healthcarereimagined

BY MIKE WHEATLEY

NXP Semiconductors N.V. has kicked off what could be the start of a new trend in the computer chipmaking industry, announcing that it’s moving the vast majority of its electronics design automation workloads to Amazon Web Services Inc.’s public cloud platform.

The company said today it has selected AWS as its preferred cloud provider. By moving its EDA workloads to Amazon’s cloud, NXP will gain increased efficiency and more compute power that should help it to design a new generation of faster and more powerful computer chips for the automotive, industrial “internet of things,” mobile and communications infrastructure sectors.

According to Amazon, NXP has already seen benefits that include enhanced collaboration and increased EDA throughput since moving to AWS, while reducing costs and gaining more time to focus on actual design, rather than managing compute resources.

More interesting, though, are the expected long-term benefits of moving such a compute-heavy workload as EDA to the cloud. NXP says it believes it will be able to achieve some important process improvements that will revolutionize the way it designs and tests its central processing units.

As the company explains, each new chip design is put through extensive testing and validation before it’s manufactured to ensure it is functionally safe and secure and delivers the expected performance. This work includes front-end design workflows such as performance simulation and verification, as well as back-end workloads around timing and power analysis, design rule checks and other applications necessary to prepare a new chip for production.

Previously, NXP, like other chipmakers, had always done this on-premises in internal data centers with a fixed compute capacity. But because of the increasing complexity of newer chips, it means these processes can take many months or even years to complete, and they call for the accurate forecasting and installation of new compute infrastructure.

As a result, it makes sense for NXP to move to the cloud, where it can tap into AWS’ advanced infrastructure and the scale and agility it needs to advance multiple chip design and testing projects at the same time. The move will enable it to run dozens of performance simulations in parallel, resulting in faster overall design times.

Shifting to the cloud also enables NXP to leverage key AWS analytics and machine learning services that can aid its research and development efforts. For instance, NXP is already using Amazon QuickSight, a machine learning-powered business intelligence service, to boost workflow efficiencies. By rapidly translating the results from one step of testing into modifications for another, it can reduce the time it takes to iterate on chip designs, NXP said.

The company also makes use of Amazon SageMaker, a service that’s used to build, train and deploy machine learning models in the cloud and at the edge, to optimize the way it structures compute, storage and third-party software application licenses.

NXP also benefits from the wide range of specialized instances available on AWS that allow it to achieve the perfect balance of price/performance for its EDA workflows.

Constellation Research Inc. analyst Holger Mueller told SiliconANGLE the key advantage of cloud platforms such as AWS is that they allow “commercial elasticity” for enterprises.

“In the roller-coaster bound semiconductor industry it makes sense to evaluate capital spending demand, so it’s a smart idea by NXP to move its EDA workloads to the cloud,” Mueller said. “EDA is early in the value chain for semiconductor makers, and not all design work leads to actual chips that are made.”

Charles King, an analyst with Pund IT Inc., said moving its EDA workloads to Amazon could provide compelling value to relatively smaller silicon player compared with the biggest ones such as Intel Corp. “Offloading compute and storage to a cloud vendor should reduce capital expenditures, and may also result in the company reducing IT headcount,” King said. “It wouldn’t be surprising if other vendors in NXP’s class are contemplating similar moves, though I doubt major semiconductor players will follow suit.”

NXP Semiconductors Chief Information Officer Olli Hyyppa said cloud-based EDA is necessary to accelerate semiconductor innovation and get new designs to market faster.

“AWS gives us the best scale, global presence, and selection of compute and storage options, with continuous improvements in price performance, that we need,” he said. “This will give precious time back to our design engineers to focus on innovation and lead the transformation of the semiconductor industry.”

Article link: https://siliconangle.com/2021/10/14/nxp-semiconductors-moves-chip-design-workloads-amazons-cloud/

How to go from a few teams to hundreds by 

• Darrell K. Rigby,
• Jeff Sutherland,
• Andy Noble

From the Magazine (May–June 2018)

Summary.   

When implemented correctly, agile innovation teams almost always result in higher team productivity and morale, faster time to market, better quality, and lower risk than traditional approaches can achieve. What if a company were to launch dozens, hundreds, or even thousands of agile teams? Could whole segments of the business learn to operate in this manner?

As enticing as such a prospect is, turning it into a reality can be challenging. Companies often struggle to know which functions should be reorganized into multidisciplinary agile teams and which should not. And it’s not unusual to launch dozens of new agile teams only to see them bottlenecked by slow-moving bureaucracies.

The authors, who have studied the scaling of agile at hundreds of companies, share what they’ve learned about how to do it effectively. Leaders should use agile methodologies themselves and create a taxonomy of opportunities to set priorities and break the journey into small steps. Workstreams should be modularized and then seamlessly integrated. Functions not reorganized into agile teams should learn to operate with agile values. And the annual budgeting process should be complemented with a VC-like approach to funding.

By now most business leaders are familiar with agile innovation teams. These small, entrepreneurial groups are designed to stay close to customers and adapt quickly to changing conditions. When implemented correctly, they almost always result in higher team productivity and morale, faster time to market, better quality, and lower risk than traditional approaches can achieve.

Naturally, leaders who have experienced or heard about agile teams are asking some compelling questions. What if a company were to launch dozens, hundreds, or even thousands of agile teams throughout the organization? Could whole segments of the business learn to operate in this manner? Would scaling up agile improve corporate performance as much as agile methods improve individual team performance?

In today’s tumultuous markets, where established companies are furiously battling assaults from start-ups and other insurgent competitors, the prospect of a fast-moving, adaptive organization is highly appealing. But as enticing as such a vision is, turning it into a reality can be challenging. Companies often struggle to know which functions should be reorganized into multidisciplinary agile teams and which should not. And it’s not unusual to launch hundreds of new agile teams only to see them bottlenecked by slow-moving bureaucracies.

We have studied the scaling up of agile at hundreds of companies, including small firms that run the entire enterprise with agile methods; larger companies that, like Spotify and Netflix, were born agile and have become more so as they’ve grown; and companies that, like Amazon and USAA (the financial services company for the military community), are making the transition from traditional hierarchies to more-agile enterprises. Along with the many success stories are some disappointments. For example, one prominent industrial company’s attempts over the past five years to innovate like a lean start-up have not yet generated the financial results sought by activist investors and the board of directors, and several senior executives recently resigned.

Our studies show that companies can scale up agile effectively and that doing so creates substantial benefits. But leaders must be realistic. Not every function needs to be organized into agile teams; indeed, agile methods aren’t well suited to some activities. Once you begin launching dozens or hundreds of agile teams, however, you can’t just leave the other parts of the business alone. If your newly agile units are constantly frustrated by bureaucratic procedures or a lack of collaboration between operations and innovation teams, sparks will fly from the organizational friction, leading to meltdowns and poor results. Changes are necessary to ensure that the functions that don’t operate as agile teams support the ones that do.

Leading Agile by Being Agile

For anyone who isn’t familiar with agile, here’s a short review. Agile teams are best suited to innovation—that is, the profitable application of creativity to improve products and services, processes, or business models. They are small and multidisciplinary. Confronted with a large, complex problem, they break it into modules, develop solutions to each component through rapid prototyping and tight feedback loops, and integrate the solutions into a coherent whole. They place more value on adapting to change than on sticking to a plan, and they hold themselves accountable for outcomes (such as growth, profitability, and customer loyalty), not outputs (such as lines of code or number of new products).

Conditions are ripe for agile teams in any situation where problems are complex, solutions are at first unclear, project requirements are likely to change, close collaboration with end users is feasible, and creative teams will outperform command-and-control groups. Routine operations such as plant maintenance, purchasing, and accounting are less fertile ground. Agile methods caught on first in IT departments and are now widely used in software development. Over time they have spread into functions such as product development, marketing, and even HR. (See “Embracing Agile,” HBR, May 2016, and “HR Goes Agile,” HBR, March–April 2018.)

Agile teams work differently from chain-of-command bureaucracies. They are largely self-governing: Senior leaders tell team members where to innovate but not how. And the teams work closely with customers, both external and internal. Ideally, this puts responsibility for innovation in the hands of those who are closest to customers. It reduces layers of control and approval, thereby speeding up work and increasing the teams’ motivation. It also frees up senior leaders to do what only they can do: create and communicate long-term visions, set and sequence strategic priorities, and build the organizational capabilities to achieve those goals.

