How Access To Voter Data Fuels Campaigns’ Drive To Win Your Vote

Reuters Content Solutions

Running for elective office is about building an organization to promote the candidate’s views. It’s about attracting professionals and volunteers to make calls and knock on doors. It’s about raising money. But today a political campaign of any size needs to be about collecting and analyzing data about voters: who supports the candidate, who can be persuaded, who may give money and who will show up at the polls.

The political parties provide their candidates with access to data, but access is just the start. To make productive use of data, campaigns must first ensure it is of high quality and then employ analysis to identify supporters, encourage them to volunteer and donate and, most importantly, get out to vote.

Sophisticated data analysis is not a level playing field—it costs a lot of money. What’s more, effective analysis of data creates a virtuous cycle: More resources enable a campaign to collect more data about voters’ views, to find more supporters, to refine messages that resonate, to recruit more volunteers, to attract even more donors and to get their supporters to the polls.

Rivals who are less adept with data or have fewer resources are at a significant disadvantage, says Daniel Kreiss, who teaches media studies at the University of North Carolina and is the author of “Prototype Politics: Technology-Intensive Campaigning and the Data of Democracy.”

“One of the things that data helps do is to figure out which groups of voters do we need to target, and which groups of voters do we need to spend our time and our messaging resources on,” says Kreiss. “And how do we efficiently do that to get more votes, again on Election Day, than the next person. So data matters greatly in terms of resources.”

A number of companies have emerged in recent years to help candidates and campaigns crunch data. NationBuilder, for example, prides itself on serving all political persuasions. Emily Schwartz, NationBuilder’s vice president of organizing, says that today’s data tools make analytical resources available to local and grassroots campaigns as well as national ones.

NationBuilder’s service is free to try, then users pay monthly fees based on the level of services, such as software for email campaigns and campaign-focused websites.

Other organizations offer data help to candidates:

  • i360, whose backers include the conservative Koch brothers, bills itself as “the leading data and technology resource for the free market political advocacy community.”
  • NGP VAN is a voter-data management platform for Democratic candidates and progressive organizations.
  • The Republican National Committee’s Data Center 2016 project is a proprietary voter file designed to give its candidates ammunition in data-driven elections.

The Obama model

Like other political experts, Meta S. Brown, president of the consultancy A4A Brown Inc. and author of “Data Mining for Dummies,” points to President Obama’s 2012 re-election victory over Mitt Romney as a recent high point in the use of data. In that election, the Obama campaign sent out volunteers to go door to door asking voters their opinions.

“You can use that information in every way you campaign,” says Brown. “They can use it in advertising and how to do ad buys effectively. That was a big competitive advantage of the Obama campaign over the Romney campaign.”

That data crunching provided another type of competitive advantage, she adds: The Obama campaign could spend fewer ad dollars to reach voters, on average, because they selected only those TV programs and times they needed.

The kind of sophisticated data analysis goes well beyond TV. It enables a campaign to microtarget people through email messages, social media, online ads, follow-up visits and phone calls to the homes of supporters to encourage them to vote.

Brown points to the Obama campaign’s expert use of social media as a model in the modern campaign. The campaign found supporters on Facebook (through their “likes” or message postings) and got them to send supportive messages to friends in swing states like Ohio. “That ability to take advantage of social media, that really is a tipping point,” says Brown.

The effective use of data can also reinforce a campaign’s relative strength against an opponent.

Campaigns that collect voters’ email addresses can conduct experiments on which messages are more effective, down to the email subject line, says Kreiss. By testing which type of message delivers better results—yielding more volunteers or more donations—the campaigns refine their efforts. The Obama campaign estimated that insights gained through these “A/B tests” added $100 million in donations during the 2012 race, according to Kreiss.

It starts with voter data

Campaigns start their data work with voter records. Voter data is largely a matter of public record in the United States. That includes names and mailing address and often when the person voted in past elections. It sometimes includes party affiliation.

For data experts, getting these names is just the start. The information needs to be in a format that computers can read. Voter rolls are subject to change as people move, die, change names or register for the first time. Keeping an accurate and up-to-date voter database is a major task for registration officials. A 2012 study by the Pew Center on the States found that about 24 million voter registrations in the United States—one in every eight—are no longer valid or are inaccurate. And voter lists do not come in a standard format, says Schwartz of NationBuilder. Wisconsin, Virginia and Washington, for example, do not provide party affiliation with their voter lists.

