Digital Devices to Enhance Children’s Education and Health

Danielle Beurteaux

Field Trips Without the Bus

Technology is changing classrooms in incredible ways, creating experiences for today’s students that would have seemed impossible a mere generation ago. Interactive capabilities let learners explore, travel, and adventure, all while at their desks.


sap_q416_digital_double_disruptors_images20The fictional Magic School Bus comes closer to reality with a virtual reality (VR)app that enables students to take field trips without leaving the classroom. Google’s Android and iOS-compatible Expeditions, with its cardboard virtual reality viewer, enables students to travel to some 200 locales, including Angkor Wat in Cambodia, the ecosystems of Borneo, and Australia’s Great Barrier Reef. The virtual trips have been created through partnerships with organizations such as the Wildlife Conservation Society and the American Museum of Natural History. Teachers can use 360-degree panoramas and 3D images to lead their students to places they otherwise might never experience.


sap_q416_digital_double_disruptors_images1Platform and content creator Lifeliqe will soon be bringing its library of educational 3D content to virtual reality headsets. Lifeliqe (as in “life like”) has partnered with HTC Vive to create immersive VR adventures for students, empowering them to explore science, technology, engineering, and mathematics, from the molecular level to outer space. Using 1,000-plus models, students from kindergarten through grade 12 will be able to travel through the human body or examine a shark from multiple angles—including the inside.

Some Assembly Code Required

Many children today have been exposed to technology since they were in utero. But that doesn’t mean they understand how it all works. Some educational technology companies are bringing the hands-on back to tech with projects designed to get kids building and coding what they imagine.


sap_q416_digital_double_disruptors_images16It arrives as a box of wooden pieces, but Piper, a DIY computer kit, is designed to make your seven-year-old tech fluent. By following the enclosed blueprint and using tools that include an old-school screwdriver, kids can make their own computer and gadgets such as controllers, lights, and buzzers. The Raspberry Pi–based laptop includes a Minecraft modification called PiperCraft, developed by scientists at Princeton and Stanford, for students to create their own games. With the goal of encouraging kids’ imaginations and sense of play, PiperCraft includes a treasure hunt adventure and virtual TNT-triggered explosions.

Mover Kit

sap_q416_digital_double_disruptors_images6For parents who don’t want to raise a couch potato, London-based tech startup Technology Will Save Us has launched its new Mover Kit to get kids away from the screen. The first DIY wearable for kids, Mover Kit uses two circuit boards to integrate a microcontroller, accelerometer, magnetometer, and eight colorful LED lights. Kids can create their own uses for the device by programming it with “if this, then that” logic to respond to physical movement.

Sensitive Sensoring

Children’s health and development have always been a top priority for parents. These devices have been created to help kids stay happy and healthy.


sap_q416_digital_double_disruptors_images11Withings’ Thermo, a U.S. Food and Drug Administration–approved thermometer, is designed to make it easier to take children’s temperatures and track fevers. Using its 16 infrared sensors to collect 4,000 measurements, Thermo needs only a skim across the forehead—without touching skin—to return a temperature reading in two seconds. The built-in Wi-Fi and Bluetooth can then send the information to a smartphone app that tracks the fever. Parents can set up profiles for different family members. Thermo also connects to Thermia, a fever calculator and database site run by Boston Children’s Hospital, which gives fever information and recommends treatments.


sap_q416_digital_double_disruptors_images4A cute orb with a digital face, Leka is a robotic programmable smart toy that moves, speaks, plays music, and vibrates. It’s designed to help children with special needs develop social, motor, and cognitive abilities. Leka’s sensors enable it to react to children’s behavior, helping the children become independent by guiding them through daily activities, such as brushing their teeth.

The device’s consistent responses to how children treat it (for example, by making a sad face if a child throws it) help minimize stress and anxiety. Single- and multiplayer games enable children to play with their Leka on their own or with family members or therapists. The platform captures data that gives parents and other care providers a picture of their children’s interactions and development. It also offers educational applications, like the picture bingo app where real-life objects are matched with images on Leka’s screen.


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


Improving Mobility With Smart Traffic In Metro Operations

Konstanze Werle

The increasing demands of a larger population are a growing concern. Estimates suggest that by 2030, around 60 percent of the world population will live in large cities. By 2040, this will increase to around 75 percent.

