The Technology Fallacy: How People Are the Real Key to Digital Transformation (Management on the Cutting Edge)

by Gerald C. Kane

Organizations that aspire to digital maturity need to be talent magnets,

They have high standards, a prodigious appetite for coaching, recognition that they also benefit from the coaching of others, a willingness to take smart risks, and the ability to deconstruct complicated activities into component parts that can be learned and mastered.

developing existing skills alone is necessary but not sufficient for competing in the future. You must not only train your existing talent, but also attract and retain new talent. Organizations must address these challenges without falling prey to well-intentioned, but largely symbolic, actions that fail to address access to this scarce and highly mobile segment of the workforce.

Digitally maturing companies spend time developing the skills their employees need to thrive, and in turn, these employees effectively help those companies execute their digital strategy. Less mature companies do not spend time developing or utilizing the skills of their employees, and—surprise!—these companies don’t seem to have sufficient talent to execute their digital strategies. These data reflect the old story about two executives discussing employee training. The first asks, “What if we train our employees and they just end up leaving?” The second responds, “What if we don’t and they stay?”

When technological disruption of human jobs happens, it will likely occur in two stages—first augmenting and enhancing the human worker, then replacing the human altogether.

This augmentation step will make the professionals more valuable in the medium term because it will free up experts to shift from routine to value-added tasks.

The question will be whether human employees can develop these new value-added roles before technology takes over those roles entirely. Then, the question shifts to whether human employees can take on other value-added roles and work.

The enterprise collaboration platform Slack is working on AI to monitor employee communications and automate many managerial tasks, reducing the need for face-to-face meetings.

As a technology that enables a secure public record, blockchain is poised to eliminate jobs that depend on mediating trust between parties.

Deloitte CEO Cathy Engelbert notes that she prefers to talk about these trends as the “work of the future” rather than the more commonly used term “the future of work.” We concur with this shift in terminology, as we think the former terminology is far more optimistic (and, we believe, more accurate) than the latter. It implies a shift in how work will be performed in the future, rather than questioning whether work has a future and will still exist. Autor notes that, in many ways, full-time work doesn’t “need” to exist now. If people were content with the standard of living as it was one hundred years ago, they would need to work only about seventeen weeks per year. Instead, people work harder and adapt their skill sets to improve their quality of life.

A report by the Atlantic describes much of the societal disruption that accompanies these types of shifts.8 People who are left behind because they are unable to adapt for whatever reason often experience psychological effects, societal disruption, and substance abuse.

A similar reason might also undergird the recent opioid epidemic in the United States, as people struggle with the disruptions they are experiencing. The difficulties caused by shifts in work can likely only be addressed through public policy and government intervention, which are worthy topics but not ones that we address in this book.

He notes, “We used to work with our hands for many centuries; then we worked with our heads, and now we’re going to have to work with our hearts, because there’s one thing machines cannot, do not, and never will have, and that’s a heart. I think we’re going from hands to heads to hearts.”

In practice, computers have proved far better at performing tasks that we once thought impossible, like facial recognition and language translation. If we primarily fit human work into the gaps left by what computers cannot do, people will increasingly be squeezed out as technology becomes more advanced.

For example, Cynthia Brezeal, of MIT Media Lab, is designing so-called sociable robots that can approximate empathetic connections. Research has shown that people are also more likely to open themselves up to robots than to humans, because fear of judgment is significantly diminished.11 So robots may, in fact, be capable of performing caring jobs in ways that people cannot. Simulations can also enable AI to make novel insights from past data that humans cannot. For example, when the AI system AlphaGo competed solely against itself to learn the game Go, instead of using data from human players, it was able to create insights and strategies that people working at the game had not developed over the centuries of playing it.12

In other words, the very task that computers may not be able to do better than humans is identifying opportunities created in the wake of technological evolution and disruption. Humans may be uniquely well suited to identify these gaps, adapting their skill sets and spending their time meeting these needs. Asking the right questions is, at least for now, a uniquely human capability.

What are the implications of the work of the future for individuals? Perhaps most important, people need to prepare to be lifelong learners. As technology continues to change at an increasing rate, people will clearly need to learn new skills to remain relevant.

Identifying the ways in which humans can uniquely provide value to the human-computer partnership is one thing, but being able to execute on those opportunities is another altogether.

people will “pivot” to new careers as their skill sets become undervalued in one job or sector, requiring them to repurpose them in new roles or industries. This pivot may take the form of traditional retraining, or it may involve applying existing skills in new contexts, which, presumably, will provide workers with a new set of skills that would then be resources for the next pivot.

This need to pivot will mean that individuals will need to chart their own career path amid these changes in work. A metaphor for these types of career paths for the future can be found in surfing. Surfers catch a wave for a set period, riding it to its natural completion, at which point they must paddle out and look for the next wave to catch.14 Some surfers choose to ride a wave as far as it will take them, while others choose to bail out once the wave passes its peak, so that they can be better positioned to catch the next wave. Likewise, some workers will choose to stay on particular paths longer, while others will attempt to pivot more quickly and jump from crest to crest.

Step up. When employees step up, they choose to develop the skills that will make them more valuable and marketable in a digitally disrupted business. Examples of this step include pursuing advanced degrees and continuing skill development to keep up with disruption. Companies could support this by developing a strategic talent development plan like Cigna’s, described in chapter 9. Step aside. Employees who step aside develop strengths in areas that are not easily disrupted by technology, such as emotional IQ or tacit knowledge that isn’t easily codified. An example here might be developing creative skills or tradecraft. This step may also help address the interest of companies in a combination of hard and soft skills. Step in. When someone chooses to step in, they begin to develop their skill set for the digitally disrupted industry. An

example might be radiologists becoming adept at using and understanding computer diagnostics to monitor the diagnoses and learn when to intervene. Companies need to support employees’ efforts to learn new technologies in their specialty. Step narrowly. In this situation, employees specialize deeply in an area that computers are not likely to disrupt in the near future. Davenport and Kirby use an example of a man who specializes in matching up buyers and sellers of Dunkin’ Donuts franchises. It is a niche competency that may never attract enough attention for automation. Organizations may be well served to identify and support employees with these niche competencies, as they may become an important source of differentiation from competitors. Step forward. With stepping forward, workers attempt to get out ahead of digital disruption and develop the technology that will represent the next wave of disruption. These people would now be working on the next great application for blockchain or developing components for autonomous vehicles. Companies in various industries are supporting these efforts by funding and engaging with an ecosystem of startup companies.

The American writer Frederick Buechner describes this as one’s calling, where the world’s deep need and the individual’s deep joy meet. The World Economic Forum describes this intersection in terms of the Japanese concept of ikigai—the junction at which what you love, what you are good at, what you can be paid for, and what the world needs all come together. We think these successive career waves can provide greater opportunities for employees to achieve ikigai, pursuing new avenues as their passions change and the disrupted world creates new opportunities to do so.

But digital culture runs deeper than that. It’s not just about how an organization decorates its space and what tools it uses. It’s about how an organization behaves, what it values, its unspoken but deeply embedded beliefs. Digital culture is often described as being “in the air” or part of the “vibe” of a place. Because culture feels nebulous, it’s often viewed as “icing on the cake.”

So, what is culture? It is often defined as the social behavior, norms, and beliefs of a group. It represents “the way things are done around here.” Culture is not just what is written in a mission statement or a code of ethics; it is what people in the organization believe to be the accepted patterns of behavior. In this way, culture can be a strong enabler (or a huge hindrance) to digital maturity.

Schein describes three levels of organizational culture. Artifacts: What we see. What a newcomer, visitor, or consultant would notice (e.g., dress, physical layout, furnishings, degree of formality). Espoused values: What they say. What we would be told is the reason things are the way they are and should be (e.g., company philosophy, norms, and justifications). Underlying assumptions: What they deeply believe in and act on. Unconscious taken-for-granted beliefs about the organization and its work, purpose, people, rewards, and so on.3

In this chapter, we focus on three important points we’ve learned about digital culture: Digital culture is critical to driving digital business adoption. Digital culture is distinct and consistent, associated with digital maturity. Digital culture is intentional.

In addition to helping get the most out of your people, culture is also an effective and important way to drive digital adoption and engagement in your organization. Companies at the three stages of digital maturity—early, developing, and maturing—have different approaches to leading change. While the difference between how early and developing companies accomplish this is nuanced, the difference between these and the most advanced maturing companies is far more striking

Early and developing companies push digital transformation through managerial directive or by technology provision. In contrast, maturing companies tend to pull digital transformation by cultivating conditions that are ripe for transformation to occur. This culture-driven, bottom-up approach is one we are actively exploring in our ongoing research.

Respondents from early stage companies reported that their primary method for driving digital adoption and engagement is to mandate initiatives from management. In this situation, organizational leadership decrees the nature of the next digital initiative, and employees are then expected to fall in line. A central problem with this approach is that top-down directives can often be surprisingly ineffective tools for driving adoption.

Developing-stage companies follow a different approach. These companies expect employees to adopt digital platforms by building them—not dissimilar to the mantra “If you build it, they will come,” from the 1989 Kevin Costner movie Field of Dreams.8 While managers know that employees will not be driven by magical forces urging them to adopt new initiatives, they often don’t provide the type of time, support, and motivation to adopt that would be necessary in other settings. Instead, companies often spend considerable time, money, and energy implementing digital platforms, expecting that the value of this technology will become so apparent to employees that they will be naturally drawn to use them to perform their work. And certainly, designing a user-friendly tool or platform with obvious value to the user is undoubtedly important. But companies that simply expect employees to adopt generally emphasize the technological side of implementation—and often execute that implementation well—while forgetting to accompany the new digital infrastructure with the organizational change management initiatives required.

Not only do employees need to be trained to use new technology, but they also need to be given time to figure out how to integrate these tools into their work.

Simply expecting employees to learn how to work with new technology while performing at pre-adoption levels puts employees and their organizations at a disadvantage for successful digital transformation. Such expectations are unrealistic, yet unfortunately quite common.

Maturing companies drive digital transformation in an entirely different way, by focusing on creating environments where digital transformation can occur.

Once the organizational conditions are ripe for digital transformation, leaders may discover that they have a much easier time engendering the types of strategic and technological changes that they need to compete. Once companies have cultivated an appropriate risk tolerance for the organizations, people are often far more willing to try new things.

Yochai Benkler, of Harvard, argues that employees are inclined to be more collaborative and cooperative, depending on the environmental conditions.

Sending the right cues to employees becomes an effective way of cultivating the right environment.11

As your company considers (or reconsiders) its own digital transformation initiatives, you should ask yourself whether you are approaching it in the right way. Are you pushing digital transformation on your organization, either through mandating adoption or by providing technology? Or, are you pulling transformation by cultivating the conditions that will elicit the types of change you desire? These differences may determine the ultimate success or failure of your digital transformation efforts.

So, what kind of culture is needed to enable talent and leaders to help drive digital adoption and transformation? It turns out that digital cultures are like snowflakes—no two are exactly alike, particularly in what Schein describes as artifacts and espoused values. But just as snowflakes share a common set of distinct characteristics, such as their precise hexagonal array (or six-fold symmetry), digital cultures also share common and distinct traits.

Specifically, digitally mature organizations are: less hierarchical and more distributed in leadership structure; more collaborative and cross-functional; encouraging of experimentation and learning; more bold and exploratory, with a higher tolerance for risk; and more agile and quick to act.

If cultural characteristics are associated with digital maturity independent of an organization’s efforts, and if digitally maturing organizations are driving digital transformation through cultural change, the most pressing challenge may really be more about shifting the organization’s culture to be more adaptable to change. If companies can get the culture right, then resulting changes in technology and business processes can more easily follow.

In other words, companies that are already ahead in driving digital transformation are doubling down on these efforts to move their companies even further down this road. The digitally rich will keep getting richer. The companies that are already the most collaborative, agile, and risk tolerant are the ones that are also most likely to strive to become more so.

For companies struggling with identifying which parts of their business to make more digitally mature first, developing a more digital culture seems like a compelling place where all companies can start. There is one clear path to digital maturity that all companies can follow across company size and industry—at least in terms of effective culture. It provides a powerful road map for

executives trying to increase the digital maturity of their companies. In the next three chapters, we dig deeper into specific cultural traits, particularly agility, collaboration, risk taking, and experimentation.

“Agile” describes an approach to software development that substitutes rapid, iterative sprints for the more traditional “waterfall” approach, which moves sequentially through several distinct phases—requirements, analysis, design, coding, testing, and operations. A key problem with the waterfall method is that if the requirements are not well understood in the beginning, the resulting product might not meet the intended user’s needs. The method is not well suited to the changing environments that characterize today’s world. Agile concepts are no longer confined to software development.

Agile methodologies, however, attempt to increase variability in the outputs, which is beneficial when the “best” approach is not always clearly known. These methods are valuable approaches for cross-functional teams to work. Agile methods forego the careful planning of more traditional development methodologies, adopting a more test-and-learn, iterative approach to development. The goal is to get to a minimum viable product (MVP), which can then be iterated with the customer in a cycle that brings continuous improvements with each subsequent, rapid release. Agile software proponents emphasize several key principles of the development process.

The first set of principles deals with collaboration and communication among key actors. The focus on individuals and interactions, as well as customer collaboration, is grounded in the need for strong communication among all stakeholders in the development projects. These open lines of communication help identify and articulate when the processes diverge from what is expected or desired. This divergence could result from a misunderstanding of the requirements, from changes in the environment, or from other factors.

The second set of principles is focused more on the process of developing the product. Delivering working software and responding to change occur hand in hand with iteratively developing the product. The team develops a working software product, and

users figure out its key strengths, weaknesses, and missing features, which becomes feedback for the next iteration of development. Each iteration can be thought of as an experiment that tests whether the next version of the product is closer to the desired goal.

Agile principles are an effective approach to digital transformation in organizations. Instead of planning a long road map of how to respond, teams develop short-term initiatives to engender small-scale changes in the company and in its processes. Next, the team evaluates how well the intervention meets its intended goals, and then plots the next small intervention. Agile teams don’t develop a grand plan for digital transformation; rather, they take one small action at a time, assess its effect, and do it again. Management must effectively communicate to these teams about the strategic direction of the organization, as well as pay attention to and circulate the results of the teams, so that they come together into a set of meaningful changes. Instead of directly telling the teams what next steps to take, a process of ongoing two-way communication permits action above planning, and future action based on present results.