The Role Of Imagination In Creating The Next Set Of Breakthrough Innovations

Mukesh Gupta

I stumbled across “As We May Think,” an article that Director of the Office of Scientific Research and Development Vannevar Bush wrote in 1945.

This article validates for me the role that imagination can play in the innovation process. Dr. Bush was able to predict in part what the world would look and feel like many years into the future. Here’s what I learned from his approach to ideation and how we can use it to assist in our own quest for using imagination to come up with innovations of the future.

Before trying to predict the future, understand the present

First, Bush thoroughly analyzed the present day (mid-1940s) situation, including what WWII had fostered and what it hindered, from the perspective of scientific inquiry and progress. He shared his thoughts on the state of scientific research and where science had seen progress and where it stood still.

Identify potentialities by extrapolation

He then extrapolated into the future by identifying the potentialities in the progress made, and shared what he though would happen in the near-to-short term if things had continued on the same trajectory. This is where he talked about immediate and imminent progress based on what was already happening. Most futurists and trend predictors use this process to forecast their trends.

Now, let your imagination fly

Once he built a good, solid foundation by identifying the progress made and what was expected in the near-to-short term, he then allowed his imagination to take flight. He talked about the camera becoming so small that someone would could carry one strapped onto their foreheads (sounds to me like a GoPro):

The camera hound of the future wears on his forehead a lump a little larger than a walnut.

He then explored and explained what the film and printing process would look like:

Often it would be advantageous to be able to snap the camera and to look at the picture immediately.

He imagined advances in micro-film technology that would enable the whole of Encyclopedia Britannica (one of the largest book collections at that time) to be available on something the size of a matchbox.

The Encyclopedia Britannica could be reduced to the volume of a matchbox. A library of a million volumes could be compressed into one end of a desk. If the human race has produced since the invention of movable type a total record, in the form of magazines, newspapers, books, tracts, advertising blurbs, correspondence, having a volume corresponding to a billion books, the whole affair, assembled and compressed, could be lugged off in a moving van.

The material for the microfilm Britannica would cost a nickel, and it could be mailed anywhere for a cent.

In addition to storing all of this knowledge in a small size, he said it is also important to create new knowledge and do so in an easy and simple way. He talked about a device into which someone speaks (in a specific way) and the device converts this into the appropriate text (sounds a lot like voice-to-text devices – Siri?)

To make the record, we now push a pencil or tap a typewriter. Then comes the process of digestion and correction, followed by an intricate process of typesetting, printing, and distribution. To consider the first stage of the procedure, will the author of the future cease writing by hand or typewriter and talk directly to the record? He does so indirectly, by talking to a stenographer or a wax cylinder; but the elements are all present if he wishes to have his talk directly produce a typed record. All he needs to do is to take advantage of existing mechanisms and to alter his language.

He then took flight in his imagination to put all of this together and predict what it would feel like to live in an era with such devices:

One can now picture a future investigator in his laboratory. His hands are free, and he is not anchored. As he moves about and observes, he photographs and comments. Time is automatically recorded to tie the two records together. If he goes into the field, he may be connected by radio to his recorder. As he ponders over his notes in the evening, he again talks his comments into the record. His typed record, as well as his photographs, may both be in miniature, so that he projects them for examination.

He acknowledged that a lot would need to happen between 1945’s reality and his imagined reality, but he was confident that it was all possible. He showed how past progress implied that the pace of innovation and creativity would only accelerate, meaning his imagined reality would not be very far from the time he was writing the piece.

Next he described mathematical inquiry and his definition of a mathematician:

A mathematician is not a man who can readily manipulate figures; often he cannot. He is not even a man who can readily perform the transformations of equations by the use of calculus. He is primarily an individual who is skilled in the use of symbolic logic on a high plane, and especially he is a man of intuitive judgment in the choice of the manipulative processes he employs.

This is probably the closest definition that I have come across for a data scientist. Bush said machines would do actual mathematical calculations and enable the mathematician to think about a higher order of logic. He also understood that the potential of such a machine is not limited to the scientist.