Urbanization raises specific concerns for metro operators, who must consider the increased traffic and safety risks associated with a growing population. Developing smart traffic strategies helps optimize the flow of people and goods in the city to reduce congestion and the risk of safety hazards. It also helps metro operators handle problems that may arise from increased traffic.

Frequency and route

Adequate transport services are a priority for transit operators, particularly as populations increase. The behavior of regular commuters, tourists, and occasional commuters, and the traffic resulting from events impact transit routes and availability of public transportation. Metro operators need to determine when to deploy transportation and the appropriate size of transport vehicles in different areas and at different times of the day. Metro operators and city officials must understand the travel patterns of patrons to provide effective transportation services.

According to World Transit Research, many residents of major cities in the United States avoid bus transit that requires them to transfer to a different bus. If schedules and routes are complicated, many residents look for alternative forms of transportation to reach their destination. World Transit Research points out that the bus transportation system in Barcelona was designed to cover the entire city. With a greater number of routes and frequency of buses, residents are more likely to transfer to a different bus to move throughout the city. Evaluating the travel patterns of local residents in a city provides an opportunity to address potential problems with frequency and available routes on public transportation.

Reducing delays from malfunctions

The Florida Department of Traffic points out that a smart traffic system actually improves the urban environment by setting up solutions in every area of traffic control and management. Cameras on traffic lights or in metro stations, for example, allow operators to identify problems at an early stage. Metro operators can then take measures to correct them in a timely manner.

Smart traffic systems gather accurate data and place sensors on public transportation to limit risks to passengers. The sensors also determine when problems develop and can catch malfunctions before they cause significant delays. Sensors help operators determine when to handle maintenance on trains or other areas of technology. The result: Better solutions to problems and fewer delays.

Greater management of incidents on public transportation

Safety management systems in public transportation have come a long way in supporting the management of risks that contribute to accidents. According to the Florida Department of Traffic, metro operators handle incidents that occur on public transportation in relation to the technology, doors, and overall systems. Smart traffic systems enhance safety and give operators access to more data from sensors, cameras, and technological tools.

The information allows operators to address incidents that may result in inconveniences, delays, or poor traffic management. As a result, risk management tools available to the operators will help professionals anticipate incidents and address potential concerns in the future.

Optimized traffic control

According to the Oregon Metro, smart traffic systems allow metro operators to limit or even prevent problems due to congestion. Smart traffic systems focus on every area of urban traffic, from driving to taking a bus. By setting up a system that directs traffic around an accident or informs drivers about potential delays with updated data, it reduces the number of incidents on the road.

Optimizing traffic control plays a significant role in the safety of residents and commuters. Metro operators improve the coordination of traffic signals to prevent accidents with trains or other traffic. It also provides real-time information about current traffic conditions, weather information in relation to the roads, and appropriate signals for transit priority or large trucks.

The result of better coordination throughout traffic control in an urban environment is greater safety. The risk of accidents reduces by providing passengers of public transportation and drivers of their own vehicles real-time data about road conditions or other potential factors. Smart traffic gives metro operators advanced incident management solutions for every area of traffic control.

Smart traffic in metro operations provides a solution for safety concerns and frustrations with transportation in urban areas. As urban populations grow, metro operators face greater challenges in relation to commuter safety. Setting up a smart traffic system allows the metro operators to stay up-to-date with real-time incidents and handle malfunctions before they cause injuries or safety concerns.

Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value: Accelerating Digital Transformation in Transportation.


Konstanze Werle

About Konstanze Werle

Konstanze Werle is a Director of Industries Marketing at SAP. She is a content marketing specialist with a particular focus on the travel and transportation, engineering and construction and real estate industries worldwide. Her goal is to help companies in these industries to simplify their business by sharing latest trends and innovation in their industry.

Plastic Waste: What The Ecological Revolution Means For Retailers

Tesni Fellows

A month traditionally dictated by Halloween outfits and premature Christmas decorations, October 2017 ignited the most momentous occasion yet in the war on plastic, revolutionizing a nation to act while beginning an ecological awakening for retailers.

