7
Leading as Transitioning
As digital shockwaves accelerate, sending out wave after wave of transformative disruption, digital will become the cornerstone of enterprise and public services competitiveness and growth, bringing both opportunities and risks. The business and social impacts of these shockwaves will intensify competition in all industries, and will require the development of new employee skills, new forms of security, and new business models.
—Thierry Breton, former CEO of Atos, European Commissioner for Internal Markets
Thierry Breton’s plan to transition the multinational IT giant Atos into a global leader of digital services was massive and urgent. At the time, digital shockwaves, as he evocatively described them, were pulsing through businesses across industries. No one was outside the seismic zone. Enterprises needed to rebuild from the shaky ground up, and Atos would provide the blueprints.
The scope of such a vision was nothing new for Breton. Neither was its prescience. In his early twenties, at the very start of his career as a tech entrepreneur and political adviser, he wrote a series of novels that presaged cybersecurity as a field. The real challenge for him and Atos was strategy and implementation. What did such a transition look like for an IT giant with over 100,000 employees? What did “digital transformation” even entail for organizations? We have asked countless people this question, and answers have varied. Some refer to the mechanics of moving from analog to digital to enhance their systems. Others aspired to scale significantly with the adoption of specific tools like cloud or AI or began to reimagine their offerings. In every case, digital transformation remained a central concern to the vast majority of companies we have engaged, even if they operated in the tech sector. Years after Breton’s announcement, digital shockwaves continue to surge, more rapid and sweeping than ever.
We define digital transformation as organizations redesigning their underlying processes and competencies to become more adaptive using data and digital technology, from artificial intelligence and machine learning to the internet of things.1 While the tech-driven methods of this redesign are an essential feature that distinguishes digital transformation from other forms of organizational change, our focus is on the mindset shift that underpins it. Although this mindset shift ultimately happens on an individual level, the larger organization can support that shift to lesser or greater degrees. If we believe that an organization has “a mind of its own” or a “hive mind” then it’s fair to also think about developing an organization’s digital mindset. The first step in digitally redesigning systems and processes is to see today’s digitally driven world through what we call a transitioning lens. In the digital age, change isn’t something that happens periodically that you need to scramble to respond to. Your technologies, organizational structure, culture, and people systems are in a constant process of transition from what came before and to what is next. But you never arrive at what you thought was coming next because it will change before you get there. That is what we mean by transitioning—you’re in a constant state of flux. That means that leading in the digital environment is no longer about navigating change when it happens, it means helping your coworkers, employees, partners, and customers to continuously prepare for what’s coming next and to embrace that they live and work in inexorable transition.
This chapter is especially relevant for leaders and managers who will be implementing digital transformation as part of a greater organizational change. For readers who are the recipients of change, this chapter provides an understanding of the challenges that can help facilitate overall digital transformation. Everyone in an organization needs to, at least, have a sense of what is going on behind the scenes and how the leaders are making their decisions on helping to equip the enterprise. Doing so can only help to develop a fuller digital mindset and to be better at work. To that end we introduce what we call the work digitization process (WDP) and an adoption framework for the differing responses that leaders, managers, and employees may have to new digital tools and processes. We also detail how organizations have helped their employees learn and can continue to successfully upskill workers with in-house learning programs.
Accept and Embrace Change to Become Adaptive
In change management, transitional states are key. They are fixed periods of time in which an organization moves from a familiar set of structures, processes, and accompanying cultural norms to new ones.2 This middle phase of the change process is characterized as the experience of being in-between.3 People typically and understandably experience strong emotions during a transitional state because it requires us to accept new perspectives and behaviors. Let’s say you, your colleagues, or your employees are nonnative English speakers who begin work at a company where you are required to communicate only in English. The transitional state would be challenging. Even if you are the manager, you might doubt your capabilities or fear repercussions if you or your employees are less productive because of having to navigate a foreign language. You might even find your perspectives toward authority and decision-making change—or not. The point is that you would expect to go through a challenging transitional period of gaining fluency, under the assumption that practice and effort would eventually have an end point. During this temporary state of ambiguity, everyone’s task, regardless of their place in company hierarchy, is to negotiate between the organization’s past and its future until the transition is complete.4
In a digitally driven context, however, there is no end point to the transitional phase. Leadership is the act of bringing others through transitions. Constantly. Digital technology—and its impact on organizational structures, job roles, people’s competencies, and customer needs—is in constant flux. You master one software release only to have it replaced by a newer version that requires learning new features. Your department is reorganized to accommodate new ways of processing information—only to be reorganized again when the first effort fails. Your customer base expands because you can reach them with one medium, and then customer needs change because demographics shift.
Change has always been a constant in work and in life; the difference today has to do with the pace of change that digital technology entails. Digital shockwaves put us in a perpetual in-between state because the cycles of change are so rapid. Leadership that doesn’t acknowledge that transition is constant will struggle.5
Seeing digital change as constant transition requires leaders at all levels to develop a mindset that can embrace both the dynamism and uncertainty of permanent instability. Within the transitioning, your task is not simply to adapt—it is to be adaptive. Much like the AI and machine learning solutions that drive digital transformation of business, you, your colleagues, and your employees must constantly be processing new data, analyzing it, and using the findings to hone a perspective for the next wave of data coming at you.
Digital transformation is not a goal that you achieve; it is the means to achieve your unique goals, which fall on you to define and pursue. AI isn’t going to detect how much support you might need in accepting ambiguity. Machine learning isn’t going to teach you how to explain new protocols to your teammates or customers. Simply put, an adaptive mindset cannot be acquired, regardless of how much you invest in digital technology, or how many “digital gurus” you hire. It must be attained. And it can be attained, provided you learn to become comfortable with ambiguity and learn to accept that there’s no end point to transformation. Although this may at first be uncomfortable or even frightening, as you develop a digital mindset, you become attuned to the thrills that digital transition provides for continual learning.
Create a process for transitioning
Digital transformation is not a one-off project, something you can hand off to the executive suite or an isolated wing of your organization. A global appliance manufacturer learned this lesson the hard way when the highly experienced executive they brought in to spearhead its digital transformation surveyed the organization and determined that its workforce was too set in its ways to change.6 Had you been one of those people reluctant to change, you might have sighed with relief when this leader created a whole new business unit—separate from headquarters—comprised of fresh digital talent, allowing you to continue doing your job as usual.
For a while, that seemed to work for the appliance company. The new unit delivered with all the speed and innovation that digital promises. But the success was in a vacuum. At headquarters, the organization was in total disarray. Partners and customers were bombarding the company with exasperated complaints that the company’s online channel was not linked with the traditional face-to-face business channels. The revenue from these channels started to drop, compounding the tension between departments. Once internal communication broke down, the new digital unit collapsed. Within a matter of eight months, the executive hired to transform the company into a digital player had instead sparked chaos within the organization.
The company’s failure was not with the technology. In fact, the company’s digital unit was an immediate success on its own. What the company lacked was a transitional process. Instead of taking the time to help everyone within the organization to develop digital mindsets that could learn to accept the frustration and fear that often accompanies transition, leaders sought an external cure and what they believed would be an easier fix.
On the second go-round, the company picked an insider who knew the organization and modeled a well-developed digital mindset. She was respected across departments, especially for her perseverance, willingness to learn, and adaptivity to new situations. She started by implementing a training program that guided everyone throughout the company, from the sales force to the executives, through each new step of the digital initiative so that they understood and bought into its potential (instead of fearing the unfamiliar). Then, she reconnected with customers on an individual basis, working to understand each one’s specific needs and adapting her digital business model accordingly. Under her leadership, the majority of employees were able to develop digital mindsets and attain a transitional perspective. The company became a digital leader.
This transitional approach is also what guided Thierry Breton to succeed in his mission of dual digital transformation at Atos—undergoing radical change throughout the organization while helping customers through the process at the same time. Although it may sound surprising that an IT company needs help with digital transformation in its own ranks, that fact underscores our point about the constant and rapid change and the adaptive state a digital mindset requires. Just because you’ve mastered one technology doesn’t automatically mean that you are ready to adapt to the next round. As the story of Atos and others throughout the chapter will show, a transitional approach to leadership must negotiate two main points of focus in order for organizations to fully achieve digital goals both for itself and, when necessary, for the clients it serves:
· Designing and aligning systems and processes
· Preparing people for a digital organizational culture
Each of these points, of course, impacts the other directly. From a transitional view, the task is for you to maintain alignment between them as the ground continues to shift underneath.
Design and align systems and processes
A digital mindset needs systems and processes that are designed to align and support. Leaders may have to reorganize teams to be rapid, agile, self-regulating, and collaborative. Here’s a brief overview of how two companies did just that.
CEO Vincent van den Boogert realized the need to make fundamental transitions within his company, ING, a financial services company based in the Netherlands, when he noticed that existing internal processes were riddled with meetings, handovers, and other bureaucracies that were spread across functional departments, making limited use of data and digital technology to increase speed.7 Plus, no one functional group assumed end-to-end responsibility for the customers, creating potential problems. When van den Boogert decided to upend the company’s whole operating model, he looked to Silicon Valley, where agile processes were already established in digital companies like Spotify, Netflix, Google, and Zappos. He determined that ING needed to make the customer experience itself a commodity rather than presenting banking as just a service. As another executive put it, they needed to “un-bank the bank.” In order to offer this new customer experience, they first had to reorganize. ING moved to agile cross-functional team structures they called tribes. Autonomous teams started to use daily stand-ups to address every pressing customer need, promote transparency, and achieve performance goals. They employed the Jeff Bezos “two-pizza rule” such that group sizes were small enough that two pizzas could feed everyone. Along with rescaled team sizes came completely new roles and the elimination of others, including middle managers. These new roles required a developed digital mindset aligned with the company’s new scaled-down and digitally driven structures.
Similarly, Unilever, a ninety-year-old London-based multinational consumer goods company, needed to figure out how to adapt its sprawling global business for the digital age. As a multinational company that makes and sells over four hundred household staples in 190 countries, success was a delicate balancing act between the specificities of local markets and the broad scale of global operations. Unilever’s solution, like ING’s, was agile teams, which could focus on the demands of a particular last mile while simultaneously guiding their work with the company’s digital capacities across multiple countries. Rahul Welde, Unilever’s executive vice president in digital transformation and a thirty-year veteran of the organization, designed an agile team structure that allowed members to remain globally distributed while making strategic use of data for tailored initiatives within rapidly changing local markets.8 Under Welde’s leadership, Unilever formed three hundred ten-person agile teams that were remote, global, and able to operate at scale.
