i-GRC And The Three Lines Of Defense

Bruce McCuaig

In my last blog, I appropriated the “i” from IDC’s The Rise of Intelligent ERP and, in a different blog, made the case that GRC professionals and standard setters are failing to adapt to the digital revolution.

What is i-GRC, you may ask, and what does it have to do with the three lines of defense framework?

It’s a fair question. Much has been written about the three lines of defense. It is widely acknowledged, but in my experience it’s misunderstood and loosely adopted at best.

To me, the fundamental outcome of a successful three lines of defense implementation is a continuous and self-correcting system to manage risks across the enterprise. Each line works independently but collaboratively to identify and assess risks and self-correct gaps. Without technology, it’s largely a manual process.

The technology required to digitize the three lines of defense is what I referred to as intelligent or “I” GRC. The information needed to manage the three lines of defense as a self-correcting system should be created by i-GRC

i-GRC: self-detecting solutions for a self-correcting system

i-GRC technology should self identify and self manage risks, controls, compliance failures, loss events, issues, and other anomalies or patterns indicating nonconformance to defined standards.

Like i-ERP as envisioned in the IDC article, i-GRC will be distinguished by:

  1. On-demand, not manual, periodic GRC practices
  1. The adoption of machine learning and advanced analytics consuming data from a carefully designed and constructed data set
  1. i-GRC professionals with high levels of digital knowledge and expertise and indifference towards today’s practices
  1. An orientation to the future, not the past, and a drive to contribute to business performance

I was inspired in writing this blog by an article from McKinsey & Company titled “The neglected art of risk detection.”  The premise is that risk detection can be automated. That’s correct: I believe almost all aspects of GRC management can be digitized. The technology required is available today.

Embedding iGRC in the business

Today’s GRC practices won’t survive the digitalization of the business. Digitalization does not mean automating today’s professional practices.

Most of what the business needs to know to manage the three lines of defense is already captured in digital form and can be detected and managed with tools that are rapidly emerging. Professional practices that impose structured manual methodologies aren’t necessary. For example:

  • Technology exists today to detect unusual and unwanted anomalies and patterns. For example, credit card companies use technology to detect and block fraudulent transactions.
  • Predictive tools exist to extrapolate and refine detection. Algorithms that detect anomalies can be tested and improved automatically.
  • Continuous monitoring and alerts are available today. Rule sets can be created to identify issues.
  • In-memory real-time processing is here now. Massive amounts of data can be accessed and processed almost instantly.
  • Machine learning to support self correction is also here now. Incidents can be detected and associated with risks. Controls can be adjusted.
  • Collaborative tools to collect and share knowledge and collective wisdom exist. Risk surveys can penetrate the first line of defense and detect new or emerging risks.
  • Analytical tools to aggregate, report, and visualize are available. A single source of truth is a good start. Now everyone can see everything in visual form at the same time.

Few of these technologies are in use by GRC practitioners today. Few if any professional standards or frameworks recognize their existence, let alone require their adoption.

Ending the inertia

Most practitioners I have spoken with see themselves standing outside the business looking in, with risk identification, control, compliance, and audit practices dictated by the standard-setters and regulators.

Some think digitalization will drive demand for more audits, more risk assessments, more controls, and more testing.

Instead, I suspect that i-GRC technologies will eventually be deeply immersed within the business, creating self-detecting, self-healing capabilities to drive the three lines of defense.

Testing the vision

My colleagues and I have been trying to develop the value proposition for using our technology to perform today’s GRC practices at the speed of light. There is none.

Please share your thoughts

  • Is there such a thing as i-GRC?
  • Will today’s standards and practices survive digitalization?
  • Have you implemented the three lines of defense in your organization?
  • What digital technologies are you using today in your GRC practice?

Learn more:

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

This article originally appeared on SAP Analytics.

Comments

Bruce McCuaig

About Bruce McCuaig

Bruce McCuaig is director - Product Marketing at SAP GRC solutions. He is responsible for development and execution of the product marketing strategy for SAP Risk Management, SAP Audit Management and SAP solutions for three lines of defense. Bruce has extensive experience in industry as a finance professional, as a chief risk officer, and as a chief audit executive. He has written and spoken extensively on GRC topics and has worked with clients around the world implementing GRC solutions and technology.

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

Comments

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.

Emerging Trends In Financial Analytics

Rob Jenkins

Stephen Hawking once said, “We should seek the greatest value of our action.” Following that sage counsel, finance teams should seek to spend more of their time on actions that create shareholder value, such as strategic and economic analysis, and less time on mundane tasks, such as data transformation, reconciliation, and report preparation.

Emerging trends in technology enable the finance team to focus on the highest-value activities and drive digital business transformation, including a new functional operating model. The finance function of the future leverages social platforms, enterprise mobility, and data science to address the insatiable desire for real-time analysis and partner with executive management to create competitive advantage.

Social finance

“Social finance” is not an oxymoron. Many millennials are accustomed to collaborative communities with a sense of common purpose and a supportive structure. Workplace culture is rapidly adapting to these norms, as evidenced by various best-places-to-work surveys. Finance teams can be social, and in fact, the best analytics results typically come from close collaboration among visionary strategists, data stewards, and results-oriented team members looking to be catalysts for change.

At first glance, not many finance team members would say budgeting is a social activity. But when seen as an objective-setting and control exercise coupled with accurate forecasting, the financial planning process can involve many stakeholders who have expertise and discretion over business operations – including daily decisions that impact revenue, expenses, and capital investments. This “crowdsourcing” mindset and its network effects are profound. As more team members analyze data, communicate, and engage in building a budget and improving forecast accuracy, they have more “skin in the game” as it relates to financial performance.

The financial analytics technology that enables this teamwork includes a shared corporate calendar focused on processes, deliverables, and due dates; a chat feature for frequent and informal “hallway conversations”; and tools for advanced business modeling (with private versioning). All of this is packaged in one easy-to-use interface: the new killer app for finance teams.

Consumer-grade software is the standard for this new generation of finance professionals. It’s “table stakes” for them because they expect intuitive, visual capabilities and predictive calculation functionality in one space, without the complex menu maze of spreadsheets or toggling among desktop applications.

AI-enabled finance

Finance has come a long way in its forecasting ability. Not long ago, manually running correlations in spreadsheets was considered advanced analytics. Now machine learning enables code to learn from data and make predictions. Tools to improve accuracy are now easy to use and enable the curious mind to pursue endless scenarios to hone the precision of the forecast.

In the current “consumerization of IT” zeitgeist, even financial analysts who aren’t statistically savvy can simulate actions, impact, and complex relationships with ease. These citizen developers are the players in the self-service movement where IT deploys the technology and finance develops and fulfills its own requirements. Whether it’s understanding demand curves, non-linearities, or social sentiment, artificial intelligence can produce a predictive scenario that does what human systems sometimes find challenging: moving beyond bias in predictions.

Although robotic process automation in finance will replace many accounts payable personnel who today manually match invoices to purchase orders, humans will still be needed to design, strategize, communicate, and express empathy when processes break.

With the advent of natural language processing, conversational interfaces will be as popular in the workplace as they are in the home. These chatbots will increasingly become the preferred mode of interaction in many financial analysis use cases.

Gone are the days of building triple exponential smoothing spreadsheet models. Welcome to the world of automated algorithms with prescriptive analytics.

Instant finance

With the evolution of technology, finance is reexamining the mindset of “batch mode.” Proactive finance organizations will produce on-demand results for the business. Continuous accounting that integrates journal entries, soft closes, and pro forma consolidation creates instant insight, simplifies reconciliation, and accelerates reporting.

New advances in hardware and software enable immediate, visual, and suggestive analytics that not only shorten the data-to-decision cycle, but also drive cultural changes. Managers will expect decision-support timelines to be drastically compressed.

Executive management sessions, including those in the boardroom, will move away from hard-copy handouts to visual presentations with live data that allow scenario-modeling capabilities, dramatically accelerating strategic decision making.

Visual finance

People love and need stories. And every good story needs a picture. New technology brings automated visualizations of financial data that go far beyond bars and pie chart representations created manually from rows and columns of data. Now one click away are sophisticated geospatial and multidimensional illustrations that intuitively explain what would take many more words and much more time to read and comprehend.

Social anthropologists can debate whether our attention spans are getting shorter – although there is no doubt that visualizations enhance communication and help audiences explore, discover, and develop insights otherwise difficult to glean from complex data relationships.

People can just filter and drill into data to get quick answers to business questions. It is now easy to build insightful data visualizations, business intelligence dashboards, and storyboards using best practices and proven design standards to help engage and inspire an audience. And with a mobile-first design approach, business stakeholders anywhere in the world on any device can interpret and act on compelling views that couldn’t have been imagined just a few years ago.

By leveraging emerging technology trends, finance can accelerate the journey to becoming a true business partner and focus more energy on the actions that count.

Find out more about how technology can enable better decision making in How AI Can End Bias.

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

Comments

Rob Jenkins

About Rob Jenkins

Rob Jenkins is a finance executive with over 20 years of experience in leading high-technology and professional services companies. He consults with CFOs on technology, analytics, and performance management. Rob has served as vice president, Corporate Finance and led finance transformation. His leadership experience also includes corporate development, M&A, strategic planning, and consulting. He has designed and implemented customer profitability, business planning, process improvement, and performance measurement systems in multiple organizations. Rob began his career as an auditor with a Big 4 CPA firm. He holds an M.S. in Accounting and is a CPA, CMA, and CFM.

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.
Comments

Tags:

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

@DeloitteSAP

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

Comments

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.