Sections

Weigh The Economics Of Higher Education

James Krouse

Fifty years ago, educational success meant graduating from high school. Thirty years ago, the same level of success required graduation from college. Today, to remain competitive, “success” requires a master’s degree. Recruiters now want to see multiple degrees on resumes. The bar to stay competitive in today’s job market continues to rise—but so too does the cost of higher education.

For decades, the assumed rite of passage for higher education was the standard four-year degree, earned on an idyllic landscaped campus, surrounded by your peers. But with the competitive pressure to attain ever-higher levels of education, does that traditional campus-based standard hold up?

Increasingly, it does not. College costs are skyrocketing. While proponents of the traditional campus model might argue that a significant part of “higher education” is the experience of the college environment and life learning, the economic pendulum continues to swing. College can be both fun and educational, but perhaps students are simply becoming more practical: economics trumps fun?

Online coursework, virtual learning, collaborative educational channels – all can serve as a path to a degree; none require on-campus attendance.

One approach many of today’s students are taking is to attend more affordable junior colleges, which enable them to work toward a degree while maintaining a relationship with four-year institutions. In this case, the student attends a junior college for two years, saving thousands of dollars on tuition and fees, and then transfers into a four-year program to complete their degree. The degree highlighted on the resume is the same; all that’s missing are those social activities and the idyllic environment of the college campus.

University Business magazine (@universitybiz) profiled an online university that entered an agreement in which community college students can apply their coursework toward a master’s degree. The Washington State Board for Community and Technical Colleges signed the agreement with Western Governors University Washington – a not-for-profit university.

These are just two examples of how students are re-examining the higher education cost vs. benefit model, and how the system is adapting to maintain educational excellence and professional growth in the face of escalating expenses.  Education costs must be balanced against the perceived rewards: The balance appears a continual shift toward economics.

For more on how economics and the digital economy is changing higher education, see The Future Of Learning – Keeping Up With The Digital Economy.

Comments

James Krouse

About James Krouse

James Krouse is the director of Global Solutions Marketing at SAP. He is the global strategic marketing lead for the healthcare and higher education industry groups and is responsible for tailoring GTM strategies, analyst relations, government relations, positioning, and messaging.

What Gen Z’s Arrival In The Workforce Means For Recruiters

Meghan M. Biro

Generation Z’s arrival in the workforce means some changes are on the horizon for recruiters. This cohort, born roughly from the mid-90s to approximately 2010, will be entering the workforce in four Hiring Generation Z words in 3d letters on an organization chart to illustrate finding young employees for your company or businessshort years, and you can bet recruiters and employers are already paying close attention to them.

This past fall, the first group of Gen Z youth began entering university. As Boomers continue to work well past traditional retirement age, four or five years from now, we’ll have an American workplace comprised of five generations.

Marketers and researchers have been obsessed with Millennials for over a decade; they are the most studied generation in history, and at 80 million strong they are an economic force to be reckoned with. HR pros have also been focused on all things related to attracting, motivating, mentoring, and retaining Millennials and now, once Gen Z is part of the workforce, recruiters will have to shift gears and also learn to work with this new, lesser-known generation. What are the important points they’ll need to know?

Northeastern University led the way with an extensive survey on Gen Z in late 2014 that included 16- through 19-year-olds and shed some light on key traits. Here are a few points from that study that recruiters should pay special attention to:

  • In general, the Generation Z cohort tends to be comprised of self-starters who have a strong desire to be autonomous. 63% of them report that they want colleges to teach them about being an entrepreneur.
  • 42% expect to be self-employed later in life, and this percentage was higher among minorities.
  • Despite the high cost of higher education, 81% of Generation Z members surveyed believe going to college is extremely important.
  • Generation Z has a lot of anxiety around debt, not only student loan debt, and they report they are very interested in being well-educated about finances.
  • Interpersonal interaction is highly important to Gen Z; just as Millennials before them, communicating via technology, including social media, is far less valuable to them than face-to-face communication.

Of course Gen Z is still very young, and their opinions as they relate to future employment may well change. For example, reality is that only 6.6% of the American workforce is self-employed, making it likely that only a small percentage of those expecting to be self-employed will be as well. The future in that respect is uncertain, and this group has a lot of learning to do and experiences yet ahead of them. However, when it comes to recruiting them, here are some things that might be helpful.

Generation Z is constantly connected

Like Millennials, Gen Z is a cohort of digital natives; they have had technology and the many forms of communication that affords since birth. They are used to instant access to information and, like their older Gen Y counterparts, they are continually processing information. Like Millennials, they prefer to solve their own problems, and will turn to YouTube or other video platforms for tutorials and to troubleshoot before asking for help. They also place great value on the reviews of their peers.

For recruiters, that means being ready to communicate on a wide variety of platforms on a continual basis. In order to recruit the top talent, you will have to be as connected as they are. You’ll need to keep up with their preferred networks, which will likely always be changing, and you’ll need to be transparent about what you want, as this generation is just as skeptical of marketing as the previous one.

Flexible schedules will continue to grow in importance

With the growth of part-time and contract workers, Gen Z will more than likely assume the same attitude their Millennial predecessors did when it comes to career expectations; they will not expect to remain with the same company for more than a few years. Flexible schedules will be a big part of their world as they move farther away from the traditional 9-to-5 job structure as work becomes more about life and less about work, and they’ll likely take on a variety of part time roles.

This preference for flexible work schedules means that business will happen outside of traditional work hours, and recruiters’ own work hours will, therefore, have to be just as flexible as their Gen Z targets’ schedule are. Companies will also have to examine what are in many cases decades old policies on acceptable work hours and business norms as they seek to not only attract, but to hire and retain this workforce with wholly different preferences than the ones that came before them. In many instances this is already happening, but I believe we will see this continue to evolve in the coming years.

Echoing the silent generation

Unlike Millennials, Gen Z came of age during difficult economic times; older Millennials were raised in the boom years. As Alex Williams points out in his recent New York Times piece, there’s an argument to be made that Generation Z is similar in attitude to the Silent Generation, growing up in a time of recession means they are more pragmatic and skeptical than their slightly older peers.

So how will this impact their behavior and desires as job candidates? Most of them are the product of Gen X parents, and stability will likely be very important to them. They may be both hard-working and fiscally savvy.

Sparks & Honey, in their much quoted slideshare on Gen Z, puts the number of high-schooler students who felt pressured by their parents to get jobs at 55 percent. Income and earning your keep are likely to be a big motivation for GenZ. Due to the recession, they also share the experience of living in multi-generational households, which may help considerably as they navigate a workplace comprised of several generations.

We don’t have all the answers

With its youngest members not yet in double digits, Gen Z is still maturing. There is obviously still a lot that we don’t know. This generation may have the opposite experience from the Millennials before them, where the older members experienced the booming economy, with some even getting a career foothold, before the collapse in 2008. Gen Z’s younger members may get to see a resurgent economy as they make their way out of college. Those younger members are still forming their personalities and views of the world; we would be presumptuous to think we have all of the answers already.

Generational analysis is part research, but also part theory testing. What we do know is that this second generation of digital natives, with its adaption of technology and comfort with the fast-paced changing world, will leave its mark on the American workforce as it makes its way in. As a result, everything about HR will change, in a big way. I wrote a post for my Forbes column recently where I said, “To recruit in this environment is like being part wizard, part astronaut, part diplomat, part guidance counselor,” and that’s very true.

As someone who loves change, I believe there has never been a more exciting time to be immersed in both the HR and the technology space. How do you feel about what’s on the horizon as it relates to the future of work and the impending arrival of Generation Z? I’d love to hear your thoughts.

Social tools are playing an increasingly important role in the workplace, especially for younger workers. Learn more: Adopting Social Software For Workforce Collaboration [Video].

The post What Gen Z’s Arrival In The Workforce Means For Recruiters appeared first on TalentCulture.

Image: Bigstock

Comments

Meghan M. Biro

About Meghan M. Biro

Meghan Biro is talent management and HR tech brand strategist, analyst, digital catalyst, author and speaker. I am the founder and CEO of TalentCulture and host of the #WorkTrends live podcast and Twitter Chat. Over my career, I have worked with early-stage ventures and global brands like Microsoft, IBM and Google, helping them recruit and empower stellar talent. I have been a guest on numerous radio shows and online forums, and has been a featured speaker at global conferences. I am the co-author of The Character-Based Leader: Instigating a Revolution of Leadership One Person at a Time, and a regular contributor at Forbes, Huffington Post, Entrepreneur and several other media outlets. I also serve on advisory boards for leading HR and technology brands.

How The Digital Economy Is Defining An Entire Generation

Julia Caruso

millennial businesswomen using digital technology at work“Innovation distinguishes between a leader and a follower.” – Steve Jobs

As a part of the last wave of Millennials joining the workforce, I have been inspired by Jobs’ definition of innovation. For years, Millennials like me have been told that we need to be faster, better, and smarter than our peers. With this thought in mind and the endless possibilities of the Internet, it’s easy to see that the digital economy is here, and it is defining my generation.

Lately we’ve all read articles proclaiming that “the digital economy and the economy are becoming one in the same. The lines are being blurred.” While this may be true, Millennials do not see this distinction. To us, it’s just the economy. Everything we do happens in the abstract digital economy – we shop digitally, get our news digitally, communicate digitally, and we take pictures digitally. In fact, the things that we don’t do digitally are few and far between.

Millennial disruption: How to get our attention in the digital economy

In this fast-moving, highly technical era, innovation and technology are ubiquitous, forcing companies to deliver immediate value to consumers. This principle is ingrained in us – it’s stark reality. One day, a brand is a world leader, promising incredible change. Then just a few weeks later, it disappears. Millennials view leaders of the emerging (digital) economy as scrappy, agile, and comfortable making decisions that disrupt the norm, and that may or may not pan out.

What does it take to earn the attention of Millennials? Here are three things you should consider:

1. Millennials appreciate innovations that reinvent product delivery and service to make life better and simpler.

Uber, Vimeo, ASOS, and Apple are some of the most successful disruptors in the current digital economy. Why? They took an already mature market and used technology to make valuable connections with their Millennial customers. These companies did not invent a new product – they reinvented the way business is done within the economy. They knew what their consumers wanted before they realized it.

Millennials thrive on these companies. In fact, we seek them out and expect them to create rapid, digital changes to our daily lives. We want to use the products they developed. We adapt quickly to the changes powered by their new ideas or technologies. With that being said, it’s not astonishing that Millennials feel the need to connect regularly and digitally.

2. It’s not technology that captures us – it’s the simplicity that technology enables.

Recently, McKinsey & Company revealed that “CEOs expect 15%–50% of their companies’ future earnings to come from disruptive technology.” Considering this statistic, it may come as a surprise to these executives that buzzwords – including cloud, diversity, innovation, the Internet of Things, and future of work – does not resonate with us. Sure, we were raised on these terms, but it’s such a part of our culture that we do not think about it. We expect companies to deeply embed this technology now.

What we really crave is technology-enabled simplicity in every aspect of our lives. If something is too complicated to navigate, most of us stop using the product. And why not? It does not add value if we cannot use it immediately.

Many experts claim that this is unique to Millennials, but it truly isn’t. It might just be more obvious and prevalent with us. Some might translate our never-ending desire for simplicity into laziness. Yet striving to make daily activities simpler with the use of technology has been seen throughout history. Millennials just happen to be the first generation to be completely reliant on technology, simplicity, and digitally powered “personal” connections.

3. Millennials keep an eye on where and how the next technology revolution will begin.

Within the next few years Millennials will be the largest generation in the workforce. As a result, the onslaught of coverage on the evolution of technology will most likely be phased out. While the history of technology is significant for our predecessors, this not an overly important story for Millennials because we have not seen the technology evolution ourselves. For us, the digital revolution is a fact of life.

Companies like SAP, Amazon, and Apple did not invent the wheel. Rather, they were able to create a new digital future. For a company to be successful, senior leaders must demonstrate a talent for R&D genius as well as fortune-telling. They need to develop easy-to-use, brilliantly designed products, market them effectively to the masses, and maintain their product elite. It’s not easy, but the companies that upend an entire industry are successfully balancing these tasks.

Disruption can happen anywhere and at any time. Get ready!

Across every industry, big players are threatened — not only by well-known competitors, but by small teams sitting in a garage drafting new ideas that could turn the market upside down. In reality, anyone, anywhere, at any time can cause disruption and bring an idea to life.

Take my employer SAP, for example. With the creation of SAP S/4HANA, we are disrupting the tech market as we help our customers engage in digital transformation. By removing data warehousing and enabling real-time operations, companies are reimagining their future. Organizations such as La Trobe University, the NFL, and Adidas have made it easy to understand and conceptualize the effects using data in real time. But only time will tell whether Millennials will ever realize how much disruption was needed to get where we are today.

Find out how SAP Services & Support you can minimize the impact of disruption and maximize the success of your business. Read SAP S/4HANA customer success stories, visit the SAP Services HUB, or visit the customer testimonial page on SAP.com.

Comments

Julia Caruso

About Julia Caruso

Julia Caruso is a Global Audience Marketing Specialist at SAP. She is responsible for developing strategic digital media plans and working with senior executives to create high level content for SAP S/4HANA and SAP Activate.

Primed: Prompting Customers to Buy

Volker Hildebrand, Sam Yen, and Fawn Fitter

When it comes to buying things—even big-ticket items—the way we make decisions makes no sense. One person makes an impulsive offer on a house because of the way the light comes in through the kitchen windows. Another gleefully drives a high-end sports car off the lot even though it will probably never approach the limits it was designed to push.

We can (and usually do) rationalize these decisions after the fact by talking about needing more closet space or wanting to out-accelerate an 18-wheeler as we merge onto the highway, but years of study have arrived at a clear conclusion:

When it comes to the customer experience, human beings are fundamentally irrational.

In the brick-and-mortar past, companies could leverage that irrationality in time-tested ways. They relied heavily on physical context, such as an inviting retail space, to make products and services as psychologically appealing as possible. They used well-trained salespeople and employees to maximize positive interactions and rescue negative ones. They carefully sequenced customer experiences, such as having a captain’s dinner on the final night of a cruise, to play on our hard-wired craving to end experiences on a high note.

Today, though, customer interactions are increasingly moving online. Fortune reports that on 2016’s Black Friday, the day after Thanksgiving that is so crucial to holiday retail results, 108.5 million Americans shopped online, while only 99.1 million visited brick-and-mortar stores. The 9.4% gap between the two was a dramatic change from just one year prior, when on- and offline Black Friday shopping were more or less equal.

When people browse in a store for a few minutes, an astute salesperson can read the telltale signs that they’re losing interest and heading for the exit. The salesperson can then intervene, answering questions and closing the sale.

Replicating that in a digital environment isn’t as easy, however. Despite all the investments companies have made to counteract e-shopping cart abandonment, they lack the data that would let them anticipate when a shopper is on the verge of opting out of a transaction, and the actions they take to lure someone back afterwards can easily come across as less helpful than intrusive.

In a digital environment, companies need to figure out how to use Big Data analysis and digital design to compensate for the absence of persuasive human communication and physical sights, sounds, and sensations. What’s more, a 2014 Gartner survey found that 89% of marketers expected customer experience to be their primary differentiator by 2016, and we’re already well into 2017.

As transactions continue to shift toward the digital and omnichannel, companies need to figure out new ways to gently push customers along the customer journey—and to do so without frustrating, offending, or otherwise alienating them.

The quest to understand online customers better in order to influence them more effectively is built on a decades-old foundation: behavioral psychology, the study of the connections between what people believe and what they actually do. All of marketing and advertising is based on changing people’s thoughts in order to influence their actions. However, it wasn’t until 2001 that a now-famous article in the Harvard Business Review formally introduced the idea of applying behavioral psychology to customer service in particular.

The article’s authors, Richard B. Chase and Sriram Dasu, respectively a professor and assistant professor at the University of Southern California’s Marshall School of Business, describe how companies could apply fundamental tenets of behavioral psychology research to “optimize those extraordinarily important moments when the company touches its customers—for better and for worse.” Their five main points were simple but have proven effective across multiple industries:

  1. Finish strong. People evaluate experiences after the fact based on their high points and their endings, so the way a transaction ends is more important than how it begins.
  2. Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
  3. Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
  4. Provide choices. People don’t like to be shoved toward an outcome; they prefer to feel in control. Giving them options within the boundaries of your ability to deliver builds their commitment.
  5. Be consistent. People like routine and predictability.

For example, McKinsey cites a major health insurance company that experimented with this framework in 2009 as part of its health management program. A test group of patients received regular coaching phone calls from nurses to help them meet health goals.

The front-loaded negative was inherent: the patients knew they had health problems that needed ongoing intervention, such as weight control or consistent use of medication. Nurses called each patient on a frequent, regular schedule to check their progress (consistency and spread-out positives), suggested next steps to keep them on track (choices), and cheered on their improvements (a strong finish).

McKinsey reports the patients in the test group were more satisfied with the health management program by seven percentage points, more satisfied with the insurance company by eight percentage points, and more likely to say the program motivated them to change their behavior by five percentage points.

The nurses who worked with the test group also reported increased job satisfaction. And these improvements all appeared in the first two weeks of the pilot program, without significantly affecting the company’s costs or tweaking key metrics, like the number and length of the calls.

Indeed, an ongoing body of research shows that positive reinforcements and indirect suggestions influence our decisions better and more subtly than blatant demands. This concept hit popular culture in 2008 with the bestselling book Nudge.

Written by University of Chicago economics professor Richard H. Thaler and Harvard Law School professor Cass R. Sunstein, Nudge first explains this principle, then explores it as a way to help people make decisions in their best interests, such as encouraging people to eat healthier by displaying fruits and vegetables at eye level or combatting credit card debt by placing a prominent notice on every credit card statement informing cardholders how much more they’ll spend over a year if they make only the minimum payment.

Whether they’re altruistic or commercial, nudges work because our decision-making is irrational in a predictable way. The question is how to apply that awareness to the digital economy.

In its early days, digital marketing assumed that online shopping would be purely rational, a tool that customers would use to help them zero in on the best product at the best price. The assumption was logical, but customer behavior remained irrational.

Our society is overloaded with information and short on time, says Brad Berens, Senior Fellow at the Center for the Digital Future at the University of Southern California, Annenberg, so it’s no surprise that the speed of the digital economy exacerbates our desire to make a fast decision rather than a perfect one, as well as increasing our tendency to make choices based on impulse rather than logic.

Buyers want what they want, but they don’t necessarily understand or care why they want it. They just want to get it and move on, with minimal friction, to the next thing. “Most of our decisions aren’t very important, and we only have so much time to interrogate and analyze them,” Berens points out.

But limited time and mental capacity for decision-making is only half the issue. The other half is that while our brains are both logical and emotional, the emotional side—also known as the limbic system or, more casually, the primitive lizard brain—is far older and more developed. It’s strong enough to override logic and drive our decisions, leaving rational thought to, well, rationalize our choices after the fact.

This is as true in the B2B realm as it is for consumers. The business purchasing process, governed as it is by requests for proposals, structured procurement processes, and permission gating, is designed to ensure that the people with spending authority make the most sensible deals possible. However, research shows that even in this supposedly rational process, the relationship with the seller is still more influential than product quality in driving customer commitment and loyalty.

Baba Shiv, a professor of marketing at Stanford University’s Graduate School of Business, studies how the emotional brain shapes decisions and experiences. In a popular TED Talk, he says that people in the process of making decisions fall into one of two mindsets: Type 1, which is stressed and wants to feel comforted and safe, and Type 2, which is bored or eager and wants to explore and take action.

People can move between these two mindsets, he says, but in both cases, the emotional brain is in control. Influencing it means first delivering a message that soothes or motivates, depending on the mindset the person happens to be in at the moment and only then presenting the logical argument to help rationalize the action.

In the digital economy, working with those tendencies means designing digital experiences with the full awareness that people will not evaluate them objectively, says Ravi Dhar, director of the Center for Customer Insights at the Yale School of Management. Since any experience’s greatest subjective impact in retrospect depends on what happens at the beginning, the end, and the peaks in between, companies need to design digital experiences to optimize those moments—to rationally design experiences for limited rationality.

This often involves making multiple small changes in the way options are presented well before the final nudge into making a purchase. A paper that Dhar co-authored for McKinsey offers the example of a media company that puts most of its content behind a paywall but offers free access to a limited number of articles a month as an incentive to drive subscriptions.

Many nonsubscribers reached their limit of free articles in the morning, but they were least likely to respond to a subscription offer generated by the paywall at that hour, because they were reading just before rushing out the door for the day. When the company delayed offers until later in the day, when readers were less distracted, successful subscription conversions increased.

Pre-selecting default options for necessary choices is another way companies can design digital experiences to follow customers’ preference for the path of least resistance. “We know from a decade of research that…defaults are a de facto nudge,” Dhar says.

For example, many online retailers set a default shipping option because customers have to choose a way to receive their packages and are more likely to passively allow the default option than actively choose another one. Similarly, he says, customers are more likely to enroll in a program when the default choice is set to accept it rather than to opt out.

Another intriguing possibility lies in the way customers react differently to on-screen information based on how that information is presented. Even minor tweaks can have a disproportionate impact on the choices people make, as explained in depth by University of California, Los Angeles, behavioral economist Shlomo Benartzi in his 2015 book, The Smarter Screen.

A few of the conclusions Benartzi reached: items at the center of a laptop screen draw more attention than those at the edges. Those on the upper left of a screen split into quadrants attract more attention than those on the lower left. And intriguingly, demographics are important variables.

Benartzi cites research showing that people over 40 prefer more visually complicated, text-heavy screens than younger people, who are drawn to saturated colors and large images. Women like screens that use a lot of different colors, including pastels, while men prefer primary colors on a grey or white background. People in Malaysia like lots of color; people in Germany don’t.

This suggests companies need to design their online experiences very differently for middle-aged women than they do for teenage boys. And, as Benartzi writes, “it’s easy to imagine a future in which each Internet user has his or her own ‘aesthetic algorithm,’ customizing the appearance of every site they see.”

Applying behavioral psychology to the digital experience in more sophisticated ways will require additional formal research into recommendation algorithms, predictions, and other applications of customer data science, says Jim Guszcza, PhD, chief U.S. data scientist for Deloitte Consulting.

In fact, given customers’ tendency to make the fastest decisions, Guszcza believes that in some cases, companies may want to consider making choice environments more difficult to navigate— a process he calls “disfluencing”—in high-stakes situations, like making an important medical decision or an irreversible big-ticket purchase. Choosing a harder-to-read font and a layout that requires more time to navigate forces customers to work harder to process the information, sending a subtle signal that it deserves their close attention.

That said, a company can’t apply behavioral psychology to deliver a digital experience if customers don’t engage with its site or mobile app in the first place. Addressing this often means making the process as convenient as possible, itself a behavioral nudge.

A digital solution that’s easy to use and search, offers a variety of choices pre-screened for relevance, and provides a friction-free transaction process is the equivalent of putting a product at eye level—and that applies far beyond retail. Consider the Global Entry program, which streamlines border crossings into the U.S. for pre-approved international travelers. Members can skip long passport control lines in favor of scanning their passports and answering a few questions at a touchscreen kiosk. To date, 1.8 million people have decided this convenience far outweighs the slow pace of approvals.

The basics of influencing irrational customers are essentially the same whether they’re taking place in a store or on a screen. A business still needs to know who its customers are, understand their needs and motivations, and give them a reason to buy.

And despite the accelerating shift to digital commerce, we still live in a physical world. “There’s no divide between old-style analog retail and new-style digital retail,” Berens says. “Increasingly, the two are overlapping. One of the things we’ve seen for years is that people go into a store with their phones, shop for a better price, and buy online. Or vice versa: they shop online and then go to a store to negotiate for a better deal.”

Still, digital increases the number of touchpoints from which the business can gather, cluster, and filter more types of data to make great suggestions that delight and surprise customers. That’s why the hottest word in marketing today is omnichannel. Bringing behavioral psychology to bear on the right person in the right place in the right way at the right time requires companies to design customer experiences that bridge multiple channels, on- and offline.

Amazon, for example, is known for its friction-free online purchasing. The company’s pilot store in Seattle has no lines or checkout counters, extending the brand experience into the physical world in a way that aligns with what customers already expect of it, Dhar says.

Omnichannel helps counter some people’s tendency to believe their purchasing decision isn’t truly well informed unless they can see, touch, hear, and in some cases taste and smell a product. Until we have ubiquitous access to virtual reality systems with full haptic feedback, the best way to address these concerns is by providing personalized, timely, relevant information and feedback in the moment through whatever channel is appropriate. That could be an automated call center that answers frequently asked questions, a video that shows a product from every angle, or a demonstration wizard built into the product. Any of these channels could also suggest the customer visit the nearest store to receive help from a human.

The omnichannel approach gives businesses plenty of opportunities to apply subtle nudges across physical and digital channels. For example, a supermarket chain could use store-club card data to push personalized offers to customers’ smartphones while they shop. “If the data tells them that your goal is to feed a family while balancing nutrition and cost, they could send you an e-coupon offering a discount on a brand of breakfast cereal that tastes like what you usually buy but contains half the sugar,” Guszcza says.

Similarly, a car insurance company could provide periodic feedback to policyholders through an app or even the digital screens in their cars, he suggests. “Getting a warning that you’re more aggressive than 90% of comparable drivers and three tips to avoid risk and lower your rates would not only incentivize the driver to be more careful for financial reasons but reduce claims and make the road safer for everyone.”

Digital channels can also show shoppers what similar people or organizations are buying, let them solicit feedback from colleagues or friends, and read reviews from other people who have made the same purchases. This leverages one of the most familiar forms of behavioral psychology—reinforcement from peers—and reassures buyers with Shiv’s Type 1 mindset that they’re making a choice that meets their needs or encourages those with the Type 2 mindset to move forward with the purchase. The rational mind only has to ask at the end of the process “Am I getting the best deal?” And as Guszcza points out, “If you can create solutions that use behavioral design and digital technology to turn my personal data into insight to reach my goals, you’ve increased the value of your engagement with me so much that I might even be willing to pay you more.”

Many transactions take place through corporate procurement systems that allow a company to leverage not just its own purchasing patterns but all the data in a marketplace specifically designed to facilitate enterprise purchasing. Machine learning can leverage this vast database of information to provide the necessary nudge to optimize purchasing patterns, when to buy, how best to negotiate, and more. To some extent, this is an attempt to eliminate psychology and make choices more rational.

B2B spending is tied into financial systems and processes, logistics systems, transportation systems, and other operational requirements in a way no consumer spending can be. A B2B decision is less about making a purchase that satisfies a desire than it is about making a purchase that keeps the company functioning.

That said, the decision still isn’t entirely rational, Berens says. When organizations have to choose among vendors offering relatively similar products and services, they generally opt for the vendor whose salespeople they like the best.

This means B2B companies have to make sure they meet or exceed parity with competitors on product quality, pricing, and time to delivery to satisfy all the rational requirements of the decision process. Only then can they bring behavioral psychology to bear by delivering consistently superior customer service, starting as soon as the customer hits their app or website and spreading out positive interactions all the way through post-purchase support. Finishing strong with a satisfied customer reinforces the relationship with a business customer just as much as it does with a consumer.

The best nudges make the customer relationship easy and enjoyable by providing experiences that are effortless and fun to choose, on- or offline, Dhar says. What sets the digital nudge apart in accommodating irrational customers is its ability to turn data about them and their journey into more effective, personalized persuasion even in the absence of the human touch.

Yet the subtle art of influencing customers isn’t just about making a sale, and it certainly shouldn’t be about persuading people to act against their own best interests, as Nudge co-author Thaler reminds audiences by exhorting them to “nudge for good.”

Guszcza, who talks about influencing people to make the choices they would make if only they had unlimited rationality, says companies that leverage behavioral psychology in their digital experiences should do so with an eye to creating positive impact for the customer, the company, and, where appropriate, the society.

In keeping with that ethos, any customer experience designed along behavioral lines has to include the option of letting the customer make a different choice, such as presenting a confirmation screen at the end of the purchase process with the cold, hard numbers and letting them opt out of the transaction altogether.

“A nudge is directing people in a certain direction,” Dhar says. “But for an ethical vendor, the only right direction to nudge is the right direction as judged by the customers themselves.” D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Sam Yen is Chief Design Officer and Managing Director at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

Comments

Tags:

The Big (Data) Problem With Machine Learning

Dan Wellers

Historically, most of the data businesses have analyzed for decision-making has been of the structured variety—easily entered, stored, and queried. In the digital age, that universe of potentially valuable data keeps expanding exponentially. Most of it is unstructured data, coming from a wide variety of sources, from websites to wearable devices. As a recent McKinsey Global Institute report noted: “Much of this newly available data is in the form of clicks, images, text, or signals of various sorts, which is very different than the structured data that can be cleanly placed in rows and columns.”

At the same time, we have entered an era when machine learning can theoretically find patterns in vast amounts of data to enable enterprises to uncover insights that may not have been visible before. Machine learning trains itself on data, and for a time, that data was scarce. Today it is abundant. By 2025, the world will create 180 zettabytes of data per year (up from 4.4 zettabytes in 2013), according to IDC.

Big Data and machine learning would seem to be a perfect match, coming together at just the right time. But it’s not that simple.

The connected world is ever-widening, enabling the capture and storage of more—and more diverse—data sets than ever before. Nearly 5,000 devices are being connected to the Internet every minute today; within ten years, there will be 80 billion devices collecting and transmitting data in the world. Voice, facial recognition, chemical, biological, and 3D-imaging sensors are rapidly advancing. And the computing muscle that will be required to churn through all this data is more readily available today. There’s been a one trillion-fold increase in computing power over the past 60 years.

The importance of data prep

But having vast amounts of data and computing power isn’t enough. For machine learning tools to work, they need to be fed high-quality data, and they must also be guided by highly skilled humans.

It’s the age-old computing axiom writ large: garbage in, garbage out. Data must be clean, scrubbed of anomalies, and free of bias. In addition, it must be structured appropriately for the particular machine-learning tool being used as the required format varies by platform. Preparing data is likely the least sexy but most important part of a data scientist’s job—one that accounts for as much as 50 percent of his or her time, according to some estimates. It’s the unglamorous heavy lifting of advanced analytics, and it takes experience and skill to do it—qualities that are, and will continue to be, in short supply even as demand for data scientists is predicted to grow at double-digit rates for the foreseeable future.

It took one bank 150 people and two years of painstaking work to address all the data quality questions necessary to build an enterprise-wide data lake from which advanced analytics tools might drink. That’s the kind of data wrangling that has to be done before companies can even begin to test the value of machine-learning capabilities.

More data, more problems

There’s also the misperception that having access to all this new data will necessarily lead to greater insight. There’s great enthusiasm around data-driven decision-making and the promise of Big Data and machine learning in boardrooms and executive suites around the world. But in reality, says UC Berkeley professor and machine learning expert Michael I. Jordan, more data increases the likelihood of making spurious connections. “It’s like having billions of monkeys typing. One of them will write Shakespeare,” said Jordan, who noted that Big Data analysis can deliver inferences at certain levels of quality. But, he said, “we have to be clear about what levels of quality. We have to have error bars around all our predictions. That is something that’s missing in much of the current machine learning literature.”

Again, this is where the expertise of the data scientist is of critical value: deciding what questions machine learning might be able to answer, with what data and at what level of quality.

These problems are not insurmountable. Tools are being developed to help businesses deal with some of the data management blocking and tackling that stands in the way of advanced analytics. One company, for example, has developed a machine-learning tool for real estate and finance companies that it says can extract unstructured data in 20 different languages from contracts and other legal documents and transform it into a structured, query-ready format.

What is clear is that the business of combining Big Data and big computing power for new insight is harder than it looks. The benefits almost certainly will be huge. But companies are still at the early stages of experimenting with new data types and emerging machine-learning tools and discovering the drawbacks and complications we will need to work through over time.

This blog is the fifth in a six-part series on machine learning.

Comments

Dan Wellers

About Dan Wellers

Dan Wellers is the Global Lead of Digital Futures at SAP, which explores how organizations can anticipate the future impact of exponential technologies. Dan has extensive experience in technology marketing and business strategy, plus management, consulting, and sales.