Machine Learning: Is Citizen Data Science Real?

Richard Mooney

We hear a lot these days about the “citizen data scientist.” Everyone wants to use data science and machine learning to understand their business and automate tasks to improve efficiency. But we have a shortage of people with data science skills, so much so that salaries are high for properly qualified people. To chief data officers, it’s an attractive proposition to take people from within their business who understand data and have a strong mathematical background and convert them to data scientists through self-study and online courses.

We have a new generation of visual composition framework tools that enable a business user to visually compose pipelines of algorithms, using techniques such as R and Python selectively to solve more complex problems. These techniques can get impressive visualizations back to the user and help them understand the business using statistics.

Challenges for citizen data scientists

But there are challenges with this approach. It’s not simply a matter of choosing the best algorithm:

  1. It’s very easy for a nonprofessional to misinterpret the results of a predictive model, making decisions based on poor results. It’s very difficult for a manager to recognize it until it’s too late.
  1. They need to master numerous skillsets to maximize model accuracy:
    • They need to understand feature engineering to extract useful insights from the data by deriving variables.
    • The mechanisms needed vary across data types. Date/time is very different from ordinal and continuous variables.
    • They need to extract how these variables change over time.
    • They also need to master complex techniques to make sure the data can be handled by the chosen algorithm and that missing values are correctly dealt with.
    • They need to understand how to deploy the model into production.
  1. They also need to deploy these models to production to generate the needed ROI. They need to understand how to keep the models current on an ongoing basis and how to make sure they are accurate, not just on training data but also validation, test, and new data.

Automation makes it easier

With automation throughout the predictive lifecycle, it’s possible to avoid or simplify these challenges.

  • You can train people to use automated predictive tooling to get a good model quickly and enforce best practices for model accuracy and robustness.
  • You can give them clear guidance on how models perform and enable them to deploy successfully into a wide variety of environments.
  • In parallel, they can hone their skills using a pipeline editor to experiment with other approaches while enforcing the same standards of model debriefing.

Most importantly, this reduces the risk of making a bad decision through an inadvertent but costly error. And the cost of entry to successfully utilizing and deploying predictive analytics is lowered, making it much easier to scale.

Don’t get me wrong, you still need training to take advantage of this. You need to know how to ask the question and how to maximize the results.

Even easier insights with an analytics cloud solution

Finally, business users can take advantage of advanced analytics for business exploration without needing to use any algorithms directly. This can be deployed to normal business users. The interface is set up to give them a simple way to frame the question. The insights are displayed in ways that help the user understand what they can and can’t infer from the data.

Is citizen data science real? 

So, to answer the original question: Yes, citizen data science is real, but we should think about what is the best way to enable people of different skillsets to successfully use data science in their business. This trend will only multiply as the automation techniques and helper tools advance and continue to lower the entry bar for data science and predictive analytics.

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Richard Mooney

About Richard Mooney

Richard is the lead product manager for the Predictive Analytics Product Portfolio including Predictive Analytics, Predictive Analytics Integrator & SAP Cloud Platform predictive services. He has 18 years experience in the software industry starting off in development and transitioning to customer facing roles including Product Management, Sales & Marketing. Richard also spent 2 years working as an innovation expert using techniques like Design Thinking, ROI Analysis and Ideation to drive customer innovation and value.

Making The Smart Hospital A Reality

Thiam Hwa Lim

The business of healthcare is quite literally one of life and death. Yet, for a very long time throughout much of the world, the system of medical care has been fraught with inefficiencies and soaring costs.

The most recent data from World Health Organization (WHO) (stemming from 117 countries) shows that an average of 9.3% of people in each country spend more than 10% of their entire household budget on healthcare – a level of spending that is likely to expose a household to financial hardship.

This status quo is certainly ripe for disruption.

Smart hospitals: Pioneers leading the way

Fortunately, healthcare’s next technological revolution – the exploitation of an unprecedented amount of data, combined with cloud computing services, machine learning (ML), artificial intelligence (AI), and the Internet of Things (IoT) – is heralding a very different model of healthcare: A model that offers expert insights and analysis on a mass scale, at a relatively low cost.

