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The Cloud: The Great Equalizer

Anja Reschke

These days, size is less important when it comes to business. In some ways it no longer matters if you are a small startup or a huge enterprise: Regardless of the size of your company, you can access the same global market, the same customers, and the same enterprise software as your biggest competitors because of the accessibility of cloud computing. In many cases, being smaller can give you an edge because your business is so much more nimble.

The cloud is changing the structure of the enterprise software market

In its simplest from, cloud computing is a flexible way for businesses to access the technology they need, when they need it, without having to own and maintain servers and other hardware.

The cloud is the great equalizer when it comes to business

With cloud computing, companies aren’t bound by the limitations of traditional systems, so growth and scalability are limitless for any size or type of business. This enables even the smallest startups to access technology that was previously unattainable.

For example, they can now easily access advanced predictive analytics through the cloud, allowing them to understand their customers on a personal level and gain a competitive edge over traditional businesses in their industry. This enables companies to innovate faster, increase revenue, and adopt new technology quicker and easier.

Strong partnerships are the key to cloud computing

Cloud computing gives businesses flexible and scalable connections to multiple applications, so individual companies are looking to partner with the strongest cloud providers to secure long-term growth potential.

Where do I start?

The SAP eBook, Digital Disruption: How Digital Technology is Transforming Our World, suggests that businesses select an appropriate cloud provider that will meet their long-term needs. Here are some things to consider:

  • Security and privacy: Make sure your cloud provider offers end-to-end encryption and is able to understand and reinforce your privacy, security, and compliance requirements.
  • Data location and ownership: Clarify who owns the data and where it will be stored geographically.
  • Disaster recovery: Verify the provider’s backup and disaster recovery capabilities.
  • Long-term partnership: Select a stable, reliable provider that will share the benefits and risks involved with a long-term partnership.

For more details on cloud computing, hyperconnectivity, and the multiple other factors driving digital transformation, download the SAP eBook, Digital Disruption: How Digital Technology is Transforming Our World.

For an in-depth look at how the digital age is changing the business landscape, download the SAP eBook, The Digital Economy: Reinventing the Business World.

Take a closer look at one industry in the midst of digital transformation. Download the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare.

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About Anja Reschke

Anja Reschke is the Senior Director of Strategic Ecosystem Marketing at SAP. She is responsible for the development of joint strategic marketing plans, programs, and activities, with global strategic services and technology partners.

Real-Time Data Transforms Political Journalism, But Context Remains Vital

John Graham

The runup to the 2016 U.S. election is being covered in interesting new ways by the political media, with analysis of Big Data and real-time opinion polling offering journalists much deeper insight than ever before. The trend of “data journalism” is peaking as the media embraces advanced technologies that allow them to deliver a new breed of numbers-driven, fact-based journalism.

The tools being used for data journalism open up possibilities for fresh perspectives, more in-depth reporting, and new stories behind the numbers that have never been seen before. Traditional journalists are beginning to see how data journalism can complement their reporting, and the U.S. election is serving as an ideal testing ground. Political reporters are lapping up the improved data literacy and access to objective analysis, which is helping to make their reports more thorough and informative.

Consequently, American voters are becoming digital voters. They have access to real-time, data-driven information and public sentiment, which is empowering them with broader insight. They’re relying on this to help them make up their minds before they cast their vote, and it’s given many voters a renewed interest in becoming informed citizens able to make an educated choice.

However, the rise of data-driven journalism brings with it a potential pitfall for media organizations and readers alike. Digital information overload will bring about a fatigue around numbers if reporting quantity becomes more highly valued than quality. Having access to mountains of data is a huge benefit, but a reporter still has to be a journalist first to ensure they’re not getting buried under the numbers and missing the stories.

In other words, a political journalist still needs to be a politico, not just a statistician. They could fall into the trap of placing too much importance on meaningless correlations as indicators of voter sentiment, losing their grasp on what made them a great political reporter in the first place. As data gets bigger, this will become harder to resist. So they need to become experts in making Big Data small—rather than obsessing over the numbers, obsessing over figuring out what they really mean. In doing that, they have an unprecedented opportunity to make people more informed rather than simply overwhelming with them a series of conflicting data sets.

Some media organizations are already tackling the challenge of remaining relevant in a world of information overload. Using big data and visualizations, they are making great strides in making data journalism more accessible to reporters, politicos, and voters, which is proving its worth in giving political reporting a new lease of life.

Reuters’ Polling Explorer tool is an example of how this is being done, offering up customizable data visualizations focusing on the biggest talking points in the U.S. leading up to the election. It’s an entirely new scale of public opinion measurement, presented in a way anyone can understand and use, while enabling Reuters to usher in its own improved brand of accurate, fact-based, and timely journalism.

We can see the true potential of using real-time data analysis to measure up-to-the-minute public opinion in one poll on the most important problem facing the US today. Immediately after the Paris attacks in November, terrorism skyrocketed way above the economy as the number-one issue, rising sharply again straight after the December San Bernardino attack. For Reuters, this is just one of many examples of their greatly increased ability to find outliers in the data.

Reuters Polling Explorer runs on SAP HANA, an in-memory data platform that allows Reuters to access and analyze 100 million survey responses for quicker and more efficient reporting of public opinion.

For more on data analytics in today’s media environment, see How Big Data Is Changing The News Industry.

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John Graham

About John Graham

John Graham is president of SAP Canada. Driving growth across SAP’s industry-leading cloud, mobile, and database solutions, he is helping more than 9,500 Canadian customers in 25 industries become best-run businesses.

Smart Machines Create Markets For Cyber-Physical Advances

Marion Heindenreich

Today, industrial machines are more intelligent than ever before. These intelligent machines are changing companies in many ways.

Why smart machines?

Mobile networked computers were a key breakthrough for making smart machines. Big Data allows machines and computers to store information and analyze complex patterns. Cloud computing offers broad access to information and more storage.

These computerized machines are both physical and virtual. Some call them “cyber-physical” machines. Technology lets them be self-aware and connected to each other and larger systems.

Businesses change their approaches

Intelligent machines allow companies to innovate in many areas. For one, the value proposition for customers is evolving. Businesses now model and plan in different ways in many industries.

Makers of industrial machines and parts work in new ways within the organization. Engineering now partners with mechanical, electronic, and software staff to develop new products. Manufacturing now seamlessly ties what happens on the shop floor to the customer.

Service models are changing too. Scheduled and reactionary servicing of machines is fading. Now intelligent machines track themselves. Machines detect problems and report them automatically. Major problems or failures are predicted and reported.

A data mining example

One good industrial example is mining, which can be dangerous and difficult. As ores become scarce, the costs of mining have increased.

“Smart machines” started in mining in the late 1990s. Software and hardware let remote users change settings. Operators moved hydraulic levers from a safe distance. Sensors observed performance and diagnosed issues.

Data cables connected machines to computers on the surface. Continuous and remote monitoring of the machines grew. Over time, embedded sensors helped improve monitoring, diagnostics, and data storage.

The technology means workers only go underground to fix specific issues. As a result, accident and injury risk is lower.

New wireless technology now lets mining companies connect data from many mine sites. Service centers access large amounts of data and can improve performance. Maintenance is prioritized and equipment downtime is reduced.

Opportunity abounds

For companies the time is now. Today, mobile “connected things” generate 17% of the digital universe. By 2020 that share grows to 27%.

You might not be investing in this so-called “Internet of Things” (devices that connect to each other). But it’s a good bet your competitors are. A December 2015 study reported 33% of industrial companies are investing in the Internet of Things. Another 25% are considering it.

There are risks

This new dawning era of manufacturing is exciting. But there are concerns. Cyber attacks on the Internet of Things are not new. But as the use of intelligent machines grows, the threat of cyber attacks in industry grows.

Data confidentiality and privacy are concerns. So too are software and hardware vulnerabilities. Exposure to attack lies not just in the virtual space but the physical too. Tampering with unattended machines and theft pose serious risk.

To address these threats, industries must invest in cybersecurity along with smart machines.

Conclusion

The potential advantages of smart machines are staggering. They can reshape industries and change how companies produce new products and create new markets.

For more information, please download the white paper Digital Manufacturing: Powering the Fourth Industrial Revolution.

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Marion Heindenreich

About Marion Heindenreich

Marion Heidenreich is a solution manager for the SAP Industrial Machinery and Components Business Unit who focuses on solution innovations like Product Costing on SAP HANA and cloud solutions, as well as providing financial and business analysis for industry business strategy definition and business planning.

Robots: Job Destroyers or Human Partners? [INFOGRAPHIC]

Christopher Koch

Robots: Job Destroyers or Human Partners? [INFOGRAPHIC]

To learn more about how humans and robots will co-evolve, read the in-depth report Bring Your Robot to Work.

Download the PDF (91KB)

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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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Building A Business Case For Financial Transformation

Nilly Essaides

There’s constant pressure on the CFO from the CEO to do better—to innovate, and to transform the finance organization into both a leaner and a more forward-looking analytics hub that provides insight and foresight to the enterprise. CFOs today must:

  • Interpret numbers instead of reporting them
  • Deploy enabling technology to automate low-value work
  • Scout for business and growth opportunities
  • Work effectively with Big Data to turn their teams into the brains of the organization
  • Act as true partners to the CEO, business leaders, and board of directors

Defining the ROI for transformation

Transformation sounds great in theory, but to get finance to literally go beyond its form—not an easy feat—executives need to see a strong business case and a tangible payback. After all, finance is all about the ROI.

Here are some solutions CFOs can wrap their heads around to help drive change:

  • Manage competitive disruption. Today’s business environment is rife with competitive threats. My last post listed five ways financial planning and analysis (FP&A) in its future form can help companies battle these threats. The cost of not transforming the finance function into the fast-thinking, forward-looking brains of the enterprise is the opportunity cost of falling behind. It’s the risk of becoming irrelevant through the inability to foresee competitive threats, or of lacking an action plan for dealing with the potential impact of such pressures on the financial health of the corporation.
  • Streamline processes. Obviously, there’s the dollars-and-cents savings that come from streamlining processes, using new technologies, and breaking down internal silos. For example, in many organizations, forecasting processes occur in different departments. Merging these disparate processes into one and using a single technology platform can save enormous resources in terms of systems and time. It eliminates duplicate entries of data and the need to reconcile discordant information, or the need to later argue about which number is right. It creates a single version of the truth.

Even within finance, things can be improved. Often the processes of budgeting, forecasting, and planning happen in isolation in different time frames. And operational and financial planning occur in different cycles and levels. By syncing up these processes, companies can get rid of redundancies. What’s more important, they can discover efficiencies and improve the quality of the end product.

  • Eliminate waste and free up strategic time. New technologies are enabling the finance function to automate low-value work and free up executives’ time to focus on strategic thinking, developing partnerships with the business, and advising management on how to drive growth. The payback is smarter decisions (faster growth, higher investment returns) while lowering operating expenses.
  • Look forward. Finance and FP&A today are shifting their focus from yesterday to tomorrow, from what happened to what’s going to happen. Transforming their mindset is key to helping the business move forward. Using techniques and technologies like driver-based modeling and predictive analytics, finance is remaking itself and producing faster, more frequent and—most importantly—more accurate forecasts. It’s giving management the one thing that matters most: time to pull business levers to affect future financial results. The payback is higher sales, wider margins, and lower cost of operations.
  • Change the mindset. There’s no transformation of the financial organization without a transformation of the financial skill set of executives. The first-quarter Deloitte CFO Signal Survey indicated that CFOs expect to embark on a wide range of efforts to improve the performance of their teams before the end of 2016. While foundational finance skills remain a must, to transform finance into the “A-team” of the future, executives must possess business acumen, diplomacy skills, intellectual curiosity, technology savvy, and a degree of comfort with ambivalence. They have to be okay with making decisions without 100% of the information. One can argue that the return on soft skills is soft. But it also means being able to move fast and grab windows of opportunity. Not all business cases are based on cost savings.
  • Build an analytics hub. The biggest challenge for CFOs today is to transform finance into the analytical hub of the organization and leverage Big Data to drive smarter business decisions—both in terms of cost cutting and in giving the business units advice on how to market, sell, develop, and grow their operations. That’s how finance fits within the digital enterprise. Finance needs to funnel Big Data from all corners of the organization—and outside it—to leverage its unique central viewpoint. It must bring the information together and run it through advanced analytics models to come up with causal relationships that explain what business initiatives are really moving the needle, what steps the company can take to improve results, and what its customers are doing and are likely to do. Digitizing finance has a huge payback: It allows companies to stay competitive in a digital economy.

Is finance transformation worth the effort? That may be the wrong question. The question is, can companies afford not to transform their finance function and remain relevant now and going forward?

Learn how the FP&A team at CF Industries Holdings Inc. prioritized business partnering options and transformed the organization to optimally support strategic goals by establishing an integrated business planning process at the AFP Annual Conference session, Driving Finance Transformation Through Integrated Business Planning.

For more of my insights on FP&A, subscribe to the monthly FP&A e-newsletter from my company, the Association for Financial Professionals. You can also connect with me on LinkedIn or follow me on Twitter.

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Nilly Essaides

About Nilly Essaides

Nilly Essaides is the director of the FP&A Practice at the Association for Financial Professionals. She has over 25 years of experience in the finance field. Nilly has written multiple in-depth research reports on FP&A and Treasury topics, as well as countless articles. She also speaks at conferences and moderates financial executives' roundtables across the country. Nilly has published a book on best-practice transfer and process excellence with the APQC, "If We Only Knew What We Know."