Blockchain? Bitcoin? Find Out What Money’s Digital Makeover Means For You

Jacqueline Prause

As the switch to digital money via blockchain technology upends modern banking practices, many people are skeptical about whether to trust the security and privacy of transactions performed in a blockchain.

“It is as if every dollar bill in your pocket has a list written on it of all the transactions it was involved in prior to reaching your hands. The blockchain ledger infrastructure has huge potential to simplify.”

— Ted Halpern, 03/29/17

Add to this some early notoriety gained by digital currencies like Bitcoin, and it’s easy to see why people remain cautious about this relatively new technology. Can we trust it? What is the “Internet of Value”? How can we separate the hype surrounding blockchain from its real benefits?

That was the topic on a recent episode of the thought-leadership roundtable program Coffee Break with Game-Changers, presented by SAP. On Money’s Digital Makeover, Part 2, host/moderator Bonnie D. Graham talked with three leading industry experts: Jeremy Epstein, chief executive officer, Never Stop Marketing; Alon Kantor, business development manager, Check Point; and Raimund Gross, innovation manager, SAP.

The show aired live on the World Talk Radio Business Channel on April 5, 2017. The recording is available on-demand at Money’s Digital Makeover, Part 2.

One point the panel was unanimous on: Blockchain technology is definitely on its way into our lives, especially in matters of verifying trust, payment, and asset transfer. Their advice: get comfortable with it.

Read on to find out what else these three experts are saying about this transformative technology.

Should we really put our faith in blockchain technology?

Epstein: Nothing’s perfect, and I would be naïve for saying this is a perfectly flawless system, because it’s not. It’s not 100% secure…We have to recognize that this [technology] is happening. The wave is coming.

Kantor: I agree that we have no other choice. This is probably going to change a lot of things in the financial industry. That said, there is a lot of risk with it, and it is important for us as security professionals to make sure that the implementations are secure. The concept itself has no threat to anyone. It’s a great concept and it works fairly well.

Gross: It sounds easy if you look at it, but it’s hard to actually do if you’re on it. Here is an example of innovation in action. I’ve been dealing with different innovation topics for 20 years now, and for the first time, here I see something that could be described as a “live experiment” that is a combination of economics, game theory, psychology, and computer science.

Why do we need an Internet of Value?

Epstein: You have to be 100% sure that everyone in the world, or everyone in the network, knows who the owner of that asset is, which is why [in the past] we’ve needed third parties for asset transfer and verification. Blockchains allow for the transfer of value directly between two people or institutions in the same way that we transfer information, but we’re doing it without any centralized party. Whereas we can send information in seconds, if I want to sell my house, probate a will, or settle a trade, these things take days, weeks, or months. That’s unacceptable if you believe time is money.

Gross: Yes, I would have a hard time disagreeing because it’s probably one of the early drivers of a whole topic: transfer of value. If you look at what the Internet can do and what IT infrastructures can do as of today, this is clearly the part that’s lacking, or always fell behind and was cumbersome and difficult to use. And you have to rely on third parties to do these things. Now blockchain promises the end user to make their life better. Obviously this is a strong indicator for me that this will be accepted in the long run.

While yes, you can transfer money and process payments online now, there is not the added layer of security that blockchain can provide, because the third party that performs the processing has access to all your data and financial information, including who you are making the payment to.

Epstein: You can certainly go down deep on the asset, but that same transfer that’s happening – it might be happening instantaneously – actually comes at a cost to the end user, which is basically our privacy and our security, because all of our information is actually going through Venmo, PayPal, or Visa.

How should we interpret publicity around Bitcoin?

Kantor: Bitcoins today are widely used and publicized by criminals – the bad guys, the bad girls. This is causing blockchain-based payment platforms to be associated notoriously with negative activities and far less with legitimate usages.

The two main issues that we saw with Bitcoin were the fluctuation in valuation, which brought a lot of speculative investment in the currency rather than actual usage, as well as a lot of criminal activity. Bitcoin became the number-one method of payment for ransomware finances. Today there are several competing coins or different financial institutions trying to overcome these issues and to become more legitimate, but still there are a lot of benefits in the anonymity and in this blockchain novel system that is attracting people who would like to remain unknown. It’s obvious that the anonymity is very attractive to those criminals.

Gross: I’ve seen progress over the last couple of months. If you just look back a year ago, this was a much tougher discussion to have – and they worked hard for that negative image. Fortunately, over the past year or so, there’s so much additional discussion of use cases, and things already branching out from the pure payment and Bitcoin example up to other industries.

I’m positive that over time we will be able to reduce that negative sentiment that was more prevalent a year ago or so and come up with other, more positive sentiments and more highlights to that technology.

Panelists’ comments have been edited for this space. To hear the full discussion, listen to the recording at Money’s Digital Makeover, Part 2. Part 1 is available at Money’s Digital Makeover, Part 1. Read the related blog on Part 1 here.

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


About Jacqueline Prause

Jacqueline Prause is the Senior Managing Editor of Media Channels at SAP. She writes, edits, and coordinates journalistic content for, SAP's global online news magazine for customers, partners, and business influencers .

Very Soon We Won’t Trust Anything Unless It’s Backed By Blockchain

Susan Galer

Most people wouldn’t set foot inside a plane with non-certified parts, bring tainted food home to their family, or hire someone with false credentials on their resume. Time was when lack of knowledge kept consumers and businesses from authenticating stuff – be it equipment, supply chains, or documents. Now blockchain is starting to emerge as fraud fighter extraordinaire. I heard several experts talk up blockchain’s potential strengths during a recent SAP Radio broadcast of Startup Focus with Game-Changers, “Blockchain, Trust, and Startups,” hosted by Bonnie D. Graham.

Ethical, compliant supply chains

The panel was united on one point: every industry can benefit from blockchain’s foundation of digital trust. Peter Ebert, senior vice president of sales and business development at Cryptowerk, expanded on a conversation I had with him during an interview at SAP TechEd, where he demonstrated a blockchain use case that that helped the pharmaceutical industry better track drugs. During the radio show, he positioned blockchain as an incredible fraud fighter supporting ethical supply chains, as well as end-to-end visibility for regulators.

“If you buy anything…you want to make sure that there’s no child labor involved, that the raw materials were sourced in a fair way, that you are not paying for a counterfeit and think it’s the real thing,” said Ebert. “Many different laws in various industries demand to know from where was something shipped, when was it delivered or returned. Blockchain automates this trust that you need to store all these events with trust embedded.”

Safety in the skies

Drew Hingorani, CEO of AI-BlockChain, recounted how an airplane crashed when a maintenance crew member put a jackscrew in the wrong place.

“The lubricant didn’t recognize the jackscrew because the actual jackscrew that was supposed to go into that spot had a different composite. But if you track the jet engine parts, which is a use case we’re talking about currently, you can actually solve that problem using blockchain technology,” said Hingorani.

Fraud fighter extraordinaire

Ebert agreed that aerospace engineering was a compelling use case for blockchain.

“You have parts that are very expensive, being swapped out of one airplane into another, and then suddenly you have a part that didn’t come from where you thought it would come from. It doesn’t comply with the quality metrics that are required, and you find yourself with your loved ones sitting in a plane where, even if it’s just five parts, they are not what they are supposed to be. And that’s very scary,” he said.

Blockchain spots fakes anywhere

Ebert thinks the same authenticity scenarios are true for enterprise software. “We see things where you look at an image, you look at a video, and you hear somebody talk and you think you know who it is and it sounds and looks completely authentic but it isn’t,” he said. “The very foundations of our trust can be shaken by [other] technologies, and blockchain can come in and can automate this trust…at some point, you will actually not trust a document that is being presented to you unless it’s anchored in a blockchain somewhere.”

Trust in blockchain

Andreas Fichter, SAP Innovation Center Network, predicted blockchain’s eventual emergence as the new standard for trust, whether tracking documents, 3D printing, or any kind of digital asset across enterprises and in the consumer space.

“Paper is dead, and everything will be digitalized and there will be a new expectation when it comes to trust in those new digital records, and in how we conduct business,” he said. “Probably we’ll get to the point where people will say, why haven’t we done this before, or why was it so complicated before?”

With the right blend of blockchain and other emerging technologies, your supply chain can become a competitive advantage. Read The Blockchain Solution.

This blog was originally posted on the Medium Community under SAP Innovation Spotlight.


Why Blockchain Is Crucial For FP&A: Part 2

Brian Kalish

Part 18 in the Dynamic Planning Series

In my last blog, I described blockchain in some detail. Now I want to dive a little deeper and expand on the potential value that blockchain could hold for the FP&A profession.

Blockchain has the potential to streamline financial processes, such as contract enforcement, by integrating delivery and payment into the contract itself. Blockchain can potentially increase IT security, because of the unprecedented protection it offers against fraud and hacking. Blockchain will also potentially improve transparency by accessing accurate transaction data from across your company’s value chain.

It would be fair to describe the current state of blockchain uptake as exploratory. Organizations are researching, assessing the potential use and value, and having discussions with the executive team.

A distributed database with cryptographic security

Blockchain has the power to challenge many of the accepted norms of global trade, finance, and supply chain management, because it reinvents the basic building block of commerce, the ledger, for a digital, connected age.

A blockchain is a digital ledger – a distributed database that can be shared across a network of computers based in different sites and geographies. An identical copy of the ledger is held by all people participating in a blockchain network. Any changes to the ledger are reflected in just minutes or seconds, thus providing all involved with real-time information and the capacity to track trends.

The security of the information in the ledger is protected cryptographically, with the participants in the network agreeing on who can perform the appropriate functions within the ledger. For blockchain, its attraction is more than the algorithmic technologies that underpin it.

This technology makes it possible to transform the ability of the ledger to record, enable, and secure a huge amount of transactions. It could be used in multiple sectors, from financial services to tax collection in the public sector. In the future, FP&A may be able to leverage blockchain to increase IT security, manage extended value chains, and streamline contract enforcement.

Blockchains are considered highly tamper-proof, providing unprecedented protection from fraud, hacking, and unauthorized use. Instead of having to reconcile the internal system of record with information from suppliers and partners, FP&A will be able to pull data from multiple blockchains to create their system of record.

A programmable ledger that contains logic

A smart-contract feature means that the delivery and payment relating to the transaction can be integrated into the contract itself. With blockchains, the ledger itself is programmable and contains logic, freeing up human resources and capital to work on higher-value objectives. For example, there can be a rule that automates a payment upon the completion of a service.

Smart contracts would automate this process, which today involves a lot of manual steps and paperwork. This will work most of the time, where there aren’t disputes. What has yet to be designed is a mechanism for handling disputes in smart contracts. This topic will emerge as an important area of blockchain research in the future.

Ultimately, there will be hybrid contracts that blend the automation of smart contracts with the provisions for dispute resolution that exist in traditional agreements.

While blockchain technology is quite new, it is likely to play an important role in FP&A in the coming years. FP&A professionals should be anticipating how they are going to build the relevant competencies and skill sets.

FP&A professionals also need to start discussing the future of their system of record, given that organizations could move from working with a single, monolithic system of record inside the enterprise to working with many different systems.

We will be addressing these issues and more at the upcoming 2018 FP&A roundtables and conferences we are hosting in St. Louis, Charlotte, Atlanta, San Diego, Las Vegas, London, Boston, Minneapolis, Dallas-Forth Worth, San Francisco, Hong Kong, Jeddah, and many other locations around the world.

For more on this topic, read the two-part “Blockchain and the CFO” series and “When Blockchain Fulfills CFOs’ Paperless Vision.”

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


Brian Kalish

About Brian Kalish

Brian Kalish is founder and principal at Kalish Consulting. As a public speaker and writer addressing many of the most topical issues facing treasury and FP&A professionals today, he is passionately committed to building and connecting the global FP&A community. He hosts FP&A Roundtable meetings in North America, Europe, Asia, and South America. Brian is former executive director of the global FP&A Practice at AFP. He has over 20 years experience in finance, FP&A, treasury, and investor relations. Before joining AFP, he held a number of treasury and finance positions with the FHLB, Washington Mutual/JP Morgan, NRUCFC, Fifth Third Bank, and Fannie Mae. Brian attended Georgia Tech in Atlanta, GA for his undergraduate studies and the Pamplin College of Business at Virginia Tech for his graduate work. In 2014, Brian was awarded the Global Certified Corporate FP&A Professional designation.

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.


The Differences Between Machine Learning And Predictive Analytics

Shaily Kumar

Many people are confused about the specifics of machine learning and predictive analytics. Although they are both centered on efficient data processing, there are many differences.

Machine learning

Machine learning is a method of computational learning underlying most artificial intelligence (AI) applications. In ML, systems or algorithms improve themselves through data experience without relying on explicit programming. ML algorithms are wide-ranging tools capable of carrying out predictions while simultaneously learning from over trillions of observations.

Machine learning is considered a modern-day extension of predictive analytics. Efficient pattern recognition and self-learning are the backbones of ML models, which automatically evolve based on changing patterns in order to enable appropriate actions.

Many companies today depend on machine learning algorithms to better understand their clients and potential revenue opportunities. Hundreds of existing and newly developed machine learning algorithms are applied to derive high-end predictions that guide real-time decisions with less reliance on human intervention.

Business application of machine learning: employee satisfaction

One common, uncomplicated, yet successful business application of machine learning is measuring real-time employee satisfaction.

Machine learning applications can be highly complex, but one that’s both simple and very useful for business is a machine learning algorithm that compares employee satisfaction ratings to salaries. Instead of plotting a predictive satisfaction curve against salary figures for various employees, as predictive analytics would suggest, the algorithm assimilates huge amounts of random training data upon entry, and the prediction results are affected by any added training data to produce real-time accuracy and more helpful predictions.

This machine learning algorithm employs self-learning and automated recalibration in response to pattern changes in the training data, making machine learning more reliable for real-time predictions than other AI concepts. Repeatedly increasing or updating the bulk of training data guarantees better predictions.

Machine learning can also be implemented in image classification and facial recognition with deep learning and neural network techniques.

Predictive analytics

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. Basic descriptive analytic techniques include averages and counts. Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data.

This concept applies complex techniques of classical statistics, like regression and decision trees, to provide credible answers to queries such as: ‘’How exactly will my sales be influenced by a 10% increase in advertising expenditure?’’ This leads to simulations and “what-if” analyses for users to learn more.

All predictive analytics applications involve three fundamental components:

  • Data: The effectiveness of every predictive model strongly depends on the quality of the historical data it processes.
  • Statistical modeling: Includes the various statistical techniques ranging from basic to complex functions used for the derivation of meaning, insight, and inference. Regression is the most commonly used statistical technique.
  • Assumptions: The conclusions drawn from collected and analyzed data usually assume the future will follow a pattern related to the past.

Data analysis is crucial for any business en route to success, and predictive analytics can be applied in numerous ways to enhance business productivity. These include things like marketing campaign optimization, risk assessment, market analysis, and fraud detection.

Business application of predictive analytics: marketing campaign optimization

In the past, valuable marketing campaign resources were wasted by businesses using instincts alone to try to capture market niches. Today, many predictive analytic strategies help businesses identify, engage, and secure suitable markets for their services and products, driving greater efficiency into marketing campaigns.

A clear application is using visitors’ search history and usage patterns on e-commerce websites to make product recommendations. Sites like Amazon increase their chance of sales by recommending products based on specific consumer interests. Predictive analytics now plays a vital role in the marketing operations of real estate, insurance, retail, and almost every other sector.

How machine learning and predictive analytics are related

While businesses must understand the differences between machine learning and predictive analytics, it’s just as important to know how they are related. Basically, machine learning is a predictive analytics branch. Despite having similar aims and processes, there are two main differences between them:

  • Machine learning works out predictions and recalibrates models in real-time automatically after design. Meanwhile, predictive analytics works strictly on “cause” data and must be refreshed with “change” data.
  • Unlike machine learning, predictive analytics still relies on human experts to work out and test the associations between cause and outcome.

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Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past. Please feel to connect on: Linkedin: Twitter: