Enter The Digital Consumer, Driver, Services Buyer

William Newman

In working with several large automotive customers, it becomes clear that what it means to become digital – and to run a digital business – can take on many forms and meanings to different companies, depending on their organization and their position in the automotive value chain.

I have written about the advent of connected platforms, whereby suppliers are moving to land-grab specific elements of the ecosystem and lay claim to their use. This includes many scenarios about the enhancement and transmission of information from the individual consumer to the car, the home, the household appliance, or the mobile device. McKinsey estimates the market for vehicle-enabled digital services to grow to $1.5 trillion by the year 2030.

Understanding how the automotive consumer will function as a services buyer, however, is an entirely different matter, whether that individual is a personal vehicle owner, rideshare passenger, renter, or simply a passenger in a friend’s car on a night out. And while automakers are determining how to enable that customer experience, one thing is clear: the automotive consumer wants the same, easy-to-use experience to carry with them from one vehicle to the next, regardless of their role or how they’re using the vehicle.

What do I mean by this? Digitally connected customers should be able to move seamlessly across vehicles with their secured personal identity and profile available for the use and purchase of services. Vehicles would provide the most driver-desired customer experiences based on real-time feedback to engineering designers, significantly reducing warranty claims and updating software during non-use windows. It shouldn’t matter if I’m a passenger in a rideshare or renting a luxury vehicle for the weekend in the big city, my wallet and profile should move with me based on personal credentials, personal preferences (for entertainment, services, etc.), and secure onboard data connectivity.

Consistent profile and digital services, vehicle-to-vehicle comparison

Vehicles should be maintained with similar consistency. Soft service events – uploading software updates or even tuning firmware – would occur in off-peak times or as needed based on severity. Hard service events would occur at low-use hours to reduce labor and operating expense while maximizing vehicle availability during peak times. Parts would be available as needed, located on the quickest route to service locations.

Automakers are learning more about the advanced options to support driver, buyer, and passenger connectivity, as well as what abilities secure data environments in automobiles can deliver.

Learn more about trends in autonomous and connected vehicles at SAPPHIRE NOW in Orlando, Florida (May 15-19). Secure your spot today!

This article originally appeared on Linkedin Pulse

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William Newman

About William Newman

William Newman is a Strategic Industry Advisor, providing industry perspective, strategic solution advice, and thought leadership to support SAP automotive and discrete industry customers and their co-innovation programs. He helps build and maintain SAP's leadership position in the automotive industry and associated industry segments. He manages SAP’s annual digital aftermarket survey program and serves as the ASUG Point of Contact for the NA Automotive SIG. He is the author of two SAP Press books and a LinkedIn Editor’s Choice contributor.

New Automotive DNA: How IoT Is Transforming The Automotive Industry

Uli Muench

Digital technology is transforming virtually every aspect of what it means to be an automotive manufacturer, OEM, or supplier. From autonomous cars to electric vehicles, the automotive industry is crossing the threshold of reinvention. This new automotive DNA is a paradigm shift for the industry, moving it away from the internal combustion engine, petroleum, and mechanical linkages and toward fuel cells, batteries, hydrogen, electricity, and electronic systems and controls. The use of new electronic-based architectures, systems, and software in vehicles creates new design challenges and opportunities.

At the same time, consumer-use models for vehicles are also evolving. For example, connected vehicles are creating new urban mobility opportunities such as vehicle sharing and usage-based insurance (UBI). Connected cars are generating massive amounts of data that can be monetized in other ways. The Internet of Things (IoT) is the powerhouse behind all the transformations.

This makes the automotive industry an especially compelling use case for how IoT is transforming discrete manufacturing to meet new market demands while continuing to achieve traditional business objectives. IoT is most impactful on four key value drivers in the automotive industry: design and ideation, service enablement, resilient lean, and product lifecycle revenue.

