How Digital Marketplaces Are Disrupting The Insurance Industry

Aditya Das

On January 30, 2018, Amazon, Berkshire Hathaway, and JPMorgan announced that they were forming an independent healthcare company.

The news threw the insurance market into a tizzy. CEOs of other large insurers met in the days following the announcement to explain how they were technologically future-proofing themselves. While the new company’s focus will be on their employees – combining Amazon’s customer engagement, BH’s insurance and reinsurance know-how, and JPMorgan’s relationships – the alliance represents a significant disruption in the industry.

Why did this partnership cause such consternation among industry incumbents? According to a recent report of Venture Scanner, there are at least 1500 insurance companies globally, with funding of USD 20 billion. And there are other promising game-changers on the horizon. South African insurer Discovery’s Vitality program has made significant waves in the health insurance industry, and startup insurers like Lemonade, Metromile, and Trov are transforming the models for insurance across the engagement cycle. But none seem to have created dissonance on the same level as the Amazon-Berkshire Hathaway-JPMorgan alliance.

It’s safe to assume that the reason has much to do with Amazon, as Berkshire Hathaway and JPMorgan have existed as they are for years. What makes Amazon such a major disruptor? The company brings a strong, scalable, and, most importantly, proven platform for digital customer engagement across a multitude of categories – both B2B and B2C. Digital is the key.

Why is digital such a game-changer for insurance?

Arguably, digital has been the most-discussed topic in recent times in the insurance world. The new age heralded by hyperconnectivity, cloud computing, supercomputing, and smart technologies promises to completely transform this industry from its traditional operating model of the last 300+ years. A massive shift is anticipated as the interplay of digital technologies now offers new possibilities, such as:

  • Complete individualization of risk for all assets, life, and health
  • Significant disintermediation of distribution and engagement
  • Embedding insurance in digitally enabled ecosystems like wellness, mobility, etc.

These possibilities have spawned a new breed of innovators known as insurtechs. Most insurtechs are either focused on customer acquisition or are targeting a part of the insurance value chain to help drive efficiencies. In either case, they are working with an insurer to influence the latter’s operating model. However, a handful of these startups are attempting to completely disrupt the conventional business models by engaging directly with the insured.

Most established insurers today know that it is just a matter of time before their business models completely transform. However, their investments in, and revenue dependence on, existing operating models act as a deterrent from proactively seeking disruption. Instead, some insurers are trying to avoid impending disruption by nurturing startup accelerator programs or committing investments into independent units within the company to incubate new business models.

Despite these strategic investments, these companies continue to resist the “Uberization” of the insurance industry by rejecting the convergence of innovation and scale. A quick analysis of successful disruptors like Uber, AirBnb, and TripAdvisor shows that these disruptors have done three things very effectively:

  • Large-scale aggregation: Created a huge canvas of choices at the consumers’ fingertips
  • Complete delayering: Removed intermediate layers to allow direct customer engagement
  • Self-contained ecosystem: Built and leveraged a large, strong ecosystem of product or service providers, logistics, payment, financers, etc. to enable significant efficiencies of cost and/or time

All of these companies had to get providers on board to bring scale, but once they had achieved a reasonable scale, the other two factors ensured a huge customer base, leaving other providers little choice but to join their platform.

What does it take to disrupt the insurance industry?

If we look at the insurance purchase process today, except for the very simple low-ticket items, most purchases start on a digital medium and remain there for a while – until the customer consciously seeks a sustained physical engagement in the validation phase and selects either a physical or digital closure. A good part of the decision-making happens while the digital touchpoints are being traversed and the digital content is being consumed over proprietary or curated third-party forums and social media.

Talking to digitally inclined customers who have completed an insurance purchase reveals that there are a number of different journeys customers can follow. Most are “phygital” – i.e., customers jump between digital and physical touchpoints during their journey. In my opinion, most digitally inclined players in the insurance industry – including insurers, distributors, and aggregators – are just starting to understand and align with customer journeys well enough to influence conversion or closure.

Many insurance manufacturers have recently been investing in advanced digital marketing and marketing automation tools to influence the pre-purchase process. The jury is still out on these, as the visible impact on the top line is not yet clear. At the risk of sounding repetitive, I feel the critical gap has been the limited ability to track and align with customer journeys. The fact that insurance is a “push” rather than a “pull” business adds to this complexity.