When leaders haven’t themselves understood and adopted agile approaches, they may try to scale up agile the way they have attacked other change initiatives: through top-down plans and directives. The track record is better when they behave like an agile team. That means viewing various parts of the organization as their customers—people and groups whose needs differ, are probably misunderstood, and will evolve as agile takes hold. The executive team sets priorities and sequences opportunities to improve those customers’ experiences and increase their success. Leaders plunge in to solve problems and remove constraints rather than delegate that work to subordinates. The agile leadership team, like any other agile team, has an “initiative owner” who is responsible for overall results and a facilitator who coaches team members and helps keep everyone actively engaged.

Bosch, a leading global supplier of technology and services with more than 400,000 associates and operations in 60-plus countries, took this approach. As leaders began to see that traditional top-down management was no longer effective in a fast-moving, globalized world, the company became an early adopter of agile methods. But different business areas required different approaches, and Bosch’s first attempt to implement what it called a “dual organization”—one in which hot new businesses were run with agile teams while traditional functions were left out of the action—compromised the goal of a holistic transformation. In 2015 members of the board of management, led by CEO Volkmar Denner, decided to build a more unified approach to agile teams. The board acted as a steering committee and named Felix Hieronymi, a software engineer turned agile expert, to guide the effort.

At first Hieronymi expected to manage the assignment the same way Bosch managed most projects: with a goal, a target completion date, and regular status reports to the board. But that approach felt inconsistent with agile principles, and the company’s divisions were just too skeptical of yet another centrally organized program. So the team shifted gears. “The steering committee turned into a working committee,” Hieronymi told us. “The discussions got far more interactive.” The team compiled and rank-ordered a backlog of corporate priorities that was regularly updated, and it focused on steadily removing companywide barriers to greater agility. Members fanned out to engage division leaders in dialogue. “Strategy evolved from an annual project to a continuous process,” Hieronymi says. “The members of the management board divided themselves into small agile teams and tested various approaches—some with a ‘product owner’ and an ‘agile master’—to tackle tough problems or work on fundamental topics. One group, for instance, drafted the 10 new leadership principles released in 2016. They personally experienced the satisfaction of increasing speed and effectiveness. You can’t gain this experience by reading a book.” Today Bosch operates with a mix of agile teams and traditionally structured units. But it reports that nearly all areas have adopted agile values, are collaborating more effectively, and are adapting more quickly to increasingly dynamic marketplaces.

Getting Agile Rolling

At Bosch and other advanced agile enterprises, the visions are ambitious. In keeping with agile principles, however, the leadership team doesn’t plan every detail in advance. Leaders recognize that they do not yet know how many agile teams they will require, how quickly they should add them, and how they can address bureaucratic constraints without throwing the organization into chaos. So they typically launch an initial wave of agile teams, gather data on the value those teams create and the constraints they face, and then decide whether, when, and how to take the next step. This lets them weigh the value of increasing agility (in terms of financial results, customer outcomes, and employee performance) against its costs (in terms of both financial investments and organizational challenges). If the benefits outweigh the costs, leaders continue to scale up agile—deploying another wave of teams, unblocking constraints in less agile parts of the organization, and repeating the cycle. If not, they can pause, monitor the market environment, and explore ways to increase the value of the agile teams already in place (for instance, by improving the prioritization of work or upgrading prototyping capabilities) and decrease the costs of change (by publicizing agile successes or hiring experienced agile enthusiasts).

To get started on this test-and-learn cycle, leadership teams typically employ two essential tools: a taxonomy of potential teams and a sequencing plan reflecting the company’s key priorities. Let’s first look at how each can be employed and then explore what more is needed to tackle large-scale, long-term agile initiatives.

Create a taxonomy of teams.

Just as agile teams compile a backlog of work to be accomplished in the future, companies that successfully scale up agile usually begin by creating a full taxonomy of opportunities. Following agile’s modular approach, they may break the taxonomy into three components—customer experience teams, business process teams, and technology systems teams—and then integrate them. The first component identifies all the experiences that could significantly affect external and internal customer decisions, behaviors, and satisfaction. These can usually be divided into a dozen or so major experiences (for example, one of a retail customer’s major experiences is to buy and pay for a product), which in turn can be divided into dozens of more-specific experiences (the customer may need to choose a payment method, use a coupon, redeem loyalty points, complete the checkout process, and get a receipt). The second component examines the relationships among these experiences and key business processes (improved checkout to reduce time in lines, for instance), aiming to reduce overlapping responsibilities and increase collaboration between process teams and customer experience teams. The third focuses on developing technology systems (such as better mobile-checkout apps) to improve the processes that will support customer experience teams.

The taxonomy of a $10 billion business might identify anywhere from 350 to 1,000 or more potential teams. Those numbers sound daunting, and senior executives are often loath even to consider so much change (“How about if we try two or three of these things and see how it goes?”). But the value of a taxonomy is that it encourages exploration of a transformational vision while breaking the journey into small steps that can be paused, turned, or halted at any time. It also helps leaders spot constraints. Once you’ve identified the teams you could launch and the sorts of people you would need to staff them, for instance, you need to ask: Do we have those people? If so, where are they? A taxonomy reveals your talent gaps and the kinds of people you must hire or retrain to fill them. Leaders can also see how each potential team fits into the goal of delivering better customer experiences.

USAA has more than 500 agile teams up and running and plans to add 100 more in 2018. The taxonomy is fully visible to everyone across the enterprise. “If you don’t have a really good taxonomy, you get redundancy and duplication,” COO Carl Liebert told us. “I want to walk into an auditorium and ask, ‘Who owns the member’s change-of-address experience?’ And I want a clear and confident response from a team that owns that experience, whether a member is calling us, logging into our website on a laptop, or using our mobile app. No finger-pointing. No answers that begin with ‘It’s complicated.’”

USAA’s taxonomy ties the activities of agile teams to the people responsible for business units and product lines. The goal is to ensure that managers responsible for specific parts of the P&L understand how cross-functional teams will influence their results. The company has senior leaders who act as general managers in each line of business and are fully accountable for business results. But those leaders rely on customer-focused, cross-organizational teams to get much of the work done. The company also depends on technology and digital resources assigned to the experience owners; the goal here is to ensure that business leaders have the end-to-end resources to deliver the outcomes they have committed to. The intent of the taxonomy is to clarify how to engage the right people in the right work without creating confusion. This kind of link is especially important when hierarchical organizational structures do not align with customer behaviors. For example, many companies have separate structures and P&Ls for online and offline operations—but customers want seamlessly integrated omnichannel experiences. A clear taxonomy that launches the right cross-organizational teams makes such alignment possible.

Sequence the transition.

Taxonomy in hand, the leadership team sets priorities and sequences initiatives. Leaders must consider multiple criteria, including strategic importance, budget limitations, availability of people, return on investment, cost of delays, risk levels, and interdependencies among teams. The most important—and the most frequently overlooked—are the pain points felt by customers and employees on the one hand and the organization’s capabilities and constraints on the other. These determine the right balance between how fast the rollout should proceed and how many teams the organization can handle simultaneously.

A few companies, facing urgent strategic threats and in need of radical change, have pursued big-bang, everything-at-once deployments in some units. For example, in 2015 ING Netherlands anticipated rising customer demand for digital solutions and increasing incursions by new digital competitors (“fintechs”). The management team decided to move aggressively. It dissolved the organizational structures of its most innovative functions, including IT development, product management, channel management, and marketing—essentially abolishing everyone’s job. Then it created small agile “squads” and required nearly 3,500 employees to reapply for 2,500 redesigned positions on those squads. About 40% of the people filling the positions had to learn new jobs, and all had to profoundly change their mindset. (See “One Bank’s Agile Team Experiment,” HBR, March–April 2018.)

But big-bang transitions are hard. They require total leadership commitment, a receptive culture, enough talented and experienced agile practitioners to staff hundreds of teams without depleting other capabilities, and highly prescriptive instruction manuals to align everyone’s approach. They also require a high tolerance of risk, along with contingency plans to deal with unexpected breakdowns. ING continues to iron out wrinkles as it expands agile throughout the organization.

Companies short on those assets are better off rolling out agile in sequenced steps, with each unit matching the implementation of opportunities to its capabilities. At the beginning of its agile initiative, the advanced technology group at 3M Health Information Systems launched eight to 10 teams every month or two; now, two years in, more than 90 teams are up and running. 3M’s Corporate Research Systems Lab got started later but launched 20 teams in three months.

Big-bang transitions are hard. It may be better to roll out agile in steps.

Whatever the pace or endpoint, results should begin showing up quickly. Financial results may take a while—Jeff Bezos believes that most initiatives take five to seven years to pay dividends for Amazon—but positive changes in customer behavior and team problem solving provide early signs that initiatives are on the right track. “Agile adoption has already enabled accelerated product deliveries and the release of a beta application six months earlier than originally planned,” says Tammy Sparrow, a senior program manager at 3M Health Information Systems.

Division leaders can determine the sequencing just as any agile team would. Start with the initiatives that offer potentially the greatest value and the most learning. SAP, the enterprise software company, was an early scaler of agile, launching the process a decade ago. Its leaders expanded agile first in its software development units—a highly customer-centric segment where they could test and refine the approach. They established a small consulting group to train, coach, and embed the new way of working, and they created a results tracker so that everyone could see the teams’ gains. “Showing concrete examples of impressive productivity gains from agile created more and more pull from the organization,” says Sebastian Wagner, who was then a consulting manager in that group. Over the next two years the company rolled out agile to more than 80% of its development organizations, creating more than 2,000 teams. People in sales and marketing saw the need to adapt in order to keep up, so those areas went next. Once the front end of the business was moving at speed, it was time for the back end to make the leap, so SAP shifted its group working on internal IT systems to agile.

Too many companies make the mistake of going for easy wins. They put teams into offsite incubators. They intervene to create easy workarounds to systemic obstacles. Such coddling increases the odds of a team’s success, but it doesn’t produce the learning environment or organizational changes necessary to scale dozens or hundreds of teams. A company’s early agile teams carry the burden of destiny. Testing them, just like testing any prototype, should reflect diverse, realistic conditions. Like SAP, the most successful companies focus on vital customer experiences that cause the greatest frustrations among functional silos.

Still, no agile team should launch unless and until it is ready to begin. Ready doesn’t mean planned in detail and guaranteed to succeed. It means that the team is:

1. focused on a major business opportunity with a lot at stake
2. responsible for specific outcomes
3. trusted to work autonomously—guided by clear decision rights, properly resourced, and staffed with a small group of multidisciplinary experts who are passionate about the opportunity
4. committed to applying agile values, principles, and practices
5. empowered to collaborate closely with customers
6. able to create rapid prototypes and fast feedback loops
7. supported by senior executives who will address impediments and drive adoption of the team’s work

Following this checklist will help you plot your sequence for the greatest impact on both customers and the organization.

Master large-scale agile initiatives.

Many executives have trouble imagining that small agile teams can attack large-scale, long-term projects. But in principle there is no limit to the number of agile teams you can create or how large the initiative can be. You can establish “teams of teams” that work on related initiatives—an approach that is highly scalable. Saab’s aeronautics business, for instance, has more than 100 agile teams operating across software, hardware, and fuselage for its Gripen fighter jet—a $43 million item that is certainly one of the most complex products in the world. It coordinates through daily team-of-teams stand-ups. At 7:30 AM each frontline agile team holds a 15-minute meeting to flag impediments, some of which cannot be resolved within that team. At 7:45 the impediments requiring coordination are escalated to a team of teams, where leaders work to either settle or further escalate issues. This approach continues, and by 8:45 the executive action team has a list of the critical issues it must resolve to keep progress on track. Aeronautics also coordinates its teams through a common rhythm of three-week sprints, a project master plan that is treated as a living document, and the colocation of traditionally disparate parts of the organization—for instance, putting test pilots and simulators with development teams. The results are dramatic: IHS Jane’s has deemed the Gripen the world’s most cost-effective military aircraft.

Leadership teams need to instill agile values throughout the entire enterprise.

Building Agility Across the Business

Expanding the number of agile teams is an important step toward increasing the agility of a business. But equally important is how those teams interact with the rest of the organization. Even the most advanced agile enterprises—Amazon, Spotify, Google, Netflix, Bosch, Saab, SAP, Salesforce, Riot Games, Tesla, and SpaceX, to name a few—operate with a mix of agile teams and traditional structures. To ensure that bureaucratic functions don’t hamper the work of agile teams or fail to adopt and commercialize the innovations developed by those teams, such companies constantly push for greater change in at least four areas.

Values and principles.

A traditional hierarchical company can usually accommodate a small number of agile teams sprinkled around the organization. Conflicts between the teams and conventional procedures can be resolved through personal interventions and workarounds. When a company launches several hundred agile teams, however, that kind of ad hoc accommodation is no longer possible. Agile teams will be pressing ahead on every front. Traditionally structured parts of the organization will fiercely defend the status quo. As with any change, skeptics can and will produce all kinds of antibodies that attack agile, ranging from refusals to operate on an agile timetable (“Sorry, we can’t get to that software module you need for six months”) to the withholding of funds from big opportunities that require unfamiliar solutions.

So a leadership team hoping to scale up agile needs to instill agile values and principles throughout the enterprise, including the parts that do not organize into agile teams. This is why Bosch’s leaders developed new leadership principles and fanned out throughout the company: They wanted to ensure that everyone understood that things would be different and that agile would be at the center of the company’s culture.

Operating architectures.

Implementing agile at scale requires modularizing and then seamlessly integrating workstreams. For example, Amazon can deploy software thousands of times a day because its IT architecture was designed to help developers make fast, frequent releases without jeopardizing the firm’s complex systems. But many large companies, no matter how fast they can code programs, can deploy software only a few times a day or a week; that’s how their architecture works.

Building on the modular approach to product development pioneered by Toyota, Tesla meticulously designs interfaces among the components of its cars to allow each module to innovate independently. Thus the bumper team can change anything as long as it maintains stable interfaces with the parts it affects. Tesla is also abandoning traditional annual release cycles in favor of real-time responses to customer feedback. CEO Elon Musk says that the company makes about 20 engineering changes a week to improve the production and performance of the Model S. Examples include new battery packs, updated safety and autopilot hardware, and software that automatically adjusts the steering wheel and seat for easier entry and exit.

In the most advanced agile enterprises, innovative product and process architectures are attacking some of the thorniest organizational constraints to further scaling. Riot Games, the developer of the wildly successful multiplayer online battle arena League of Legends, is redesigning the interfaces between agile teams and support-and-control functions that operate conventionally, such as facilities, finance, and HR. Brandon Hsiung, the product lead for this ongoing initiative, says it involves at least two key steps. One is shifting the functions’ definition of their customers. “Their customers are not their functional bosses, or the CEO, or even the board of directors,” he explains. “Their customers are the development teams they serve, who ultimately serve our players.” The company instituted Net Promoter surveys to collect feedback on whether those customers would recommend the functions to others and made it plain that dissatisfied customers could sometimes hire outside providers. “It’s the last thing we want to happen, but we want to make sure our functions develop world-class capabilities that could compete in a free market,” Hsiung says.

Riot Games also revamped how its corporate functions interact with its agile teams. Some members of corporate functions may be embedded in agile teams, or a portion of a function’s capacity may be dedicated to requests from agile teams. Alternatively, functions might have little formal engagement with the teams after collaborating with them to establish certain boundaries. Says Hsiung: “Silos such as real estate and learning and development might publish philosophies, guidelines, and rules and then say, ‘Here are our guidelines. As long as you operate within them, you can go crazy; do whatever you believe is best for our players.’”

In companies that have scaled up agile, the organization charts of support functions and routine operations generally look much as they did before, though often with fewer management layers and broader spans of control as supervisors learn to trust and empower people. The bigger changes are in the ways functional departments work. Functional priorities are necessarily more fully aligned with corporate strategies. If one of the company’s key priorities is improving customers’ mobile experience, that can’t be number 15 on finance’s funding list or HR’s hiring list. And departments such as legal may need buffer capacity to deal with urgent requests from high-priority agile teams.

Over time even routine operations with hierarchical structures are likely to develop more-agile mindsets. Of course, finance departments will always manage budgets, but they don’t need to keep questioning the decisions of the owners of agile initiatives. “Our CFO constantly shifts accountability to empowered agile teams,” says Ahmed Sidky, the head of development management at Riot Games. “He’ll say, ‘I am not here to run the finances of the company. You are, as team leaders. I’m here in an advisory capacity.’ In the day-to-day organization, finance partners are embedded in every team. They don’t control what the teams do or don’t do. They are more like finance coaches who ask hard questions and provide deep expertise. But ultimately it’s the team leader who makes decisions, according to what is best for Riot players.”

Some companies, and some individuals, may find these trade-offs hard to accept and challenging to implement. Reducing control is always scary—until you do so and find that people are happier and success rates triple. In a recent Bain survey of nearly 1,300 global executives, more respondents agreed with this statement about management than with any other: “Today’s business leaders must trust and empower people, not command and control them.” (Only 5% disagreed.)