Brown notes that data has to be organized to be useful, and that takes work. “It doesn’t matter who the source is, you have to expect some quality problems and do some investigations,” she says. That’s where the well-funded and data-savvy campaign has a significant advantage.

Data and our democracy

Experts on data analysis disagree on its implications for the country. Kreiss says cynics argue that candidates use data to manipulate voters, but he argues for the benefits of analysis.

“We live in world where it is a lot harder to reach voters than it was 40 years ago because people’s media habits have changed significantly,” he says. “So to the extent that data is enrolled in the ability of campaigns to actually figure out which sorts of voters should we be talking to, how do we mobilize them, how do we get them to the polls and, ultimately, what should we be saying in order to get people excited about particular candidates, I think that is a good thing for democracy.”

The rise of data crunching in politics also tends to favor incumbents, because those who have been in the game before will have more detailed data in their files.

Eitan Hersh, an assistant professor of political science at Yale, says that while political parties share data with candidates about voters in their district, incumbents are able to take advantage of the data they have collected in previous campaigns to reconnect with previously identified supporters.

“They make lists of everyone who asked for a yard sign and made a donation and volunteered. And if you have been in Congress for 10 years, and you have a whole bunch of people on that list, that can be very valuable,” says Hersh. “If a challenger comes around, they might not have that.”

The technology used to analyze voter data—which costs less than buying TV ads—can help an upstart to level the playing field, but it requires the insurgent campaign to have data savvy and a lot of volunteers.

“One huge advantage that is closely tied to data is volunteer support because a lot of the strategies that utilize data are things like door-to-door canvassing and phone banking, strategies where the data helps you [know] who to contact and helps you study the effectiveness of contacts,” says Hersh. “Once you have a certain level of data access, that data can power volunteers. And it’s hard to manufacture volunteers.”

Another effect of campaign data-crunching is the potential for increased voter turnout.

Ryan Enos, an associate professor of government at Harvard, co-authored a study of get-out-the-vote efforts in the 2012 presidential race. Both the Obama and Romney campaigns successfully used data-driven techniques to encourage citizens to vote. In total, the campaigns raised voter turnout by 2.6 million people, or 7 percent, says Enos. “If we define a healthy democracy as one with larger participation, then that is probably a good thing,” he says.

However, there is a participation gap in who responds to these get-out-the-vote efforts, says Enos. People who are already more likely to vote are more responsive. “What we find is that these sorts of techniques work best for people who tend to be politically conservative. They tend to be richer, they tend not to be racial minorities. In some ways what these techniques do is widen the gap in what we might call participators and non-participators,” he says.

At the end of the day, successful use of data is no substitute for a strong candidate. Schwartz, who worked on Obama’s 2008 campaign, notes that effectively using data saves time and money in targeting voters. It does not substitute for a candidate’s message. “They ran an incredible campaign,” she says of 2008. But they also had Barack Obama.”

This blog was written through a partnership with Thompson Reuters. To learn how SAP is helping them Run Live, click here.

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The Value Of Digital Transformation In The Chemicals Industry

Dr. Thorsten Wenzel

The chemicals industry is more than a single industry. It is a group of industries that produce a wide range of products across many unique segments. Base chemicals, paints, beauty products, fragrances, and food flavorings all have one thing in common. These segments are under pressure due to rapid changes in digital technology, consumer demand, and global competition.

In the past, large producers dominated the market. These large producers valued operational efficiency over flexibility and adaptability. Today, the market is challenged by niche players who strongly focus on customer or even consumer demand. These have prompted incumbents to differentiate themselves by producing smaller batches for individual customer needs, selling services, experiences, and outcomes, and being early adopters of digital technology at the business core.

Large, established firms and smaller, emerging competitors deal with the same dynamics. Rapid commoditization of the industry has accelerated as oil prices have remained low. Volatile feedstock prices have added an element of cost variability. New technologies, such as 3D printing, have provided new opportunities for plastics, resins, ceramics, and powders.

Globalization has also altered the chemicals industry. New competitors, markets, and regulatory issues have changed industry dynamics. Economic and manufacturing growth in Asia has made its mark. As a result, many firms have moved towards mergers and acquisitions to remain competitive and drive growth. For such firms, the daily challenges of integrating operating systems into a single system have become a reality.

