Three Misconceptions About Advanced Analytics

Henner Schliebs

As the role of the finance function continues to become more complex, proactive CFOs are recognizing that obtaining a real-time view of all business operations is no longer “nice to have,” but imperative. Gone are the days of living and dying by the spreadsheet and waiting for monthly or even yearly figures to make financial projections and operational course corrections.

To act as a strategic business partner within the C-suite, finance needs advanced, robust data and analytics capabilities. In fact, a recent survey by Oxford Economics found that having a strong influence beyond the finance function and improving efficiency with automation were paramount in boosting performance. When using the right tools, finance executives can measure overall performance, shape strategy, and look for opportunities to grow.

While the importance of data intelligence is felt, many CFOs and finance teams still hold common misconceptions about what advanced analytics really is. When speaking with customers and CFOs, there are three misconceptions that seem to be most prominent:

  1. Advanced analytics is expensive
  2. Advanced analytics takes a long time to deploy
  3. Advanced analytics is complex

Misconception 1: Advanced analytics is expensive

Most business are sitting on a gold mine of data but have yet to uncover its transformative value. This is because many financial leaders think investing in analytics is too costly. Advanced analytics however, does not have to be expensive. Finance teams just beginning their digital transformation journey have a ton of reliable, inexpensive, and free options available. Modern ERP platforms can connect freely to statistical libraries, so finance executives do not have to “reinvent the wheel.” The best solutions provide the functionality needed to embed advanced analytics on raw data levels, which improves accuracy of the models used to predict revenue forecasts and profitability of customers/products.

Once implemented, the benefits quickly outweigh the initial costs, as advanced technologies can replace timely tasks to optimize time, value, and money by standardizing some aspects of financial reporting. Cash forecasting is one such example – leveraging insights to look at trends to identify slow and fast payers and address and improve receivables management. With less time spent reviewing spreadsheets and more time spent leveraging insights, finance teams can become more cost effective. Also, this is the base for an effective and efficient use of machine learning technologies to drive performance.

Misconception 2: Advanced analytics takes a long time to deploy

For most analytics tools, implementation is typically quite fast – a matter of weeks, in most cases, regardless of the existing IT infrastructure. Once deployed correctly – on a transactional level within ERP and not as a separate data mart on higher levels – the benefits are rapidly evident:

  • Advanced analytics can group customers and products to see what makes them profitable and define what drives their growth. With this, finance can analyze and identify outliers.
  • Predictive analytics can help finance professionals forecast mid-period to avoid surprising events, which is especially crucial amid today’s global economic volatility.
  • Advanced analytics can optimize receivables processes and collect overdue amounts faster by setting alerts when customers deviate from past payment patterns.

Misconception 3: Advanced analytics are complex

While the backend technology that powers advanced analytics is sophisticated, complexity in use would defeat its purpose. The goal is to put data at a CFO’s and controller’s fingertips and make assessing information easier than ever.

Technology companies want to ensure that their customers get the most out of their technology investments, which is why they build dedicated teams responsible for preparing, developing, and deploying solutions in close collaboration with the customers’ finance teams. These teams, typically composed of finance experts, technology experts, and data scientists, help each customer streamline the process of solution deployment and user adoption. They are available to teach executives how to use the new solution and to answer questions as they arise. Deployment teams take the complexity out of the technology to ensure that their customers are optimizing its value.

The biggest benefit of advanced analytics is that CFOs no longer have to live and die by the spreadsheet. Truly successful CFOs are embracing their position as strategic thinkers and understand that insights and foresights needed for making high-level decisions cannot be realized without advanced analytics. It’s time finance leaders move beyond traditional misconceptions. Armed with previously untapped insights, the CFO can provide unmatched strategy and insight to support informed business decisions, and ultimately help sustain and grow the company.

This article originally appeared in FEI Daily and is republished by permission.

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

Comments

About Henner Schliebs

Henner Schliebs is global vice president Audience Marketing for SAP S/4HANA and Finance at SAP. He is a progressive sales/marketing executive with 15+ years of experience in business software solutions focused on corporate functions. He has strong marketing and go-to-market skills and a proven track record in enterprise software solutions, along with significant experience in solution management and customer engagement.

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

Comments

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.

Think Bigger: Two Strategic Wins For Implementing Continuous Accounting

Elizabeth Milne

Part 4 in the “Continuous Accounting Action Plan” series

Welcome to the fourth post in our series on how to reinvigorate your finance and accounting processes to make them more responsive, agile, efficient, and trusted.

We kicked off the series introducing the concept of continuous accounting. In a nutshell, it’s taking activities like the financial close and providing better access to real-time data by applying more automation. The goal is to free up accounting teams to focus on the quality of the process, rather than repetitive, mundane manual tasks. Teams can now spend more time partnering with the business instead of being crunched at month’s end. The same applies to FP&A, moving from infrequent forecasting, which often becomes an academic process, to rolling, continuous forecasts that improve accuracy.

In the previous blog, we tackled three examples of quick wins because, like any initiative, it’s important to get some rapid successes under your belt and show value back to the business. Now we’re going to focus on some examples around larger-scale wins, specifically within the corporate and entity close. Here again, your specific big wins might be different. These are examples; depending on your organization, big and small will vary. Intercompany, for example, may be a huge issue at a company with large volumes of intercompany transactions; here, automating and improving the process could be a big win. On the flip side, if your company has fewer intercompany transactions, automating that process may be a quick win. The important takeaway is that you plan your journey in steps and discrete chunks of increasing value.