Talent acquisition and motivation.

Companies that are scaling up agile need systems for acquiring star players and motivating them to make teams better. (Treat your stars unfairly, and they will bolt to a sexy start-up.) They also need to unleash the wasted potential of more-typical team members and build commitment, trust, and joint accountability for outcomes. There’s no practical way to do this without changing HR procedures. A company can no longer hire purely for expertise, for instance; it now needs expertise combined with enthusiasm for work on a collaborative team. It can’t evaluate people according to whether they hit individual objectives; it now needs to look at their performance on agile teams and at team members’ evaluations of one another. Performance assessments typically shift from an annual basis to a system that provides relevant feedback and coaching every few weeks or months. Training and coaching programs encourage the development of cross-functional skills customized to the needs of individual employees. Job titles matter less and change less frequently with self-governing teams and fewer hierarchical levels. Career paths show how product owners—the individuals who set the vision and own the results of an agile team—can continue their personal development, expand their influence, and increase their compensation.

Companies may also need to revamp their compensation systems to reward group rather than individual accomplishments. They need recognition programs that celebrate contributions immediately. Public recognition is better than confidential cash bonuses at bolstering agile values—it inspires recipients to improve even further, and it motivates others to emulate the recipients’ behaviors. Leaders can also reward “A” players by engaging them in the most vital opportunities, providing them with the most advanced tools and the greatest possible freedom, and connecting them with the most talented mentors in their field.

Annual planning and budgeting cycles.

In bureaucratic companies, annual strategy sessions and budget negotiations are powerful tools for aligning the organization and securing commitments to stretch goals. Agile practitioners begin with different assumptions. They see that customer needs change frequently and that breakthrough insights can occur at any time. In their view, annual cycles constrain innovation and adaptation: Unproductive projects burn resources until their budgets run out, while critical innovations wait in line for the next budget cycle to compete for funding.

In companies with many agile teams, funding procedures are different. Funders recognize that for two-thirds of successful innovations, the original concept will change significantly during the development process. They expect that teams will drop some features and launch others without waiting for the next annual cycle. As a result, funding procedures evolve to resemble those of a venture capitalist. VCs typically view funding decisions as opportunities to purchase options for further discovery. The objective is not to instantly create a large-scale business but, rather, to find a critical component of the ultimate solution. This leads to a lot of apparent failures but accelerates and reduces the cost of learning. Such an approach works well in an agile enterprise, vastly improving the speed and efficiency of innovation.

CONCLUSION

Companies that successfully scale up agile see major changes in their business. Scaling up shifts the mix of work so that the business is doing more innovation relative to routine operations. The business is better able to read changing conditions and priorities, develop adaptive solutions, and avoid the constant crises that so frequently hit traditional hierarchies. Disruptive innovations will come to feel less disruptive and more like adaptive business as usual. The scaling up also brings agile values and principles to business operations and support functions, even if many routine activities remain. It leads to greater efficiency and productivity in some of the business’s big cost centers. It improves operating architectures and organizational models to enhance coordination between agile teams and routine operations. Changes come on line faster and are more responsive to customer needs. Finally, the business delivers measurable improvements in outcomes—not only better financial results but also greater customer loyalty and employee engagement.

Agile’s test-and-learn approach is often described as incremental and iterative, but no one should mistake incremental development processes for incremental thinking. SpaceX, for example, aims to use agile innovation to begin transporting people to Mars by 2024, with the goal of establishing a self-sustaining colony on the planet. How will that happen? Well, people at the company don’t really know…yet. But they have a vision that it’s possible, and they have some steps in mind. They intend to dramatically improve reliability and reduce expenses, partly by reusing rockets much like airplanes. They intend to improve propulsion systems to launch rockets that can carry at least 100 people. They plan to figure out how to refuel in space. Some of the steps include pushing current technologies as far as possible and then waiting for new partners and new technologies to emerge.

That’s agile in practice: big ambitions and step-by-step progress. It shows the way to proceed even when, as is so often the case, the future is murky.A version of this article appeared in the May–June 2018 issue (pp.88–96) of Harvard Business Review.Read more on Change management or related topics Leading teams and Agile project management

• Darrell K. Rigby is a partner in the Boston office of Bain & Company. He heads the firm’s global innovation practice. He is the author of Winning in Turbulence and is a co-author of Doing Agile Right: Transformation Without Chaos (Harvard Business Review Press, 2020).
• Jeff Sutherland is a cocreator of the scrum form of agile innovation and the CEO of Scrum Inc., a consulting and training firm.
• Andy Noble is a partner in Bain & Company’s Organization practice and is located in the Boston office.

Article link: https://hbr.org/2018/05/agile-at-scale?

by Merete Wedell-WedellsborgApril 12, 2019

On a warm evening after a strategy off-site, a team of executives arrives at a well-known local restaurant. The group is looking forward to having dinner together, but the CEO is not happy about the table and demands a change. “This isn’t the one that my assistant usually reserves for me,” he says. A young waiter quickly finds the manager who explains that there are no other tables available.

The group tries to move on but is once again interrupted by the CEO. “Am I the only one annoyed by the view? Why is there construction happening today?” he demands to know. The waiter tries to explain, but to no avail. “You really need to up your game here,” the CEO replies. The air is thick with tension. After the waiter walks away, someone makes a joke about the man’s competence. This seems to please the CEO, who responds with his own derogatory quip. The group laughs.

If you were present at that dinner would you let the CEO know that you disapprove of his language and behavior? Would you try to set a better example? Or stay silent?

This scene encapsulates three psychological dynamics that lead to crossing ethical lines. First, there’s omnipotence: when someone feels so aggrandized and entitled that they believe the rules of decent behavior don’t apply to them. Second, we have cultural numbness: when others play along and gradually begin to accept and embody deviant norms. Finally, we see justified neglect: when people don’t speak up about ethical breaches because they are thinking of more immediate rewards such as staying on a good footing with the powerful.

The same dynamics come into play when much bigger lines get crossed in the corporate arena: allegations of corruption at Nissan, sexual harassment charges in the media sector,privacy breaches at Facebook, money laundering in the financial sector, and pharmaceuticals’ role in the opioid crisis.

While it is hard, if not impossible, to find evidence that leaders in general have become less ethical over the years, some are sounding the alarm. Warren Buffett, explaining Berkshire Hathaway’s practices in the annual letter shareholders, notes that he and vice chairman Charlie Munger

“…have seen all sorts of bad corporate behavior, both accounting and operational, induced by the desire of management to meet Wall Street expectations. What starts as an ‘innocent’ fudge in order to not disappoint ‘the Street’ — say, trade-loading at quarter-end, turning a blind eye to rising insurance losses, or drawing down a ‘cookie-jar’ reserve — can become the first step toward full-fledged fraud.”

Buffett’s note is important because it’s really about the majority of us:  neither saints nor criminals but well-meaning leaders who sometimes fail to consult their moral compass while speeding ahead in a landscape full of tripwires and pitfalls. For that majority, moral leadership is not simply a question of acting in good or bad faith. It is about navigating the vast space in between.

So how do you know when you, or your team, is on the road to an ethical lapse?  Here’s more on how to identify omnipotence, cultural numbness, and justified neglect in yourself and on your team, and a few tips on fighting each dynamic: 

Omnipotence. Many moral lapses can be traced back to this feeling that you are invincible, untouchable, and hyper-capable, which can energize and create a sense of elation. To the omnipotent leader, rules and norms are meant for everyone but them. Crossing a line feels less like a transgression and more like what they are owed. They feel they have the right to skip or redraw the lines. In the dinner party example above, it is no coincidence that the CEO’s entitled and condescending behavior comes after a day of strategizing and masterminding the next big moves.

Omnipotence is not all bad. Sometimes the rush you get from bold action is what’s required to make breakthroughs or real progress. But, the higher you climb on the ladder, the more it can become a liability. This is especially true if fewer and fewer of the people around you are willing and able to keep you grounded. If no one tells you “no,” you have a problem. One way to gauge whether you’ve reached “peak omnipotence” is if your decisions are met only with applause, deference, and silence.

The psychological counterweight to omnipotence is owning your flaws. It’s a mature capability to look in the mirror and recognize that you are not above it all. Especially if you’re in a leadership position, assume you have weaknesses and think about them regularly.

Sometimes, you’ll need help with this. The best performing executives I see have close colleagues, friends, coaches, or mentors who dare to tell them the truth about their performance and judgment. You should cultivate a similar group of trusted peers who will tell you the truth even when it is unpleasant. In addition, make sure to encourage an “obligation to dissent” among your core team.

