levels of government, community, and private sector cooperation, all of which seem to be at depressingly low levels these days.

However, Rifkin has some influential adherents to his philosophy. He has advised three presidents of the European Commission—Romano Prodi, José Manuel Barroso, and the current president, Jean-Claude Juncker—as well as the European Parliament and numerous European Union (EU) heads of state, including Angela Merkel, on the ushering in of what he calls “a smart, green Third Industrial Revolution.” Rifkin is also advising the leadership of the People’s Republic of China on the build out and scale up of the “Internet Plus” Third Industrial Revolution infrastructure to usher in a sustainable low-carbon economy.

The internet has already shaken up one of the three major economic sectors: communications. Today it takes little more than a cell phone, an internet connection, and social media to publish a book or music video for free—what Rifkin calls zero marginal cost. The result has been a hollowing out of once-mighty media empires in just over 10 years. Much of what remains of their business models and revenues has been converted from physical (remember CDs and video stores?) to digital.

But we haven’t hit the trifecta yet. Transportation and energy have changed little since the middle of the last century, says Rifkin. That’s when superhighways reached their saturation point across the developed world and the internal-combustion engine came close to the limits of its potential on the roads, in the air, and at sea. “We have all these killer new technology products, but they’re being plugged into the same old infrastructure, and it’s not creating enough new business opportunities,” he says.

All that may be about to undergo a big shake-up, however. The digitalization of information on the IoT at near-zero marginal cost generates Big Data that can be mined with analytics to create algorithms and apps enabling ubiquitous networking. This digital transformation is beginning to have a big impact on the energy and transportation sectors. If that trend continues, we could see a metamorphosis in the economy and society not unlike previous industrial revolutions in history. And given the pace of technology change today, the shift could happen much faster than ever before.

The speed of change is dictated by the increase in digitalization of these three main sectors; expensive physical assets and processes are partially replaced by low-cost virtual ones. The cost efficiencies brought on by digitalization drive disruption in existing business models toward zero marginal cost, as we’ve already seen in entertainment and publishing. According to research company Gartner, when an industry gets to the point where digital drives at least 20% of revenues, you reach the tipping point.

“A clear pattern has emerged,” says Peter Sondergaard, executive vice president and head of research and advisory for Gartner. “Once digital revenues for a sector hit 20% of total revenue, the digital bloodbath begins,” he told the audience at Gartner’s annual 2017 IT Symposium/ITxpo, according to The Wall Street Journal. “No matter what industry you are in, 20% will be the point of no return.”

Communications is already there, and energy and transportation are heading down that path. If they hit the magic 20% mark, the impact will be felt not just within those industries but across all industries. After all, who doesn’t rely on energy and transportation to power their value chains?

The eye of the technology disruption hurricane has moved beyond communications and is heading toward … the rest of the economy.

That’s why businesses need to factor potentially massive business model disruptions into their plans for digital transformation today if they want to remain competitive with organizations in early adopter countries like China and Germany. China, for example, is already halfway through an US$88 billion upgrade to its state electricity grid that will enable renewable energy transmission around the country—all managed and moved digitally, according to an article in The Economist magazine. And it is competing with the United States for leadership in self-driving vehicles, which will shift the transportation process and revenue streams heavily to digital, according to an article in Wired magazine.

Once China’s and Germany’s renewables and driverless infrastructures are in place, the only additional costs are management and maintenance. That could bring businesses in these countries dramatic cost savings over those that still rely on fossil fuels and nuclear energy to power their supply chains and logistics. “Once you pay the fixed costs of renewables, the marginal costs are near zero,” says Rifkin. “The sun and wind haven’t sent us invoices yet.”

In other words, zero marginal cost has become a zero-sum game.

To understand why that is, consider the major industrial revolutions in history, writes Rifkin in his books, The Zero Marginal Cost Society and The Third Industrial Revolution. The first major shift occurred in the 19th century when cheap, abundant coal provided an efficient new source of power (steam) for manufacturing and enabled the creation of a vast railway transportation network. Meanwhile, the telegraph gave the world near-instant communication over a globally connected network.