In the light of the above, the entry of Amazon and others adds a new dimension to the industry. Such marketplaces bring unique capabilities, including:

  • A strong understanding of how to track and influence customer journeys
  • A large, loyal customer base that comes to them to purchase anything and everything
  • A large portfolio of products with a natural affinity for bundled insurance

In my opinion, the likes of Amazon are ideally placed to disrupt insurance distribution. They have a set of core strengths in digital customer engagement. This, complemented with insurance product and process know-how, can help create innovative models for insurance when carefully orchestrated in tandem with the manufacturers. Berkshire Hathaway and JP Morgan will act as strong accelerators to build scale on the provider side; in many countries, this model can also be affected by a large progressive insurer and a hospital chain.

What could the marketplaces do differently?

Insurance marketplaces could consider the following three tactics:

  1. Maximizing bundled insurance – For products like mobile devices, electronic appliances, etc. where “bundled protection” is a possibility, insurance can be calibrated to the buyer’s profile and protection requirements – which should be cheaper than current stand-alone offers. A “digital exchange,” where insurance manufacturers can push real-time quotes based on appliance buyer’s profile can be a game-changer in this segment. Customer journeys could also be analyzed to optimize the insurance purchase during and after the mobile/appliance purchase.
  1. Innovating for millennials – For millennials whose first port of call is the digital marketplace, “bite-sized” innovative lifestyle protection products could gain traction. Products that are simple to understand and straightforward can bind this segment for good. This approach will also expand the market by creating a completely new product-market segment that can be engaged for deeper portfolio penetration through lifestyle/life events mapping.
  1. Algorithmic targeting – Insurance purchase and retention, like any other purchase, can be predicted. Analytics-led digital targeting for stand-alone insurance purchases has been proven to drive retention and life insurance renewals (also called persistency). With their proven competence in consumer analytics, digital marketplaces are much better positioned to monetize this. This approach will require a strong interplay among actuarial, sales, and analytics teams. Eventually, it will be key to building a profitable life insurance portfolio, which will be critical to drive scale for a marketplace.

Digital marketplaces can eventually work with insurer product teams to target long-term insurance products, including pensions and annuities, to build profits of significant scale through “phygital” customer journeys.

What’s next?

The next 6-12 months will see decisive moves by Amazon, BH, and JPMorgan – first for their employees and then for the larger U.S. market. Flipkart, a marketplace that’s larger than Amazon in India, will launch its own insurance offering there, and it’s likely that other evolved marketplaces in other economies will also make plans to enter the insurance market.

While Amazon will have Berkshire Hathaway and JPMorgan for insurance expertise and a provider ecosystem, the pace of entry and success for other newcomers will depend on their ability to develop and grow similar partnerships. I believe that marketplaces will carve a niche for a large category of insurance products and disrupt insurance consumption for good.

For more insight on digital disruption in the insurance industry, see The Must-Do Bucket List For Insurance Providers Moving Into 2018.


Aditya Das

About Aditya Das

Aditya leads the insurance practice for SAP Indian Subcontinent from a domain perspective. In his role he engages with Insurance leaders to help them chart a transformation roadmap to leverage the digital economy. Aditya is an engineer and a MBA. After his initial years in management consulting, he has spent about 15 years in Insurance - 8 years with a leading Insurance MNC and 7 years with Analytics and Technology providers focused on Insurance. Aditya is passionate about strategy, growth and innovation."

How Restaurants Can Survive Digital Disruption

Stephanie Waters

The restaurant business is being disrupted by new, digitally enabled competitors. In 2016, delivery transactions made up about 7% of total U.S. restaurant sales. Predictions are that restaurant delivery could eventually reach 40% or higher.

Third-party delivery services such as UberEats, GrubHub, Amazon Restaurants, and Deliveroo have emerged, and while they can increase brand awareness for some restaurants, their fees can be as high as 30% of the transaction. Many restaurants can’t survive that kind of margin hit.

Ambitious food delivery services now want to get more involved in food preparation. UberEats recently acquired Ando, a delivery-only ‘restaurant’ founded by Momofuku chef David Chang.

TGI Fridays, the iconic casual dining chain with 500 locations, is up to the challenge. In the first year they introduced online ordering, take-out sales grew 30%, online order size was 7.2% higher than in-restaurant, and more than 70% of online orders came from new customers. They’ve also recently announced a partnership with Lash, a startup in Dallas, to deliver alcohol and food. The company is also working on an at-home bartending service to offer a more complete TGI Fridays experience outside of the restaurant.

What’s next: How restaurants can survive digital disruption

So, what’s next? Restaurants can survive digital disruption, right?

