Innovate Your Business Model With Conversational AI: Part 2

Ivo van Barneveld

Part 2 in the 3-part “Driving Innovation with Conversational AI” series

In my recent blog series UX Design for CIOs, I analyzed trends fueling the rise of conversational AI. Now, let’s look at how conversational AI can be used to innovate your business model. To do so, I will use one of the most successful business model representations currently: the Business Model Canvas (Osterwalder and Pigneur, 2010), which has been widely taken up by practitioners. Since I am a big fan of the business model canvas, I will use this framework as a guiding light, analyzing how the injection of conversational AI propagates through the canvas, thus transforming the business model. The focus will be on the following building blocks:

  • Value proposition
  • Customer relationships

Please note that the business model canvas has nine building blocks; I am concentrating on those where the impact and propagation effects on other blocks are greatest. In my approach, I will loosely follow the digital business modelling methodology described by my colleagues Uwe Riss and Marco Cigaina in their excellent white paper.

Let’s consider conversational AI as a digital capability. Other examples of digital capabilities are the Internet of Things, Big Data, blockchain, machine learning, and so on. Introducing a digital capability will affect each of the building blocks of the business model canvas. A company’s business model describes how the organization creates, delivers, and captures value. Therefore, I am interested in how the addition of a digital capability like conversational AI to an existing business model will generate value, and how it will affect the other business model components.

So, enough with theory – let’s put it into action!

Innovate your value proposition

The heart of the business model canvas is the value proposition: the value delivered to specific customer segments, which customer problems are being solved and which needs are being satisfied.

In the picture below, you can find a representation of the business model canvas. Different blocks and colors show the digital value drivers, and explain the impact of injecting conversational AI into the value proposition. The arrows indicate the relationship between the different components, and nicely show the logic behind the business model.

First, let’s have a look at the blue boxes and arrows. Conversational AI has yielded completely new products and services that did not exist before (I am ignoring sci-fi movies here). Examples are Amazon Echo or Google Home, which are both smart speakers meant to be intelligent personal assistants at home. The Amazon Echo, introduced in 2015, marked the start of a whole new product category. This new product category of smart speakers appeals to new customer segments in the market, segments that Amazon or Google, or any other manufacturer, did not address before. In this way, smart speakers create new revenue streams when customers are buying these new devices.

A slightly different impact of conversational AI is depicted with the green boxes and arrows. Here, conversational AI is used to enrich existing products and services – that is, it provides extra functionality on top of an existing product. A good example is Apple Siri: it was introduced in 2011 as an integral part of the iPhone 4S, augmenting its value proposition. At that time (and probably still today), nobody bought an iPhone exclusively because of Siri, but having the assistant available at one’s fingertips (literally!) certainly contributed to the overall value perception of the device. The same goes for Google Assistant.

Another example, but in a business context, is SAP CoPilot, SAP’s digital assistant for the enterprise. SAP CoPilot offers new ways of interacting with SAP software, with features like collaboration and context awareness – and soon, also natural language interaction.

Adding new functionality to existing products

For all these examples, conversational AI has added new functionality to existing products and services to address a wider range of customers. The new functionality will appeal to a wider audience so more people will be converted into customers, leading to incremental revenues. Incremental revenues will also be generated when new functionality leads to increased usage of your product or service.

A special group worth mentioning in this context are users with special needs, such as blind or visually-impaired users, or users with physical disabilities who cannot easily operate graphical user interfaces.

The yellow boxes and arrows show some “spinoff effects,” which create value and indirect revenues. One of the effects of conversational AI is that it lowers the barrier to interact with a product or service. Combined with its ubiquitous access, the effect will be that you can more easily lock customers into your ecosystem. For example, it’s likely that a user of Amazon Echo also uses other Amazon services such as Amazon Prime.

Another effect is the collection of customer data through millions of conversations with users. This data is a true goldmine. Not only can it be used to train and improve the machine learning models powering conversational AI; it will also allow for more personalized conversations and advertisements. It’s a closed loop: the more conversation you have with the system, the more the system gets to know you and learns your patters and preferences, and the better it will be at predicting your needs and making suggestions.

In my next blog, we’ll explore how conversational AI can change the way you interact with your customers.

Read Innovate Your Business Model With Conversational AI: Part 1.


Ivo van Barneveld

About Ivo van Barneveld

Ivo van Barneveld is a passionate evangelist of innovations in user experience, mobile, and Internet of Things. His work focuses on the intersection of technology and business. He is currently a member of the UX Customer Office team in SAP Global Design, with the remit to drive adoption of SAP’s award-winning user experience, SAP Fiori. Previously, he worked at SAP as a lead consultant, supporting customers with planning and executing digital transformation strategies. Prior to joining SAP in 2012, he held several business development, account manager, and partner manager roles at Nokia and Layar, among others. Ivo holds a Master’s degree in Applied Physics from the Delft University of Technology, and is based in the Netherlands.

How Facebook And Data Privacy Are Pushing Boundaries Of Trust

Paul Taylor

Mark Zuckerberg’s appearance before Congressional investigators probing the Facebook user-data scandal has highlighted the trust chasm that has opened between consumers and some of the biggest brands in the Internet era.