According to Welde, this strategy had three vectors. The first one involved the use of enabling technology and tools, which could reduce global-local divides. With digital platforms, brands could engage directly with customers in local markets on a vastly larger scale. The second was redesigning processes to adapt to new technology and tools. The last dimension was people. In the end, Welde recognized that people would be the change makers. Within eighteen months, Unilever had its three thousand agile team members deployed worldwide.
Follow data across silos—integrate!
Organizations must also use a transitional perspective to streamline communication across departments that were previously siloed. Moderna, an American biotechnology company made headlines in 2020, bringing out one of the first Covid-19 vaccines at breakneck speed. Integration across groups played a key role.9 The cofounder and CEO, Stéphane Bancel, calls Moderna a “tech company that happens to do biology.” Moderna exemplifies three of the main components of the current digital transformation. The first and foundational layer is its enormous access to data—the source of the company’s value in developing vaccines and other therapeutics. The second layer is its reliance on the cloud—it is not only cheaper but faster and more agile than in-house computing. The third is its capacity for automation—building AI algorithms to perform R&D processes with an accuracy and speed impossible to achieve manually.
Historically, big pharma companies have been globally distributed operations of siloed units, but Moderna uses a fully integrated structure where data flow freely among different teams that work together in real time.10 Juan Andres, the company’s chief technical operations and quality officer in charge of production processes, says, “What’s more important than having sophisticated digital tools or algorithms, is integration at all levels. The way things come together is what matters about technology, not the technology itself.” When Moderna was tasked with the urgent need to develop the vaccine, they could accelerate the process because that integration was already in place. Bancel had hired Marcello Damiani five years before the pandemic to be in charge of both digital and operational excellence. Bancel did not separate the two roles, explaining that “enabling Marcello to design the processes was key. Digitization only makes sense once the processes are done. If you have crappy analog processes, you’ll get crappy digital processes.” Fully integrated systems and processes allow Moderna to source some preexisting digital solutions for the vaccine and build many others in-house, either designing algorithms from scratch or tweaking existing ones to perform deeper and more specialized analyses. By spring 2020, Moderna had roughly twenty algorithms in production and another twenty in development. Integration is what made development of those algorithms possible, and it is ultimately what made the speedy and successful vaccine rollout happen.
Identify and implement the right digital tools
Although we each develop a digital mindset individually as we learn to become adaptive, that can only happen if organizational leaders realize that how digital tools are deployed is a core part of digital transformation. Leading continuous transition means managers must be heavily involved in selecting and implementing the digital tools that support change. To do that, it’s helpful to understand what today’s IT department can and cannot do. Historically IT departments have been well equipped to handle large, enterprise-wide implementations of software and to make sure that the software undergirding a company’s digital transformation works the way it should. This function of IT is still true for implementations of bespoke tools or, say, ERP systems. However, most of the technologies that companies adopt to enable digital transformation today are cloud-based tools that don’t require costly implementation efforts and are updated frequently and unobtrusively by another company. In most cloud implementations, if you are a functional or project manager, director, or in another senior leadership position, your role is to simply buy licenses, download the software, and get started without ever looping in IT. Just to be clear, we’re not advocating that you exclude IT completely. There are good reasons (e.g., cost, security, sustainability) to bring IT into any technology purchasing decision. But the stark reality is that a great number of SaaS implementations happen at the departmental or project level, without IT ever being involved. Ask any IT leader and they’ll tell you that managing departmental flexibility with the need for corporate regulation is becoming one of the most difficult parts of the job.
It’s important to deploy new digital technologies and manage implementations as a manager because these new technologies directly facilitate changes in the way people perform their tasks. These changes lead to new roles and responsibilities (such as when ING restructured into hundreds of ten-person agile teams), and they allow for new collaborative networks to open up within the organization (for example, Moderna’s integrated systems and processes). These new networks are the real positive drivers for the organization. While IT is accustomed to managing support applications, the task of defining new roles and networks—and effectively reshaping organizational culture and goals—is best suited for business leaders.
Preparing People and Culture for a Digital Shift
If everyone can plan for a transformation by thinking about how they will actually interact with and use the new digital tools, they will be more successful in acquiring the adaptive mindset necessary for successful transformation. Likewise, if everyone understands how tools will help attain better results, they will see how they can become the means for greater organizational change and problem-solving rather than the new technology as an end unto itself.
In other words, becoming comfortable with transitional states involves shifting the organization’s culture, its values, norms, attitudes, and behaviors.11 As a leader trying to promote the transformation and develop digital mindsets, how do you ensure that people understand that a new day has dawned? You start with a bold stroke: an act that commands attention and prompts the organization to understand that a new direction is required.12 Examples of bold strokes include a major reorganization, an acquisition, significant resources diverted, hiring a digital transformation czar who reports to the CEO, closures of legacy systems, or mandating that everyone learn some coding within a short time. A bold stroke has to be followed by a long march: the organized and enduring advancement toward new routines and behaviors.
Move from frustration to inspiration
A bold stroke is necessary but insufficient to gain buy-in. Any change provokes anxiety. With digital change, you, your colleagues, or your employees might be apprehensive not only about the unknown environment that will replace existing surroundings, but you may also worry about your own capacity to learn and apply the requisite technical material that you will need to perform effectively. These anxieties will affect technical and non-technical roles in equal measure. Engineers, for example, might not have the relevant technical competencies, as we discussed in earlier chapters.
We recommend a deceptively simple adoption framework that we have used to help leaders at many companies to influence people’s behaviors so that they are motivated to engage with a change program that requires learning new skills.13
Do I have buy-in such that people believe digital transformation will be beneficial for them and the organization? And can I learn what I need to in order to succeed in this transformed organization?
FIGURE 7-1
Four types of employee responses with digital transformation
Mapping the answers to these two questions produces four types of responses you’ll typically see and suggests what you need to do to make transformation successful. (See figure 7-1.)
The matrix of responses allows managers to locate where your team members might be. In the best-case scenario, people will be in the top-right quadrant, inspired by the change, believing that they have the capacity to learn digital content, and excited to go through the change. But, of course, you’ll have varying proportions in the four quadrants.
The good news is that leaders and managers can move individuals from one quadrant to another. To shift people from oppressed or indifferent to inspired, you first must increase buy-in by helping everyone believe that learning digital competencies is good for them and their organization. Three factors are crucial to promote buy-in:
· Increase messaging from leadership that stresses the importance of digital transformation as a new and critical frontier for the company.
· Launch internal marketing campaigns to help employees imagine the positive potential of a company powered by digital technology.
· Promote a shift in people’s identities; that is, encourage people to view themselves as contributing members of a digital organization.
After establishing buy-in, leaders can shift individuals from frustrated to inspired by boosting confidence in their capacity. Three factors contribute to people’s confidence in learning digital skills:
· People’s past experience with digital technologies—whether it was through education, employment, or work—tends to give them the confidence they need to succeed in this task.
· Vicarious experience of others, including peers and managers, influences beliefs in one’s own capabilities.
· Persuasion and encouragement from managers and executives promotes confidence in employees.
Upskilling
Hiring digitally trained employees is an efficient way to bring your workforce into the digital age, but it is unrealistic to rely on hiring alone to accomplish your goals, given the war for talent. An expansive upskilling plan of existing talent must supplement the new talent.
Let’s turn back to Thierry Breton from Atos. He spent his initial years as CEO doubling the size of company into a sprawling global enterprise with over 100,000 employees working in specialty IT areas like system integration, cloud, big data, cybersecurity, and others.14 This strategy was designed to fend off a sea of global competitors flanking him—startups from Silicon Valley, India, and China—many of which were born digital. While Atos had not yet integrated AI and other data-driven services into their processes when Breton took over, competitors were emerging with digital strategy in place and had employees with digital mindsets and expertise from their inception.
Breton couldn’t just acquire the skills to compete. He moved fast to upskill a large workforce comfortable with legacy IT and lacking the modern capabilities of a digital environment. In one survey, Atos had ranked thirty-ninth out of forty in digital maturity—the “continuous and ongoing process of adaptation to a changing digital landscape”—despite the fact that the company focused on IT systems.15 The upskilling was an ambitious three-year plan that required employees to learn new skills in training sessions that took them away from their day-to-day responsibilities.
Others in the C-suite resisted, convinced that the only way for people to learn was on the job. There was also disagreement about what percentage and which parts of the workforce would need digital training. After intense debate, as competitors kept increasing market share, Breton made the call: he created a digital transformation factory upskilling certification program. The goal was to train about thirty-five thousand people, both technical and non-technical, in digital technologies and portfolios, including big data, AI, hybrid cloud, business accelerators, and cybersecurity.16
The upskilling program was voluntary. A significant internal marketing campaign was launched to motivate people to build their digital mindsets. In addition, a peer and managerial nomination system was instituted, along with rewards for achieving various benchmarks in certification completion. The belief was that employees who decided on their own to get certified would be more likely to internalize the new skills and shift their behaviors for the digital era. Executives throughout the company would encourage training or demonstrate specific needs that people could pursue. For example, one executive said to his group that he needed people with cybersecurity skills and asked who would be interested to get training in that subject area. Approximately 250 people raised their hands, and 80 of the people who entered the training went on to become cybersecurity experts.
The company created a full suite of certifications under the Atos University Academy. It designed its digital programs in partnership with heavyweights like Google, EMC, Microsoft, and SAP, as well as universities and corporate learning companies. Sessions were delivered virtually, which meant that any employee could take courses regardless of their location. In addition, the content of the sessions was designed to accommodate everyone from the most technical engineers and data scientists to sales and marketing professionals, whose functions had limited technical dimensions. On average, each course took between four and eight weeks to complete with approximately five to sixteen hours of learning per week. For example, the hybrid cloud architect certification program took sixty to eighty hours over the course of two months. Assignments included four case studies, a written exam, and two labs. Less technical roles such as sales were offered digital awareness courses that people could select from four categories: cloud, business accelerators, digital workplace codex, and cybersecurity. One course was called “Cybersecurity landscape and Atos’s position”; another offering was “IoT solutions” within the digital workplace category.
Within three years, more than seventy thousand digital certifications had been completed. Every Atos employee had access to certification programs tailored to functional roles. Leaders at Atos saw that people were motivated to get certified because their jobs entailed some sort of a digital component. For example, salespeople had to be fluent in cloud computing or cybersecurity. Project managers needed to have a strong grasp of digital technologies’ functions and applications, even if they didn’t require an in-depth understanding of how the technologies worked. Those in technical roles, such as engineers or data analysts, needed to understand and operate new digital technologies with the same depth of expertise previously required for legacy technologies. Before long, it was clear to everyone that relevance and upward mobility at the company required a digital mindset that the certifications could help foster. Managers were also encouraged to take courses to build general awareness about digital offerings with emphasis on leading in a digital age.
Of course, Atos isn’t the only company that has become aggressive in upskilling its workforce; even technical companies are seeing that teaching employees digital skills is an imperative. When Google moved from a desktop-first to a mobile-first and then to a digital mindset, skills had to be upgraded accordingly—especially among the engineers. The company introduced a “Learn with Google AI” training program as a fast-paced introduction to machine learning and trained more than eighteen thousand employees globally over two years, a third of its engineering headcount. And Amazon, the online retail giant, committed to spend more than $700 million to retrain a third of its US workforce to be better equipped to deal with digital transformation because it saw technology threatening to upend the way many of its employees do their jobs.
Key practices for employee learning programs
Companies that have successfully implemented employee training programs to upskill a workforce in a digital era have followed these six practices:
1. Set a companywide goal.
2. Design learning opportunities that include all functional roles.
3. Prioritize virtual delivery, making learning scalable and accessible to everyone.
4. Motivate people to learn through campaigns, nominations, and rewards.
5. Provide managers digital training to understand the offerings and motivate employees.
6. Encourage projects within the company to adopt digital components, leading to direct application.
It’s important to note that organizations have to determine whether instituting a voluntary or compulsory program is best for them. In some companies, industries, and even countries, mandating learning might be the best approach. For example, Hiroshi Mikitani at Rakuten required his entire organization to learn how to code as part of his digital transformation objectives. This move was congruent with his mandate nearly a decade earlier that his Japanese-headquartered employees learn the English language for everyday work—a major initiative that he called “Englishnization.”17 Mandating with a deadline works for a company like Rakuten. Every organization needs to consider its own context when determining how to influence their employees to develop requisite digital skills.
Autoworks: A Process for Leading a Transition to Digitization
A formal example of leading transitions to digitization is what we call the work digitization process, which has six phases (see figure 7-2):18
FIGURE 7-2
How to plan your company’s transformation
By understanding how change naturally rolls out, you can start your planning with where you want to end up—identifying the gains in performance you can achieve with new digital tools—and work back from there to set company goals that employees will embrace.
Source: Adapted from P. Leonardi, “You’re Going Digital—Now What?” MIT Sloan Management Review (Winter 2020).
To illustrate the phases of this work digitization process, we’ll use an example from a European automotive company we’ll call Autoworks—a different company than the one Balaji and Davide worked for—which used the process to manage a digital transformation. Auto companies make great case studies because they have such complex physical products, but they have been at the forefront of digital transformation.
We’ll describe how digital transformations tend to be experienced and processed by those on the ground and then show how reverse planning—working backward, phase by phase, to set broad corporate goals—leads to digital transitioning that sticks.
Most digital transformation efforts are launched with extensive rollout plans that outline such activities as financing the transformation, reorganizing the company to make it agile enough to get the most out of digital tools, developing data-driven insights that allow the company to deliver more-customized products, and reducing time to market.
Phase 1: Leaders sell the digital transformation
Without widespread buy-in from employees, any major change initiative will wither and die. That’s why the first step in a successful effort is to explain the benefits of digital change to the workforce.
The leaders of Autoworks understood this. Autoworks had embarked upon a digital transformation in the mid-2000s. One goal was to accelerate product development while cutting costs in resource-intensive areas. Eager to get started, Autoworks’ senior leaders beefed up the company’s supercomputing center and licensed a slew of digital design applications. The CEO declared, “We’re going to be a digital company.”
Senior leaders were vocal and clear about the change they wanted. Digital performance testing meant that product development could get done faster and cheaper. Directors heard “faster and cheaper” in their staff meetings, managers heard “faster and cheaper” in their division meetings, and engineers heard “faster and cheaper” over and over from managers, directors, and executives in training sessions, at conferences, during all-hands meetings, and in everyday work. “Faster and cheaper” became the mantra of the digital transformation.
Studies show that employees listen when senior leaders broadcast goals and announce bold initiatives for achieving them.19 Early on, such pronouncements create frames of reference that people use to understand the technology they’re being asked to implement. If you asked employees at Autoworks how they would know if new tools could transform the organization, they would (and often did!) answer, “I’ll know if they help me build simulation models ‘faster and cheaper.’ ”
Phase 2: Employees decide whether to use the new technology
With messaging and training in place, leaders then fully expect that employees will shift their work to the new applications. But there’s no guarantee that will happen.20 At Autoworks, roughly 40 percent of potential users decided not to use the technology, even when it was mandated by their direct supervisors.
That’s a big number—big enough, in fact, to derail a digital transformation. So, it’s important for leaders to understand why so many employees might make that choice. We’ve found that employees consider whether the technology enables them as individuals to carry out the goals announced by the company’s leaders. At Autoworks, that meant that the engineers asked themselves, “Will this software help me develop new car designs faster and cheaper?”
As it turned out, not everyone thought it would. “Faster and cheaper” was more complicated rhetoric than Autoworks leaders had imagined. The phrase inadvertently encouraged people to compare the new tools with the old ones they knew inside and out and could already use quite efficiently. (“Faster” and “cheaper” grammatically are literally called “comparatives.”) Top engineers, who served as early adopters, did just that—they compared the new with the old—and decided that the new software actually slowed their work down. While they could see that it had other distinct advantages for the organization, they rejected it for failing, in their experience, to be faster and cheaper for them. These engineers decided that it was in their company’s best interest for them to stick with the tools they were already using. Making matters worse, the early experimenters had become negative influencers in the network of company engineers: other engineers decided that if a colleague they respected had rejected the new software, they didn’t even have to give it a try.
Of course, senior leaders had intended that “faster and cheaper” would be seen as the broad goal of the transformation effort. They hadn’t considered how those words might scan at various levels and influence granular decision-making. That’s why senior leaders must take great care in crafting their rhetoric. If it doesn’t match up with the reality of how work gets done, their prized new technology won’t get implemented in the way they hope.21
Phase 3: Employees decide how they will use the new technology
Even if the new technology encounters a band of naysayers, the many employees who do make the switch will come to a second critical decision: how to use it. Almost any digital technology can be adopted in many different ways, intended and not intended.22 In a digital transformation, the features people choose to apply are deeply consequential, since they determine what kind of data will be recorded, produced, or analyzed and how that data will be used.
Autoworks’ leaders believed that data were a key benefit of moving design processes into a digital environment. The use of simulation tools would make it possible for engineers to run hundreds or thousands of iterations of tests for crashes, or noise and vibration, and many other types. By comparing all those results, engineers would be able to optimize a vehicle’s design with far more sophistication than when the company ran a few dozen wrecks with crash test dummies. At least, that was the theory.
For one year, we tracked two departments that used the same digital tool for automating simulation designs. In one department, engineers engaged with the tool in widely varying ways, according to individual preference. In the other, every engineer used the same features in the same order. By the end of that year, the vehicles designed by the latter group were outperforming those created by the former by a 2-to-1 margin. The data produced by the engineers who had followed the same path had a uniform foundation and could be analyzed for patterns of effectiveness. The engineers who had followed their own paths produced just as much data, but the information arose from varying assumptions and choices.23 These kinds of differences around the company made it difficult to create a set of best practices for the new digital tools. If a central value of digital technologies is the creation of data that can be mined for efficiencies and other valuable learning, shaping consistent usage patterns is essential.
Phase 4: New kinds of data change the way employees behave
In its pre-digital days, Autoworks vehicle design testing standard operating procedure went like this: engineers conducted crashes and various other simulations, collected the data, and passed it along to the data analysis group, where analysts tried to glean universal principles for good vehicle design. There were engineers; there were data analysts. The difference between the two was clear.
Remember those engineers who used the new digital simulation tools in consistent ways to produce comparable data? They started to change the status quo by slowly integrating analysis into their work. They could see the results of their own tests, of course, and could examine results in the aggregate. But then they started talking to one another about their results and thinking about them together. As one engineer commented, “Now that we’ve gone digital, our roles as design engineers are changing.” Instead of being siloed away from one another while they ceded analysis to an equally siloed analysis department, the design engineers had become a collaborative team of data analysts.
Some “by-the-book” managers tried to curtail this empowerment by insisting on the separation between analysts and engineers. But this process of more and better data changing employee tasks, resulting in changed roles and relationships, is an inevitable by-product of digital transformations. At their core, relationships between people in different roles are based on data. When people start performing new roles because they have new data and information, they necessarily start interacting with different people. The result is the formation of new and initially invisible social networks. According to some research, these powerful new networks may be the most important ingredient in driving a digital transformation.24
Phase 5: Performance improves locally
There’s often a dichotomy between the targets business leaders impose for their digital transformations and the benefits employees experience at a local level.
Once they were effectively using the new digital tools and comparing results with others in their emerging social network, Autoworks engineers started to see real concrete gains that they could appreciate. For instance, they found that it was becoming easier for them to optimize designs for key features like crashworthiness and fuel economy.
The process of moving from testing to final design solutions improved significantly, as well. In fact, according to our analysis, engineers who changed their roles to incorporate data analytics and shifted their social networks to interact with other engineers solidified the design of their vehicles 23 percent faster and with 31 percent fewer laboratory tests than engineers whose roles didn’t change. In other words, engineers were working “faster and cheaper,” after all.
That sounds like the kind of success Autoworks leaders had been hoping for. And it is. But there are two important caveats. The first, of course, is that 40 percent of engineers initially rejected the software because they hadn’t found it obviously “faster and cheaper.” The second is that those engineers who did achieve “faster and cheaper” gains arrived at them via metrics that mattered to them in their roles, like design quality improvements. If senior executives had customized their rhetoric early on to resonate with engineers’ own experience of their work, they might have motivated more engineers to adopt the new digital tools sooner and secured even more significant gains.
Phase 6: Local performance aligns with company goals
A digital transformation gets traction when it meets key corporate goals by employing technologies that improve local processes and results.
One reason Autoworks chose to focus intently on vehicle design is that twenty years of robust statistical analysis had identified that process—along with supply chain, regulatory compliance, and manufacturing efficiency—as critical to reducing the time it took to get cars from concept to dealer. Better time-to-market would accelerate top-line growth.
Needless to say, the company was happy that the technologies led to “faster and cheaper” designs. Rather than sit on its laurels, however, Autoworks conducted a deep analysis of how the gains had been achieved. That’s how they discovered the remarkable value of the social network that had been unleashed by the new design software: engineers who spent three times as many hours discussing vehicle design with one another as they spent instrumenting simulation models dramatically reduced the amount of rework that needed to be done in later stages of development. Sure, new software helped engineers speed up the delivery of a final, optimized vehicle design, but the dialogue spurred by the software accelerated things even more.
Autoworks Best Practices
By digging into its success, Autoworks uncovered two key learnings that could fuel further improvements in the years ahead. One focuses on the planning process and the other on whom you involve in the process.
Plan in reverse
The six phases we’ve just described illustrate the way change develops internally during a digital transformation. Now let’s turn to how understanding this process should shape planning for your own company’s transformation. This process can be derailed at any stage, so it is crucial to plan in a way that keeps everyone’s experience front-of-mind. (See figure 7-3.)
FIGURE 7-3
How to plan your company’s transformation
By understanding how change naturally rolls out, you can start your planning with where you want to end up—identifying the gains in performance you can achieve with new digital tools—and work back from there to set company goals that employees will embrace.
Source: Adapted from P. Leonardi, “You’re Going Digital—Now What?” MIT Sloan Management Review (Winter 2020).
The key is to plan backward, with the end goal first. One approach is to identify which local activities have the highest potential to transform, since this will inform the choice of digital tools and the direction of the digital transformation. To do so, organizations need to gather and analyze internal data on which local outcomes best drive larger organizational goals: this will highlight an area of improvement that can be targeted and facilitated with a digital tool. In the middle of this process, the organization must continue to gather data to see if the efforts are working, and whether behaviors within the organization are helping or hindering those efforts.
It is also key to foster an environment that allows everyone to meet their goals through the transformation, especially as their tasks and roles change in the process. Leaders can help facilitate this by understanding how information flows within the organization and by removing institutional obstacles that might prevent employees from embracing the change. Diagnostic processes like an organizational network analysis can be particularly effective.25 This kind of analysis can show which groups of employees interact with one another, how they interact, and what kinds of new groups might emerge through the transformation process. This analysis can in turn help leadership facilitate the appropriate formal role transitions and identify key influencers to help champion the change.
Identify and recruit digital mindset influencers
Encourage those that are already further along in developing a digital mindset to become exemplars or beacons for those who are more reluctant. In addition, take the time to discuss the desired transformation with influencers who are trusted by others. That discussion may surface general concerns and ideas for improvements. Ultimately, you will want to ask influencers to help generate the messaging that would convey the benefits to the workforce. Hearing directly from trusted colleagues can significantly improve employees’ willingness to embrace the change and the new technology. Holding training sessions, clearly establishing new targets, and even looking to hire new employees who already have the newly desired skill set are also part of digital transformation.
When campaigning for digital transformation, if you fail to explain the benefits of the desired change in terms that are meaningful for those who will be using the technology, you can fail to generate much-needed early buy-in, or even create misunderstandings about how the transformation will take place at the practical level. Even when there is substantial buy-in, many may choose not to use the new technology if they perceive themselves to be better equipped at meeting desired goals with preexisting technology. People will find reasons to resist change if they can. For example, if the stated goal of the transformation is to make processes faster and cheaper, some people may feel that the best option for them is to continue using the tools they already are proficient at using. Moreover, even among groups who readily adopt the new digital tools, if a consistent pattern of usage is not sufficiently adopted, the efficacy of the new technology—as well as the analyzable data its adoption produces—can be diminished.
Transition to Continuous Learning
Continuous learning has become an economic imperative for people and organizations alike in the face of rapid changes in the digital economy.26 Continuous learning environments work best if there is employee autonomy, tailored curricula, and psychological safety. And to state the obvious, these conditions have to align with the strategic combination of digital technology (AI- and cloud-enabled platforms, in particular) and effective leadership.
Successful continuous learning initiatives are ones that foster individual autonomy for learners to own the process themselves. That is, learning has to be decentralized and become a responsibility that each person owns. At Spotify, for example, all employees are responsible for their learning, although the company has a robust learning and development group called the GreenHouse to honor the company’s focus on enablement. As a greenhouse does for plants, the group promotes the idea of watering and fertilizing growth. It also understands that in order to promote self-ownership, finding modular content online has to be easy for employees. Spotify built an in-house learning platform for delivering education that has the same functionality as a social media or entertainment platform (think Instagram). Other companies, like Philips, have adopted the playlist. Employees can share playlists of their tailored lessons with colleagues, thereby helping to enhance knowledge exchange from the ground up. Ultimately, an organization’s ability to adapt through continuous learning is dependent on the motivation and commitment of its employees to engage in the process themselves. For continuous learning to be sustainable in the long term, learners must be internally motivated.
Tailored curricula are the core of continuous learning initiatives. Instead of generic training programs applied to the whole workforce, customized learning plans are designed for specific roles and functions based on the skills and credentials necessary for each. Software engineers might learn a new coding language, while salespeople might learn business development strategy of technologies like cloud or cybersecurity. To tailor curricula even further, AI-enabled learning experience platforms (LXPs) can adapt content to an individual’s own pace and needs. One learner might thrive within a fast-paced curriculum that keeps her on her toes. Another might do better with a slower pace that allows him to chew on the subject matter. As learners progress, they gain microcredentials—certifications or badges for validating specific digital skills (for instance, “web scraping in Python”) that can be acquired in a much shorter time than the traditional educational formats offered by universities. To offset the feeling of isolation that sometimes accompanies individualized learning, Westpac, one of Australia’s biggest banks, also encourages community building among people who share similar areas of interest.
Continuous learning marks a new paradigm for education and career growth (see appendix for examples). This paradigm is inherently dynamic. It differs from the previous model that provided the stability of a fixed role and skill set for one’s whole career. A common denominator of effective continuous learning programs is a blended approach that can be individualized for employee autonomy and flexibility. Capital One, the bank holding company, offers a blend of learning choices to its software engineering teams that include online courses, in-person workshops, boot camps, and trainings from outside experts. In addition to the tech curriculum offered through its own internal university, Capital One also partners with larger, distance-learning organizations.
For employees to feel comfortable reaching outside their wheelhouse and learning new skills for the rest of their professional lives, leaders must establish a culture of psychological safety that encourages exploration and the courage to fail. Ideally, leaders will model their own failures, as is done at Spotify. For example, the online travel and lodging agency Booking.com has fostered an environment of continuous learning that allows employees to pursue completely different roles within the organization with the understanding that they will have become beginners and may not immediately be as proficient as they were in their previous role. Kim dos Santos, an employee who began in the human resources department, explains how his interest in design led him to take classes in user experience (UX) design offered by the company.27 Despite having no previous background in UX before joining the company, he learned and progressed to such a degree that he was eventually hired internally as a UX designer.
While leadership and employee development have always been essential to organizational performance and stability, the rate of technological change inherent in the digital economy makes continuous learning a necessary component to achieve these goals. Support to develop leaders who can mentor less experienced employees and pathways for growth and mobility within the company are both crucial. For example, at AT&T, leaders provide emotional support, strategic advice, honest feedback, and of course, encouragement. The crowdsourcing business review platform Yelp, an early adopter of continuous learning, also encourages managers to mentor with the principle “leaders who teach.” Horizontal learning and the exchange of new ideas and information across the company is fostered in several ways at Yelp. The engineering team regularly invites guest speakers for lunch—usually someone from within the company—enabling collaboration as well as stimulating growth. An informal, voluntary program introduces employees to someone within the company they haven’t met in order to learn from one another or simply connect. Innovations that result from groups of engineers who participate in two-day hackathons are successful to the extent that team members learn from one another; they are also opportunities to meet new people.
Centralized support for people to learn and try new things is essential to nurture a culture that encourages continuous learning. Thoughtful attention to the learning environment and employee learning needs is as imperative to success as new knowledge and skill sets.
Fittingly, it’s digitization itself that provides the technology for online, individualized, and autonomous learning that makes this possible.
GETTING TO 30 PERCENT
Transitioning and Preparing for Continuous Change
Digital transformation is when organizations redesign underlying systems and processes to align with today’s data and digital technology, including artificial intelligence, machine learning, and the internet of things. Digital transformation is not a one and done; it’s a state of perpetual transition; your task is not simply to adapt, but to be adaptive. Leaders can emphasize specific mindsets and strategies:
· Teams must become agile, autonomous, and collaborative. Communication must be fast and effective to keep up with the speed of digital transformation.
· Every member of the team must be able to identify how, why, when, and which digital tools align with strategic goals. Tech savvy is no longer strictly the realm of IT.
· Work backward: identify your strategic goals first, then find the right digital solution. Gain buy-in by showing team members how the solution achieves team goals. This is the work digitization process.
· Replace obstacles to learning new skills with boosts: hold training sessions, establish new targets, and recruit digital mindset influencers who can champion change.
· Use the adoption framework to turn frustration about digital change into inspiration. The framework is built on the following two questions team members must ask themselves: Have I bought in? and Am I capable of learning? To bring employees from “no” to “yes” on both questions, stress the importance of digital transformation for the organization, each employees’ critical role in the process, and your confidence in their capacity to learn.
· For continuous learning to be sustainable, learners must be internally motivated and develop individual autonomy.
· For employees to feel comfortable learning new skills for the rest of their professional lives, leaders must establish a culture of psychological safety that encourages exploration and the courage to fail.
Upskill your team! The war for digital talent is fierce. Focus on upskilling talent within your ranks over hiring talent from the outside. Hard skills can be learned; institutional knowledge takes time to build. This new educational paradigm means employees and organizations must continually upskill to stay competitive.