David Attenborough’s Blue Planet disturbed viewers on a global scale, forcing them to consider the consequences and the damage of plastic waste. Highlighting harrowing truths such as “a year’s plastic wastage weighs roughly as much as all all the world’s people” signified the extent to which we need to address this issue more than ever.

Plastic-not-so-fantastic: What the ecological revolution means for retailers

Despite the tax on plastic carrier bags adopted by many retail chains, Attenborough’s influence expanded consumers’ desire to understand what more could be done to save our planet and how to change a culture. Retailers are listening and changing the forefront of their business strategies to accommodate how people want to shop, who they want to shop with, what changes they need to implement, and what this all means for the future of retail.

What can retailers do to support the demands of customers who want to eliminate plastic waste?

Be transparent: The rise of social media has been the catalyst of change in the era of digital disruption and transformation, altering consumer behavior to encourage lifestyle purchasing. This shift has advanced through increasing societal and political issues around climate change.

As consumers are made accountable for their role regarding plastic waste, they are making more conscious changes in how they shop and who they shop with. Since 2016, consumer research on where to find the “best” products has grown by 80%, illustrating the need for quality products and ethical businesses that mirror consumer principles. However, this information is not always available to the public. For example, under an EU directive, groceries and large supermarkets are subject to share the amount of plastic they put on the market annually. Nevertheless, there is no mandate that these figures are released, so customers cannot effectively choose businesses that align with their morals. Ultimately, businesses should invest in being transparent to demonstrate their support of customer demands, enabling them to retain loyal customers and win new clients. Otherwise, inevitably, they will lose out to their competition that does.

The emphasis on lifestyle purchasing is further enhanced by focusing the change on a permanent, global level. The Cleaner Britain campaign in January 2018 emphasized eliminating avoidable plastic wastage within 25 years. Despite not all retailers being ready to admit their contributions to plastic waste, the idea of being the “first” to do so during this consumerism shift brings value to their branding in the market. Many grocery chains are showcasing their plastic-free successes. For example, Bulk Market has a bring-your-own-container (BYOC) policy, Iceland has begun a five-year plan to be the first plastic-free supermarket, and most recently, Ekoplaza opened the world’s first plastic-free aisle.

This trend is filtering into other retail areas like sports, where London-based gym 1Rebel is providing reusable plastic bottles to customers. These public initiatives allow consumers to be more knowledgeable about who to trust and ultimately, who to align with. Consumers wield the power in the buying process and are driving cultural change, meaning retailers can no longer afford to hide information about what they deliver to market.

As international players in the retail industry, it’s the responsibility of corporations to be visionary leaders in these changes, too. For example, in England, plastic bags use in retail stores has dropped 85% since a 5p tax was implemented. Global players can make a difference by listening to the customer and implementing initiatives that filter down to smaller enterprises and local merchants. With every small victory, a larger cultural shift is created.

Be ethical: Transparency in business creates a paradigm of cultural and ethical changes among retailers. The concept of mindful purchasing has become one that businesses must support across all channels to demonstrate their values and willingness to support their customers. This requires retailers to be more ethical in their products and in their brand values. For example, the fashion company Batoko produces affordable swimwear solely made from recycled plastics from the oceans. This is a unique brand proposition and demonstrates that a company’s ethical culture is just as important as its products. These creative possibilities are inspiring others to do the same and enabling wider cultural changes.

Retailers can make sustainable changes in their products by choosing to work with ethical suppliers. Businesses must start asking how they can work with suppliers to create new alternatives without driving up consumer cost. How can they implement these alternatives as norms? As customers are researching more about what they buy, they are also learning more about where materials are sourced and what role different companies play in this process. The customer relationship is going beyond product-based values, placing ethics as a priority. Retailers who invest in the suppliers they work with are able to adopt more changes as brand ambassadors.

Businesses partnering to support societal initiatives are imperative to driving change in the retail industry. Engaging socially savvy millennials allows brands to reach thousands across social channels to influence change. Business-to-business initiatives within the retail industry can also be beneficial. Within the beauty industry, the Ellen MacArthur Foundation launched The New Plastics Economy, combining a range of third-party support such as “corporations, local government leaders, academics, NGOs, and other stakeholders” to change how plastic is exchanged globally. Once small and large companies work together to create influential communities, other industries and global players are incentivized to make ethical changes, spread unified messaging across their platforms, and get involved to champion consumer demands.

Understand your customer: Businesses must understand their customers and how they shop when implementing changes across their omnichannel platforms. Reducing plastic is easier to accomplish in physical stores, such as with coffee shops Pret a Manger and Starbucks, which cuts the price of drinks when using a reusable cup. Nevertheless, going completely plastic-free must become an integral part of retail business models, both online and in store. By understanding the conscious changes consumers make in-store to reduce plastic, organizations can figure out how to apply those choices to their online purchasing.

How retailers can support the elimination of plastic waste

Retailers can help eliminate plastic waste by using recyclable materials, like cardboard boxes, for packaging. Tailoring and personalizing customer messaging and marketing campaigns via promotions, incentives, and content ensures you are building awareness about how you are making changes to reduce plastic waste. Additionally, promoting charities or industry initiatives you are supporting demonstrates your contributions to the wider change. Addressing the topic lends credibility and puts your business at the forefront of the agenda.

With brick and mortar here to stay, along with Instagram, Pinterest, and other social apps influencing consumer purchasing behavior, the omnichannel revolution demands retailers respond across all mediums and touchpoints to meet their customers’ demands. This enables businesses to be a step ahead and support consumers as effectively as possible.

For retailers to meet the customer’s ever-changing demands, they need to adapt. To do this, they need to be transparent and listen to their customers, especially with regard to options for reducing their plastic consumption across various purchasing methods.

Plastic is no longer being treated as a disposable material, and therefore we cannot treat it as a disposable issue. With customers at the helm of this cultural paradigm, businesses need to jump onboard the bandwagon or be left behind.

Learn more about Why Corporate Social Responsibility Matters.

This article originally appeared on The Future of Customer Engagement and Commerce.


Tesni Fellows

About Tesni Fellows

Tesni Fellows is the Global Partner Marketing Associate for SAP Hybris. Her experience throughout SAP Hybris has expanded from supporting marketing initiatives across Northern Europe to strategizing, coordinating, organizing, and executing marketing campaigns across a global remit of SI, ISV, and GB partners. Having studied English Language and Political Science at Newcastle University, Tesni has also explored her passion for writing in different fields such as sport and music, contributing to her universities paper, The Courier.

The Blockchain Solution

By Gil Perez, Tom Raftery, Hans Thalbauer, Dan Wellers, and Fawn Fitter

In 2013, several UK supermarket chains discovered that products they were selling as beef were actually made at least partly—and in some cases, entirely—from horsemeat. The resulting uproar led to a series of product recalls, prompted stricter food testing, and spurred the European food industry to take a closer look at how unlabeled or mislabeled ingredients were finding their way into the food chain.

By 2020, a scandal like this will be eminently preventable.

The separation between bovine and equine will become immutable with Internet of Things (IoT) sensors, which will track the provenance and identity of every animal from stall to store, adding the data to a blockchain that anyone can check but no one can alter.

Food processing companies will be able to use that blockchain to confirm and label the contents of their products accordingly—down to the specific farms and animals represented in every individual package. That level of detail may be too much information for shoppers, but they will at least be able to trust that their meatballs come from the appropriate species.

The Spine of Digitalization

Keeping food safer and more traceable is just the beginning, however. Improvements in the supply chain, which have been incremental for decades despite billions of dollars of technology investments, are about to go exponential. Emerging technologies are converging to transform the supply chain from tactical to strategic, from an easily replicable commodity to a new source of competitive differentiation.

You may already be thinking about how to take advantage of blockchain technology, which makes data and transactions immutable, transparent, and verifiable (see “What Is Blockchain and How Does It Work?”). That will be a powerful tool to boost supply chain speed and efficiency—always a worthy goal, but hardly a disruptive one.

However, if you think of blockchain as the spine of digitalization and technologies such as AI, the IoT, 3D printing, autonomous vehicles, and drones as the limbs, you have a powerful supply chain body that can leapfrog ahead of its competition.

What Is Blockchain and How Does It Work?

Here’s why blockchain technology is critical to transforming the supply chain.

Blockchain is essentially a sequential, distributed ledger of transactions that is constantly updated on a global network of computers. The ownership and history of a transaction is embedded in the blockchain at the transaction’s earliest stages and verified at every subsequent stage.

A blockchain network uses vast amounts of computing power to encrypt the ledger as it’s being written. This makes it possible for every computer in the network to verify the transactions safely and transparently. The more organizations that participate in the ledger, the more complex and secure the encryption becomes, making it increasingly tamperproof.

Why does blockchain matter for the supply chain?

  • It enables the safe exchange of value without a central verifying partner, which makes transactions faster and less expensive.
  • It dramatically simplifies recordkeeping by establishing a single, authoritative view of the truth across all parties.
  • It builds a secure, immutable history and chain of custody as different parties handle the items being shipped, and it updates the relevant documentation.
  • By doing these things, blockchain allows companies to create smart contracts based on programmable business logic, which can execute themselves autonomously and thereby save time and money by reducing friction and intermediaries.

Hints of the Future

In the mid-1990s, when the World Wide Web was in its infancy, we had no idea that the internet would become so large and pervasive, nor that we’d find a way to carry it all in our pockets on small slabs of glass.

But we could tell that it had vast potential.

Today, with the combination of emerging technologies that promise to turbocharge digital transformation, we’re just beginning to see how we might turn the supply chain into a source of competitive advantage (see “What’s the Magic Combination?”).

What’s the Magic Combination?

Those who focus on blockchain in isolation will miss out on a much bigger supply chain opportunity.

Many experts believe emerging technologies will work with blockchain to digitalize the supply chain and create new business models:

  • Blockchain will provide the foundation of automated trust for all parties in the supply chain.
  • The IoT will link objects—from tiny devices to large machines—and generate data about status, locations, and transactions that will be recorded on the blockchain.
  • 3D printing will extend the supply chain to the customer’s doorstep with hyperlocal manufacturing of parts and products with IoT sensors built into the items and/or their packaging. Every manufactured object will be smart, connected, and able to communicate so that it can be tracked and traced as needed.
  • Big Data management tools will process all the information streaming in around the clock from IoT sensors.
  • AI and machine learning will analyze this enormous amount of data to reveal patterns and enable true predictability in every area of the supply chain.

Combining these technologies with powerful analytics tools to predict trends will make lack of visibility into the supply chain a thing of the past. Organizations will be able to examine a single machine across its entire lifecycle and identify areas where they can improve performance and increase return on investment. They’ll be able to follow and monitor every component of a product, from design through delivery and service. They’ll be able to trigger and track automated actions between and among partners and customers to provide customized transactions in real time based on real data.

After decades of talk about markets of one, companies will finally have the power to create them—at scale and profitably.

Amazon, for example, is becoming as much a logistics company as a retailer. Its ordering and delivery systems are so streamlined that its customers can launch and complete a same-day transaction with a push of a single IP-enabled button or a word to its ever-attentive AI device, Alexa. And this level of experimentation and innovation is bubbling up across industries.

Consider manufacturing, where the IoT is transforming automation inside already highly automated factories. Machine-to-machine communication is enabling robots to set up, provision, and unload equipment quickly and accurately with minimal human intervention. Meanwhile, sensors across the factory floor are already capable of gathering such information as how often each machine needs maintenance or how much raw material to order given current production trends.

Once they harvest enough data, businesses will be able to feed it through machine learning algorithms to identify trends that forecast future outcomes. At that point, the supply chain will start to become both automated and predictive. We’ll begin to see business models that include proactively scheduling maintenance, replacing parts just before they’re likely to break, and automatically ordering materials and initiating customer shipments.

Italian train operator Trenitalia, for example, has put IoT sensors on its locomotives and passenger cars and is using analytics and in-memory computing to gauge the health of its trains in real time, according to an article in Computer Weekly. “It is now possible to affordably collect huge amounts of data from hundreds of sensors in a single train, analyse that data in real time and detect problems before they actually happen,” Trenitalia’s CIO Danilo Gismondi told Computer Weekly.

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials.

The project, which is scheduled to be completed in 2018, will change Trenitalia’s business model, allowing it to schedule more trips and make each one more profitable. The railway company will be able to better plan parts inventories and determine which lines are consistently performing poorly and need upgrades. The new system will save €100 million a year, according to ARC Advisory Group.

New business models continue to evolve as 3D printers become more sophisticated and affordable, making it possible to move the end of the supply chain closer to the customer. Companies can design parts and products in materials ranging from carbon fiber to chocolate and then print those items in their warehouse, at a conveniently located third-party vendor, or even on the client’s premises.

In addition to minimizing their shipping expenses and reducing fulfillment time, companies will be able to offer more personalized or customized items affordably in small quantities. For example, clothing retailer Ministry of Supply recently installed a 3D printer at its Boston store that enables it to make an article of clothing to a customer’s specifications in under 90 minutes, according to an article in Forbes.

This kind of highly distributed manufacturing has potential across many industries. It could even create a market for secure manufacturing for highly regulated sectors, allowing a manufacturer to transmit encrypted templates to printers in tightly protected locations, for example.

Meanwhile, organizations are investigating ways of using blockchain technology to authenticate, track and trace, automate, and otherwise manage transactions and interactions, both internally and within their vendor and customer networks. The ability to collect data, record it on the blockchain for immediate verification, and make that trustworthy data available for any application delivers indisputable value in any business context. The supply chain will be no exception.

Blockchain Is the Change Driver

The supply chain is configured as we know it today because it’s impossible to create a contract that accounts for every possible contingency. Consider cross-border financial transfers, which are so complex and must meet so many regulations that they require a tremendous number of intermediaries to plug the gaps: lawyers, accountants, customer service reps, warehouse operators, bankers, and more. By reducing that complexity, blockchain technology makes intermediaries less necessary—a transformation that is revolutionary even when measured only in cost savings.

“If you’re selling 100 items a minute, 24 hours a day, reducing the cost of the supply chain by just $1 per item saves you more than $52.5 million a year,” notes Dirk Lonser, SAP go-to-market leader at DXC Technology, an IT services company. “By replacing manual processes and multiple peer-to-peer connections through fax or e-mail with a single medium where everyone can exchange verified information instantaneously, blockchain will boost profit margins exponentially without raising prices or even increasing individual productivity.”

But the potential for blockchain extends far beyond cost cutting and streamlining, says Irfan Khan, CEO of supply chain management consulting and systems integration firm Bristlecone, a Mahindra Group company. It will give companies ways to differentiate.

“Blockchain will let enterprises more accurately trace faulty parts or products from end users back to factories for recalls,” Khan says. “It will streamline supplier onboarding, contracting, and management by creating an integrated platform that the company’s entire network can access in real time. It will give vendors secure, transparent visibility into inventory 24×7. And at a time when counterfeiting is a real concern in multiple industries, it will make it easy for both retailers and customers to check product authenticity.”

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials. Although the key parts of the process remain the same as in today’s analog supply chain, performing them electronically with blockchain technology shortens each stage from hours or days to seconds while eliminating reams of wasteful paperwork. With goods moving that quickly, companies have ample room for designing new business models around manufacturing, service, and delivery.

Challenges on the Path to Adoption

For all this to work, however, the data on the blockchain must be correct from the beginning. The pills, produce, or parts on the delivery truck need to be the same as the items listed on the manifest at the loading dock. Every use case assumes that the data is accurate—and that will only happen when everything that’s manufactured is smart, connected, and able to self-verify automatically with the help of machine learning tuned to detect errors and potential fraud.

Companies are already seeing the possibilities of applying this bundle of emerging technologies to the supply chain. IDC projects that by 2021, at least 25% of Forbes Global 2000 (G2000) companies will use blockchain services as a foundation for digital trust at scale; 30% of top global manufacturers and retailers will do so by 2020. IDC also predicts that by 2020, up to 10% of pilot and production blockchain-distributed ledgers will incorporate data from IoT sensors.

Despite IDC’s optimism, though, the biggest barrier to adoption is the early stage level of enterprise use cases, particularly around blockchain. Currently, the sole significant enterprise blockchain production system is the virtual currency Bitcoin, which has unfortunately been tainted by its associations with speculation, dubious financial transactions, and the so-called dark web.

The technology is still in a sufficiently early stage that there’s significant uncertainty about its ability to handle the massive amounts of data a global enterprise supply chain generates daily. Never mind that it’s completely unregulated, with no global standard. There’s also a critical global shortage of experts who can explain emerging technologies like blockchain, the IoT, and machine learning to nontechnology industries and educate organizations in how the technologies can improve their supply chain processes. Finally, there is concern about how blockchain’s complex algorithms gobble computing power—and electricity (see “Blockchain Blackouts”).

Blockchain Blackouts

Blockchain is a power glutton. Can technology mediate the issue?

A major concern today is the enormous carbon footprint of the networks creating and solving the algorithmic problems that keep blockchains secure. Although virtual currency enthusiasts claim the problem is overstated, Michael Reed, head of blockchain technology for Intel, has been widely quoted as saying that the energy demands of blockchains are a significant drain on the world’s electricity resources.

Indeed, Wired magazine has estimated that by July 2019, the Bitcoin network alone will require more energy than the entire United States currently uses and that by February 2020 it will use as much electricity as the entire world does today.

Still, computing power is becoming more energy efficient by the day and sticking with paperwork will become too slow, so experts—Intel’s Reed among them—consider this a solvable problem.

“We don’t know yet what the market will adopt. In a decade, it might be status quo or best practice, or it could be the next Betamax, a great technology for which there was no demand,” Lonser says. “Even highly regulated industries that need greater transparency in the entire supply chain are moving fairly slowly.”

Blockchain will require acceptance by a critical mass of companies, governments, and other organizations before it displaces paper documentation. It’s a chicken-and-egg issue: multiple companies need to adopt these technologies at the same time so they can build a blockchain to exchange information, yet getting multiple companies to do anything simultaneously is a challenge. Some early initiatives are already underway, though:

  • A London-based startup called Everledger is using blockchain and IoT technology to track the provenance, ownership, and lifecycles of valuable assets. The company began by tracking diamonds from mine to jewelry using roughly 200 different characteristics, with a goal of stopping both the demand for and the supply of “conflict diamonds”—diamonds mined in war zones and sold to finance insurgencies. It has since expanded to cover wine, artwork, and other high-value items to prevent fraud and verify authenticity.
  • In September 2017, SAP announced the creation of its SAP Leonardo Blockchain Co-Innovation program, a group of 27 enterprise customers interested in co-innovating around blockchain and creating business buy-in. The diverse group of participants includes management and technology services companies Capgemini and Deloitte, cosmetics company Natura Cosméticos S.A., and Moog Inc., a manufacturer of precision motion control systems.
  • Two of Europe’s largest shipping ports—Rotterdam and Antwerp—are working on blockchain projects to streamline interaction with port customers. The Antwerp terminal authority says eliminating paperwork could cut the costs of container transport by as much as 50%.
  • The Chinese online shopping behemoth Alibaba is experimenting with blockchain to verify the authenticity of food products and catch counterfeits before they endanger people’s health and lives.
  • Technology and transportation executives have teamed up to create the Blockchain in Transport Alliance (BiTA), a forum for developing blockchain standards and education for the freight industry.

It’s likely that the first blockchain-based enterprise supply chain use case will emerge in the next year among companies that see it as an opportunity to bolster their legal compliance and improve business processes. Once that happens, expect others to follow.

Customers Will Expect Change

It’s only a matter of time before the supply chain becomes a competitive driver. The question for today’s enterprises is how to prepare for the shift. Customers are going to expect constant, granular visibility into their transactions and faster, more customized service every step of the way. Organizations will need to be ready to meet those expectations.

If organizations have manual business processes that could never be automated before, now is the time to see if it’s possible. Organizations that have made initial investments in emerging technologies are looking at how their pilot projects are paying off and where they might extend to the supply chain. They are starting to think creatively about how to combine technologies to offer a product, service, or business model not possible before.

A manufacturer will load a self-driving truck with a 3D printer capable of creating a customer’s ordered item en route to delivering it. A vendor will capture the market for a socially responsible product by allowing its customers to track the product’s production and verify that none of its subcontractors use slave labor. And a supermarket chain will win over customers by persuading them that their choice of supermarket is also a choice between being certain of what’s in their food and simply hoping that what’s on the label matches what’s inside.

At that point, a smart supply chain won’t just be a competitive edge. It will become a competitive necessity. D!

About the Authors

Gil Perez is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Tom Raftery is Global Vice President, Futurist, and Internet of Things Evangelist, at SAP.

Hans Thalbauer is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Dan Wellers is Global Lead, Digital Futures, at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

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



The Differences Between Machine Learning And Predictive Analytics

Shaily Kumar

Many people are confused about the specifics of machine learning and predictive analytics. Although they are both centered on efficient data processing, there are many differences.

Machine learning

Machine learning is a method of computational learning underlying most artificial intelligence (AI) applications. In ML, systems or algorithms improve themselves through data experience without relying on explicit programming. ML algorithms are wide-ranging tools capable of carrying out predictions while simultaneously learning from over trillions of observations.

Machine learning is considered a modern-day extension of predictive analytics. Efficient pattern recognition and self-learning are the backbones of ML models, which automatically evolve based on changing patterns in order to enable appropriate actions.

Many companies today depend on machine learning algorithms to better understand their clients and potential revenue opportunities. Hundreds of existing and newly developed machine learning algorithms are applied to derive high-end predictions that guide real-time decisions with less reliance on human intervention.

Business application of machine learning: employee satisfaction

One common, uncomplicated, yet successful business application of machine learning is measuring real-time employee satisfaction.

Machine learning applications can be highly complex, but one that’s both simple and very useful for business is a machine learning algorithm that compares employee satisfaction ratings to salaries. Instead of plotting a predictive satisfaction curve against salary figures for various employees, as predictive analytics would suggest, the algorithm assimilates huge amounts of random training data upon entry, and the prediction results are affected by any added training data to produce real-time accuracy and more helpful predictions.

This machine learning algorithm employs self-learning and automated recalibration in response to pattern changes in the training data, making machine learning more reliable for real-time predictions than other AI concepts. Repeatedly increasing or updating the bulk of training data guarantees better predictions.

Machine learning can also be implemented in image classification and facial recognition with deep learning and neural network techniques.

Predictive analytics

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. Basic descriptive analytic techniques include averages and counts. Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data.

This concept applies complex techniques of classical statistics, like regression and decision trees, to provide credible answers to queries such as: ‘’How exactly will my sales be influenced by a 10% increase in advertising expenditure?’’ This leads to simulations and “what-if” analyses for users to learn more.

All predictive analytics applications involve three fundamental components:

  • Data: The effectiveness of every predictive model strongly depends on the quality of the historical data it processes.
  • Statistical modeling: Includes the various statistical techniques ranging from basic to complex functions used for the derivation of meaning, insight, and inference. Regression is the most commonly used statistical technique.
  • Assumptions: The conclusions drawn from collected and analyzed data usually assume the future will follow a pattern related to the past.

Data analysis is crucial for any business en route to success, and predictive analytics can be applied in numerous ways to enhance business productivity. These include things like marketing campaign optimization, risk assessment, market analysis, and fraud detection.

Business application of predictive analytics: marketing campaign optimization

In the past, valuable marketing campaign resources were wasted by businesses using instincts alone to try to capture market niches. Today, many predictive analytic strategies help businesses identify, engage, and secure suitable markets for their services and products, driving greater efficiency into marketing campaigns.

A clear application is using visitors’ search history and usage patterns on e-commerce websites to make product recommendations. Sites like Amazon increase their chance of sales by recommending products based on specific consumer interests. Predictive analytics now plays a vital role in the marketing operations of real estate, insurance, retail, and almost every other sector.

How machine learning and predictive analytics are related

While businesses must understand the differences between machine learning and predictive analytics, it’s just as important to know how they are related. Basically, machine learning is a predictive analytics branch. Despite having similar aims and processes, there are two main differences between them:

  • Machine learning works out predictions and recalibrates models in real-time automatically after design. Meanwhile, predictive analytics works strictly on “cause” data and must be refreshed with “change” data.
  • Unlike machine learning, predictive analytics still relies on human experts to work out and test the associations between cause and outcome.

Explore machine learning applications and AI software with SAP Leonardo.


Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past.