Tested For You: How Are European Retailers Performing In Online Customer Service?

Martin Stocker and Erica Vialardi

The sunny and warm weather has finally arrived. What could be more fun than having some cocktails and nice foods on your terrace together with friends? My colleague Erica and I decided to meet on a Saturday afternoon for a summer barbecue with our families. I would take care of the preparation of the barbecue itself, while Erica would look into the cocktails.

Since we both like good and innovative online shopping experiences, we decided to make it a little bit more challenging and ended up testing the online customer services of the top 10 European online retailers to get everything ready for the party. We were both confident that, in the golden age of online retailing, the whole setup would go smoothly. In reality, we went through quite surprising experiences.

What makes customer service future-proof

Finally, we met for the barbecue and had a very nice time with good food and fresh cocktails. In the kitchen, Erica took me aside and told me, “It was fun to do the cocktails stuff, but not all parts of it. I thought it would be way easier!” I shared the same impressions with her.

To test which of the top 10 European retailers would score best in terms of online customer service performance, we selected the two main criteria that, today, prove a retailer’s ability to walk down a future-oriented path in customer service:

1) the customer engagement effectiveness of their customer service

2) the availability of self-service channels

Each criterion got an assessment on a 1 to 10 scale, where 1 means “not available” and 10 means “extremely effective and innovative”. Are retail brands walking the walk, or just talking the talk of providing great online customer service?

Forward-thinking retailers don’t wait for a complaint

The first criterion we assessed was the level of customer engagement that retailers could provide on the customer service side. Leading retailers are aware that customer service is increasingly becoming an actual engagement channel and no longer a mere post-sale troubleshooting tool.

The differentiator here lies in the ability to provide customers with enough valuable product information so that they can have all their questions answered before they make the purchase decision, and in addition, are encouraged to increase the value in their shopping carts. The elements we analysed to assess customer engagement performance in service included: detail of product description; product advice and suggestions of use through service channels; cross-and up-selling; personalization tools; and re-marketing through service channels.

Testing brought its share of fun and sharing our experiences ended up in conversations like this one:

Martin: “I hoped that some online shops would support a much more intelligent and convenient way on how to find the items on my list. Take the new gas bottle for my barbecue: unfortunately, when I browsed the first online shop, the size of the bottle was not the perfect fit for my grill.”

Erica: “Do you mean that not only didn’t the store recommend products related to a specific grill, even a basic thing like a gas bottle, but they couldn’t even provide more product information through their service channels?”

Martin: “Exactly! I wished I could, for example, have immediately chatted with a store consultant when visiting the page of the gas bottle to get some product advice. Some of the online shops did indeed have a Service button, but when I clicked on it, I got the usual contact information via phone, email to address technical or delivery issues only. What held me back from purchasing was not getting a helpful answer fast enough about the product I wanted to purchase.”

Erica: “Frustrating! Now I understand why you had to drive to the next DYI store to talk to a salesperson.”

A multifaceted gem called self-service

The second criterion was about measuring the retailers’ performance in offering self-service channels, which enable customers to solve their service requests on their own and find answers with ease, without having to contact a service operator. The higher the number of self-service channels, the higher the score of the retailer. We analysed the presence of the following self-service methods at each retailer’s website: FAQs; buying guides; personalization tools; customer communities and ratings; and chatbots.

Here again, the two of us had interesting conversations, for better or for worse:

Erica: “I wanted to make everything ready to be the ‘hostess with the mostest’ that day, so I went on an online quest for cocktail items on two different home goods online retailers. When looking for barware, I heavily relied on self-service tools to guide me in my purchase. Through communities, peer reviews and Q&As, I could easily determine that a key differentiator in a cocktail shaker was the lid and felt confident in my purchase.”

Martin: “Now that’s what I call great service! Better than my experience with the gas bottle for sure. At least you found all the info on your own, directly on the website.”

Erica: “Wait—unfortunately, the fun didn’t last long. When it came to the actual cocktail preparation, I would have expected at least something as simple as a link to a cocktail recipe book on the glassware section of the store, but it wasn’t available anywhere. This made it very hard for me to choose the right glasses and… guess what?”

Martin: “… you clicked away and ended up on Google.”

European retailers could serve themselves better

There is still a long way to go, but with our research, we could highlight some strengths and growth opportunities. Here is the final ranking:

The strongest performers overall were by far the UK apparel and home goods retailers. They showed very advanced service functionality, such as a striking 20-question personalization tool to select the best outfit, and in another case, sophisticated, searchable communities together with product comparison tools.

The two biggest German fashion vendors provided good service performances, the only ones with a live chat available on their homepages that also included a separate, product advice chat. A good experience, which combined the advantages of an online and an offline shop. No long waiting times, direct responses, and very uncomplicated recommendations.

The third and last cluster were the grocery retailers from France, who offered the weakest performance in terms of customer engagement and self-service capabilities and instead seemed to concentrate most of their service efforts on the delivery/pickup side, which may reflect the intrinsic nature of the fresh food industry, where convenient delivery is a priority.

The first takeaway of our research has been that good service is key to hold consumers from clicking away. Eighty-six percent of all consumers are indeed likely to pay for good service or pay more for their items on the shopping list. Another finding was that customer service should start transforming from solving “administrative” complaints to managing revenue-generating customer engagement activities.

In addition, it still seems to be hard for retailers in specific branches to move away from their product-based core businesses toward a more service-oriented offering, based on the usage/experience for the consumer. Here again, service will play an ever more discriminating role in customer retention in the future.

Conversational commerce is today

Probably inspired by the lavish dinner and cocktails, a thought struck us: Isn’t it a paradox that with today’s availability of sophisticated online, one-to-one conversational channels that brands could only dream of five years ago, those same conversational channels are still often used as mere “complaint centres”? Turn the complaints into opportunities, and you will transform those tools into powerful customer engagement gates, in times where boundaries between service, marketing and commerce are blurring.

For example, with intelligent chatbots, both authors are convinced, shopping will be much easier, faster, and more convenient. Even supermarkets could offer their customers a menu with the ingredients they are looking for and put these on their pick list. It is worth noting that of all 10 retailers we tested, not one used chatbots on their online stores yet.

One conversational commerce tool that is already existing and working is Chatbot Charly, developed at SAP Hybris Labs. It would be a win for both sides: retailers could serve their customer needs, increase the satisfaction and the revenue of their shoppers, and consumers could spend more time on the most important things in life: having a great time with their families and friends.

For a in-depth analysis of the evolution of customer service, shifting from strictly a post-sale approach to an entire end-to-end process, read the report “Supporting the Buying Journey with Customer Service” from Forrester.


Martin Stocker

About Martin Stocker

Martin Stocker is Director of Global Programs Marketing at SAP Hybris.

Erica Vialardi

About Erica Vialardi

Erica Vialardi is the EMEA Audience Engagement Marketing Manager at SAP Hybris.

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.

How Real-Time Consumer Intent Is Changing The Sales Cycle

Ralf Kern

As a marketer, it’s your job to know what a consumer bought, thought, and did a month ago, a week ago, and even yesterday. But do you know what a consumer is thinking right now?

Understanding real-time consumer intent allows marketers to deliver targeted information, like special product promos or offers, at the exact moment in time when a consumer is searching for this information. Real-time intent is a powerful marketing tool that helps businesses close more deals by providing the information consumers need at the exact moment they’re open to receiving this information. This drives decision-maker consensus, reduces barriers to sales, and primes consumer to take immediate action.

The contemporary sales cycle: More options, more stakeholders, more challenges

Motivating a customer to complete a purchase has always been a challenge for sales and marketing professionals at both B2B (business-to-business) and B2C (business-to-consumer) companies. At B2B companies, for example, shrinking budgets and a greater wealth of available options has led to longer sales cycles. More decision-makers means everyone needs to weigh in on a potential decision. This makes it more difficult to drive stakeholder consensus and also lengthens the decision-making process. Everyone wants to have a voice in the decision, but no one wants to be the deciding voice and risk getting blamed if the decision is a mistake.

The B2C decision-making cycle is also changing, thanks to social media and smartphone technology. Mobile shopping is disrupting the consumer decision journey for retail. Google reports that while foot traffic in retail stores has declined by 57% in the past five years, the value of every visit has nearly tripled. With smartphones in tow, consumers are researching product information, checking social media for product reviews, and doing a quick price comparison search before they make a purchase. Most significantly, these mobile searches are happening at the exact moment consumers are in stores. They’re holding the product in their hands, asking, “Should I buy this right now?”

How does intent targeting increase sales?

Intent targeting allows businesses to reach consumers at these critical, decision-making moments. Whether it’s delivering a case study that drives decision-maker consensus at a B2B company or targeting consumers with a special promo discount while they’re doing a mobile price comparison, intent targeting delivers the right information at the right moment.

Intent targeting is different than showing an ad on a website that simply mirrors that website’s content. When businesses truly understand real-time customer intent, they can target a customer with information aligned with the consumer’s needs across a variety of touch points. Most importantly, the timing is spot-on: marketers can target a customer at the exact moment that customer is open to receiving information.

Targeting consumers in the moment with dynamic, contextually relevant experiences

Successful customer engagement must be proactive, tapping into the emotional drivers behind the buying process and delivering relevant customer experiences in real time. The more compelling and relevant the experience, the more likely customers will stay engaged (or re-engage) during the buying journey.

In order to successfully engage with today’s customers, businesses need more than just historical data. They need knowledge of “in-the-moment” customer activity to accurately target and deliver relevant and engaging customer offers and promotions. They need to understand the real-time intent of each customer and dynamically deliver contextually relevant experiences across channels. This requires a 360-degree view of customer’s behavior and actions. Businesses need to be able to process large volumes of structured and unstructured data, score implicit and explicit behavior across channels, and convert this information into real-time insights that drive marketing decisions.

Static customer segmentation approaches don’t cut it anymore. Progressive customer profiling taking into account each and every customer interaction and sentiment are required to show empathy, build trust, and earn customer loyalty. Customer happiness is the ultimate currency in retail. A concise and contextual brand experience based on a deep understanding of the customer is a prerequisite to creating customers for life.

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?


Ralf Kern

About Ralf Kern

Ralf Kern is the Global Vice President, Business Unit Retail, at SAP, responsible for the future direction of SAP’s solution and global Go-to-Market strategy for Omnicommerce Retail, leading them into today’s digital reality.

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: http://linkedin.com/in/shaily Twitter: https://twitter.com/meisshaily