Design ideation

IoT makes it easier to manage the product lifecycle by accelerating product and engineering timelines. This results in a faster time-to-market and improved customer/product satisfaction. IoT helps reduce manufacturing costs by identifying non-value driving components and removing these components from future vehicles. Future design ideation opportunities include applying machine learning to past product performance information and using this information to augment the design and ideation process.

Service enablement

Today’s vehicles have at least 10 million lines of mission-critical software code, creating an enormous need for ongoing code management and service. Streamlined service enablement is the most common scenario for IoT in the automotive after-market. IoT is improving customer satisfaction via aftermarket quality assurance and upgrades, while also increasing revenue from aftermarket services.

Connected technology is making it easier for manufacturers not only to track product defects and maintenance needs, but also to communicate proactively with consumers about these service updates and notifications. Thanks to IoT, manufacturers have the luxury of pushing out software updates or even software upgrade offers. This is revolutionary as manufacturers seldom have any relationship with the end user.

Resilient lean

Process automation via IoT data and analytics is one of the top priority improvements for manufacturers. Factors pushing auto manufacturers to adopt a resilient lean manufacturing approach include shorter time-to-market cycles, rapidly changing demand, highly complex products, and processes, and increasing material considerations around light-weighting and 3D printing. IoT is enabling this adoption with real-time scheduling to meet changing demand and more efficient, flexible manufacturing processes—including material optimization.

Platform revenue

A virtual treasure trove of data including information on consumption patterns and preferences, demographics, and location usage is produced every moment a car operates. Manufacturers are turning to IoT and advanced analytics to gain insights from this data and create new revenue-generating opportunities. Key opportunities include increasing aftermarket revenue via upgrade and content monetization, and improving overall customer satisfaction through experience enhancements. Companies can leverage usage and engagement information to send content, such as paid software upgrades and infotainment, to the consumer.

Next steps: Selecting an IoT partner

As the new automotive DNA transformation demonstrates, today’s competitive market demands that manufacturers offer integrated products, services, and business models that enhance the customer experience. At the same time, manufacturers must also stay focused on traditional objectives including increasing uptime and throughput in the plant and closely managing operational costs.

Whether a scenario can be implemented today or on your roadmap for the near future, your business must get the right technology and IT infrastructure in place or risk being outperformed by the competition. When selecting the right IoT partner, your business should consider the following: integration, scale, ecosystem, and trust. Your IoT solution should allow you to integrate business systems, digital platforms, and industry clouds—ideally providing a common foundation for all three. IoT partner should be able to scale digital activities as your business grows and offer your company access to a robust third-party developer community to meet your evolving needs. Finally, your partner of choice should be willing to co-innovate.

The digital transformation in the automotive industry and across the entire manufacturing sector is well underway. Time is of the essence. Your company must act now to realize the tremendous value and competitive advantage offered by IoT, including new business models and new customer relationships.

Learn how to bring new technologies and services together to power digital transformation: download The IoT Imperative for Discrete Manufacturers: Automotive, Aerospace and Defense, High Tech, and Industrial Machinery. Explore how to bring Industry 4.0 insights into your business today: read Industry 4.0: What’s Next?

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Uli Muench

About Uli Muench

Uli Muench is Global Vice President of the Automotive Industry Business Unit at SAP.

How To Improve Manufacturing Productivity With Predictive Analytics

Mukund Rao

When you’re in manufacturing, time is money. Factors that cause your production process to go offline cost profitability. But how do you optimize uptime without risking machine breakdowns or malfunctions? One way to get around the problem is through predictive analytics. Used for a wide range of purposes, the applications for this type of technology are exceptional for improving production and even product design. But how important is it to improving profitability? Today’s IoT industrial sector is worth $11 trillion. Using predictive analytics is estimated to save manufacturers $630 billion by 2031. Here’s an overview of how adding this capability improves uptime and profitability.