Cultural numbness. No matter how principled you are, you must recognize that, over time, the bearings of your moral compass will shift toward the culture of your organization or team.

From my work with police and military units infiltrating criminal groups, I have seen examples of how cultural numbness makes leaders cross lines. It usually starts subtly. Officers need to get to know and infiltrate a new culture. They need to fit in by speaking the language, acting according to code, and dressing to fit in. But, in doing that, they risk going too far — mimicking the culture of the gang members they are out to stop and getting caught up in a group’s values system.

The same kind of “moral capture” takes place in companies, not overnight, but gradually. Psychologically, you’re making a trade-off between fitting into the culture and staying true to what you value.

At first, cultural numbness can take the shape of ironic distance or disillusioned resignation when there is a discrepancy between the two, or between the ideals your company espouses and what you see demonstrated and rewarded. But the mind needs resolution. So, over time, you stop noticing when offensive language becomes the norm or you start to behave in ways that you would never have expected to be part of your repertoire.

Cultural numbness is where I have seen the most severe breakdowns in ethical leadership because it’s so hard to detect. Leaders who have crossed a line never describe this as a clear choice on that path but as wandering down a muddy road, where there they lost track of what was right and wrong. They describe a process where they became numb to others’ language and behavior and then to their own and lost their sense of objectivity. In essence, their warning bells simply stopped ringing.

So, start looking out for signs of moral capture:  those brief moments when you don’t recognize yourself and any other indications that you are subjecting your own personal agency to the deviant norms of the collective. Another regular gut-check you can use involves asking whether you would be comfortable telling a journalist or a judge about what’s going on.

At the same time, you can’t always trust yourself in these situations. As with omnipotence, it can help to get an outsider’s perspective, turning to a trusted friend or family member, who might be able to detect changes in you that you are not able to see. Also remember to regularly extract yourself from your organization to compare and contrast its culture with others and remind yourself that the rest of the world may not work the same way.

Justified neglect. The human mind is skilled at justifying minor incursions when there is a tangible reward at stake — and when the risk of getting caught is low.

On the production line of a pharmaceutical company, for example, a hurried lab assistant forgets to remove all of her makeup. A speck of mascara accidentally drops into a batch of medicine large enough to serve a mid-sized country for a year. For a brief moment, the miniscule impurity draws a thin, yellowish color trail, but then it is gone, impossible to detect. The medicine is life-saving and very valuable, with just a hint of makeup that’s probably harmless.

Would you report the incident? If you were a manager who was quietly asked what to do, would you destroy the batch?  Would you change your mind knowing that patients might suffer or even die from a serious production delay? Would your ballooning production budget and the tenuous financial situation of your company factor into your decision? Would you push the problem up to your superiors knowing that those with a greater stake in the outcome might turn a blind eye to the incident?

Many leaders have faced a choice between getting the reward or doing the right thing. The slippery slope starts right when you begin to rationalize actions and tell yourself and others, “This is an exceptional situation,” or “We have to bend the rules a little to get things done here,” or “We are here to make money, not to do charity.”

These initial slips cascade into more, which turn into habits you know are bad but which start to feel excusable and even acceptable, given the circumstances, and eventually, become part of your moral fabric. It is hard to pinpoint exactly when an important line is crossed, but it’s much easier to course-correct at the very start of the slippery slope than when you are gliding full speed away from what is right.

Remember that power corrodes more than it corrupts, often as a result of clever justifications of ethical neglect. You can combat this psychological dynamic by creating formal and social contracts that obligate both you and your colleagues to do right; rewarding ethical behavior; and defining and sharing your boundaries. The latter could be as simple as making a list of things you will not do for profit or pleasure, keeping it in a convenient place to read regularly, and occasionally showing it to your team as a reminder.

****

The reality is that, for many leaders, there is no true straight-and-narrow path to follow. You beat the path as you go. Therefore, ethical leadership relies a lot on your personal judgment. Because of this, the moral or ethical dilemmas you experience may feel solitary or taboo — struggles you don’t want to let your peers know about. It can sometimes feel shameful to admit that you feel torn or unsure about how to proceed. But you have to recognize that this is part of work life and should be addressed in a direct and open way.

Even though most companies have some cultural and structural checks and balances, including values statements, CSR guidelines, and even whistleblower functions, leaders must also be mindful of the psychological conditions that push people — including themselves — to cross ethical lines. Understanding the dangers of omnipotence, cultural numbness, and justified neglect are like installing the first few warning signs on the long road of your career. You will inevitably hit some bumps, but the more prepared you are to handle them, the likelier you are to keep your integrity intact.

Dr. Merete Wedell-Wedellsborg runs her own business psychology practice with clients in the financial, pharmaceutical, and defense sectors, as well as family offices. Merete holds a Ph.D. in Business Economics from Copenhagen Business School and an M.A. in Psychology from University of Copenhagen (Clinical Psychology). she is the author of the book Battle Mind: How to Navigate in Chaos and Perform Under Pressure.

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Article link: https://hbr-org.cdn.ampproject.org/c/s/hbr.org/amp/2019/04/the-psychology-behind-unethical-behavior

https://youtu.be/OYxP_DCENaI

Companies committed to building workforces equipped for the future apply seven key principles to training and development.

Organizations are struggling to keep pace with the new skills needed in their workforces, thanks to large-scale trends such as the shift to digital business models and the increased adoption of workplace automation, AI, and advanced analytics. The pandemic accelerated those trends, putting an increased premium on learning and development (L&D) as a means of equipping companies to handle both long-term challenges and short-term crises.

To understand the implications of these changes, we recently engaged in more than 60 in-depth conversations with CEOs, chief human resources officers, chief learning officers, chief operating officers, and other senior HR and business leaders across six countries. We supplemented that research through surveys of more than 250 professionals worldwide about their approaches to L&D. The results show that relatively few organizations had strong L&D programs in place before the pandemic.

Those companies offer a model of how learning and development makes companies more responsive and agile. In studying their practices, we identified seven core principles that other companies can implement to improve their L&D efforts and equip themselves to thrive in both the short and long terms.

The Case for Investments in L&D

We conducted our quantitative survey in 2019 and found that few organizations had a strategic, forward-looking approach to L&D. Only 4 in 10 respondents to our survey identified preparing for the future as a high or top priority for their organization, and only 30% of respondents were confident in their ability to meet future skill needs.

Before COVID-19, technology was already changing employee and customer behaviors in dramatic ways, but the pace has now increased. Consultancy Global Workplace Analytics expects that an estimated 25% to 30% of the labor force will be working from home multiple days a week by the end of 2021.1 There is evidence of a growing performance gap between companies with digitally enabled, agile business models and those with traditional, legacy business models.2

We gained a unique perspective based on the timing of our research, given that we began interviewing company leaders before the pandemic and continued to speak with them throughout the crisis. We found that companies that had a strong, long-term L&D orientation going into the pandemic were well equipped to handle the short-term pressures that it created and to adapt quickly to new ways of working. Our findings are consistent with prior research showing that organizations that were already in the lead in terms of L&D before a crisis are better positioned for the post-crisis rebound. For example, research on previous global recessions shows the value of investment in L&D in equipping businesses for the subsequent recovery.3

There is a clear case for making investments now to build for the future. Some organizations are already making changes. According to a recent LinkedIn Learning report reflecting the impact of the COVID-19 pandemic, L&D professionals reported a 159% increase in the extent to which their CEOs were championing learning and development in their organizations, while 64% reported that reskilling the workforce was more of a priority than ever before.4 The imperative is to make sure that those investments yield results, building the skills and capabilities needed to take advantage of technologies such as big data and AI, and adjust to changes in work due to automation and on-demand contingent labor.

The digitalization of business processes and models and the attendant implications for how and where people work, and how customers engage with organizations, emerged as key areas of focus in our research. We identified seven key insights from the organizations that have been most successful in developing and implementing strong L&D programs.

1. Identify a North Star to guide L&D decisions. Organizations that were best prepared to respond to the changing world of work are guided by what we call a North Star — an overarching objective that informs decisions about employee skills and development.

Consider global pharmaceutical company Novartis, which set a North Star of evolving into a data-driven business in order to reimagine medicine and improve patients’ lives. To support that mission, Novartis identified five strategic priorities and built the underlying L&D components to support each of them. The initiative is backed by an investment of $100 million in learning and development over a five-year period, with an aim for all employees to spend 5% of their time learning. It includes partnerships with learning platforms such as Skillsoft, GetAbstract, Coursera, and LinkedIn.

For example, benchmark data from Coursera aided the L&D team in identifying a need for enhanced data visualization skills, in line with its strategic priority of data and digitalization. The team took a range of actions to build these skills and close the gap, tracking performance on a quarterly basis. Within two years of the program’s launch, Novartis surpassed the industry benchmark for data visualization skills.

In the U.S., Dell has repositioned itself from a traditional technology hardware company to a cloud-based infrastructure provider, with the ambition of enabling digital transformation for its customers. This is the organization’s North Star, and it has guided Dell to rethink the skills base of the organization. Dell developed a new career framework with 23 core skills, as well as a set of leadership principles to deliver on that ambition. Those core skills in turn inform the L&D strategy in terms of program design and content curation.

2. Establish a skills baseline. The second key insight is the importance of conducting an inventory of the current skills and capabilities of your workforce. Among the companies we studied, inventories such as these were seen as crucial in understanding current capabilities, identifying skills gaps more quickly, and taking action to fill any deficits.

For example, a European technology company launched a nine-month project to assess both the supply and demand of strategic skills that it would need in the future. The project, executed through IBM’s Kenexa Talent Frameworks, resulted in the company taking an inventory of skills across the organization and mapping them to job profiles as it worked to define and audit individual skills and roles. The skills inventory also provided a way to think about the key responsibilities, job levels, and core competencies of these roles.

The analysis highlighted that the company was hiring overqualified candidates for some roles. This resulted in annual labor costs that were roughly 1 million euros (about $1.2 million) higher than necessary to acquire skills that were not being deployed. The analysis also identified a number of new skill sets already in the organization that were likely to prove valuable in the future, and resulted in a renewed focus on internal development over external hiring.

We recognize that in larger organizations, completing such skills audits across so many roles, business units, and geographies can be a challenge, particularly when the pace of change is so rapid. Our research found that companies often succeed by breaking the process down into more manageable chunks, such as pilot exercises or skills inventories conducted at the level of business units or geographic regions. Regardless of the ultimate scope of the project, organizations should not think of these as “one and done” processes. Rather, the audits must be repeated to account for changes in the business landscape and within the organization itself.

3. Align L&D efforts with strategic priorities. We identified relatively few organizations that were systematically planning for the skills they would need in the future. The areas of AI and automation are good examples. Our findings show that those technologies were regularly overlooked by L&D teams prior to the crisis (likely due to significant pressure to deliver on short-term priorities, combined with a lack of resources), despite their visibility and clear business value. Many organizations continue to build L&D plans that overemphasize skills that were important in the past.

In contrast, leading organizations look forward and assess their strategic priorities, skills needed to execute on those priorities, and the future
impact on their workforces. For example, in 2019 a European insurance company projected changes in jobs due to the impact of technology and other factors over the next five to 10 years. It estimated that 15% of the company’s jobs were likely to be eliminated by technology and an additional 50% would be augmented by technology in that period. This analysis provided a road map as the company planned for the reskilling and redeployment of workers. Some of these measures overlapped with more urgent ones needed to respond to the pandemic; for example, the company was forced to accelerate its shift to digital processes in areas such as claims handling. The project provided a clear template for the development of digital and analytical skills by identifying the areas with the most opportunity for redeployment and where reskilling would add the most value.

Similarly, at professional services firm PwC, a team composed of business heads and led by the global human capital leader was tasked with ensuring that the organization had the capabilities to match its growth ambitions. A key initiative launched in 2019, supported by a $3 billion investment, focused on digital upskilling. All 276,000 employees worldwide underwent a two-day digital training session, and PwC offered new incentives to digitalize processes and improve performance across the organization. So far, millions of work hours have been saved through process improvements and innovations across the organization. In one example, an audit process that formerly took two weeks to complete is now automated and takes just 12 minutes. PwC’s digitalization journey was particularly valuable in the shift to virtual working in response to COVID-19.5

4. Ensure that the L&D team has the right skills and resources. The capabilities that L&D professionals need are quickly evolving alongside those of the overall workforce. We found an increased demand for digital and analytical skills among L&D teams, particularly regarding digital learning, virtual facilitation, and the curation of online content. We also saw increased expectations of L&D professionals in terms of their knowledge of the business and strategy, as well as the coaching and consulting skills required to fully engage with and deliver strategic value for the business.

At a U.K. bank, these demands have resulted in an L&D team that is smaller than in the past but more skilled and delivering a higher level of value for the business. As a more credible partner to the business, the team is now equipped to have more challenging conversations with organizational leaders to ensure that content offerings and even delivery modes match business needs and expectations. The team has also helped challenge outdated views on learning needs and has instead focused L&D investments on the future. Data analytics and visualization capabilities within the team, combined with deep knowledge of the business, have played a key role on this journey. In a recent regrading exercise, all members of the team had their job grades increased one level to reflect their increased contributions.

Technology also plays an increasingly important role as a platform for enabling L&D to support a company’s organizational strategy. In some cases, technology can create efficiencies and free up people for value-creating work. At ICON, an Irish global health care organization, we saw the deployment of a digital bot to schedule training in 2019. This bot freed up capacity equivalent to a full-time employee on the team, enabling that person to focus on more important tasks. Other companies have invested in technology to upgrade learning management systems, equipping L&D teams to deliver learning both during and after the crisis.

Not only did these organizations have the capabilities required for enabling digital learning and targeted curation of online content, but they also demonstrated a deep understanding of the challenges and opportunities of virtual learning design and facilitation.

5. Design learning to accommodate evolving conditions. Many organizations’ L&D budgets have been cut or frozen in response to current economic conditions. Additionally, most face-to-face training has been halted, at least in the short term. However, this offers the opportunity to shift from formal, event-based training that is separate from work to learning that happens in a more organic fashion throughout an employee’s workday, often termed learning in the flow of work.6 By blending technology, strategic partnerships, and internal processes, top-performing companies create learning that is “just in time, just enough, and just for me.”7 These opportunities might include short video clips on YouTube or active discussions on collaboration platforms such as Slack, Zoom, Facebook Workplace, or Microsoft Teams.

In fact, the shift to learning in the flow of work can offer real advantages in terms of employee engagement. Research by The Conference Board shows a strong preference among employees for working on tasks that require them to learn new things.8 In our own research, we also found that employee attitudes about learning are evolving, with an increased appreciation for virtual delivery. In the past, online learning was often viewed as a second-rate option, but for many employees, it is now the primary way to access training. For example, polling and analytics company Gallup reported that its employees appreciated a more individualized focus on their needs, combined with greater connection and intimacy enabled by virtual L&D.9

A number of organizations where we conducted interviews cited the value of global collaboration via virtual channels. Although programs may have been delivered onsite locally or regionally in the past, the shift to virtual operations means that participants from across the globe are more likely to be part of a single cohort. This has led to increased knowledge sharing across geographies.

Internal opportunity marketplaces, which match organizational needs with employee capabilities, are also increasingly prevalent.10 A Dell initiative connects people to work opportunities inside the company that are not full-time jobs and focuses on the skills that the future will demand. The internal talent marketplace is akin to crowdsourcing for skills — individuals bid to work on projects where their skills would fill a need on the project team. These projects are viewed as a means of developing individual capabilities while also building one’s social capital within the organization.

A number of our respondents pointed to the increasing emphasis on the 70:20:10 model of development. Under this model, development through on-the-job experiences should account for 70% of learning, while 20% comes from feedback and coaching and only 10% from more formal instruction.11 As one chief learning officer noted, the COVID-19 crisis served as a proof of concept for the 70:20:10 model because the organization was essentially forced to emphasize learning in the flow of work.

6. Create individualized learning pathways. Companies are also seeing an accelerated trend toward individualized learning pathways, reflecting the wider range of priorities and responsibilities among individual employees as their roles have evolved in response to the crisis. This also reflects a shift away from standardized learning pathways, which typically assume a standard baseline level of ability as people enter an organization and follow standard career paths.

As the head of L&D in a European banking organization told us, “We’re in this age where people just want the stuff that they need. They just want it really efficiently. ‘What can I do just to get this information, get it done, and move on?’” Notably, L&D platform LinkedIn Learning reported a threefold increase in its site traffic over the course of the pandemic through late 2020.12

A key challenge for L&D teams lies in helping employees understand which skills they need and how to access relevant content. As part of its digitalization strategy, PwC developed an app that allows employees to assess their current level of “digital fitness” and identifies resources to help them improve their scores. (The app is now available to the public for free.) In other organizations, technology has also played a key role, with LinkedIn Learning and YouTube also providing bite-size content focused on immediate needs.

7. Stay agile and adapt over time. The disruptions caused by the pandemic have shown companies how rapidly the priorities and requirements of L&D functions can change. This volatility challenges L&D teams to be responsive and agile. Rather than seeking perfection in program offerings, nimble L&D teams think in terms of getting a minimal viable product into the hands of users, testing the program, learning from experience, and making iterative changes and upgrades over time.

During the first few months of the pandemic, the initial requirement for L&D teams was to support employees working at home. However, priorities quickly shifted to a focus on well-being and mental health, and then to helping teams collaborate in new ways through virtual channels. This is a major shift from traditional L&D frameworks, which were often quite rigid. Yet the L&D teams that responded effectively recognized the importance of reevaluating decisions and priorities as new data became available.

A recurring theme among our recent discussions with organizational leaders was how the L&D team maintained its credibility by being responsive to the needs of the business during the crisis. We also had a small number of organizations report that adopting agile methodologies in their HR and L&D teams has aided their ability to adapt quickly in response to changing business needs. These examples point to the importance of continually assessing the effectiveness of L&D interventions and adapting to meet individual and organizational needs.

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We also observed a number of instances in which organizational frameworks were too slow to respond to the pace of change during the pandemic, and L&D teams had to innovate to ensure responsive delivery. In one global organization, the signoff requirements for the centrally managed learning management system were slowing down content development. To move faster, some national units in that organization developed content locally and delivered it via Facebook Workplace.

Amid competing priorities, L&D may appear to be an issue that is secondary to more urgent challenges. However, L&D is itself the means by which companies equip themselves to take on those challenges, in particular by ensuring that their workforces have the skills to implement and adopt technologies that enhance competitiveness and productivity. As our research shows, that requires investing in learning and development with a long-term perspective and a strategic orientation, and being prepared to adapt over time.https://7d2e8d5f0842fa5843c841a5cef08fdf.safeframe.googlesyndication.com/safeframe/1-0-38/html/container.html

ABOUT THE AUTHORS

David G. Collings (@collingsdg) is a professor of human resource management at Dublin City University Business School. John McMackin is an assistant professor in human resource management and organizational behavior at Dublin City University Business School.

Article link: https://sloanreview.mit.edu/article/the-practices-that-set-learning-organizations-apart/

REFERENCES (12)

1. “Work-at-Home After COVID-19 — Our Forecast,” Global Workplace Analytics, accessed Dec. 16, 2020, https://globalworkplaceanalytics.com.

2. C. Bradley, M. Hirt, S. Hudson, et al., “The Great Acceleration,” McKinsey & Company, July 14, 2020, http://www.mckinsey.com.

3. Y. Kim and R.E. Ployhart, “The Effects of Staffing and Training on Firm Productivity and Profit Growth Before, During, and After the Great Recession,” Journal of Applied Psychology 99, no. 3 (May 2014): 361-389.

4. “Leading With Learning: Insights and Advice on the New State of L&D,” PDF file (Carpinteria, California: LinkedIn Learning, 2020), https://learning.linkedin.com.

5. A. Kidwai, “How PwC Keeps Its Digital Upskilling Relevant,” HRDive, May 12, 2020, http://www.hrdive.com.

6. J. Bersin and M. Zao-Sanders, “Making Learning a Part of Everyday Work,” Harvard Business Review, Feb. 19, 2019, https://hbr.org.

7. K. Peters, “m-Learning: Positioning Educators for a Mobile, Connected Future,” International Review of Research in Open and Distance Learning 8, no. 2 (June 2007): 1-17.

8. R.L. Ray, P. Hyland, A. Pressman, et al., “DNA of Engagement: How Organizations Can Foster Employee Ownership of Engagement,” PDF file (New York: The Conference Board, 2017), http://www.conference-board.org.

9. V. Ratanjee, “Four Ways to Continue Employee Development When Budgets Are Cut,” Gallup, Aug. 3, 2020, http://www.gallup.com.

10. M. Schrage, J. Schwartz, D. Kiron, et al., “Opportunity Marketplaces: Aligning Workforce Investment and Value Creation in the Digital Enterprise,” MIT Sloan Management Review, April 28, 2020, https://sloanreview.mit.edu.

11. M. Lombardo and R.W. Eichinger, “The Career Architect Development Planner” (Minneapolis: Lominger, 1996).

12. T. Vander Ark, “Pandemic Spike in AI Learning — and What It Means for Schools,” Forbes, May 7, 2020, http://www.forbes.com.

Document Link: https://www.belfercenter.org/sites/default/files/files/publication/Ahead%20of%20the%20Digital%20Curve%20-%20Leyne%20and%20Nonte.pdf

Miriam was only 21 when she met Nick. She was a photographer, fresh out of college, waiting tables. He was 16 years her senior and a local business owner who had worked in finance. He was charming and charismatic; he took her out on fancy dates and paid for everything. She quickly fell into his orbit.

It began with one credit card. At the time, it was the only one she had. Nick would max it out with $5,000 worth of business purchases and promptly pay it off the next day. Miriam, who asked me not to use their real names for fear of interfering with their ongoing divorce proceedings, discovered that this was boosting her credit score. Having grown up with a single dad in a low-income household, she trusted Nick’s know-how over her own. He readily encouraged the dynamic, telling her she didn’t understand finance. She opened up more credit cards for him under her name.

The trouble started three years in. Nick asked her to quit her job to help out with his business. She did. He told her to go to grad school and not worry about compounding her existing student debt. She did. He promised to take care of everything, and she believed him. Soon after, he stopped settling her credit card balances. Her score began to crater.

Still, Miriam stayed with him. They got married. They had three kids. Then one day, the FBI came to their house and arrested him. In federal court, the judge convicted him on nearly $250,000 of wire fraud. Miriam discovered the full extent of the tens of thousands of dollars in debt he’d racked up in her name. “The day that he went to prison, I had $250 cash, a house in foreclosure, a car up for repossession, three kids,” she says. “I went within a month from having a nanny and living in a nice house and everything to just really abject poverty.”

Miriam is a survivor of what’s known as “coerced debt,” a form of abuse usually perpetrated by an intimate partner or family member. While economic abuse is a long-standing problem, digital banking has made it easier to open accounts and take out loans in a victim’s name, says Carla Sanchez-Adams, an attorney at Texas RioGrande Legal Aid. In the era of automated credit-scoring algorithms, the repercussions can also be far more devastating.

Credit scores have been used for decades to assess consumer creditworthiness, but their scope is far greater now that they are powered by algorithms: not only do they consider vastly more data, in both volume and type, but they increasingly affect whether you can buy a car, rent an apartment, or get a full-time job. Their comprehensive influence means that if your score is ruined, it can be nearly impossible to recover. Worse, the algorithms are owned by private companies that don’t divulge how they come to their decisions. Victims can be sent in a downward spiral that sometimes ends in homelessness or a return to their abuser.

Credit-scoring algorithms are not the only ones that affect people’s economic well-being and access to basic services. Algorithms now decide which children enter foster care, which patients receive medical care, which families get access to stable housing. Those of us with means can pass our lives unaware of any of this. But for low-income individuals, the rapid growth and adoption of automated decision-making systems has created a hidden web of interlocking traps.

Fortunately, a growing group of civil lawyers are beginning to organize around this issue. Borrowing a playbook from the criminal defense world’s pushback against risk-assessment algorithms, they’re seeking to educate themselves on these systems, build a community, and develop litigation strategies. “Basically every civil lawyer is starting to deal with this stuff, because all of our clients are in some way or another being touched by these systems,” says Michele Gilman, a clinical law professor at the University of Baltimore. “We need to wake up, get training. If we want to be really good holistic lawyers, we need to be aware of that.”

“Am I going to cross-examine an algorithm?”

Gilman has been practicing law in Baltimore for 20 years. In her work as a civil lawyer and a poverty lawyer, her cases have always come down to the same things: representing people who’ve lost access to basic needs, like housing, food, education, work, or health care. Sometimes that means facing off with a government agency. Other times it’s with a credit reporting agency, or a landlord. Increasingly, the fight over a client’s eligibility now involves some kind of algorithm.

“This is happening across the board to our clients,” she says. “They’re enmeshed in so many different algorithms that are barring them from basic services. And the clients may not be aware of that, because a lot of these systems are invisible.”

She doesn’t remember exactly when she realized that some eligibility decisions were being made by algorithms. But when that transition first started happening, it was rarely obvious. Once, she was representing an elderly, disabled client who had inexplicably been cut off from her Medicaid-funded home health-care assistance. “We couldn’t find out why,” Gilman remembers. “She was getting sicker, and normally if you get sicker, you get more hours, not less.”