There is also the threat from innovative companies that have reimagined their markets, products, services, and technologies. An example of this is the paint and coatings market. Companies are selling customer experiences instead of products. It’s not the color of the paint, it’s how the paint looks on the wall and fits into the larger home experience. Companies are using an integrated digital supply chain along with consumer data to create a direct-to-consumer model. By working with retail outlets and automated sensor-enabled mixing systems, they are also moving closer to the quality of custom products. During the process they are gaining valuable customer data and insights.

Gaining the edge

The impact of these industry changes is easy to see, as are the challenges they create. Chemical companies must identify new revenue streams, including innovative services and outcome-based models. To do this, they must address an aging, non-digital workforce and find ways to attract new talent that embraces the digital workplace. This talent will be key to leveraging technology to offer core business value. For this to happen, companies must leverage large amounts of data to better understand their operations and their customers.

Overcoming these challenges is the only way to address the single largest challenge the industry faces today. The future of the chemicals industry is no longer the one-shot, blockbuster product model. It’s in the creation of an ecosystem focused on improving the customer’s experience.

The right technologies, the right approach

Digital technology and the data it brings hold tremendous promise for the chemicals industry. These technologies can all play a role in driving business value.

  • The Internet of Things (IoT), leveraging sensors to capture data from manufacturing, storage, and distribution
  • The cloud, a platform to support a common system of record for both suppliers and customers
  • Analytics, to correlate supply data to product quality and customer satisfaction
  • Machine learning, to assist in predictive maintenance of operational equipment
  • Blockchain, to better track transactions for assets, materials, and products

But technology alone isn’t the answer. In the chemicals industry, it’s the use of technology against the right digital strategy that holds the real value. This requires a focus on implementing a true digital core that enables a common system of record through the business. It also requires a corporate mindset that embraces agility, adaptability, and innovation. It requires a mindset that is driven by a customer-first, design thinking perspective.

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

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Dr. Thorsten Wenzel

About Dr. Thorsten Wenzel

Thorsten Wenzel is Vice President and Global Head of Chemicals at SAP.

The Power Of Digital In The Utilities Industry

Henry Bailey

The utilities industry touches every person, every household, and every business. It provides generation, transmission, distribution, and metering of all forms of energy and water, as well as waste disposal and recycling. It is considered the foundation for modern life. It is also considered by many to be an industry at risk, as the way consumers perceive and consume resources is changing. It is also an industry that stands much to gain from current and emerging digital technologies.

There are three macro forces shaping the industry today: decentralization, deregulation, and decarbonization. Decentralization involves a shift in how and where energy is consumed. No longer the exclusive domain of power companies, energy is now being produced at an increasing rate by both businesses and households leveraging solar, wind, and battery technologies. Most customers that produce their own energy are still connected to the power grid. In fact, many of them sell surplus energy back to the local power utility. This has resulted in a market dynamic where customers have now become suppliers. As a benefit, this allows utility companies to better manage supply and demand, particularly during peak periods. But it also adds significantly to the complexity of the supply chain.

Deregulation is another force shaping the industry. As regulatory bodies have opened the door to new competition, energy resellers (using utility company transmission systems) have become an alternative to the traditional electric or gas company. Deregulation is also allowing non-utility companies into the home, as seen in the rapid rise of on-premises monitoring and control products and companies. These firms, such as Amazon (Nest), offer new ways for consumers to manage their energy usage. In the process, they also have the ability to take control of the customer relationship, often positioning the utility company as a commodity item, while they provide the value-add today’s consumer seeks.

Decarbonization is also changing the utility landscape, as the strong customer-driven push for carbon energy alternatives (e.g., solar, wind, hydro) has resulted in higher demand for energy saving and the use of renewable resources.

The challenges of being a utility

Combined, these three forces are placing a number of challenges on utilities, which are increasingly asking:

  • How can they support and even encourage consumers to smartly generate power, all while retaining control of the relationship (or partnership)?
  • How can they drive the use of smart in-home control and metering devices that add value to both the consumer (lower energy utilization) and the utility (improved load management)?
  • How can they offer clean energy and cost-savings programs through the use of smart sensors and intelligent assets?
  • How can they evolve their businesses, services, and operational processes to survive in a world where the consumer is asking for improved energy consumption at a lower price point than before?

Utility providers are also asking how they can attract and retain the talent necessary to address these problems.

Enter the digital solution

The answers to these questions can be found through the right application of digital technologies, a willingness to rethink business operations and revenue models, and the appropriate tools necessary to capture, analyze, and act on the massive amount of data that is available to utilities today.

With the right digital core, the cloud can become a secure and ubiquitous platform for storing data and a common system of record for the company, its partners, and its customers. Internet of Things (IoT) sensors can be used to gather data from operational infrastructure, supply chain partners, employees, and customers to better understand and manage the generation, distribution, and consumers of its offerings. Predictive analytics and machine learning can offer insights into improved operations and maintenance. Even emerging technologies such as blockchain can play a role, helping record and track supply chain and customer equipment transactions.

The bottom line is digital offers the ability to foster innovation, develop new revenue opportunities, and address the challenges faced by today’s utilities industry.

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

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Henry Bailey

About Henry Bailey

Henry Bailey is global vice president of Utilities Industry Business Unit for SAP. He leads a team of customer focused professionals creating end-2-end solutions across the 5 key market categories; Core Applications, Cloud Computing, Mobile Platforms, Business Intelligence and Database Technologies with HANA.

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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Four Retail Technology Trends To Take Off In 2018

Shaily Kumar

Over the past few years, technology has seen a significant shift from cyclical, invention-led spending on point solutions to investments targeting customer-driven, end-to-end value. The next wave of disruption and productivity improvements is here, which means a huge opportunity for digital-focused enterprises – if you are following the right roadmap.

Technology trends have significant potential over the next few years. Establishing a digital platform will not only set the stage for business innovation to provide competitive advantage, but it will also create new business models that will change the way we do business. Technology trends in 2018 will lay the foundation for the maturity of innovative technologies like artificial intelligence and machine learning and will prepare both businesses and shoppers to be ready for their consumption.

Like any other industry, retail is being disrupted. It is no longer enough to simply stock racks with alluring products and wait for customers to rush through the door. Technological innovation is changing the way we shop. Customers can find the lowest price for any product with just a few screen touches. They can read online reviews, have products sent to their home, try them, and return anything they don’t want – all for little or nothing out of pocket. If there are problems, they can use social networks to call out brands that come up short.

Retailers are making their products accessible from websites and mobile applications, with many running effective Internet business operations rather than brick-and-mortar stores. They convey merchandise to the customer’s front entry and are set up with web-based networking media if things turn out badly.

Smart retailers are striving to fulfill changing customer needs and working to guarantee top customer service regardless of how their customer interacts with them.

2017 saw the development of some progressive technology in retail, and 2018 will be another energizing year for the retail industry. Today’s informed customers expect a more engaging shopping experience, with a consistent mix of both online and in-store recommendations. The retail experience is poised to prosper throughout next couple of years – for retailers that are prepared to embrace technology.

Here are four areas of retail technology I predict will take off in 2018:

In-store GPS-driven shopping trolleys

Supermarkets like Tesco and Sainsbury’s now enable their customers to scan and pay for products using a mobile app instead of waiting in a checkout line. The next phase of this involves intelligent shopping trolleys, or grocery store GPS: Customers use a touch screen to load shopping lists, and the system helps them find the items in the store. Customers can then check off and pay for items as they go, directly on-screen. These shopping trolleys will make their way into stores around the last quarter of 2018.

Electronic rack edge names

Electronic rack edge names are not yet broadly utilized, but this could change in 2018 as more retailers adopt this technology. Currently, retail workers must physically select and update printed labels to reflect changes in price, promotions, etc. This technology makes the process more efficient by handling such changes electronically.

Reference point technology

Despite the fact that it’s been around since 2013, reference point technology hasn’t yet been utilized to its fullest potential. In the last few years, however, it’s started to pick up in industries like retail. It’s now being used by a few retailers for area-based promotions.

Some interesting uses I’ve observed: Retailers can send messages to customers when they’re nearby a store location, and in-store mannequins can offer information about the clothing and accessories they’re wearing. I anticipate that this innovation will take off throughout 2018 and into 2019.

Machine intelligence

The technological innovations describe above will also provide retailers with new data streams. These data sources, when merged with existing customer data, online, and ERP data, will lead to new opportunities. Recently Walmart announced it would begin utilizing rack examining robots to help review its stores. The machines will check stock, prices, and even help settle lost inventory. It will also help retailers learn more about changing customer behavior in real time, which will boost engagement.

Clearly, technology and digital transformation in retail have changed the way we live and shop. 2018 will see emerging technologies like machine learning and artificial intelligence using structured and unstructured data to deliver innovation. As technology develops, it will continue to transform and enhance the retail experience.

For more insight on e-commerce, see Cognitive Commerce In The Digital World: Enhancing The Customer Journey.

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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.