The second big change occurred at the beginning of the 20th century, when inexpensive oil began to displace coal and gave rise to a much more flexible new transportation network of cars and trucks. Telephones, radios, and televisions had a similar impact on communications.

Breaking Down the Walls Between Sectors

Now, according to Rifkin, we’re poised for the third big shift. The eye of the technology disruption hurricane has moved beyond communications and is heading toward—or as publishing and entertainment executives might warn, coming for—the rest of the economy. With its assemblage of global internet and cellular network connectivity and ever-smaller and more powerful sensors, the IoT, along with Big Data analytics and artificial intelligence, is breaking down the economic walls that have protected the energy and transportation sectors for the past 50 years.

Daimler is now among the first movers in transitioning into a digitalized mobility internet. The company has equipped nearly 400,000 of its trucks with external sensors, transforming the vehicles into mobile Big Data centers. The sensors are picking up real-time Big Data on weather conditions, traffic flows, and warehouse availability. Daimler plans to establish collaborations with thousands of companies, providing them with Big Data and analytics that can help dramatically increase their aggregate efficiency and productivity in shipping goods across their value chains. The Daimler trucks are autonomous and capable of establishing platoons of multiple trucks driving across highways.

It won’t be long before vehicles that navigate the more complex transportation infrastructures around the world begin to think for themselves. Autonomous vehicles will bring massive economic disruption to transportation and logistics thanks to new aggregate efficiencies. Without the cost of having a human at the wheel, autonomous cars could achieve a shared cost per mile below that of owned vehicles by as early as 2030, according to research from financial services company Morgan Stanley.

The transition is getting a push from governments pledging to give up their addiction to cars powered by combustion engines. Great Britain, France, India, and Norway are seeking to go all electric as early as 2025 and by 2040 at the latest.

The Final Piece of the Transition

Considering that automobiles account for 47% of petroleum consumption in the United States alone—more than twice the amount used for generators and heating for homes and businesses, according to the U.S. Energy Information Administration—Rifkin argues that the shift to autonomous electric vehicles could provide the momentum needed to upend the final pillar of the economic platform: energy. Though energy has gone through three major disruptions over the past 150 years, from coal to oil to natural gas—each causing massive teardowns and rebuilds of infrastructure—the underlying economic model has remained constant: highly concentrated and easily accessible fossil fuels and highly centralized, vertically integrated, and enormous (and enormously powerful) energy and utility companies.

Now, according to Rifkin, the “Third Industrial Revolution Internet of Things infrastructure” is on course to disrupt all of it. It’s neither centralized nor vertically integrated; instead, it’s distributed and networked. And that fits perfectly with the commercial evolution of two energy sources that, until the efficiencies of the IoT came along, made no sense for large-scale energy production: the sun and the wind.

But the IoT gives power utilities the means to harness these batches together and to account for variable energy flows. Sensors on solar panels and wind turbines, along with intelligent meters and a smart grid based on the internet, manage a new, two-way flow of energy to and from the grid.

Today, fossil fuel–based power plants need to kick in extra energy if insufficient energy is collected from the sun and wind. But industrial-strength batteries and hydrogen fuel cells are beginning to take their place by storing large reservoirs of reserve power for rainy or windless days. In addition, electric vehicles will be able to send some of their stored energy to the digitalized energy internet during peak use. Demand for ever-more efficient cell phone and vehicle batteries is helping push the evolution of batteries along, but batteries will need to get a lot better if renewables are to completely replace fossil fuel energy generation.

Meanwhile, silicon-based solar cells have not yet approached their limits of efficiency. They have their own version of computing’s Moore’s Law called Swanson’s Law. According to data from research company Bloomberg New Energy Finance (BNEF), Swanson’s Law means that for each doubling of global solar panel manufacturing capacity, the price falls by 28%, from $76 per watt in 1977 to $0.41 in 2016. (Wind power is on a similar plunging exponential cost curve, according to data from the U.S. Department of Energy.)

Thanks to the plummeting solar price, by 2028, the cost of building and operating new sun-based generation capacity will drop below the cost of running existing fossil power plants, according to BNEF. “One of the surprising things in this year’s forecast,” says Seb Henbest, lead author of BNEF’s annual long-term forecast, the New Energy Outlook, “is that the crossover points in the economics of new and old technologies are happening much sooner than we thought last year … and those were all happening a bit sooner than we thought the year before. There’s this sense that it’s not some distant risk or distant opportunity. A lot of these realities are rushing toward us.”

The conclusion, he says, is irrefutable. “We can see the data and when we map that forward with conservative assumptions, these technologies just get cheaper than everything else.”

The smart money, then—72% of total new power generation capacity investment worldwide by 2040—will go to renewable energy, according to BNEF. The firm’s research also suggests that there’s more room in Swanson’s Law along the way, with solar prices expected to drop another 66% by 2040.

Another factor could push the economic shift to renewables even faster. Just as computers transitioned from being strictly corporate infrastructure to becoming consumer products with the invention of the PC in the 1980s, ultimately causing a dramatic increase in corporate IT investments, energy generation has also made the transition to the consumer side.

Thanks to future tech media star Elon Musk, consumers can go to his Tesla Energy company website and order tempered glass solar panels that look like chic, designer versions of old-fashioned roof shingles. Models that look like slate or a curved, terracotta-colored, ceramic-style glass that will make roofs look like those of Tuscan country villas, are promised soon. Consumers can also buy a sleek-looking battery called a Powerwall to store energy from the roof.

The combination of solar panels, batteries, and smart meters transforms homeowners from passive consumers of energy into active producers and traders who can choose to take energy from the grid during off-peak hours, when some utilities offer discounts, and sell energy back to the grid during periods when prices are higher. And new blockchain applications promise to accelerate the shift to an energy market that is laterally integrated rather than vertically integrated as it is now. Consumers like their newfound sense of control, according to Henbest. “Energy’s never been an interesting consumer decision before and suddenly it is,” he says.

As the price of solar equipment continues to drop, homes, offices, and factories will become like nodes on a computer network. And if promising new solar cell technologies, such as organic polymers, small molecules, and inorganic compounds, supplant silicon, which is not nearly as efficient with sunlight as it is with ones and zeroes, solar receivers could become embedded into windows and building compounds. Solar production could move off the roof and become integrated into the external facades of homes and office buildings, making nearly every edifice in town a node.

The big question, of course, is how quickly those nodes will become linked together—if, say doubters, they become linked at all. As we learned from Metcalfe’s Law, the value of a network is proportional to its number of connected users.

The Will Determines the Way

Right now, the network is limited. Wind and solar account for just 5% of global energy production today, according to Bloomberg.

But, says Rifkin, technology exists that could enable the network to grow exponentially. We are seeing the beginnings of a digital energy network, which uses a combination of the IoT, Big Data, analytics, and artificial intelligence to manage distributed energy sources, such as solar and wind power from homes and businesses.

As nodes on this network, consumers and businesses could take a more active role in energy production, management, and efficiency, according to Rifkin. Utilities, in turn, could transition from simply transmitting power and maintaining power plants and lines to managing the flow to and from many different energy nodes; selling and maintaining smart home energy management products; and monitoring and maintaining solar panels and wind turbines. By analyzing energy use in the network, utilities could create algorithms that automatically smooth the flow of renewables. Consumers and businesses, meanwhile, would not have to worry about connecting their wind and solar assets to the grid and keeping them up and running; utilities could take on those tasks more efficiently.

Already in Germany, two utility companies, E.ON and RWE, have each split their businesses into legacy fossil and nuclear fuel companies and new services companies based on distributed generation from renewables, new technologies, and digitalization.

The reason is simple: it’s about survival. As fossil fuel generation winds down, the utilities need a new business model to make up for lost revenue. Due to Germany’s population density, “the utilities realize that they won’t ever have access to enough land to scale renewables themselves,” says Rifkin. “So they are starting service companies to link together all the different communities that are building solar and wind and are managing energy flows for them and for their customers, doing their analytics, and managing their Big Data. That’s how they will make more money while selling less energy in the future.”

The digital energy internet is already starting out in pockets and at different levels of intensity around the world, depending on a combination of citizen support, utility company investments, governmental power, and economic incentives.

China and some countries within the EU, such as Germany and France, are the most likely leaders in the transition toward a renewable, energy-based infrastructure because they have been able to align the government and private sectors in long-term energy planning. In the EU for example, wind has already overtaken coal as the second largest form of power capacity behind natural gas, according to an article in The Guardian newspaper. Indeed, Rifkin has been working with China, the EU, and governments, communities, and utilities in Northern France, the Netherlands, and Luxembourg to begin building these new internets.

Hauts-de-France, a region that borders the English Channel and Belgium and has one of the highest poverty rates in France, enlisted Rifkin to develop a plan to lift it out of its downward spiral of shuttered factories and abandoned coal mines. In collaboration with a diverse group of CEOs, politicians, teachers, scientists, and others, it developed Rev3, a plan to put people to work building a renewable energy network, according to an article in Vice.

Today, more than 1,000 Rev3 projects are underway, encompassing everything from residential windmills made from local linen to a fully electric car–sharing system. Rev3 has received financial support from the European Investment Bank and a handful of private investment funds, and startups have benefited from crowdfunding mechanisms sponsored by Rev3. Today, 90% of new energy in the region is renewable and 1,500 new jobs have been created in the wind energy sector alone.

Meanwhile, thanks in part to generous government financial support, Germany is already producing 35% of its energy from renewables, according to an article in The Independent, and there is near unanimous citizen support (95%, according to a recent government poll) for its expansion.

If renewables are to move forward …, it must come from the ability to make green, not act green.

If renewable energy is to move forward in other areas of the world that don’t enjoy such strong economic and political support, however, it must come from the ability to make green, not act green.

Not everyone agrees that renewables will produce cost savings sufficient to cause widespread cost disruption anytime soon. A recent forecast by the U.S. Energy Information Administration predicts that in 2040, oil, natural gas, and coal will still be the planet’s major electricity producers, powering 77% of worldwide production, while renewables such as wind, solar, and biofuels will account for just 15%.

Skeptics also say that renewables’ complex management needs, combined with the need to store reserve power, will make them less economical than fossil fuels through at least 2035. “All advanced economies demand full-time electricity,” Benjamin Sporton, chief executive officer of the World Coal Association told Bloomberg. “Wind and solar can only generate part-time, intermittent electricity. While some renewable technologies have achieved significant cost reductions in recent years, it’s important to look at total system costs.”

On the other hand, there are many areas of the world where distributed, decentralized, renewable power generation already makes more sense than a centralized fossil fuel–powered grid. More than 20% of Indians in far flung areas of the country have no access to power today, according to an article in The Guardian. Locally owned and managed solar and wind farms are the most economical way forward. The same is true in other developing countries, such as Afghanistan, where rugged terrain, war, and tribal territorialism make a centralized grid an easy target, and mountainous Costa Rica, where strong winds and rivers have pushed the country to near 100% renewable energy, according to The Guardian.

The Light and the Darknet

Even if all the different IoT-enabled economic platforms become financially advantageous, there is another concern that could disrupt progress and potentially cause widespread disaster once the new platforms are up and running: hacking. Poorly secured IoT sensors have allowed hackers to take over everything from Wi-Fi enabled Barbie dolls to Jeep Cherokees, according to an article in Wired magazine.

Humans may be lousy drivers, but at least we can’t be hacked (yet). And while the grid may be prone to outages, it is tightly controlled, has few access points for hackers, and is physically separated from the Wild West of the internet.

If our transportation and energy networks join the fray, however, every sensor, from those in the steering system on vehicles to grid-connected toasters, becomes as vulnerable as a credit card number. Fake news and election hacking are bad enough, but what about fake drivers or fake energy? Now we’re talking dangerous disruptions and putting millions of people in harm’s way.

The only answer, according to Rifkin, is for businesses and governments to start taking the hacking threat much more seriously than they do today and to begin pouring money into research and technologies for making the internet less vulnerable. That means establishing “a fully distributed, redundant, and resilient digital infrastructure less vulnerable to the kind of disruptions experienced by Second Industrial Revolution–centralized communication systems and power grids that are increasingly subject to climate change, disasters, cybercrime, and cyberterrorism,” he says. “The ability of neighborhoods and communities to go off centralized grids during crises and re-aggregate in locally decentralized networks is the key to advancing societal security in the digital era,” he adds.

Start Looking Ahead

Until today, digital transformation has come mainly through the networking and communications efficiencies made possible by the internet. Airbnb thrives because web communications make it possible to create virtual trust markets that allow people to feel safe about swapping their most private spaces with one another.

But now these same efficiencies are coming to two other areas that have never been considered core to business strategy. That’s why businesses need to begin managing energy and transportation as key elements of their digital transformation portfolios.

Microsoft, for example, formed a senior energy team to develop an energy strategy to mitigate risk from fluctuating energy prices and increasing demands from customers to reduce carbon emissions, according to an article in Harvard Business Review. “Energy has become a C-suite issue,” Rob Bernard, Microsoft’s top environmental and sustainability executive told the magazine. “The CFO and president are now actively involved in our energy road map.”

As Daimler’s experience shows, driverless vehicles will push autonomous transportation and automated logistics up the strategic agenda within the next few years. Boston Consulting Group predicts that the driverless vehicle market will hit $42 billion by 2025. If that happens, it could have a lateral impact across many industries, from insurance to healthcare to the military.

Businesses must start planning now. “There’s always a period when businesses have to live in the new and the old worlds at the same time,” says Rifkin. “So businesses need to be considering new business models and structures now while continuing to operate their existing models.”

He worries that many businesses will be left behind if their communications, energy, and transportation infrastructures don’t evolve. Companies that still rely on fossil fuels for powering traditional transportation and logistics could be at a major competitive disadvantage to those that have moved to the new, IoT-based energy and transportation infrastructures.

Germany, for example, has set a target of 80% renewables for gross power consumption by 2050, according to The Independent. If the cost advantages of renewables bear out, German businesses, which are already the world’s third-largest exporters behind China and the United States, could have a major competitive advantage.

“How would a second industrial revolution society or country compete with one that has energy at zero marginal cost and driverless vehicles?” asks Rifkin. “It can’t be done.” D!


About the Authors

Maurizio Cattaneo is Director, Delivery Execution, Energy and Natural Resources, at SAP.

Joerg Ferchow is Senior Utilities Expert and Design Thinking Coach, Digital Transformation, at SAP.

Daniel Wellers is Digital Futures Lead, Global Marketing, at SAP.

Christopher Koch is Editorial Director, SAP Center for Business Insight, at SAP.


Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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Human Is The Next Big Thing

Traci Maddox

One of my favorite movies of 2016 was Hidden Figures. The main character, Katherine Johnson, and her team of colleagues had an interesting job title: Computer. Here’s what Katherine said about her job: “On any given day, I analyze the binomial levels of air displacement, friction, and velocity. And compute over 10 thousand calculations by cosine, square root, and lately analytic geometry. By hand.”

That was the 1960s. It was amazing work, but work that took hours to complete – and something an in-memory computer could do in a fraction of a second today.

Just as in-memory computing transformed calculating by hand (and made jobs like Katherine’s much easier), digital technologies are transforming the way we work today – and making our day-to-day activities more efficient.

What’s the real impact of technology in today’s workplace?

We are surrounded by technology, both at home and at work. Machine learning and robotics are making their way into everyday life and are affecting the way we expect to engage with technology at work. That has a big impact on organizations: If a machine can do a job safely and more efficiently, a company, nonprofit, or government – and its employees – will benefit. Digital technologies are becoming increasingly more feasible, affordable, and desirable. The challenge for organizations now is effectively merging human talent and digital business to harness new capabilities.

How will jobs change?

What does this mean for humans in the workplace? In a previous blog, Kerry Brown showed that as enterprises continue to learn, human/machine collaboration increases. People will direct technology and hand over work that can be done more efficiently by machine. Does that mean people will go away? No – but they will need to leverage different skills than they have today.

Although we don’t know exactly how jobs will change, one thing is for sure: Becoming more digitally proficient will help every employee stay relevant (and prepare them to move forward in their careers). Today’s workforce demographic complicates how people embrace technology – with up to five generations in the workforce, there is a wide variety in digital fluency (i.e., the ability to understand which technology is available and what tools will best achieve desired outcomes).

What is digital fluency and how can organizations embrace it?

Digital fluency is the combination of several capabilities related to technology:

  • Foundation skills: The ability to use technology tools that enhance your productivity and effectiveness
  • Information skills: The ability to research and develop your own perspective on topics using technology
  • Collaboration skills: The ability to share knowledge and collaborate with others using technology
  • Transformation skills: The ability to assess your own skills and take action toward building your digital fluency

No matter how proficient you are today, you can continue to build your digital IQ by building new habits and skills. This is something that both the organization and employee will have to own to be successful.

So, what skills are needed?

In a Technical University of Munich study released in July 2017, 64% of respondents said they do not have the skills necessary for digital transformation.

Today's workplace reality

These skills will be applied not only to the jobs of today, but also to the top jobs of the future, which haven’t been imagined yet! A recent article in Fast Company mentions a few, which include Digital Death Manager, Corporate Disorganizer, and 3D Printing Handyman.

And today’s skills will be used differently in 2025, as reported by another Fast Company article:

  • Tech skills, especially analytical skills, will increase in importance. Demand for software developers, market analysts, and computer analysts will increase significantly between now and 2025.
  • Retail and sales skills, or any job related to soft skills that are hard for computers to learn, will continue to grow. Customer service representatives, marketing specialists, and sales reps must continue to collaborate and understand how to use social media effectively to communicate worldwide.
  • Lifelong learning will be necessary to keep up with the changes in technology and adapt to our fast-moving lives. Teachers and trainers will continue to be hot jobs in the future, but the style of teaching will change to adapt to a “sound bite” world.
  • Contract workers who understand how businesses and projects work will thrive in the “gig economy.” Management analysts and auditors will continue to be in high demand.

What’s next?

How do companies address a shortage of digital skills and build digital fluency? Here are some steps you can take to increase your digital fluency – and that of your organization:

  • Assess where you are today. Either personally or organizationally, knowing what skills you have is the first step toward identifying where you need to go.
  • Identify one of each of the skill sets to focus on. What foundational skills do you or your organization need? How can you promote collaboration? What thought leadership can your team share – and how can they connect with the right information to stay relevant?
  • Start practicing! Choose just one thing – and use that technology every day for a month. Use it within your organization so others can practice too.

And up next for this blog series – a look at the workplace of the future!

The computer made its debut in Hidden Figures. Did it replace jobs? Yes, for some of the computer team. But members of that team did not leave quietly and continue manual calculations elsewhere. They learned how to use that new mainframe computer and became programmers. I believe humans will always be the next big thing.

If we want to retain humanity’s value in an increasingly automated world, we need to start recognizing and nurturing Human Skills for the Digital Future.

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Traci Maddox

About Traci Maddox

Traci Maddox is the Director of the North America Customer Transformation Office at SAP, where she is elevating customer success through innovation and digital transformation. Traci is also part of the Digital Workforce Taskforce, a team of SAP leaders whose mission is to help companies succeed by understanding and addressing workforce implications of digital technology.