As a result, we have reached an inflection point in the debate over consumer data privacy and regulation in the U.S. that could have far-reaching consequences not only for consumer brands, but also the technology companies that provide the tools brand leaders use to manage the customer experience.

The implications of this trust deficit were reflected in the comments of Rep. Michael Doyle, a Democrat from Pennsylvania, who told Facebook’s CEO during one exchange: “To my mind, the only way we will close the trust gap is through legislation that creates and empowers a sufficiently (powerful) oversight agency with rule-making authority to protect the digital privacy and ensure that companies protect our users’ data.”

Ramming home his point, Rep. Doyle added; “Why should we trust you to follow through on these promises when you have demonstrated that you’re willing to flaunt your internal policies and government oversight when the need suits you?” Zuckerberg had no real answer.

At the root of the problem are what might be called the “terms of trust.” Consumers want a personalized, customized experience online, but not at any cost. Consumers will share information about themselves in return for something, e.g., better products and better services. But they will only do that if they can control and understand what’s happening with their data. This is what is technically thought of as “consent.”

“We are moving to a world where data is probably the most valuable asset, but trust is the ultimate currency in this new data economy,” says Patrick Salyer, chief executive of SAP’s recently acquired Gigya unit. “Trust is everything. The next leading brands will be the most trusted brands,

He argues that over the past decade, brands have delivered on personalization, but that at some point a line was crossed. “They began tracking people without their permission and creepy things were happening,” he says. “Their data was being sold without their knowledge. Ultimately, all of this has eroded consumer trust.”

In fact, a recent survey suggested that two-thirds of consumers don’t trust brands anymore. “Consumers still want personalization,” he says, “I don’t think that’s something they want to move away from, but transparency and control around their data is becoming critical.“

Download the free e-book Personalization: How to Avoid Crossing the Line from Cool to Creepy.

This article originally appeared on Forbes SAPVoice.


Making The Strongest Case Possible For Platform Migration

Joseph Msays

Driven partly by the optimistic economic outlook and partly by the increasing maturity of the platforms available in the marketplace today, more companies than ever are planning migrations to digital platforms. By 2020, it’s estimated that 60% of all enterprises will be in the process of implementing an organization-wide strategy.

If your company is among them, you’re probably already shaping a business case to justify the capital expenditures your migration will require. To maximize your chances of success, there are several key topics you’ll need to plan for, including:

  • Digital transformation initiatives
  • Future business models
  • Cutting-edge technologies

Building a new foundation for digital transformation

The business benefits of a technical platform migration are usually not enough on their own to justify the cost. The true value of platform migration comes from the fact that it serves as the core of an organization’s digital transformation efforts, helping them tackle the challenges of a changing business world.

By now, most organizations already have big ideas about how they’re going to approach digital transformation, but all those ideas aren’t worth much without the funding needed to put them into action. According to the Global Innovation 1000 report from Strategy+Business, average R&D intensity – a measurement indicating innovation spending as a percentage of total revenues – reached an all-time high of 4.5% in 2017, with many well-known companies spending significantly more than average. Clearly, many organizations have already recognized the growing importance of shifting more resources toward innovation.

Your business case should show how platform migration will help simplify and streamline your IT environment, including business processes, information flows, and infrastructure. Taking complexity out of your environment can help reduce operational expenses, freeing up new funding to dedicate to innovation. Reducing complexity also paves the way for you to implement new innovations quickly, while limiting disruption to ongoing processes.

Preparing for success with future business models

Many companies have a well-built and well-maintained ERP solution for today’s business, but can’t say for sure that they’re prepared for the future, when they’ll likely face threats from new digital entrants.

Quantifying the benefits of a present-day migration against future business models is easier said than done. However, it’s a challenge that must be overcome in order to build a compelling business case. To do so, companies must be able to define their future business model in concrete terms and understand how the new platform will flexibly support it.

One example of this is enterprise mobility. With a generation of young people who can’t remember a time before smartphones entered the workforce in large numbers, the need for enterprises to adopt a mobile strategy is clear.

However, enterprise mobility can be both a challenge and an opportunity. When adding enterprise mobility to their business plan, organizations must know the investment needed and accurately predict how the future benefits of reinventing work will make this investment worthwhile.

Embracing new technologies

To meet the business requirements of tomorrow, organizations must embrace transformative new solutions like blockchain, artificial intelligence, machine learning, robotic process automation, and cloud microservices. These new technologies will help them work across both structural and skills barriers.

It’s impossible to overstate the potential impact these new technologies could have on the business world, and the transformation is taking place right in front of our eyes. According to IDC, worldwide spending on cognitive and AI will reach US$57.6 billion by 2021, representing a compound annual growth rate of 50.1% over a five-year period.

Building a robust business case requires an organization to look beyond the immediate platform migration itself; they must also consider how these technologies will fit into the new platform. By doing so, organizations can feel confident that when the time comes, they’ll be fully prepared to capitalize on the massive opportunities these technologies present.