In the last blog, we defined a “quick win.” But what makes a win a “big win”?

  1. It delivers significant improvements in strategic areas like financial and accounting efficiency, reduces risk and exposure, or measurably enables the business to better meet its strategic goals. Since the initiative is larger-scale, the timeline in which it should deliver value to the organization would be significantly longer than a “quick win.”
  2. The initiative, while complementary, may replace existing investments.
  3. While finance and accounting should own the initiative and manage the new process, it may initially require support from IT or DevOps, to create a deeper integration with the finance application landscape.

With that, let’s start with some examples.

Renovating your financial consolidation processes

Financial consolidation is the nexus of complexity and risk in the financial close process. This is because when there are numerous entities, ERPs, local accounting rules, currencies, and people in play, there’s often substantial room for error. A survey by EY of 1,000 CFOs and heads of reporting of large organizations found that one in five has 20 or more reporting systems. And about two-thirds (63%) said that they’re seeing a rise in the number of reporting standards.

So how can you know if your financial consolidation process needs an upgrade? We talked about the importance of benchmarking earlier, and it turns out that the top 20% of organizations in terms of financial close maturity spend about a day to complete their consolidation process. The least mature 20% spend about three days, with an additional day quarterly, and six days more for annual reporting. In terms of risk, a study by Audit Analytics found that nearly 20% of restatements over a 15-year period were due to areas related to financial consolidation, including acquisitions, mergers, disposals, re-org accounting, foreign party-related transactions, subsidiaries, intercompany accounting, and overall consolidation.

So, we’ve established that financial consolidation meets the benefits-improvement criteria around a strategic win. But what does a project look like?

The objective of any consolidation initiative should improve how the organization can meet different financial reporting requirements; automate the consolidation process across GLs, currencies, and entities; and improve audit trials. It should also shift tasks like intercompany eliminations, minority interest, and currency translations away from spreadsheets.

From a continuous accounting perspective, financial consolidation renovation can also play a significant role in providing information to the business faster. Moving to a virtual close, and performing more consolidation tasks in real time, can provide a consolidated perspective of the business at any point in the period. If consolidations and planning are brought together into a single application, it provides the perfect vehicle to drive rolling forecasts for real-time consolidated results.

Options include renovating your current process and/or technology or perhaps replacing it altogether. In terms of integration, because a corporate financial consolidation system can touch multiple ERPs in the financial landscape, the project should include attention to data governance, integration, and master data management.

Financial close task orchestration

Within the financial close, another significant area of opportunity is ensuring stronger collaboration, sequencing, approvals, and level of detail in the close processes. If your organization uses a spreadsheet-based task list to manage the timing and sequencing of things like journal entries, accruals, intercompany reconciliations, or gathering data from different apps for consolidation and/or validation, then you’re not alone. While task management can improve speed, for example, a recent Wall Street Journal article cited PwC research finding that the top quartile of closers using technology was able to close the books in 3.5 days, while the bottom quartile, who often were more spreadsheet-centric, took 7.5 days or more. Think of it this way: the best closers require less than half the resources versus the bottom-quartile to close the books.

But task orchestration isn’t just about speed and resources. It’s about ensuring that everything is complete and approved at the right level of detail in the closing checklist to reduce financial reporting and regulatory risk. In fact, a recent survey by FSN found that the reporting process is what keeps most CFOs awake at night. An unmanaged process creates both risk and stress. The problem is that a close checklist at a high level is likely to leave too much of the close process to chance, while too much detail can overwhelm accounting teams, causing accounting to get even more bogged down.

Financial close task orchestration enables “detail at scale”; that is, ensuring that everything is checked off on the checklist, while effectively acting as a traffic cop. A central collaborative environment manages what needs to be done, who needs to do it, what the blocking tasks are, and even going as far as kicking off tasks that can be handled without human intervention. The goal is to improve collaboration and monitoring across the entire entity closing cycle for all companies within the group. This approach also helps accounting teams collaborate more effectively, know what to work on next, report their status, and ensure that they perform their work on time and in the proper sequence, resulting in fewer errors and delays. Task management is essential to move to continuous accounting, where close tasks don’t all occur at the end of the period; they occur throughout, which makes tracking what can occur “now” versus period-end, particularly important.

Getting a task management and orchestration project rolling means working to understand what your entity checklist should ideally look like, understanding what approval processes should look like for the various close tasks, knowing which ones can be scheduled robotically, and training the team to move towards checking off tasks using an application rather than using emails or verbal sign-offs. Done right, the results can yield significant efficiency and risk benefits.

In our next post, we’ll jump into controls, and how to use continuous accounting to reduce exposure.

Ready to deploy continuous accounting? Click the button in the banner on the top right to learn more.

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

Comments

Elizabeth Milne

About Elizabeth Milne

Elizabeth Milne has over 20 years of experience improving the software solutions for multi-national, multi-billion dollar organizations. Her finance career began working at Walt Disney, then Warner Bros. in the areas of financial consolidation, budgeting, and financial reporting. She subsequently moved to the software industry and has held positions including implementation consultant and manager, account executive, pre-sales consultant, solution management team at SAP, Business Objects and Cartesis. She graduated with an Executive MBA from Northwestern University’s Kellogg Graduate School of Management. In 2014 she published her first book “Accelerated Financial Closing with SAP.” She currently manages the accounting and financial close portfolio for SAP Product Marketing. You can follow her on twitter @ElizabethEMilne

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.

Comments

Tags:

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.

Comments

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.