China Leads On Mobile Wallets — Will Others Follow?

Tom Groenfeldt

Mobile wallets have taken off faster in China than in the U.S., concluded a recent Forrester Research study. It found that 76% of metro Chinese consumers use mobile wallets or are interested in doing so, compared with only 36% of the urban online U.S. population.

The past influences the future, and as a fast-developing country, China has not had the payments infrastructure and regulatory legacy that developed in the U.S., said Brendan Miller, a principal analyst at Forrester.

“Incumbency is a factor. We have the highest penetration and usage of credit cards in the world, plus high debit card usage. As you go into other countries you will find they have alternative or local payment options, so consumers are used to using these methods like direct debit from a checking account and they avoid a lot of the credit card and interchange fees we have.”

Asia has smart cities and well-developed networks that are simpler than those in the U.S., where multiple levels of government make integration of payments and services more complicated.

Asia’s mobile wallet providers have the potential to gain the understanding of customers that department stores used to enjoy before the big brands replaced many store cards. “Nordstrom,  Kohl’s, Macy’s, Sears — all those retailers had their own private label credit cards for years and years,” Miller noted. “They provided a way of getting a better understanding of what consumers were buying, and a way to avoid credit card and debit interchange fees.”

The rise of Alipay and WeChat in China has been driven by the value the services provide for consumers. “First they made it super convenient for consumers to buy, and then they layered on additional services that consumers found engaging, such as gamification and the idea of sending gifts on the Chinese New Year — red envelopes — that got people engaged with the system.”

In the U.S., payments systems have made it convenient, but that’s the lowest rung on the ladder, Miller added. “Mobile wallet providers will have to up their game.”

Mobile payments with NFC have the potential to be faster than EMV, which Forrester expected would drive mobile payments. Miller said that when he presented to a group of retailers last year, they told him that hasn’t been the case. “Retailers haven’t updated their terminal logic. So when you pay with NFC you should be able to tap and have transaction process immediately. Instead, I get prompted for my debit PIN or a signature because the POS is using the old terminal logic and not running NFC.”

If a buyer provides a thumb scan in Apply Pay, no additional identification should be needed. “But it is going to take a while for retailers to reprogram those terminals to improve the flow at checkout.”

Retailers have been preoccupied with getting EMV to work right that they haven’t focused on the user experience with NFC, he added. “Right now NFC is not that much more convenient, and meanwhile EMV is getting faster. Visa and Microsoft have done a lot to speed those up.”

The Forrester study predicted mainstream mobile wallets in the U.S. will add customer engagement features. The Chinese may provide some examples.

Miller said that Alipay has made some announcements of partnerships with American payment processors, primarily with a focus on targeting Chinese consumers within the U.S., such as pushing adoption in place where Chinese consumers visit. The Chinese payment companies may have the potential to reach beyond the Chinese markets, he said, but the attitudes of U.S. consumers will be different from the Chinese. “This is all harder that anyone thinks is it. Everyone is disappointed by Apple Pay or Android Pay adoption. This is going to take time; payments is hard to do.”

Consumers won’t bother with mobile wallets until they see some extra value beyond what cards or cash can offer, like the ability to order ahead at Starbucks or Dunkin Donuts, or get recommendations or coupons while shopping. Alipay and WeChat have evolved into lifestyle platforms for Chinese consumers. Miller predicts space will open in the U.S. for third-party providers like Apple, Facebook, and Google that could merge their other customer engagement tools with a mobile wallet.

For more on this topic, see Survey: Mobile Payments Can Boost Growth And Profitability.

Twitter @tomgroenfeldt

Image: AP


About Tom Groenfeldt

Tom Groenfeldt is a freelance reporter who focuses largely on finance and technology including trading, risk, back-office systems, big data, analytics, retail banking, international banking, and e-commerce. His work appears in several publications, including in the U.S. and Banking Technology in London. In 2015, he was named to the "FinServ 25," the top 25 top global influencers in banking, by The Financial Brand.

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.


Lessons On GRC Platforms From The Forrester Wave: Keep Your Eyes On The Road

Bruce McCuaig

On February 15, Forrester released The Forrester Wave: Governance, Risk, and Compliance Platforms, Q1 2018. SAP continues to be rated a leader. But the market for governance, risk, and compliance (GRC) platforms is maturing, and at SAP, we believe the criteria for evaluating and selecting a vendor are evolving.

Should you choose the GRC vendor with the strongest current offering or the GRC vendor with the strongest strategy?

SAP occupies neither position. But is there a third and better option?

Keep your eyes on the road, not the vendor

Anyone buying a new car has access to consumer reports comparing and rating vehicle manufacturers and models against a variety of criteria. Vehicle entertainment systems are among the criteria rated.

However, for most vehicles made in the last 5-10 years, the supplier of the original equipment vehicle entertainment system is not displayed. In some cases, the supplier is not even mentioned in the owner’s manual. There may be a lesson here for customers looking for GRC solutions.

In automobiles, the entertainment system is an outcome, not a separate process. The outcome is evaluated, not the vendor. Customers evaluate and purchase the complete vehicle, not an individual component.

In my recent vehicle purchase, the UI of the OEM entertainment system was rated poorly in several analyst reports.

The real issue, however, isn’t whether the vehicle entertainment system’s UI is easy to learn. That may be a useful criterion for an in-home entertainment system. But the critical criterion for the UI in a vehicle entertainment system is this: Can you use it while keeping your eyes on the road? That is the essential outcome. Acoustic performance is a given. But can the system add value and synergies from other vehicle systems through native integration and continuous monitoring?

Does the entertainment system provide continuous monitoring of the vehicle navigation system, integration with the alarm system, compatibility with the mobile communication and vehicle maintenance systems? Does it provide audio alerts for maintenance and safety issues? Will it warn you of hazards ahead? Does it connect to the cloud?

Does it make the vehicle better?

The specific stand-alone features and UI of the entertainment system in your vehicle are important but secondary to the main goal. Integration of the system into the vehicle’s overall performance is the key criterion. Criteria that help you select a home entertainment system are not useful for evaluating a system for your car. And beyond the core capabilities that are important for your home entertainment system, are there other features that add value and influence the car-buying decision?

The path for ERP providers in the GRC market

The goal is balance and integration. GRC performance without strategy is short-lived. GRC strategy without strong capability is not effective. Growing both simultaneously is difficult, but in the end, is the only sustainable option.

I’d suggest that is exactly where an ERP provider should be positioned and exactly the trajectory to follow.

Eventually, GRC systems, like car entertainment systems, will be subsumed into the ERP landscape of your business. The value of the GRC systems will lie in their integration into the underlying ERP system and the cloud and their contribution to performance, not in their stand-alone virtues.

Download and read The Forrester Wave: Governance, Risk, and Compliance Platforms, Q1 2018.

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


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.

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.

Explore machine learning applications and AI software with SAP Leonardo.


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: