Why Finance Must Meet The Demands Of A Digital Economy

Judy Cubiss

Digital transformation is a top-of-mind issue for many executives, including finance. This was highlighted at the Davos Conference in January 2016, where digital was a key theme. During the conference, business leaders such as Pierre Nanterme, CEO of Accenture, argued that digital disruption has only just begun. Nanterme believes digital will be much more than just a commercial opportunity. He predicts that saving lives, creating jobs, and better stewardship of the environment will also be direct outcomes.

In another Davos session, Dominic Barton, global managing director of McKinsey & Company, asked “How can companies catch the digital wave?” He pointed out that disruptive new players are having a massive impact on markets, and technology is enabling disruption by lowering the cost of entry. Thack Brown, general manager and global head for SAP’s line of business finance, and Henner Schliebs, SAP VP and head of finance audience marketing, agreed. “We are at the outset of a once-in-a-generation wave of innovation and transformation,” they wrote in an SAPinsider article. “Enterprises at the forefront of the digital revolution are reimagining traditional processes and beliefs about the role of the finance organization.”

273919_h_srgb_s_gl.jpgTechnology innovation has removed barriers

So how will the digital economy impact finance organizations? Finance is the backbone of every process, yet still has a large number of manual processes.  to How will the digital economy impact finance organizations? If finance is not limited by technology, processes can be reimagined to better meet business needs. This means finance processes can be designed to meet business needs, not just accommodate what the technology allows. This could be a daily soft close, weekly or continuous planning processes, or touchless invoices.

Let’s not overlook the fact that existing processes can be automated right now. Leveraging business networks will help remove media breaks and many manual tasks. Recent McKinsey research states that in most jobs, not only finance, 30% of current tasks could be automated. Increasing the level of automation will help finance organizations focus on innovation and delivering insight. I discussed this in more detail previously in an earlier blog: 5 Strategies Being Used to Reimagine Finance.

Don’t forget the people

Yet the digital revolution is not only about technology; it also about people and skills. Bruno Berthon, managing director, Digital Strategy, Accenture Strategy, raised this point in a re/code article. He stated that it is a myth that all that is needed is greater technology investment. To realize all potential benefits, there has to be focus on the skills needed to apply the technology. This is particularly relevant in finance organizations. Finance professionals are looking to be more strategic and expand responsibilities. Business partners are asking them for more detailed analysis and insight. This requires the technology to provide real-time data, but also for them to be able to analyze, present options, and influence decisions.

273914_l_srgb_s_gl.jpgThe digital journey

All this is happening at an unprecedented rate. Cloud solutions, business networks, and platforms mean that implementations are happening faster than ever and at lower cost, and this is set to continue. However, there are many resources such as the SAP S/4HANA Finance Journey Map, which outlines how to manage finance transformation and how to drive quick time to value. Brown and Schliebs concluded in the SAPinsider article, “With more than 2,000 customers choosing SAP S/4HANA Finance, it is the fastest-growing product in SAP’s history and the platform of choice for finance organizations around the world looking to transform themselves for the digital economy.”

So it will be no surprise to hear that digital transformation will be front and center at the SAPinsider Financials 2016 and GRC 2016. Join us to discuss how finance can meet the demands of the digital economy and how you can help your company’s people, processes, and systems be ready. The co-located events will take place March 15-18 at the MGM Grand in Las Vegas.

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Judy Cubiss

About Judy Cubiss

Judy is director of content marketing for Finance at SAP. She has worked in the software industry for over 20 years in a variety of roles, including consulting, product management, solution management, and content marketing in both Europe and the United States.

How Machine Learning Helps Improve Security: Part 1

Lane Leskela

As our businesses become more digital in all dimensions, high-profile information security breaches are making the news headlines with increasing frequency. The recently announced card-hacking activity at online travel service Orbitz is just one of the latest examples. On March 20, Orbitz announced a security breach that exposed information derived from at least 880,000 customer payment cards. The breach took place between October and December 2017 involving customer transaction records dating from 2016 and 2017. Although data captured on Orbitz.com was not affected, the company advised customers using Orbitz travel services within the past two years to check their credit and debit card billing statements from this period and to contact their banks if fraudulent charges were identified.

At-risk organizations around the world are increasing their investments in cybersecurity protection. According to Gartner, worldwide cybersecurity spending will climb to US$96 billion in 2018. Unfortunately, some of this spending is not aligned with actual security threats and their known sources. Surveys continue to show that solutions such as network antivirus, malware detection, and website firewalls continue to receive the most investment, although misuse and abuse of user credentials is the most common source of data breaches.

The reasons for persistent misalignment of security breach causes and remediation solutions are not well documented. One of the reasons may be the proliferation of specific security tools in IT departments over a fair number of years. The fact remains that human (mis)behavior confounds, supersedes, or works around many of the go-to security technology “fixes.”

With regard to this gap, a number of interesting findings were revealed in a recently released Dow Jones Customer Intelligence study (learn more in “CEO Disconnect on Cybersecurity Increases Risk of Breaches”). Among other revelations, this study found that:

  • 55% of responding CEOs admit their organizations have experienced at least one breach, while 79% of CTOs acknowledge breaches have occurred. One in four CEOs (24%) was not aware whether their companies have had even a single security breach.
  • 68% of responding executives whose companies experienced “significant” breaches now believe that these incidents could have been prevented by more mature identity and access management strategies.

One of the most valuable findings from this study was that CEOs can reduce the risk of a security breach by improving their identity and access management capabilities. Nevertheless, 62% of the responding CEOs said they believe that “multi-factor authentication” is difficult to manage. Thus, a related primary concern of these CEOs is how to avoid delivering poor user experiences with an increase in user security controls.

In the context of this general misunderstanding, machine learning approaches can help strengthen the foundation of authentication and screening techniques to improve security effectiveness without complicating user experiences.

Role of machine learning in preventing major security issues

Machine learning tools can help resolve an ongoing dilemma faced by many organizations. The problem is, we spend millions of dollars each year to strengthen information security, yet experience major breaches that threaten our stability and ability to grow. Thus, we continue to look for better answers.

It turns out there are many ways machine learning can be used to help improve enterprise security. With identity authentication and password authorization being primary points of attack, there are several ways machine learning can be leveraged to help minimize data breach incidents.

In Part 2 of this series, we’ll examine some key examples of machine learning applied to user access authorizations that improve information security. In addition, we’ll highlight some related areas in which machine-learning security capabilities are being embedded today.

The SAP GRC team will be exhibiting at several events related to cybersecurity this year. We hope you’ll join us there.

Learn more about the full range of SAP security offerings, and please continue to read all of the blogs in our GRC series.

This article originally appeared on the SAP Analytics blog and is republished by permission.

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

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Lane Leskela

About Lane Leskela

Lane Leskela, global business development director, Finance and Risk, for SAP, is an accomplished enterprise software leader with years of experience in customer advisory, marketing, market research, and business development. He is an expert in risk and compliance management software functions, solution road maps, implementation strategy, and channel partner management.

Four Ways To Improve Cash Application With Machine Learning

Gina McNamara

As CFOs operating in the digital age, we must apply new technology to improve old processes. Here in the financial offices of SAP, our shared services team in Singapore has been improving our processes through machine learning. This technology teaches accounting programs how to perform tasks without being programmed, using sophisticated algorithms to learn by analyzing enormous amounts of data.

One process we’ve improved with machine learning is cash application. Traditionally, accountants receivable teams would spend hours analyzing data to resolve discrepancies in digital payments. Our shared services team overcame this problem by applying machine learning to the task. Specifically, we developed and implemented cash application across our accounts receivable department.

In doing so, we discovered four key ways machine learning can improve the cash application process.

Reduce sales outstanding with accountant behavior analysis

Machine learning software can study the behavior of accountants and apply it to future payments. At the same time, it can improve arduous processes by analyzing areas of improvement. This can reduce your day’s sales outstanding, saving CFOs the pressure of a prolonged DSO.

In addition, AI’s ability to improve itself saves the time it would otherwise take to optimize processes.

Use automation to save human skills for more important aspects of the process

A question that I am asked over and over is: What will accountants do when they are replaced by machines? Accountants are highly skilled in many aspects of a business and often get buried by manual processes. Automation gives our teams the chance to become more integrated into our business, acting as a transformation agent to drive better business outcomes by enabling more time to partner and utilize the information that is analyzed.

I’ve referenced millennials in previous blogs. They have grown up with technology and are eager to bring their ideas to the table. Millennials are very hard to retain when you bring them into old/traditional environments.

Eliminate reprogramming for changes to the process

As the way we pay for goods and services evolves, so too should our cash application process. Machine learning is the most effective way to manage this evolution. To explore this, let’s use the evolution of digital payments as an example.

New forms of digital payment are being established at a dizzying rate. To retain customers, your company must keep up with each of them. Ordinarily, this would require extensive reprogramming of your accounts receivable system. Thankfully, machine learning programs can recognize new forms of payment and adjust their clearing accordingly.

Enhance decision-making with AI-driven insights

While it’s important to embrace risk as a CFO, it’s our responsibility to reduce it. To that end, imagine if you could simulate new clearing models without costly trials. Imagine if you could know for certain if suspicious invoicing was a sign of fraud.

Machine-learning programs can give your team access to advantageous insights by analyzing patterns and running predictive simulations. Instead of worrying about “what-ifs,” your team can work with confidence in their AI-driven insights.

Machine learning is one of the most effective ways to manage your cash application process. Explore SAP Cash Application today to accelerate this arduous accounts receivable process.

Join us at SAPPHIRE NOW

To learn more about this and many other finance topics, please join us at SAPPHIRE NOW June 5-7 in Orlando, Florida. These two sessions are especially relevant:

Explore How Machine Learning Is Changing the Life of a CFO

Turbocharge Lockbox Processing with Machine Learning-Based Cash Application

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

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Gina McNamara

About Gina McNamara

Gina McNamara is the CFO for SAP Australia and New Zealand, leading a team of approximately 40 staff across core finance, legal and contracts, facilities, purchasing, and information technology. She has been with SAP since May 2007. Before taking on the CFO position, Gina worked in Commercial Finance Business Support for SAP Australia and New Zealand, where she supported sales and consulting teams with revenue recognition and deal support. Gina is a strong advocate for demonstrating how SAP runs SAP and technology to improve operations for the office of the CFO, particularly around moving from an on-premise environment to the cloud.

The Blockchain Solution

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

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

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

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

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

The Spine of Digitalization

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

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

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

What Is Blockchain and How Does It Work?

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

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

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

Why does blockchain matter for the supply chain?

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

Hints of the Future

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

But we could tell that it had vast potential.

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

What’s the Magic Combination?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Blockchain Is the Change Driver

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

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

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

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

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

Challenges on the Path to Adoption

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

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

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

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

Blockchain Blackouts

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

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

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

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

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

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

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

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

Customers Will Expect Change

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

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

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

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


About the Authors

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

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

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

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

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

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

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CEO Priorities And Challenges In The Digital World

Dr. Chakib Bouhdary

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Download this short executive document. 

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Dr. Chakib Bouhdary

About Dr. Chakib Bouhdary

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