There are two areas where auto manufacturers can improve their company using predictive analytics. The first involves adding predictive analytics to the production line itself, limiting downtime and improving output and profitability. The second involves using analytics to improve the products themselves, improving price support and customer satisfaction. Let’s take a quick look at both options.

Improve production line productivity

When an automotive company purchases industrial machinery, that machinery will be in service for a long time. In fact, the industry average is over two decades. Over that time period, there’s a lot of opportunity for something to go wrong. When the production line stops, profitability goes down. In the past, a manufacturer had very few options to ensure reliability. It could choose a brand with a reputation for excellent reliability and hope for the best. Otherwise, it could stick to a tight maintenance schedule that may not provide optimum line uptime and productivity.

Fortunately, there’s a better way to go about production line maintenance today. Predictive analytics uses a combination of IoT, cloud, and analytic technology to monitor machine conditions. When certain conditions match up to part or machine failures, the analytics use that data to predict future failures. That way, when a particular condition precedes a larger failure, the manufacturer can make a small repair with minimal downtime for the assembly line. This technology can be included in new machinery or retrofitted into existing machinery. By doing so, you can see an immediate improvement in unexpected downtime.

But what about regularly required maintenance? If your factory’s conditions are optimal to allow the machinery to last longer between servicing, you can lessen the amount of downtime required. But when is the best time to undertake this maintenance? What if you could use regular shifts in demand to your advantage? If you need to perform extensive maintenance, scheduling it during a downtime is a great way to avoid production delays. Predictive analytics can look at past purchasing behavior and find the best times for scheduling this type of maintenance.

Provide better quality control

But manufacturing line uptime isn’t the only area where predictive analytics can improve your bottom line. Many businesses have begun using this technology to improve their product’s quality control. In addition, these same analytic systems can be used to develop service recommendations for customers. This allows the best possible blend of reliability and post-sale revenue streams. At the same time, it provides an opportunity to improve the company’s reputation.

In today’s industry, the time from product development to market has drastically accelerated. This means that the time spent in product development and quality testing is minimized. By adding predictive analytics to the process, high quality and accelerated production can go hand in hand. Flaws in design can be quickly weeded out and changes to specs made to ensure better quality in the finished product. In addition, sensors in the production machinery allow for better monitoring of material quality, freeing up the staff to only focus on exception handling of out-of-spec problems.

When it comes to cars, few brands are as recognized for luxury as Mercedes-Benz. Known for its well-engineered, hand-built engines, the German manufacturer decided to add predictive analytics to its production in 2013. The company recognized it had an opportunity to add predictive analytics capabilities to its engine testing process. This allows the engines to be tested more quickly, speeding up production. At the same time, it still provides more in-depth insights than prior testing had delivered.

Following the success of this project, Mercedes-Benz and other manufacturers have begun to explore the additional opportunities available through predictive analytics. Among options that are being considered is to broaden the engine development process and analytics to improve collaboration across projects. It also provides better business transparency. With the increasing number of options and models being made available, predictive analytics helps manufacturers determine optimal combinations and potential interactions before production begins.

By adding predictive analytic capabilities to your production line, you can improve uptime, output, and profitability. But how do you go about putting this capability in place in a way that works for your company?

Learn how to bring new technologies and services together to power digital transformation: download The IoT Imperative for Discrete Manufacturers: Automotive, Aerospace and Defense, High Tech, and Industrial Machinery. Explore how to bring Industry 4.0 insights into your business today: read Industry 4.0: What’s Next?

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Mukund Rao

About Mukund Rao

Mukund Rao is Director of the Automotive Business Unit at SAP. He has been a key contributor to the business unit for over 18 years, focusing on both OEMs and suppliers. Mukund earned his MBA from University of Michigan and M.S. degree in Mechanical Engineering from Oklahoma State University.

Hack the CIO

By Thomas Saueressig, Timo Elliott, Sam Yen, and Bennett Voyles

For nerds, the weeks right before finals are a Cinderella moment. Suddenly they’re stars. Pocket protectors are fashionable; people find their jokes a whole lot funnier; Dungeons & Dragons sounds cool.

Many CIOs are enjoying this kind of moment now, as companies everywhere face the business equivalent of a final exam for a vital class they have managed to mostly avoid so far: digital transformation.

But as always, there is a limit to nerdy magic. No matter how helpful CIOs try to be, their classmates still won’t pass if they don’t learn the material. With IT increasingly central to every business—from the customer experience to the offering to the business model itself—we all need to start thinking like CIOs.

Pass the digital transformation exam, and you probably have a bright future ahead. A recent SAP-Oxford Economics study of 3,100 organizations in a variety of industries across 17 countries found that the companies that have taken the lead in digital transformation earn higher profits and revenues and have more competitive differentiation than their peers. They also expect 23% more revenue growth from their digital initiatives over the next two years—an estimate 2.5 to 4 times larger than the average company’s.

But the market is grading on a steep curve: this same SAP-Oxford study found that only 3% have completed some degree of digital transformation across their organization. Other surveys also suggest that most companies won’t be graduating anytime soon: in one recent survey of 450 heads of digital transformation for enterprises in the United States, United Kingdom, France, and Germany by technology company Couchbase, 90% agreed that most digital projects fail to meet expectations and deliver only incremental improvements. Worse: over half (54%) believe that organizations that don’t succeed with their transformation project will fail or be absorbed by a savvier competitor within four years.

Companies that are making the grade understand that unlike earlier technical advances, digital transformation doesn’t just support the business, it’s the future of the business. That’s why 60% of digital leading companies have entrusted the leadership of their transformation to their CIO, and that’s why experts say businesspeople must do more than have a vague understanding of the technology. They must also master a way of thinking and looking at business challenges that is unfamiliar to most people outside the IT department.

In other words, if you don’t think like a CIO yet, now is a very good time to learn.

However, given that you probably don’t have a spare 15 years to learn what your CIO knows, we asked the experts what makes CIO thinking distinctive. Here are the top eight mind hacks.

1. Think in Systems

A lot of businesspeople are used to seeing their organization as a series of loosely joined silos. But in the world of digital business, everything is part of a larger system.

CIOs have known for a long time that smart processes win. Whether they were installing enterprise resource planning systems or working with the business to imagine the customer’s journey, they always had to think in holistic ways that crossed traditional departmental, functional, and operational boundaries.

Unlike other business leaders, CIOs spend their careers looking across systems. Why did our supply chain go down? How can we support this new business initiative beyond a single department or function? Now supported by end-to-end process methodologies such as design thinking, good CIOs have developed a way of looking at the company that can lead to radical simplifications that can reduce cost and improve performance at the same time.

They are also used to thinking beyond temporal boundaries. “This idea that the power of technology doubles every two years means that as you’re planning ahead you can’t think in terms of a linear process, you have to think in terms of huge jumps,” says Jay Ferro, CIO of TransPerfect, a New York–based global translation firm.

No wonder the SAP-Oxford transformation study found that one of the values transformational leaders shared was a tendency to look beyond silos and view the digital transformation as a company-wide initiative.

This will come in handy because in digital transformation, not only do business processes evolve but the company’s entire value proposition changes, says Jeanne Ross, principal research scientist at the Center for Information Systems Research at the Massachusetts Institute of Technology (MIT). “It either already has or it’s going to, because digital technologies make things possible that weren’t possible before,” she explains.

2. Work in Diverse Teams

When it comes to large projects, CIOs have always needed input from a diverse collection of businesspeople to be successful. The best have developed ways to convince and cajole reluctant participants to come to the table. They seek out technology enthusiasts in the business and those who are respected by their peers to help build passion and commitment among the halfhearted.

Digital transformation amps up the urgency for building diverse teams even further. “A small, focused group simply won’t have the same breadth of perspective as a team that includes a salesperson and a service person and a development person, as well as an IT person,” says Ross.

At Lenovo, the global technology giant, many of these cross-functional teams become so used to working together that it’s hard to tell where each member originally belonged: “You can’t tell who is business or IT; you can’t tell who is product, IT, or design,” says the company’s CIO, Arthur Hu.

One interesting corollary of this trend toward broader teamwork is that talent is a priority among digital leaders: they spend more on training their employees and partners than ordinary companies, as well as on hiring the people they need, according to the SAP-Oxford Economics survey. They’re also already being rewarded for their faith in their teams: 71% of leaders say that their successful digital transformation has made it easier for them to attract and retain talent, and 64% say that their employees are now more engaged than they were before the transformation.

3. Become a Consultant

Good CIOs have long needed to be internal consultants to the business. Ever since technology moved out of the glasshouse and onto employees’ desks, CIOs have not only needed a deep understanding of the goals of a given project but also to make sure that the project didn’t stray from those goals, even after the businesspeople who had ordered the project went back to their day jobs. “Businesspeople didn’t really need to get into the details of what IT was really doing,” recalls Ferro. “They just had a set of demands and said, ‘Hey, IT, go do that.’”

Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants.

But that was then. Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants. “If you’re building a house, you don’t just disappear for six months and come back and go, ‘Oh, it looks pretty good,’” says Ferro. “You’re on that work site constantly and all of a sudden you’re looking at something, going, ‘Well, that looked really good on the blueprint, not sure it makes sense in reality. Let’s move that over six feet.’ Or, ‘I don’t know if I like that anymore.’ It’s really not much different in application development or for IT or technical projects, where on paper it looked really good and three weeks in, in that second sprint, you’re going, ‘Oh, now that I look at it, that’s really stupid.’”

4. Learn Horizontal Leadership

CIOs have always needed the ability to educate and influence other leaders that they don’t directly control. For major IT projects to be successful, they need other leaders to contribute budget, time, and resources from multiple areas of the business.

It’s a kind of horizontal leadership that will become critical for businesspeople to acquire in digital transformation. “The leadership role becomes one much more of coaching others across the organization—encouraging people to be creative, making sure everybody knows how to use data well,” Ross says.

In this team-based environment, having all the answers becomes less important. “It used to be that the best business executives and leaders had the best answers. Today that is no longer the case,” observes Gary Cokins, a technology consultant who focuses on analytics-based performance management. “Increasingly, it’s the executives and leaders who ask the best questions. There is too much volatility and uncertainty for them to rely on their intuition or past experiences.”

Many experts expect this trend to continue as the confluence of automation and data keeps chipping away at the organizational pyramid. “Hierarchical, command-and-control leadership will become obsolete,” says Edward Hess, professor of business administration and Batten executive-in-residence at the Darden School of Business at the University of Virginia. “Flatter, distributive leadership via teams will become the dominant structure.”

5. Understand Process Design

When business processes were simpler, IT could analyze the process and improve it without input from the business. But today many processes are triggered on the fly by the customer, making a seamless customer experience more difficult to build without the benefit of a larger, multifunctional team. In a highly digitalized organization like Amazon, which releases thousands of new software programs each year, IT can no longer do it all.

While businesspeople aren’t expected to start coding, their involvement in process design is crucial. One of the techniques that many organizations have adopted to help IT and businesspeople visualize business processes together is design thinking (for more on design thinking techniques, see “A Cult of Creation“).

Customers aren’t the only ones who benefit from better processes. Among the 100 companies the SAP-Oxford Economics researchers have identified as digital leaders, two-thirds say that they are making their employees’ lives easier by eliminating process roadblocks that interfere with their ability to do their jobs. Ninety percent of leaders surveyed expect to see value from these projects in the next two years alone.

6. Learn to Keep Learning

The ability to learn and keep learning has been a part of IT from the start. Since the first mainframes in the 1950s, technologists have understood that they need to keep reinventing themselves and their skills to adapt to the changes around them.

Now that’s starting to become part of other job descriptions too. Many companies are investing in teaching their employees new digital skills. One South American auto products company, for example, has created a custom-education institute that trained 20,000 employees and partner-employees in 2016. In addition to training current staff, many leading digital companies are also hiring new employees and creating new roles, such as a chief robotics officer, to support their digital transformation efforts.

Nicolas van Zeebroeck, professor of information systems and digital business innovation at the Solvay Brussels School of Economics and Management at the Free University of Brussels, says that he expects the ability to learn quickly will remain crucial. “If I had to think of one critical skill,” he explains, “I would have to say it’s the ability to learn and keep learning—the ability to challenge the status quo and question what you take for granted.”

7. Fail Smarter

Traditionally, CIOs tended to be good at thinking through tests that would allow the company to experiment with new technology without risking the entire network.

This is another unfamiliar skill that smart managers are trying to pick up. “There’s a lot of trial and error in the best companies right now,” notes MIT’s Ross. But there’s a catch, she adds. “Most companies aren’t designed for trial and error—they’re trying to avoid an error,” she says.

To learn how to do it better, take your lead from IT, where many people have already learned to work in small, innovative teams that use agile development principles, advises Ross.

For example, business managers must learn how to think in terms of a minimum viable product: build a simple version of what you have in mind, test it, and if it works start building. You don’t build the whole thing at once anymore.… It’s really important to build things incrementally,” Ross says.

Flexibility and the ability to capitalize on accidental discoveries during experimentation are more important than having a concrete project plan, says Ross. At Spotify, the music service, and CarMax, the used-car retailer, change is driven not from the center but from small teams that have developed something new. “The thing you have to get comfortable with is not having the formalized plan that we would have traditionally relied on, because as soon as you insist on that, you limit your ability to keep learning,” Ross warns.

8. Understand the True Cost—and Speed—of Data

Gut instincts have never had much to do with being a CIO; now they should have less to do with being an ordinary manager as well, as data becomes more important.

As part of that calculation, businesspeople must have the ability to analyze the value of the data that they seek. “You’ll need to apply a pinch of knowledge salt to your data,” advises Solvay’s van Zeebroeck. “What really matters is the ability not just to tap into data but to see what is behind the data. Is it a fair representation? Is it impartial?”

Increasingly, businesspeople will need to do their analysis in real time, just as CIOs have always had to manage live systems and processes. Moving toward real-time reports and away from paper-based decisions increases accuracy and effectiveness—and leaves less time for long meetings and PowerPoint presentations (let us all rejoice).

Not Every CIO Is Ready

Of course, not all CIOs are ready for these changes. Just as high school has a lot of false positives—genius nerds who turn out to be merely nearsighted—so there are many CIOs who aren’t good role models for transformation.

Success as a CIO these days requires more than delivering near-perfect uptime, says Lenovo’s Hu. You need to be able to understand the business as well. Some CIOs simply don’t have all the business skills that are needed to succeed in the transformation. Others lack the internal clout: a 2016 KPMG study found that only 34% of CIOs report directly to the CEO.

This lack of a strategic perspective is holding back digital transformation at many organizations. They approach digital transformation as a cool, one-off project: we’re going to put this new mobile app in place and we’re done. But that’s not a systematic approach; it’s an island of innovation that doesn’t join up with the other islands of innovation. In the longer term, this kind of development creates more problems than it fixes.

Such organizations are not building in the capacity for change; they’re trying to get away with just doing it once rather than thinking about how they’re going to use digitalization as a means to constantly experiment and become a better company over the long term.

As a result, in some companies, the most interesting tech developments are happening despite IT, not because of it. “There’s an alarming digital divide within many companies. Marketers are developing nimble software to give customers an engaging, personalized experience, while IT departments remain focused on the legacy infrastructure. The front and back ends aren’t working together, resulting in appealing web sites and apps that don’t quite deliver,” writes George Colony, founder, chairman, and CEO of Forrester Research, in the MIT Sloan Management Review.

Thanks to cloud computing and easier development tools, many departments are developing on their own, without IT’s support. These days, anybody with a credit card can do it.

Traditionally, IT departments looked askance at these kinds of do-it-yourself shadow IT programs, but that’s changing. Ferro, for one, says that it’s better to look at those teams not as rogue groups but as people who are trying to help. “It’s less about ‘Hey, something’s escaped,’ and more about ‘No, we just actually grew our capacity and grew our ability to innovate,’” he explains.

“I don’t like the term ‘shadow IT,’” agrees Lenovo’s Hu. “I think it’s an artifact of a very traditional CIO team. If you think of it as shadow IT, you’re out of step with reality,” he says.

The reality today is that a company needs both a strong IT department and strong digital capacities outside its IT department. If the relationship is good, the CIO and IT become valuable allies in helping businesspeople add digital capabilities without disrupting or duplicating existing IT infrastructure.

If a company already has strong digital capacities, it should be able to move forward quickly, according to Ross. But many companies are still playing catch-up and aren’t even ready to begin transforming, as the SAP-Oxford Economics survey shows.

For enterprises where business and IT are unable to get their collective act together, Ross predicts that the next few years will be rough. “I think these companies ought to panic,” she says. D!


About the Authors

Thomas Saueressig is Chief Information Officer at SAP.

Timo Elliott is an Innovation Evangelist at SAP.

Sam Yen is Chief Design Officer at SAP and Managing Director of SAP Labs.

Bennett Voyles is a Berlin-based business writer.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.
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Cloud Computing: Separating Myth From Reality

Misa Rawlins and Krishnakant Dave

Across industries, many enterprise leaders believe and understand that cloud computing is here to stay. Globally, public cloud services market revenue is projected to reach US$411 billion by 2020, compared with $260 billion in 2017, according to research firm Gartner, Inc. Cloud technology in all its forms—software, platform, or infrastructure as a service—is rapidly becoming essential to the needs of business today. With cloud computing, organizations can simplify IT, save costs, scale rapidly, drive standardization and user adoption, and start getting ahead of tomorrow’s needs when it comes to customer engagement, the supply chain, the workforce, a simplified finance function, and more.

Despite the short- and long-term advantages, some executives remain uncertain about the next steps or have lingering questions about the benefits of moving to the cloud. For many leaders, separating the cloud myths from the facts can prove daunting. Start here, with these insights that can help you bust big myths about the cloud and start moving confidently toward a cloud-enabled transformation of your organization.

Myth No. 1: Moving to the cloud is too costly. “Costly” is a relative term. The cloud can be costly – but costs should be weighed against benefit and return once requirements and migration plans are in place. Rapidly evolving business demands, for example, can dramatically alter cloud-related requirements. Meanwhile, new technologies are dramatically redefining the art of the possible with the cloud. Because migrating to the cloud is not a true “plug-and-play” proposition, and many enterprise leaders underestimate what a migration or implementation involves, some organizations can be surprised by the costs of a cloud transformation. Without a clear understanding of the potential benefits—without a clear business case for moving to the cloud—the focus on costs can overshadow the return on investment. Knowing the value that cloud solutions can bring—not just the costs—can help manage expectations.

Myth No. 2: The benefits of the cloud aren’t substantial enough. As vendors adopt a “cloud-first” stance for many solutions and product updates, organizations that move to the cloud may have a competitive advantage—no matter the size of the enterprise. Cloud solutions continue to offer abundant and increasing functionality. And with the help of an end-to-end solution provider, you can configure cloud solutions to the specific needs of your industry and your business. For larger organizations, rapidly deployable cloud solutions can help support growth or the unique needs of certain business units, such as new acquisitions or foreign subsidiaries, for example. For smaller organizations, the cloud can help you position your organization to tap new opportunities and tame growth challenges.

Myth No. 3: Cloud is too risky. All digital technologies and all business models come with inherent risk. In a hyperconnected world, no system is immune from cyber attacks, insider threats, data leakage, or related risks. No transformation project is a guaranteed success. Market changes, new competition, regulatory issues, and other factors can require you to change your cloud strategy overnight.

Because the risks are real, take advantage of resources and capabilities that can help reduce risk and ensure that your technology investments align tightly with clear business objectives. The maturity of the software goes a long way toward mitigating risk with cloud projects. You can add an extra layer of capabilities such as managed cloud services to provide active, hands-on oversight of cloud applications and infrastructure—helping you to avoid service interruptions and address issues proactively.

Myth No. 4: Cloud computing is still an immature technology. Like other evolving technologies, cloud is advancing every day. Those who wait for the next generation of cloud offerings may find themselves missing out on tangible benefits as competitors leverage cloud technology to sharpen their edge. Across industries, leading organizations are not waiting. Many view cloud technology as evolving but necessary, and they are leveraging it effectively today. Some, for example, are tightly integrating cloud software solutions to streamline supply chain processes, boost information transparency, and improve decision-making across the board—all the while tapping the cloud benefits of cost savings and scalability. Others are confidently turning to infrastructure solutions delivered and running solutions in a private or hybrid cloud. Still others are turning to cloud platform solutions to extend the power of existing applications, build modern analytics platforms, or support new Internet of Things business models. Turning the cloud to your advantage may depend less on the maturity of the technology and more on the power of your imagination.

Myth No. 5: Moving to the cloud will be easy. Cloud technology can help organizations streamline and simplify their IT landscapes and their business processes, reducing needs around capital expenses and infrastructure while helping to save costs. But migrating to the cloud requires more than simply plugging in technology. It requires an ability to address a host of considerations—data migration, the business-specific capabilities of solutions, change management, governance, systems integration, security, and more.

A cloud transformation is more than a plug-and-play project or a traditional system implementation. It requires progressive thinking and an ability to align technology with your business needs and processes— for today and for the future. Migrating to the cloud is a journey. Moving forward with the cloud will require a vision of your “to be” state—your destination—as well as a strategy for getting you there.

To learn more, and to find out what IDC thinks about the future of the cloud, please read this study that presents a strategic blueprint for enterprises on their digital transformation journey.

For more information on how to simplify innovation with cloud technology, learn more about SAP Cloud Platform.

Ready to reimagine the potential of the cloud? Contact us to get the conversation started.

Contact Krishnakant Dave at kdave@deloitte.com and follow him on Twitter: @kkdave

Contact Misa Rawlins at mrawlins@deloitte.com and follow her on Twitter: @misa_rawlins

www.deloitte.com/SAP

SAP@deloitte.com

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This article originally appeared on Deloitte.com and is republished by permission.

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Misa Rawlins

About Misa Rawlins

As a senior manager and consultant in Deloitte’s SAP practice, Misa Rawlins enjoys helping her clients not only to figure out how to solve their current business problems, but also to envision how a modern cloud platform can transform their organizations moving ahead. Within the practice, she has specifically chosen to take a leadership role around the sales and delivery of SAP S/4HANA Cloud because she considers it the wave of the future. She has made it her mission to deeply understand this technology to better advise clients on what moving to a cloud infrastructure really means.

Krishnakant Dave

About Krishnakant Dave

As a principal in Deloitte’s global SAP practice, KK Dave is a consulting leader for Deloitte’s largest clients; part of the U.S. SAP leadership team where he spearheads Deloitte's cloud offerings; and leader of global go-to-market efforts in the wholesale distribution and manufacturing sector. In these roles, he assists clients in their business transformation journeys using the absolute latest SAP toolset, which presently comprises SAP S/4HANA, SAP Cloud Platform, and SAP S/4HANA Cloud, among other technologies.