The scientist, however, is not the only person who manipulates data and examines the world about him by the use of logical processes, although he sometimes preserves this appearance by adopting into the fold anyone who becomes logical, much in the manner in which a British labor leader is elevated to knighthood. Whenever logical processes of thought are employed – that is, whenever thought for a time runs along an accepted groove – there is an opportunity for the machine. Formal logic used to be a keen instrument in the hands of the teacher in his trying of students’ souls. It is readily possible to construct a machine which will manipulate premises in accordance with formal logic, simply by the clever use of relay circuits. Put a set of premises into such a device and turn the crank, and it will readily pass out conclusion after conclusion, all in accordance with logical law, and with no more slips than would be expected of a keyboard adding machine.

I think this sounds like a general purpose computer or even a smartphone. He then goes on to imagine how a retail store could be run if all these innovations became a reality. It sounds a lot like an ERP system running the entire store and its operations.

He also predicted that machines can be taught to learn and operate, not just on selection by indexing, but by association, and that machines would be able to beat humans (the story of IBM’s Watson winning Jeopardy?) – what’s called today machine learning.

Man cannot hope fully to duplicate this mental process artificially, but he certainly ought to be able to learn from it. In minor ways he may even improve, for his records have relative permanency. The first idea, however, to be drawn from the analogy concerns selection. Selection by association, rather than indexing, may yet be mechanized. One cannot hope thus to equal the speed and flexibility with which the mind follows an associative trail, but it should be possible to beat the mind decisively in regard to the permanence and clarity of the items resurrected from storage.

He described a personal machine (he calls it “memex”) that stores all the information and data that we need as individuals (including all the knowledge that humans have accumulated over the centuries) and is available whenever a person wants it. Information would be accessible by associative indexing (sounds like hyperlinking to me), which would allow us to move across connected and relevant topics.

The owner of the memex, let us say, is interested in the origin and properties of the bow and arrow. Specifically he is studying why the short Turkish bow was apparently superior to the English longbow in the skirmishes of the Crusades. He has dozens of possibly pertinent books and articles in his memex. First he runs through an encyclopedia, finds an interesting but sketchy article, leaves it projected. Next, in a history, he finds another pertinent item, and ties the two together. Thus he goes, building a trail of many items. Occasionally he inserts a comment of his own, either linking it into the main trail or joining it by a side trail to a particular item. When it becomes evident that the elastic properties of available materials had a great deal to do with the bow, he branches off on a side trail which takes him through textbooks on elasticity and tables of physical constants. He inserts a page of longhand analysis of his own. Thus he builds a trail of his interest through the maze of materials available to him.

And his trails do not fade. Several years later, his talk with a friend turns to the queer ways in which a people resist innovations, even of vital interest. He has an example, in the fact that the outraged Europeans still failed to adopt the Turkish bow. In fact he has a trail on it. A touch brings up the code book. Tapping a few keys projects the head of the trail. A lever runs through it at will, stopping at interesting items, going off on side excursions. It is an interesting trail, pertinent to the discussion. So he sets a reproducer in action, photographs the whole trail out, and passes it to his friend for insertion in his own memex, there to be linked into the more general trail.

Sounds a lot like a combination of Google, Wikipedia, and Evernote to me.

He then goes on to talk about the fact that science is a tool that could create weapons and innovations that could not only enable humanity to keep track of its history, but create a completely new future as well.

Applied imagination

In a single 1945 article, Vannevar Bush imagined so many innovations that we enjoy today, seven decades later. He imagined things similar to GoPro, selfie sticks, Google Glass, ERP systems, digitized Encyclopedia Britannica, search engines, note-taking in the cloud, voice-to-text and text-to-voice conversions, personal computers, mobile phones, and much more.

This shows that if we start from the place where we are today, apply our imagination, and take leaps of faiths, we can imagine what the future will look like and then go after this future with all our current strengths.

This ability to imagine is critical for all of us who wish to be part of the generation of innovators who will define what and how our future shapes up.

How to develop this ability to imagine

In “The Real Neuroscience of Creativity,” Scott Barry Kaufman talks about three kinds of neural networks – the Executive Attention Network (activated when we need focused attention to do something specific), the Imagination Network (also called the default network), and the Salience Network (acts as the “switching” network and decides which neural network needs to be activated when).

… the Default Network (referred to here as the Imagination Network) is involved in “constructing dynamic mental simulations based on personal past experiences such as used during remembering, thinking about the future, and generally when imagining alternative perspectives and scenarios to the present.” The Imagination Network is also involved in social cognition. For instance, when we are imagining what someone else is thinking, this brain network is active. The Imagination Network involves areas deep inside the prefrontal cortex and temporal lobe (medial regions), along with communication with various outer and inner regions of the parietal cortex.

Conclusion

What this tells me is that the ability to imagine is inherently human and we are all capable of letting our imagination soar, if we want to.

So, the inability to imagine new or alternate realities is totally self-induced – and sometimes induced by our systems (e.g., education and even the culture of our organizations). This also means that it is in our very hands to set this right and start imagining alternate realities. The more we practice, the better we will get at it.

The more important it is for us to innovate and create, the more critical the skill to imagine alternate realities.

When Vannevar wrote this piece, it was a time where technological breakthroughs were imminent.

We are again at the same crossroads & technological breakthroughs are imminent. The question we need to now ask is:

Will we bring in the breakthroughs, or will we stand and wait for someone to do it for us?

PS: You can view a visual tour of Vannevar Bush’s Work below:

More predictions: AI will make customers and employees happier – as long as it learns to respect our boundaries. Learn more about Empathy: The Killer App for Artificial Intelligence.

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Mukesh Gupta

About Mukesh Gupta

Mukesh Gupta previously held the role of Executive Liaison for the SAP User group in India. He worked as the bridge between the User group and SAP (Development, Consulting, Sales and product management).

Analytics And Big Data: Driving Agility In The Chemical Industry

Michael Laprocido

How important are concepts like Big Data and analytics to the modern enterprise environment? In a word: Very. One study estimates there are currently six million developers all over the world currently working on Big Data and advanced analytics projects. To put that into perspective, that’s about the size of the populations of Houston and Los Angeles combined.

Spending on Big Data tech is expected to reach $57 billion by the end of the year. The business intelligence and analytics market worldwide will be worth about $18.3 billion by the same time. But the true strengths of concepts like Big Data and analytics comes by way of their symbiotic relationship. As the quality of data improves, so does the value of the insight generated by sophisticated analytics solutions.

This is particularly true in the chemical industry, where many companies are currently using Big Data and analytics to support a bold new level of strategic agility that has not been available until now.

Dynamic visibility empowers dynamic resource allocation

Resource planning and allocation have always been critical processes in the chemical industry. Until the somewhat recent past, changes both upstream and downstream from the chemical manufacturer evolved more slowly and predictably. Analysis of markets and competitive position in target segments performed either as a one-off annual or even biennial exercise were adequate to enable a chemical company to have the requisite amount of agility to compete successfully.

Today, complexity and fundamental change are increasing exponentially due to the impacts of globalization, the rapidly shifting center of gravity for demand towards the rising middle class in Asia, the unprecedented influence of US unconventional oil production on raw material costs and global competition, the ongoing compression of product lifecycles experienced by their customers, and the speedy adoption of technology to evolve business models. Thus, analysis must be continually rendered as events and change unfold to be effective in responding. In fact, agility is becoming increasingly important as a source of competitive advantage as the pace of change accelerates making the attainment of an agile culture a board-level imperative.

Unfortunately, being agile is particularly difficult for chemical companies given the breadth and scope of their target markets. Specifically, the challenge lies in the ubiquitous application of their products (in that they are sometimes applied in many industries and in millions of uses) and that the industry is usually at least one step (sometimes several) removed from the ultimate consumer. Thus, chemical companies must be agile on many fronts to be successful. This requires a thorough understanding of the dynamics associated with the value chains for each major product/application/market combination they serve – no small feat given the complexity associated with a single value chain in today’s reality! If attained, this level of insight will not only ensure that chemical companies are providing the appropriate level of resources to support these target segments but that they are focused on the right ones to begin with.

This segues into the true value of Big Data and analytics in this context. Capacity, capital, and skilled people are hardly abundant. It is senior management’s responsibility to ensure that these critical resources are applied to the firm’s best prospects in the light of their strategic objectives. Leveraging Big Data and analytics will allow senior management to guarantee that these finite resources can accomplish both current and future goals at the same time. Not only can organizations put themselves in the best position to maximize shareholder return through action today, but they can also build a bridge to profitable and sustainable growth in the long term.

To become agile, you need to glean insight from data generated both internally and externally. Leveraging internally generated data can help companies see how well they are making use of their available resources today. Layering in external data allows you to get a better understanding of how a chemical business needs to allocate their resources in the future so that it can then better position itself in the direction that leadership wants.

Case in point: Big Data and analytics are invaluable when examining something like growth versus share. Tracking changes in growth and share dynamically based on analytical data gives leadership an almost real-time view into how things are changing, how well the business is positioned to address that change, and the strategic implications of it. Important metrics like profitability, cost to serve, and competitive position are added into the mix, generating an additional level of context to this data to help quickly discern potential opportunities and threats that may be emerging. Use of predictive analytics can lead to strategies to capture or mitigate these under any given timeframe by identifying trends and patterns in things like short to mid-term inflections in demand that might have otherwise gone unnoticed.

Over the longer term, having a dynamic capability to analyze markets in real time will also let you examine things like potential structural market changes. The ability to consider how your competitive advantage will change given the potential for things like competitor capacity addition, supply disruption, and more gives you a much more dynamic ability to understand your business in the context of your target markets. Applying these scenarios in your planning will provide the ability to perpetually allocate scarce resources to provide the greatest return under any condition at a moment’s notice.

It may not be possible to see into the future, but the insights and projections generated by analytics and Big Data may very well be the next big thing. This is certainly true in the chemicals industry, where organizations are struggling to stay malleable and agile amidst ever-changing market conditions.

Using the path to build the future

In the end, it’s important to understand that the true pathway to strategic agility for chemical companies begins with possessing a capability to make sense of the flood of data that is both inside and outside its walls. Insights derived from real-time Big Data and analytics is the key to realizing a dynamic ability to understand your business as it exists in the current context of the market, and can make it easier to take advantage of strategic opportunities as they arise. By gaining a superior level of visibility into both the state of an organization as it exists today and a forward-looking view of their future markets, leaders have the best and most accurate information to work from when making decisions that affect things tomorrow, a year from now, and beyond. You can reallocate scarce resources to provide the best return for any set of conditions, which is what strategic agility is really all about.

Hidden inside your organization’s data is the key to remaining nimble moving forward. Analytical tools let chemical companies go beyond that data, extracting the valuable insight and narrative hidden underneath. That narrative then lets organizational leaders write the future of the company on their own terms.

Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value: read  Accelerating Digital Transformation in Chemicals. Explore how to bring Industry 4.0 insights into your business today: read Industry 4.0: What’s Next?

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Michael Laprocido

About Michael Laprocido

Mike Laprocido serves as a Strategic Industry Advisor for SAP. He is responsible for developing thought leadership and driving SAP solution adoption in the chemical and oil and gas industries. With over three decades in various executive roles at BP Oil, BP Chemicals, Kuraray America, Panda Energy and IBM prior to joining SAP, Mike has gained a broad and deep industry knowledge base that he leverages to help his clients to innovate and transform their business through the application of digital technology.

Exploring The Future Of Insurance

Uwe Hofstaetter

The insurance industry is evolving quickly. New technology and innovative solutions are providing consumers with much more than a basic policy that sits in a drawer and is sought after only when they need to file a claim. Today’s insurance industry is far-reaching, providing a wide variety of services to consumers. Insurance has become a life service.

Insurance is transforming as innovation continues

Insurance is evolving from a service that provides help when a problem occurs to a tool that helps prevent the problem in the first place. Insurance is helping people live healthier lives, enjoy safer homes, avoid vehicle accidents, and much more.

Predicting risks helps reduce loss

Information allows insurance companies to assess situations with real-time data and lessen the potential damage from natural disasters. For example, over the previous few years, devastating hurricanes have hit the United States and other areas of the world. However, the amount of destruction and the number of lives lost has decreased due to better use of data. According to Bob Cummings, head of the insurance industry business unit at SAP, data and technology behind the scenes are helping make this possible. In the “S.M.A.C. Talk Technology” podcast, he explains, “This is just because we’ve been able to protect much more, and much of that protection actually is thanks to technology, thanks to data, thanks to sensor technologies which allow us to have early warning systems.”

Zillow Research indicates that in Florida alone, $400 billion in real estate value is at risk from climate change by the year 2100. Analyzing and assessing data could help reduce this loss significantly. Today’s innovative technology is leading the way.

Companies can innovate and still reduce privacy risks

A key concern with innovation in the insurance industry is privacy. A survey from On Device Research for Mobile Ecosystems Forum found that 70 percent of Americans, and 62 percent of people globally, are worried about privacy and the Internet of Things.

There’s no doubt that the insurance industry has an unnerving amount of access to a person’s private information. Consider, for example, a watch that monitors a person’s pulse, or a device that constantly gathers information about their level of physical fitness. These devices can help health insurers provide more cost-effective policies to healthy patients and guide to others to obtain health care before life-threatening conditions arise. Yet there is a privacy concern here. Can data stream in and still be protected?

“I would say even most importantly, wrap it in-iron clad security so that this data really stays within its business context and its business model and is not available to other areas. This is probably our fastest growing area,” says Bob Cummings in the podcast. In many ways, the technology that’s now transforming this data into usable information is becoming some of most sophisticated from a security perspective. That’s good news for both consumers and insurance companies: It reduces risks, enhances access to usable data, and ensures privacy.

Harnessing data has never been easier

Just a few decades ago, insurance companies could not access data to accurately predict risk with consumers. Today, that data is available in many forms. Consumers wear smartwatches that stream data. Mobile connectivity through smartphone apps has exploded. New technology is synthesizing patient data to make it usable in real time.

Consumers benefit first and foremost when insurers have data from such technological advances and connection points. Weather data can help predict storms. Smart home technology can save lives by monitoring carbon monoxide levels.

While IoT, machine learning, and predictive analytics technologies help consumers, they also help mitigate risks to insurance companies. Insurers can provide better service to consumers and work to improve systems and offer health guidance to minimize claims. With privacy solutions built in, consumers can feel confident that sharing their personal information will benefit them in both the short and long term. In this way, technology empowers insurance companies, brokers, agents, and industry leaders to provide a life service.

Where will the insurance industry go from here?

It is an exciting time to be in the insurance industry. New resources and tools are becoming available as companies explore innovative ways to meet the needs of their customers. To explore the innovation and changes occurring and how your company can adapt to them, take a few minutes to listen to the full podcast from SAP’s Bob Cummings at S.M.A.C. Talk Technology.

Hear the full podcast episode here. Learn how to bring new technologies and services together to power digital transformation by downloading The Future Services Sector: Connected Services for Continuous Delivery.

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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.

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CEO Priorities And Challenges In The Digital World

Dr. Chakib Bouhdary

Digital transformation is here, and it is moving fast. Companies are starting to realize the enormous power of digital technologies like artificial intelligence (AI), Internet of things (IoT) and blockchain. These technologies will drive massive opportunities—and threats—for every company, and they will impact all aspects of business, including the business model. In fact, business velocity has never been this fast, yet it will never be this slow again.

To move quickly, companies need to be clear on what they want to achieve through digital transformation and understand the possible roadblocks. Based on my meetings with customer executives across regions and industries, I have learned that CEOs often have the same three priorities and face the same three challenges:

1. Customer experience – No longer defined by omnichannel and personalized marketing.

Not surprisingly, 92 percent of digital leaders focus on customer experience. However, this is no longer just about omnichannel and personalized marketing – it is about the total customer experience. Businesses are realizing that they need to reimagine their value proposition and orchestrate changes across the value chain – from the first point of interaction to manufacturing, to shipment, to service – and be able to deliver the total customer experience. In some cases, it will even be necessary to change the core product or service itself.

2. Step change in productivity – Transform productivity and cost structure through digital technologies.

Businesses have been using technology to achieve growth for decades, but by combining emerging technologies, they can now achieve a significant productivity boost and reduce costs. For this to happen, companies must first identify the scenarios that will drive significant change in productivity, prioritize them based on value, and then determine the right technologies and solutions. Both Mckinsey and Boston Consulting Group expect a 15 to 30 percent improvement in productivity through digital advancements – blowing the doors off business-as-usual and its incremental productivity growth of 1 to 2 percent.

3. Employee engagement – Fostering a culture of innovation should be at the core of any business.

Companies are looking to create an environment that encourages creativity and innovation. Leaders are attracting the needed talent and building the right skill sets. Additionally, they aim for ways to attract a diverse workforce, improve collaborations, and empower employees – because engaged employees are crucial in order to achieve the best results. This Gallup study reveals that approximately 85 percent of employees worldwide are performing below their potential due to engagement issues.

As CEOs work towards achieving these three desired outcomes, they face some critical challenges that they must address. I define the top three challenges as follows: run vs. innovate, corporate cholesterol, and digital transformation roadmap.

1. Run vs. innovate – To be successful you must prioritize the future.

The foremost challenge that CEOs are facing is how they can keep running current profitable businesses while investing in future innovations. Quite often these two conflict as most executives mistakenly prioritize the first and spend much less time on the latter. This must change. CEOs and their management teams need to spend more time thinking about what digital is for them, discuss new ideas, and reimagine the future. According to Gartner, approximately 50 percent of boards are pushing their CEOs to make progress on digital. Although this is a promising sign, digital must become a priority on every CEOs agenda.

2. Corporate cholesterol – Do not let company culture get in the way of change.

The older the company is, the more stuck it likely is with policies, procedures, layers of management, and risk averseness. When a company’s own processes get in the way of change, that is what I call “corporate cholesterol.” CEOs need to change the culture, encourage cross-team collaborations, and bring in more diverse thinking to reduce the cholesterol levels. In fact, both Mckinsey and Capgemini conclude that culture is the number-one obstacle to digital effectiveness.

3. Digital transformation roadmap – Digital transformation is a journey without a destination.

Many CEOs struggle with their digital roadmap. Questions like: Where do I start? Can a CDO or another executive run this innovation for me? What is my three- to five-year roadmap? often come up during the conversations. Most companies think that there is a set roadmap, or a silver bullet, for digital transformation, but that is not the case. Digital transformation is a journey without a destination, and each company must start small, acquire the necessary skills and knowledge, and continue to innovate.

It is time to face the digital reality and make it a priority. According to KPMG, 70 percent to 80 percent of CEOs believe that the next three years are more critical for their company than the last fifty. And there is good reason to worry, as 75 percent of S&P 500 companies from 2012 will be replaced by 2027 at the current disruption rate.

Download this short executive document. 

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Dr. Chakib Bouhdary

About Dr. Chakib Bouhdary

Dr. Chakib Bouhdary is the Digital Transformation Officer at SAP. Chakib spearheads thought leadership for the SAP digital strategy and advises on the SAP business model, having led its transformation in 2010. He also engages with strategic customers and prospects on digital strategy and chairs Executive Digital Exchange (EDX), which is a global community of digital innovation leaders. Follow Chakib on LinkedIn and Twitter