Already, we are witnessing innovative healthcare leaders making strides in this direction. Singapore’s Woodlands Health Campus (WHC), a part of the National Healthcare Group (NHG), is one such pioneering effort that is embracing new technologies to deliver seamless, person-centric, outcomes-based care.

Designed to fully integrate a general hospital, a community hospital, a nursing home, as well as daycare facilities for seniors in a single development, WHC is conceived to incorporate SMART technology, automation, and IT innovations campus-wide. This includes the building design, hospital operations, care delivery, and patient experience. A plethora of services will go online, driving higher productivity and efficiency. Automation of manual work, such as filling in medical information or ordering medications, is also expected to allow healthcare professionals to focus on their core work, devoting more time to their clinical and direct patient-care roles. Technological tools such as data analytics and artificial intelligence will also augment patient care, maximizing outcomes at each touch point.

Rethinking the way hospitals work

But what does all this really mean to the patient or healthcare team? Visualize this.

A patient, John, with a history of heart disease finds himself with an episode of abnormal chest pain and rushes to the hospital. The automated and streamlined admission process shaves precious hours and minutes of waiting time. At the point of admission, John is tagged with an electronic wristband that allows doctors and nurses to track his vital signs – heartbeat, medication times, sleep patterns, rehabilitation sessions, etc. – remotely throughout his stay in the hospital. The tracker also alerts healthcare professionals of any anomalies so that the necessary action can be taken.

John’s condition is stabilized and he is kept as an inpatient for further diagnostic tests and observation. It is past midnight. On a wall of beeping screens, the healthcare team monitors John  and their other charges’ vital signs. They can also zoom in on any patient via a camera at the foot of each bed, which also gathers video data for analytics. Together, the various IoT-enabled devices allow emotion recognition (among other signals), which is integrated with the electronic medical record and shared with the nurses.

A cardiac technician notices a light flashing over John’s chart. His premature ventricular contractions are getting worse. He zooms the camera in on John and observes abnormal behavior, which prompts him to alert a nurse on the ground. The quick action halted John’s condition from deteriorating.

Example of an In-Ward Activity Monitor

Example of an in-ward activity monitor

The next day, John finds that he is able to order meals, select entertainment options, and call for assistance via his digital bedside assistant. After further diagnostic tests, the healthcare team concludes that John can be discharged, but needs to be on regular medication and embark on an activity program as part of disease management. Based on John’s individual profile and preferences, the doctor discusses alternatives and sets up an individualized care plan and health goals with John. As part of his post-hospitalization care plan, John will continue wearing the electronic wristband after discharge to allow the healthcare team to continue monitoring his vitals and activities, and to intervene when required.

With the ability to create closely monitored care plans, hospitals can free up hospital beds quicker – allowing patients to manage diseases from the comfort of their home – in order to provide those beds to new patients who need them. John is discharged via an automated process, which also allows him to order public transport, such as a taxi, or to connect to his family member for a ride home.

Back home, the electronic wristband reminds John to take his medicine and order refills. A week later, the system sends out an alert to the doctor that John is not following the prescription plan. The doctor sends out an invite for a follow-up video consultation to check the reasons for non-adherence. This nips the issue in the bud before it gets more severe.

All of John’s relevant data is also anonymized and made available to digital health networks for secondary scientific usage and clinic trials. This allows continuous learning from each individual case.

It’s about moving forward steadily in the digitization journey

Bill McDermott, CEO of SAP said, “There’s nothing that can make a difference in the world more than improving the outcomes of health in society. And, therefore, we are totally dedicated to it.” Picturing what hospitals could be – how much more efficient, cost-effective, as well as patient- and outcome-centric they could become – it becomes clear why he said that.

The fact is that smart hospitals can be a reality. The question is: Has your healthcare organization started and moved forward steadily in its digitization journey?