This post provides a few examples of the things you can’t afford to leave out of your business case. Working with a migration partner can help you gain the deep business and technical insights you need to make sure you don’t miss anything else.

If SAP S/4HANA is your platform of choice, IBM offers a number of tools to help you build a business case that quantifies and communicates the value it can offer. Request an SAP S/4HANA impact assessment today to get started.

IBM will be at SAPPHIRE NOW and ASUG Annual Conference June 5-7 in Orlando. Visit IBM at booth #612 and talk to IBM experts. Check out our event website to see what we’re doing at the event.

Also, visit our website to learn more about how IBM can help accelerate your migration to SAP S/4HANA.


Joseph Msays

About Joseph Msays

Joseph Msays is an experienced IBM global executive, currently serving as Vice President and Global Managing Partner for NextGen Enterprise Cloud Applications Center of Excellence. In this role, he is pioneering new ways of engaging CxOs in their digital reinvention agendas, and building and migrating new cloud-based business applications. Joseph has experience managing many IBM professional services units and large strategic systems, integration and outsourcing relationships, and has lived and worked in virtually every major market across the globe.

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.

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Survey: Four Ways Machine Learning Will Disrupt Your Business

Dan Wellers and Dirk Jendroska

We are entering the era of the machine learning enterprise, in which this subset of artificial intelligence (AI) capabilities will revolutionize operating models, shake up staffing methods, upend business models, and potentially alter the nature of competition itself. The adoption of machine learning capabilities will be limited only by an organization’s ability to change – but not every company will be willing or able to make such a radical shift.

Very soon, the difference between the haves and the have-nots of machine learning will become clear. “The disruption over the next three to five years will be massive,” says Cliff Justice, principal in KPMG’s Innovation and Enterprise Solutions team. Companies hanging onto their legacy processes will struggle to compete with machine learning enterprises able to compete with a fraction of the resources and entirely new value propositions.

For those seeking to be on the right side of the disruption, a new survey, conducted by SAP and the Economist Intelligence Unit (EIU), offers a closer look at organizations we’ve identified as the Fast Learners of machine learning: those that are already seeing benefits from their implementations.

Machine learning is unlike traditional programmed software. Machine learning software actually gets better – autonomously and continuously – at executing tasks and business processes. This creates opportunities for deeper insight, non-linear growth, and levels of innovation previously unseen.

Given that, it’s not surprising that machine learning has evolved from hype to have-to-have for the enterprise in seemingly record time. According to the SAP/EIU survey, more than two-thirds of respondents (68%) are already experimenting with it. What’s more, many of these organizations are seeing significantly improved performance across the breadth of their operations as a result, and some are aiming to remake their businesses on the back of these singular, new capabilities.

So, what makes machine learning so disruptive? Based on our analysis of the survey data and our own research, we see four primary reasons:

1. It’s probabilistic, not programmed

Machine learning uses sophisticated algorithms to enable computers to “learn” from large amounts of data and take action based on data analysis rather than being explicitly programmed to do something. Put simply, the machine can learn from experience; coded software does not. “It operates more like a human does in terms of how it formulates its conclusions,” says Justice.

That means that machine learning will provide more than just a one-time improvement in process and productivity; those improvements will continue over time, remaking business processes and potentially creating new business models along the way.

2. It creates exponential efficiency

When companies integrate machine learning into business processes, they not only increase efficiency, they are able to scale up without a corresponding increase in overhead. If you get 5,000 loan applications one month and 20,000 the next month, it’s not a problem, says Sudir Jha, head of product management and strategy for Infosys; the machines can handle it.

3. It frees up capital – financial and human

Because machine learning can be used to automate any repetitive task, it enables companies to redeploy resources to areas that make the organization more competitive, says Justice. It also frees up the employees within an organization to perform higher-value, more rewarding work. That leads to reduced turnover and higher employee satisfaction. And studies show that happier employees lead to higher customer satisfaction and better business results.

4. It creates new opportunities

AI and machine learning can offer richer insight, deeper knowledge, and predictions that would not be possible otherwise. Machine learning can enable not only new processes, but entirely new business models or value propositions for customers – “opportunities that would not be possible with just human intelligence,” says Justice. “AI impacts the business model in a much more disruptive way than cloud or any other disruption we’ve seen in our lifetimes.”

Machine learning systems alone, however, will not transform the enterprise. The singular opportunities enabled by these capabilities will only occur for companies that dedicate themselves to making machine learning part of a larger digital transformation strategy. The results of the SAP/EIU survey explain the makeup of the evolving machine learning enterprise. We’ve identified key traits important to the success of these machine-learning leaders that can serve as a template for others as well as an overview of the outcomes they’re already seeing from their efforts.

Learn more and download the full study here.  

 


Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Dirk Jendroska

About Dirk Jendroska

Dr. Dirk Jendroska is Head of Strategy and Operations Machine Learning at SAP. He supports the vision of SAP Leonardo Machine Learning to enable the intelligent enterprise by making enterprise applications intelligent. He leads a team working on machine learning strategy, marketing and communications.