by Keith Orndoff
Date Published - Last Updated February 26, 2016

The year is 2019. Julie, a college student, is still in bed, sleeping off the all-nighter she pulled the evening before. Julie’s never been a morning person, though, and she’s tried everything to make getting up early just a little easier, including a new wake-up app, which she installed on her refrigerator. And which is currently screeching fit to wake the dead.

Julie had tried installing alarm apps on her phone, but she ended up putting the phone in the bottom drawer of her nightstand. Then she went old-school: setting the timer on her coffee machine, hoping that the smell of fresh-brewed coffee would draw her out of bed—that hadn’t worked either. Finally, she went for the fridge app, figuring that, unlike her phone, she wasn’t going to be able to stick her fridge in the bottom of any drawer.

After Julie slept through the first two alarms, the fridge went into “extreme” wake-up mode. When she finally dragged herself to the fridge and commanded the alarm to shut off, the fridge notified Julie that she was late for her physics class, but if she acted immediately, she could take 25 percent off of two pairs of smart “Wake-Me-Up Pajamas.” The colorful ad flashes across the surface of the fridge, advertising pajamas that “gently tickle you awake.” Just what I need, Julie thinks. She tells the fridge to reject the ad.

After sorting out the fridge, Julie returns to her bedroom to shower and dress, putting on her smart blouse, her smart watch, and her smart necklace. Then she dashes out the door to try and catch the end of her class.

At age 21 in the year 2019, Julie represents the customer of the future, straddling the line between the Millennial and the Digital Native generations. She’s never experienced a life where technology wasn’t integrated into every aspect of her life, from the moment she woke up until the moment she closed her eyes at night. Technology is now so integrated into her life that the only time she really thinks about it is when it doesn’t work. How can organizations use emerging technologies to make sure the Julies of future generations are well served and happy?

In the May/June issue of SupportWorld, I presented a variety of emerging technologies and identified several ways in which these technologies might change the nature of technical service and support in the useful future, or the next three to five years. In this article, we’re going to look at some traits of the Millennial generation that may affect the cross-impact of those technologies.

The Unpredictable Future

In The Black Swan, statistician and former Wall Street trader Nassim Nicholas Taleb proposes that the future is inherently unpredictable. The only way to deal with the future effectively, he argues, is to find ways to minimize damage from random, unpredictable downside events while finding ways to create an environment where one can most benefit from random, unpredictable upside events.

While Taleb’s point is certainly valid, it fails to take into account man’s ability to look at the present, make a reasoned assessment, and prepare for (or create) the future. This is the essential story of human progress throughout the ages. We’re reenacting this story now, at the intersection of data analytics, Big Data, cognitive computing, and Millennials.

Predicting the unpredictable is indeed an imperfect process. No matter how good you are at predicting the future, what you can see is only a small part of the way things will ultimately be. But there are things we can reasonably surmise and imagine about the useful future by looking at the present—and this is especially true in the arena of emerging technologies. Many of these technologies exist now, though they may not be widely available or even visible.

To take trends in technology, however, and predict the future based on interactions with a generational group is without question more difficult and problematic than simply considering the technologies in isolation. It is much more useful, though, because it is at that intersection that organization’s can make informed decisions about risks and opportunities.

In the next section, we will trace the contours of the Millennial generation. Then, we will use a technique called cross-impact analysis to derive several questions support organizations should ask themselves about how technology and users will change by 2020.

Millennials, Young and Old

Before we dig into perceptions about Millennials, allow me to share recent findings on Millennials and technology from the Pew Research Center:

  • Millennials tend to “mark their territory” by the use of their technology.
  • The typical Millennial sent or received twenty texts in the last 24-hour period.
  • Three-fourths of Millennials have a social networking profile.
  • Ninety-six percent of those with at least some college experience have created a social networking profile.
  • Sixty-two percent of Millennials connect to the Internet wirelessly when away from home or work.
  • Forty-one percent of Millennials do not have mobile phones but instead rely on wireless.
  • Eighty-three percent of Millennials sleep or have slept with a mobile phone next to their bed.
  • Eighty-eight percent of Millennials use their mobile phones to text.

There is a danger, however, in labeling a generational group and assuming they’re all the same. Consider the following statement: Millennials are typically defined as those born between 1980 and 2000—by that definition, as of 2014, the youngest Millennial is 14 and the oldest is 34. This means that when the first smartphone was introduced in 2007, the youngest Millennial was 7 and the oldest was already 27. Those are two radically different “technology childhoods” for people in the same generation—the youngest Millennials have grown up in a world of ubiquitous interconnectivity, while the Internet and mobile phones didn’t even feature in the childhoods of the oldest Millennials. Yet they are all “Millennials,” and we talk about them as if they’re all the same.

From the perspective of support organizations, this distinction between “old” Millennials and “young” Millennials is not trivial. Why? Because in the next three to five years, the adults entering the workforce will be those “young” Millennials who’ve never known anything other than a fully mobile, completely interconnected world, unlike the “old” Millennials. And it is these younger Millennials whose interactions with the world of Big Data, data analytics, and cognitive computing will be the most interesting to observe.

The Millennial Clichés: A Blanket of Data, Love, and Concern

Much of what has been written about Millennials is already a cultural cliché: They’re a collaborative generation, used to using technologies such as Yammer and Confluence for work, discussions, and chats. They frequently use Facebook and other social media channels to create and participate in their own online communities. They’re accustomed to instant gratification. They seek work that is meaningful, as much for the work itself as for money and status, and they frequently say they find value in being committed to something “bigger than themselves.” But they also want to work flexible hours and on their own terms. They’ve also been described (and derided) as the “helicopter” generation—kids raised with the constant hovering of parents and caregivers demanding regular communications and updates on their activities and whereabouts.

Mobile devices have changed the nature of childhood. Younger Millennials have grown up with their parents’ expectations of constant status updates, and they know their parents can track them through their mobile devices (there are even apps for just that purpose). One might expect this level of scrutiny and surveillance to have a negative impact on Millennials, but quite the contrary. Their comfort with the tools and practices of “helicopter parenting” may serve them well in the Big Data era.

The Intersection Between Millennials and Big Data

According to Pew, Millennials are significantly more likely than older adults to say technology makes life easier and brings family and friends closer. In other words, they’re far less likely to be distressed or discomfited by new technologies simply because they’re unknown, as long as they believe the technology will make their lives easier.

Millennials also appear far less concerned with privacy than any other generation. (Indeed, the entire concept of privacy may be changing; see CNBC’s “Social Radar” for an interesting look at one example.)They’re much more comfortable than older generations with the tracking, harvesting, and usage of large amounts of data about preferences and behavior that might once have before been considered too personal to disclose. It seems likely that many of the things that bother elders about the collection of information are unlikely to upset the Millennial generation—in other words, data analytics and Big Data will not be restrained by their fears of being tracked but will instead be enabled by their desire for the convenience that this tracking will bring.

One of the implications of this is that not only will this generation be comfortable with the emerging tools of data analytics, Big Data, and cognitive computing they may also have very little tolerance for poor service resulting from companies’ failure to leverage these tools. It may well be that Millennials will happily volunteer personal information in exchange for more effective support. Here are several additional emerging characteristics of Millennials—particularly younger Millennials—that will have an effect on support: 

  • They might be quite comfortable communicating to and with nonhumans.
  • They will be more impatient for instant solutions to their problems.
  • They will have greater attachment to their personal technology, and therefore greater expectations that they’ll be able to use those devices at work (BYOD).
  • They will embrace wearable technology, and expect support for it.

Cross-impact analysis enables us to examine the intersection between major trends or capabilities.

By analyzing the intersection between these technological and societal trends, I developed a list of working questions to give support organizations strategic insight into the useful future.

  • With technologies that promise instant solutions, along with the generational tendency to expect instant solutions, will Millennials have any patience for problems?
  • Could Millennials increasingly see the mere hint of a problem as a failure of support?
  • Should organizations develop different levels of support based on their customers’ willingness to share data and their comfort with being the subject of data analytics? (Facebook, for example, recently announced an opt-out option on customer data tracking for third-party apps. It will be interesting to see if customers who opt-out perceive a reduction in overall value.)
  • Will Millennials continue to see contact with a human at any level as an advantage, or will they see human intervention as a failure of support?
  • Will Millennials see any instance of restricted access to the cloud as a failure of support?
  • What kind of personality traits do Millennials have that could only be satisfied using Big Data tools?
  • What kind of event might create a massive shift from comfort to discomfort with traditional means of support? How can organizations prepare for this loss of confidence?

All of these are important questions, though they’re by no means all or even the most significant questions that should be considered in an effort to better understand the trajectory of technical service and support over the next three to five years. But developing and asking these questions is an essential step toward a better understanding of the future. There are no right answers, because your answers will vary based on context (e.g., industry, company, or role).

If you’re not considering the convergence of these technological and sociological trends, you can bet someone else is. Organizations no longer have the luxury of waiting for change; they have to be vigilant, watching for change and considering whether those changes pose a danger or promise opportunities. They need to be ready to act, not just react. By anticipating change, organizations have the opportunity to create something truly new and revolutionary. The future is truly one of unlimited possibility.

Final Thoughts: Black Swans and Opportunities

Wild cards are unforeseen events that change everything, usually for the worst (Taleb calls them “black swans”). But wild cards can also be opportunities. Edward Snowden was just such a wild card. Snowden’s actions exposed the NSA’s misuse of data, which prompted calls for a return to old-fashioned standards of privacy. As more companies put their eggs in the Big Data basket, it’s worth considering how severe future abuses would have to be to engender such a dramatic change in Millennials’ attitudes. If your customers ask if you’re tracking them and why, support should have an answer—and probably an “off” switch. This could give your organization considerable strategic advantage.

Heartbleed and global Internet viruses are two more examples of wild cards. Support organizations with contingency and disaster recovery plans will weather storms like this—can you think of a better opportunity?

Opportunity (and risk) can come from many directions: the unexpected, the predictable, and that which we create ourselves. In the technical service and support industry, there are many fast-moving and rapidly evolving parts. The best approach is one that allows you to step back, look at the big picture, and take practical action.

As you reflect on the contents of my last two articles, think about Julie, our sleep-deprived Millennial and ask yourself, “Where are the risks and opportunities? What surprises might bring the danger to the fore? What actions could allow my organization to seize the incredible opportunities these changes are creating?” The answers to these questions, however they’re shaped by your organization’s particular circumstances, will help your organization thrive in the useful future.


Keith Orndoff is a futurist who delivers high-impact workshops and keynotes on the near future (3-5 years). Keith has been a consulting futurist since 1997. He has written internal reports for, consulted with, and spoken to hundreds of clients, including NASA, General Motors, the American Society of Interior Designers, the American Bankers Association, the Kellogg Corporation, and many others. Keith has a MS in Studies of the Future from the University of Houston – Clear Lake, and he can be contacted by phone at 832.335.2031 or by email at [email protected] .  

Tag(s): future of support


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