Discover what other forerunners in digital healthcare is doing. Download exclusive resources on the healthcare industry.

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Thiam Hwa Lim

About Thiam Hwa Lim

Thiam Hwa Lim is the Director of the Healthcare Industry Unit for Southeast Asia at SAP.

Marketing Vision 2017: New Realities And Promise For The Modern Marketer

Fred Isbell

“The pressure on business-to-business (B2B) marketers is great, but the opportunity ahead is even greater. With the rise of the connected economy, B2B marketers are leading the way with new strategies for growth. Find out what’s working, what’s new, and what’s next.”

This was the challenge given to marketing leaders from organizations of all sizes at the annual ITSMA Marketing Conference Marketing Vision 2017. And this got me thinking: What is working, new, and next? Here’s a quick view of what I see.

What’s working: ABM reigns supreme

This year’s Marketing Vision event was my eighth, and the folks at ITSMA have introduced me to many things in B2B and modern marketing over the past decade. But probably the most significant thing in recent years has been account-based marketing (ABM). By definition, ABM “is a strategic approach to business marketing based on account awareness in which an organization considers and communicates with individual prospects or customer accounts as markets of one … and is typically employed in enterprise level sales organizations.”

ABM has certainly navigated the Gartner “hype cycle.” After proving its worth against very high expectations, this approach is now part of successful B2B marketing programs at the companies that have adopted it. ABM has grown to embrace not only one-to-one account-specific marketing, but also elements of one-to-few. And in some cases, it is used in one-to-many marketing, especially in the case of large, complex global organizations and audiences.

ABM maturity has come a long way, as evidenced by an ABM toolkit approach showcased by SAP as one of the 2017 ITSMA Marketing Excellence Award winners and clearly a best practice.ITSMA Marketing Vision 2017

What’s new: Thought leadership evolves

For years, thought leadership and related programs have been a strong passion of mine. However, I am still struck by the continued maturation of thought leadership among successful B2B marketers. Companies such as ITSMA have a process to ascertain thought-leadership maturity, which is a valuable process to determine where an organization stands relative to peers.

Thought leadership has turned into a marketing necessity. According to ITSMA’s research on how buyers consume B2B content, the role of thought leadership is considerable. In fact, 89% of buyers view content, especially thought leadership, as critical or important during the early stages of the buying process.

For some of us experienced in this area, this finding is nothing new. However, we should appreciate that the numbers have continued to grow, especially considering the importance of defining points of view, new ideas, and a focused vision when influencing the purchase process. The combination of both online and offline consumption is relatively new. Meanwhile, the availability of subject-matter experts for conversations, meetings, and workshops makes these interactions critical at the account level and in support of ABM.

What’s next: The rise of artificial intelligence and intelligent insights

After attending several external conferences this year, I see a common thread stitched throughout marketing: the rise of artificial intelligence (AI) and the combination of marketing technology (martech), Big Data, and analytics. While this trend is not purely unexpected, its impact on the future of work is.

Malcolm Frank, executive vice president, chief strategy officer, chief marketing officer, and evangelist at Cognizant, linked how AI will have a profound impact on all industries, across all jobs and roles, in his Market Vision keynote. He stated while 12% of all jobs will be replaced, 75% will be enhanced, and another 13% will be created and provide roles we haven’t yet envisioned. That’s an extraordinarily positive vision of the future!

From bots automating functions such as customer support conversations to cobots serving as virtual digital assistants, marketing will be one of the many functions that will be impacted. In addition, increased volumes of Big Data will bring huge advances in the science part of modern marketing. One day, a cobot may bring the sum total of data sciences knowledge to your marketing team. AI will likely spawn a whole new generation of IT and further enhanced martech. Only time will tell, as marketers research and watch these trends for many years to come.

Please check out my “virtual trip report” from Market Vision 2017I am looking forward to participating in more events in 2018 – stay tuned for the additional insights to follow.

Fred is the senior marketing director for SAP HANA Enterprise Cloud and Digital Business Services Marketing at SAP. Join Fred online: TwitterFacebookLinkedInsap.com

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Fred Isbell

About Fred Isbell

Fred Isbell is the Senior Director of SAP Digital Business Services Marketing at SAP. He is an experienced, results- and goal-oriented senior marketing executive with broad and extensive experience & expertise in high technology and marketing. He has a BA from Yale and an MBA from the Duke Fuqua School of Business.

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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IDC 2018 Predictions: If You’re Not In The Cloud, You’re Isolated From Innovation

Susan Galer

IDC Research just released its top ten 2018 predictions, outlining why every company must operate like a digital-native enterprise. Frank Gens, IDC senior vice president and chief analyst, shared an expansive to-do list for CEOs, line-of-business and IT organizations during a webinar entitled, “IDC FutureScape: Worldwide IT Industry 2018 Predictions.”  His central message was that business is rapidly entering the Cloud 2.0 phase where public cloud is the best and increasingly only platform that every company’s ecosystem will use to hyper-connect industries for accelerated digital transformation journeys with technologies like AI, machine learning, IoT, augmented reality (AR), virtual reality (VR), and blockchain.

“Companies must re-architect operations around large-scale digital innovation networks, in effect becoming a new corporate species. We’re going to see a massive jump in the number of digital services and the pace of innovation. This is the ticking clock running inside the heads of CEOs in every industry, driving them quickly along digital transformation journeys,” said Gens. “Cloud everywhere for everything is what we’re likely to see over the next several years. Companies need to assess their cloud supplier’s ability to support an expanding range of use cases. If you’re not in the cloud, you’re isolated from innovation.”

These are IDC’s top ten 2018 IT predictions:

  1. By 2021, at least 50 percent of global GDP will be digitized, with growth driven by digitally-enhanced offerings, operations and relationships. By 2020, investors will use platform/ecosystem, data value, and customer engagement metrics as valuation factors for all enterprises.
  1. By 2020, 60 percent of all enterprises will have fully articulated an organization-wide digital transformation strategy, and will be in the process of implementing that strategy as the new IT core for competing in the digital economy.
  1. By 2021, spend on cloud services and cloud enabling hardware, software and services doubles to over $530 billion, leveraging the diversifying cloud environment that is 20 percent at the edge, over 15 percent specialized compute, and over 90 percent multi-cloud.
  1. By 2019, 40 percent of digital transformation initiatives will use AI services; by 2021, 75 percent of commercial enterprise apps will use AI, over 90 percent consumers interact with customer support bots, and over 50 percent of new industrial robots will leverage AI.
  1. By 2021, enterprise apps will shift toward hyper-agile architectures, with 80 percent of application development on cloud platforms using microservices and functions, and over 95 percent of new microservices deployed in containers.
  1. By 2020, human-digital (HD) interfaces will diversify, as 25 percent of field-service techs and over 25 percent of info-workers use AR, nearly 50 percent of new mobile apps use voice as a primary interface, and 50 percent of consumer-facing Global 2000 companies use biometric sensors to personalize experiences.
  1. By 2021, at least 25 percent of Global 2000 companies will use blockchain services as a foundation for digital trust at scale; by 2020, 25 percent of top global transaction banks, nearly 30 percent manufacturers and retailers, and 20 percent of healthcare organizations will use blockchain networks in production.
  1. By 2020, 90 percent of large enterprises will generate revenue from data-as-a-service, selling raw data, derived metrics, insights, and recommendations — up from nearly 50 percent in 2017.
  1. Improvements in simple (“low-/no-code”) development tools will dramatically expand the number of non-tech developers over the next 36 months; by 2021, these non-traditional tech developers will build 20 percent of business applications and 30 percent new application features (60 percent by 2027).
  1. By 2021, more than half of Global 2000 companies will see an average one-third of their digital services interactions come through their open API ecosystems, up from virtually zero percent in 2017, amplifying their digital reach far beyond own customer interactions.

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This article originally appeared on Forbes SAPVoice.

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