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Cloud, Mobility, Security, And Big Data: The Big Four For Business Growth

Shelly Kramer

Companies failing to make a strategic investment in technology in key areas of their business may be missing out on opportunities for growth as a consequence. That’s one of the key findings from a recent report that suggests that it’s not just operational efficiencies that investment in technology can offer, but also impressive increases in revenue growth rates.

This suggestion comes from Dell’s second annual Global Technology Index (GTAI 2015) – a survey of 2,900 business and IT decision makers in mid-market organizations (100-4,999 employees), distributed across multiple industries in North and South America, Europe, Asia, and Australia. The survey was designed to gain a greater understanding of solution maturity levels, as well as adoption drivers and inhibitors in the key technologies of cloud, mobility, Big Data, and security. If you’re behind the curve on the adoption of technology in your business, this statistic from the study should give you pause: Companies actively investing in these big four technologies are seeing up to 53% higher revenue rates.

Dell GTAI chart

It’s perhaps time to start doing some serious thinking about what technology can do for your organization, now and in the future. Equally as important is exploring what your competitors are doing with regard to the adoption of technology and how that might present a competitive advantage. I know this is something we explore with our B2B clients of all sizes on a regular basis – and is an important part of our overall strategic plans. 

Cloud boosts efficiency and revenue growth

The adoption of cloud technology has the potential to support operational and organizational efficiencies, with the study identifying three key benefits:

  • Cost savings were identified by 42% of respondents
  • Getting things done more efficiently (40%)
  • Better allocation of IT resources (38%)

But over and above these benefits, the research was also able to establish that the organizations that were actively employing the cloud were seeing much higher revenue growth rates. These amounted to a significant 46% increase for on-premises cloud and 51% when off-premises cloud technology was used.

Infographic: GTAI Cloud – higher revenue growth rates

The results of the study suggest that cloud adoption and expansion are driven largely by the expectation of greater organizational speed and improved employee satisfaction. And that higher revenue growth finding – that should be enough to motivate anyone still sitting on the cloud fence.

Mobility strategies boost growth but BYOD on the decline

Organizations implementing a mobility strategy are also seeing revenue growth fueled by improvements in efficiency, smoother business processes, and reduced paperwork. The study found that companies deploying mobile technology showed 44% higher revenue growth rates than those who weren’t, while effective use of a BYOD program could boost revenues by an even more impressive 53%.

With mobility though, the waters are somewhat muddied with the expansion of the BYOD tech trend restricted by fears over the potential security problems that allowing employee-owned devices might deliver.

Infographic: GTAI mobility – employee-owned devices

The suggestion that enthusiasm for BYOD might be waning will come as a surprise to many, as the use of employee-owned devices has gained considerable momentum over the last few years. Perhaps lower-cost devices and the need for greater control over access to company resources is what’s beginning to swing the pendulum away from this popular business practice. I’m curious to know how these “restricted employees” feel, and whether shadow IT will simply rise as a result.

Big revenue gains from Big Data

The results of the study suggest that organizations that have actively embraced the use of Big Data are seeing 50% higher revenue rates than those who haven’t. Not a surprising finding. The integration of Big Data into operations and using data to drive strategies is pretty much table stakes these days – for businesses of all sizes. Respondents to the survey agree, with 41% saying that Big Data has resulted in better targeting and increased ROI from their marketing efforts.

Also not surprising is that we’re not there yet. Progress in harnessing the full power of Big Data appears be moderate at best, with almost half (44%) of survey respondents reporting they are still not sure how to get the best from the plethora of information they have at their fingertips.

Lets face it; the science of Big Data is still in its infancy. But if the results of the Dell study are anything to go by, businesses that can reach that nirvana have the potential to create spectacular revenue gains.

Strategic security can equal competitive advantage

Digital security challenges are undoubtedly increasing across the board for all businesses. For many though, rather than seeing a strategic security investment as a burden, they consider that it can actually give them a competitive advantage. As this infographic from the study illustrates, almost eight out of every 10 respondents thought security enhances the organization’s ability to react to market conditions.

Infographic: GTAI security – market conditions response

The result is that for an increasing number of companies, particularly in North America, business managers are taking the view that the implementation of strong security measures allows them to feel confident being innovative, thereby gaining a competitive advantage.

Paradoxically, security concerns – together with cost – are the biggest obstacles to adoption of cloud, mobile, and Big Data for many organizations (a topic that I’ll return to here soon).

Technology playing a key revenue role

The latest GTAI survey clearly demonstrates the correlation between the use of technology and a resultant growth in revenue. Strategic investment in the “big four” technologies of cloud, Big Data, mobile, and security is seen as doing a lot more than just boosting efficiency and saving time. These technologies and their use actually frees up resources that allow organizations to invest in other areas of the business, areas that can have a direct impact on revenue growth.

The study suggests that it is business leaders who are driving adoption of Big Data and mobility, while cloud and security projects tend to be more equal partners with IT. Organizations who marry the interests of the C-suite when it comes to Big Data and mobility and the IT team when it comes to cloud and security will be well-placed for success (and increased productivity and profitability) moving forward.

What do you think about the data presented here? Is it accurate as it relates to what you see either in your organization or with your clients? How far along the technology adoption process are you? Are you a corporate early adopter facing push-back from senior leaders and constantly having to argue your case? Have you experienced first-hand how technology has helped a business succeed? I’d love to hear your thoughts and stories. Tweet me @ShellyKramer and copy @DellPowerMore.

Learn more about how SAP sees its role in the digital economy. Our Digital Planet: A Digital-First World.

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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."