There are success stories of restaurants preparing for and staying ahead of the disruption in their industry. But there are also lessons to be learned from other retailers’ false starts, e.g.:

  • Taking the fast and easy route of partnering with a third-party provider for your online delivery business, only to have them acquired by one of your biggest competitors
  • Over-investing in an elaborate warehouse and distribution system for an initial foray into selling online, rather than using existing store assets to build scale
  • Building a supply chain system from scratch that results in empty shelves and unhappy employees, rather than choosing a best-in-class, time-tested solution

For restaurants to succeed in the face of industry disruption, they need to:

  • Have leadership vision and commitment
  • Look outside your industry to fill resource and experience gaps
  • Explore what the world has to offer in terms of business models and solutions
  • Be open to coopetition partnerships and acquisition

But most of all, restaurants need to select a technology partner that has:

  • The industry expertise, resources, and tools to help you create your vision and build your strategic plan and road map
  • Market-leading “innovation to execution” pre-integrated modular solutions
  • Long-term financial stability to invest in new technologies such as IoT, artificial intelligence, machine learning, conversational commerce, blockchain, and more
  • Global experience with local presence and expertise

Learn more about what your customers want here

This article originally appeared on The Future of Customer Engagement and Commerce.


Connected Marketing: How IoT Is Revolutionizing Customer Engagement

Joerg Koesters

It’s 6 pm, and you’re driving home from work, using a navigation app to make your way through rush-hour traffic. As you pass one of your favorite fast-food restaurants, a 2-for-1 deal pops up on your navigation screen. Seconds later, you’re in the restaurant’s drive-thru, about to enjoy a tasty snack.

This example of real-time customer engagement is not a futuristic scenario. It’s happening right now, thanks to new connected technologies driven by the Internet of Things (IoT). IoT is transforming the way companies and customers interact by revolutionizing customer engagement, leveraging data and insights for real-time action.

How IoT is changing customer engagement

A company’s interaction with its customers used to be limited to the point of sale. Companies had to piece together data from anecdotal feedback, customer surveys, product returns, and customer service complaints to gather any insight into their customer’s needs and behaviors. Consequently, customer engagement was reactive rather than proactive. That’s all changing thanks to data available through the Internet of Things.

IoT has long been the domain of industrial B2B (business-to-business) applications. Now, B2C (business-to-consumer) companies are beginning to understand the power of IoT to revolutionize customer engagement. Consumer brands like Nestle, Philips, and Target are using IoT applications to better predict and respond to consumers’ needs.

Using IoT to exceed consumer expectations: 3 applications for B2C companies

Today’s digital-savvy consumers expect personalized products and services that suit their unique needs and situations. They also expect contextual and meaningful interactions through their choice of channels. IoT technology makes both possible by connecting people, processes, and things. IoT platforms provide immediate, actionable insights so companies can respond to customer needs in real time. The result: Companies do not just meet customer expectations—they exceed them.

Here’s how IoT is transforming customer engagement for B2C companies:

  1. Creating new points of differentiation by shortening the R&D cycle:
    IoT allows companies to interact with customers in unique ways, differentiating these companies from other businesses that have not made IoT engagement a priority. Product developers, for example, can gain valuable insights from customer feedback and immediately apply these insights to deliver higher-performing products and services. By better understanding how customers use their products, developers can update features to better align with customer needs and expectations.
  1. Refining the marketing process with greater personalization:
    IoT offers a tremendous volume of data on consumer habits and behaviors, positioning companies to better understand customers’ needs and wants. Rather than flooding customers with an onslaught of poorly timed advertising, companies can better market their products to customers at the exact moment of need. Personalized, “in-moment” offers – like the one described above – also reduces unnecessary marketing expenditures and delivers a better advertising ROI.
  1. Strengthening customer loyalty: IoT makes it possible for companies to act on real-time data insights by offering rewards and discounts. For example, CITO Research reports that Coca-Cola gathered data from its vending machines and determined that beverage consumption spikes on college campuses at specific times correlated with popular TV shows. Coca-Cola can then use this data to offer targeted rewards through cross-promotions, driving immediate consumer action and boosting brand loyalty.

Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value: Accelerating Digital Transformation in Retail. Explore how to bring Industry 4.0 insights into your business today: Industry 4.0: What’s Next?


Joerg Koesters

About Joerg Koesters

Joerg Koesters is the Head of Retail Marketing and Communication at SAP. He is a Technology Marketing executive with 20 years of experience in Marketing, Sales and Consulting, Joerg has deep knowledge in retail and consumer products having worked both in the industry and in the technology sector.

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: