GDPR: More Than Data Management, It’s About Governance

Neil Patrick

As you know, the General Data Protection Regulation (GDPR), or Regulation (EU) 2016/679, is the revision to the European Union (EU) data protection law that becomes enforceable on May, 25 2018. Lately, I’ve been noticing that several software solutions and presentations focus on the data management aspects of GDPR—the “consent, deleting, blocking, retention” spectrum of GDPR compliance. Of course, this is necessary, and a good starting point.

However, the challenge posed to companies by GDPR is more about the organisational and procedural changes that will be necessary to demonstrate that a company is taking seriously the need to protect personal data as a business-as-usual regime through all echelons of stakeholders, operations, technology, and partnerships.

GDPR: It’s complicated

The figure below indicates why this is necessary. It shows the complexity of GDPR by linking interrelationships between the 99 articles in the regulation.

Almost half of the articles in GDPR are related to business procedures associated with policies, record-keeping, and accountabilities of roles and entities in order to demonstrate that a company’s approach to handling personal data is taken as seriously as the regulation requires.

Processing shall be lawful only if the data subject has given consent to processing of personal data (or one of the other five reasons) for a specific purpose, and each purpose must be distinct. Each data-processing activity must connect to a purpose that has a finite business scope, specific lawful reasons for conducting it, and a finite lifetime.

The fact that so many of the articles reference each other indicates the need for robust, enterprise-ready, holistic policy and process compliance software to address this plate of regulatory spaghetti. The governance is a challenge.

Why GDPR is a bit like wiretapping

Let me use wiretapping as a topical analogy to separate the technical from the  governance aspects.

Conducting modern wiretapping is a technical task requiring modern technology, leading-edge software, and smart and experienced people. This is the equivalent of the data-play conversation in GDPR: how to tag data, delete data, block access to it, archive it with legal retention periods, and so on.

However, the parallel activity—and many would argue a more important aspect—is the actual governance of wiretapping. This governance includes whether a wiretapping should take place, who approves it, what is the duration and scope, and what levels of intrusion are acceptable. This is the equivalent of the governance of GDPR, or the meat that the supervising authorities will want to pick over as evidence of compliance.

The controller’s responsibilities

GDPR Article 5 Chapter 2 requires that “the controller shall be responsible for, and be able to demonstrate compliance with, paragraph 1 (‘accountability’).”

I was talking to someone recently who picked out Article 30 as a troublesome area. To help me understand it, I created a mind-map diagram that spells out in detail the record-keeping requirements of processors and controllers.

Data processors now have direct obligations, like controllers. They must maintain a written record of the processing categories carried out on behalf of each controller, and notify each controller as they become aware of a data breach without undue delay.

Controllers must maintain a written record of processing activities.

So as in the wiretapping analogy, it’s not enough to be able to technically achieve the requirement. Tight governance must be maintained on how the task is managed.

Compliance must be done, and be seen as done

The governance complexity becomes an almost exponential equation:

  • Multiply these duties by number of purposes (with dates when they expire), business activities, and new initiatives
  • Factor in business units engaged in all or parts of these activities
  • Add software systems that deliver the content and analysis
  • And finally, consider categories of data subjects, categories of processing, post-processing retention requirements, subprocessors, and relevant contact people.

Companies need to document all of these and be able to show  evidence to the regulator. In other words, the governance expectations of data controllers and data processors is significant. And this is really why companies have been given two years to implement GDPR—because to demonstrate compliance with the regulation (and avoid the eye-watering fines), an organisation must show ongoing and systematic accountability, good governance, and sustainable procedures to the regulator.

Learn more

Follow this link for more information on control monitoring and risk management.

This article, GRC Tuesdays: GDPR Is about More Than Data Management, It’s about Governance, originally appeared on the SAP BusinessObjects Analytics blog and is republished by permission.

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Neil Patrick

About Neil Patrick

Dr. Neil Patrick is a Director of SAP Centre of Excellence for GRC & Security covering EMEA. He has over 12 years’ experience in Governance, Risk Management and Compliance (GRC) & Security fields. During this time he has been a managing consultant, run professional services delivery teams in the UK and USA, conducted customer business requirements sessions around the world, and sales and business development initiatives. Neil has presented core GRC and Security thought leadership sessions in strategic customer-facing engagements, conferences and briefing sessions.

CFO 2018: Finance And The Move To Outcome-Based Business Models

Tony Klimas

Part 1 in the 4-part “SAP Finance and EY Talk” series by Tony Klimas of EY and Joel Bernstein of SAP

The question for so many companies in 2018 is as simple as it is daunting: How do I reinvent my business? Answers to this question will vary – but whatever the answer is, the CFO will be right in the middle of it.

I recently participated in an interview with my colleague Joel Bernstein, CFO of SAP Global Customer Operations. In that discussion, Joel talked about the impact on finance of changing business models. One prevalent change is the move toward outcome-based business models, where companies are realizing what customers want most: not so much products, but positive experiences with outcomes that deliver value.

Take SAP, for example, which has been transitioning to a cloud-based delivery model. “There’s still demand for perpetual-based licenses and software delivered on-premise in the traditional way,” Joel said. “But the real growth is coming from cloud services.”

The impact on finance

What does this mean for CFOs like Joel? It means that the finance function needs to transform itself to serve a new business model, where revenues and profits are recognized in entirely different ways.

“It’s one thing when you follow a traditional sales cycle, sign a contract, deliver code, and then recognize revenue and profit at that point in time,” Joel said. “But when you follow an outcome-based model, things are entirely different.”

With such models, finance needs to be integrated into the cloud service-delivery model at a fundamental level — because revenue and profit are often based on consumption. What’s needed here is a way of monitoring usage and calculating prices systematically, as well as ways to measure delivery performance across variables, including availability and uptime. All of this has an impact on everything from deal structuring and execution to invoicing and cash collection.

The same across industries

The move to outcome- and service-based models is common elsewhere. Take, for instance, Kaeser Kompressoren, an SAP customer. Until recently, this century-old manufacturer of industrial air compressors made and sold equipment, and made money from service contracts. Today, it provides and maintains the units for free and charges according to how much compressed air customers consume. This is tracked by IoT sensors. You can imagine the changes required in the finance role to support this new business model.

Even at EY, where I serve as global performance improvement finance leader, we’ve started to make a similar transition to what we call asset-based help services. This means that instead of selling our traditional product — hours of consulting time — we’re now looking at value-added services generated by an asset. An example might include a subscription-based risk management service or specific assets related to analytics, which would be extensions of traditional consulting work. This creates a whole host of new challenges for finance from a valuation and performance measurement perspective.

The importance of innovation

To be sure, the particular challenge your finance team and company face transitioning to new business models will differ. But a likely connecting thread across all transitions will be a need for finance to emphasize innovation.

As data flows in and out of new outcome-based business models, finance organizations are in a unique position to generate insight — which is what it’s all about in a digital economy. This is why it’s so important to instill a culture of innovation within finance. People should feel encouraged to go out, analyze the data, and innovate new solutions.

Changing the discussion

Joel’s team at SAP, for instance, has transformed the finance function to a shared services model. Today, much of SAP gets access to core finance functions, such as order-to-pay, through these shared services.

Leveraging a shared service model has allowed SAP and the finance teams to standardize best practices across end-to-end processes. Joel said this allows new acquisitions to connect much more quickly. The efficiency and scale of this new model, in other words, make growth easier for SAP. That’s strategic.

This model has also helped to transform data visibility at SAP. Now, the finance team at SAP can support the business with real-time analytics. People can gain even the insight they need themselves.

How do you know when you’ve succeeded? Joel answered this way: “The sense of success comes when the discussions begin to change.” Instead of talking about reports that finance has provided, “Now the business and finance teams are talking about new insights that the business has discovered and what we should do to take advantage.”

This, of course, only increases the pressure on finance to innovate. But in the grand scheme of things, this is a good problem to have.

To learn more about how finance leaders are taking charge of innovation, take a look at this animated infographic, and this great resource for CFOs: Agile Finance 2.0 white paper.

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.

Follow SAP Finance online: @SAPFinance (Twitter)  | LinkedIn | FacebookYouTube

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Tony Klimas

About Tony Klimas

Tony Klimas, global finance practice leader with EY, LLP, is a member of EY’s Advisory Executive team with global responsibility for the Finance consulting practice. He is an experienced consultant with 20+ years of experience across a variety of industries. His areas of expertise include finance strategy and transformation, shared services/offshoring, and BPO advisory. Tony also has significant experience with finance and accounting systems and has traveled and worked extensively in Asia, Europe, and Latin America. He spent most of his consulting career in the Southeast U.S. before moving to the greater New York City area in 2009.

Unlock The Future Of Procurement With Cognitive Computing

Tom Cassell

In many ways, a company’s procurement operations represent one of its best opportunities to drive new innovation and business value. In fact, one report found that 65% of the total value of a company’s products and services comes directly from its suppliers, which for many companies represents millions or even billions of dollars. So, making even a minor improvement in the efficiency and/or effectiveness in this area can end up driving significant financial benefits for a company.

However, recognizing this opportunity and actually taking advantage of it are two different things entirely. Most companies have already picked off the low-hanging fruit: they’ve done everything they can to extract savings from their procurement operations using traditional methods and technologies. To get to the next level of value and start driving new sources of savings, they need to take a dramatic step forward. One way to take such a step is by leveraging a transformational technology like cognitive computing.

Cognitive technologies in procurement

Procurement is a domain that is ripe for cognitive disruption: it’s both data-heavy and transaction-heavy, and as I mentioned, it typically involves large financial potential.  Cognitive computing empowers human procurement professionals to do more than they possibly could using traditional technologies alone. By helping procurement professionals find better information and insights faster, cognitive systems can enhance situational awareness, speed up the decision-making process, and ultimately drive superior procurement performance.

Although the entire source-to-pay cycle can benefit from cognitive enablers, I’d like to highlight two specific areas of this process in which we are currently using cognitive computing to drive significant value: sourcing and contracts.

Intelligent sourcing

Sourcing events can be transformed by applying cognitive capabilities to help with tasks such as:

  • Defining the correct request for proposal type
  • Identifying appropriate suppliers to participate based on commodity category, region, or industry
  • Delivering intelligence on market signals and pricing pressures

In general, these capabilities help procurement professionals bypass the time-consuming research and manual data aggregation that are typically part of the sourcing process. Instead, cognitive systems give procurement professionals the insights they need to quickly make informed decisions about price points. This allows them to drive business value and cost savings by finding the right suppliers for a specific situation, identifying the optimal price points, and then moving to the contract negotiation stage quickly.

Intelligent contracts

Cognitive computing can also help make the contract negotiation process smarter and more comprehensive. Procurement organizations can deploy cognitive-enabled applications that can automatically identify relevant terms and conditions matched to a legal library and taxonomy, identifying similar contract terms that have been used in the past. This contributes to a shorter contract negotiation cycle, which in turn represents an opportunity for cost savings and optimized resource utilization.

In addition, cognitive systems can create contracts that automatically target ideal price points, based on expected volume and contractual discounts. The end result is that procurement organizations can quickly and easily turn out comprehensive contracts for specific regions and commodities while feeling confident that those contracts include the most favorable terms and conditions possible for the business.

Learn more

SAP Ariba and IBM are working together to help make the kind of intelligent procurement described in this post a reality for our customers. Our partnership brings together the best of cognitive procurement capabilities from IBM Watson, expertise from the IBM Procurement Services team, and an extensive portfolio of industry-leading procurement solutions from SAP Ariba.

Visit us at Ariba Live, March 5-7 in Las Vegas, to explore intelligent procurement based on IBM Watson, and see a live demonstration of some of our first use cases. You can also download our white paper “The Road to Intelligent Procurement” to learn more.

Follow SAP Finance online: @SAPFinance (Twitter)  | LinkedIn | FacebookYouTube

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Tom Cassell

About Tom Cassell

Tom Cassell is an IBM Executive and the Global Leader for IBM’s Ariba Practice. He has led multiple transformation programs that improved source-to-pay capabilities by leveraging Ariba solutions He is leading IBM GBS’s Cognitive Procurement initiative, which includes the integration of Watson into Ariba. Tom has over 20 years of experience in supply chain management, with a particular focus in the planning and procurement domains.

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.