Not until they were standing in the courtroom in the middle of a hearing did the witness representing the state reveal that the government had just adopted a new algorithm. The witness, a nurse, couldn’t explain anything about it. “Of course not—they bought it off the shelf,” Gilman says. “She’s a nurse, not a computer scientist. She couldn’t answer what factors go into it. How is it weighted? What are the outcomes that you’re looking for? So there I am with my student attorney, who’s in my clinic with me, and it’s like, ‘Oh, am I going to cross-examine an algorithm?’”

For Kevin De Liban, an attorney at Legal Aid of Arkansas, the change was equally insidious. In 2014, his state also instituted a new system for distributing Medicaid-funded in-home assistance, cutting off a whole host of people who had previously been eligible. At the time, he and his colleagues couldn’t identify the root problem. They only knew that something was different. “We could recognize that there was a change in assessment systems from a 20-question paper questionnaire to a 283-question electronic questionnaire,” he says.

It was two years later, when an error in the algorithm once again brought it under legal scrutiny, that De Liban finally got to the bottom of the issue. He realized that nurses were telling patients, “Well, the computer did it—it’s not me.” “That’s what tipped us off,” he says. “If I had known what I knew in 2016, I would have probably done a better job advocating in 2014,” he adds.

“One person walks through so many systems on a day-to-day basis”

Gilman has since grown a lot more savvy. From her vantage point representing clients with a range of issues, she’s observed the rise and collision of two algorithmic webs. The first consists of credit-reporting algorithms, like the ones that snared Miriam, which affect access to private goods and services like cars, homes, and employment. The second encompasses algorithms adopted by government agencies, which affect access to public benefits like health care, unemployment, and child support services.

On the credit-reporting side, the growth of algorithms has been driven by the proliferation of data, which is easier than ever to collect and share. Credit reports aren’t new, but these days their footprint is far more expansive. Consumer reporting agencies, including credit bureaus, tenant screening companies, or check verification services, amass this information from a wide range of sources: public records, social media, web browsing, banking activity, app usage, and more. The algorithms then assign people “worthiness” scores, which figure heavily into background checks performed by lenders, employers, landlords, even schools.

Government agencies, on the other hand, are driven to adopt algorithms when they want to modernize their systems. The push to adopt web-based apps and digital tools began in the early 2000s and has continued with a move toward more data-driven automated systems and AI. There are good reasons to seek these changes. During the pandemic, many unemployment benefit systems struggled to handle the massive volume of new requests, leading to significant delays. Modernizing these legacy systems promises faster and more reliable results.

But the software procurement process is rarely transparent, and thus lacks accountability. Public agencies often buy automated decision-making tools directly from private vendors. The result is that when systems go awry, the individuals affected——and their lawyers—are left in the dark. “They don’t advertise it anywhere,” says Julia Simon-Mishel, an attorney at Philadelphia Legal Assistance. “It’s often not written in any sort of policy guides or policy manuals. We’re at a disadvantage.”

The lack of public vetting also makes the systems more prone to error. One of the most egregious malfunctions happened in Michigan in 2013. After a big effort to automate the state’s unemployment benefits system, the algorithm incorrectly flagged over 34,000 people for fraud. “It caused a massive loss of benefits,” Simon-Mishel says. “There were bankruptcies; there were unfortunately suicides. It was a whole mess.”

Low-income individuals bear the brunt of the shift toward algorithms. They are the people most vulnerable to temporary economic hardships that get codified into consumer reports, and the ones who need and seek public benefits. Over the years, Gilman has seen more and more cases where clients risk entering a vicious cycle. “One person walks through so many systems on a day-to-day basis,” she says. “I mean, we all do. But the consequences of it are much more harsh for poor people and minorities.”

She brings up a current case in her clinic as an example. A family member lost work because of the pandemic and was denied unemployment benefits because of an automated system failure. The family then fell behind on rent payments, which led their landlord to sue them for eviction. While the eviction won’t be legal because of the CDC’s moratorium, the lawsuit will still be logged in public records. Those records could then feed into tenant-screening algorithms, which could make it harder for the family to find stable housing in the future. Their failure to pay rent and utilities could also be a ding on their credit score, which once again has repercussions. “If they are trying to set up cell-phone service or take out a loan or buy a car or apply for a job, it just has these cascading ripple effects,” Gilman says.

“Every case is going to turn into an algorithm case”

In September, Gilman, who is currently a faculty fellow at the Data and Society research institute, released a report documenting all the various algorithms that poverty lawyers might encounter. Called Poverty Lawgorithms, it’s meant to be a guide for her colleagues in the field. Divided into specific practice areas like consumer law, family law, housing, and public benefits, it explains how to deal with issues raised by algorithms and other data-driven technologies within the scope of existing laws.

If a client is denied an apartment because of a poor credit score, for example, the report recommends that a lawyer first check whether the data being fed into the scoring system is accurate. Under the Fair Credit Reporting Act, reporting agencies are required to ensure the validity of their information, but this doesn’t always happen. Disputing any faulty claims could help restore the client’s credit and, thus, access to housing. The report acknowledges, however, that existing laws can only go so far. There are still regulatory gaps to fill, Gilman says.

Gilman hopes the report will be a wake-up call. Many of her colleagues still don’t realize any of this is going on, and they aren’t able to ask the right questions to uncover the algorithms. Those who are aware of the problem are scattered around the US, learning about, navigating, and fighting these systems in isolation. She sees an opportunity to connect them and create a broader community of people who can help one another. “We all need more training, more knowledge—not just in the law, but in these systems,” she says. “Ultimately it’s like every case is going to turn into an algorithm case.”

In the long run, she looks to the criminal legal world for inspiration. Criminal lawyers have been “ahead of the curve,” she says, in organizing as a community and pushing back against risk-assessment algorithms that determine sentencing. She wants to see civil lawyers do the same thing: create a movement to bring more public scrutiny and regulation to the hidden web of algorithms their clients face. “In some cases, it probably should just be shut down because there’s no way to make it equitable,” she says.

As for Miriam, after Nick’s conviction, she walked away for good. She moved with her three kids to a new state and connected with a nonprofit that supports survivors of coerced debt and domestic violence. Through them, she took a series of classes that taught her how to manage her finances. The organization helped her dismiss many of her coerced debts and learn more about credit algorithms. When she went to buy a car, her credit score just barely cleared the minimum with her dad as co-signer. Since then, her consistent payments on her car and her student debt have slowly replenished her credit score.

Miriam still has to stay vigilant. Nick has her Social Security number, and they’re not yet divorced. She worries constantly that he could open more accounts, take out more loans in her name. For a while, she checked her credit report daily for fraudulent activity. But these days, she also has something to look forward to. Her dad, in his mid-60s, wants to retire and move in. The two of them are now laser-focused on preparing to buy a home. “I’m pretty psyched about it. My goal is by the end of the year to get it to a 700,” she says of her score, “and then I am definitely home-buyer ready.”

“I’ve never lived in a house that I’ve owned, ever,” she adds. “He and I are working together to save for a forever home.”

Article link: https://www.technologyreview.com/2020/12/04/1013068/algorithms-create-a-poverty-trap-lawyers-fight-back/?

This is the second in a series of explainers on quantum technology. The other two are on quantum computing and post-quantum cryptography.

Barely a week goes by without reports of some new mega-hack that’s exposed huge amounts of sensitive information, from people’s credit card details and health records to companies’ valuable intellectual property. The threat posed by cyberattacks is forcing governments, militaries, and businesses to explore more secure ways of transmitting information.

Today, sensitive data is typically encrypted and then sent across fiber-optic cables and other channels together with the digital “keys” needed to decode the information. The data and the keys are sent as classical bits—a stream of electrical or optical pulses representing 1s and 0s. And that makes them vulnerable. Smart hackers can read and copy bits in transit without leaving a trace.

Quantum communication takes advantage of the laws of quantum physics to protect data. These laws allow particles—typically photons of light for transmitting data along optical cables—to take on a state of superposition, which means they can represent multiple combinations of 1 and 0 simultaneously. The particles are known as quantum bits, or qubits.

The beauty of qubits from a cybersecurity perspective is that if a hacker tries to observe them in transit, their super-fragile quantum state “collapses” to either 1 or 0. This means a hacker can’t tamper with the qubits without leaving behind a telltale sign of the activity.

Some companies have taken advantage of this property to create networks for transmitting highly sensitive data based on a process called quantum key distribution, or QKD. In theory, at least, these networks are ultra-secure.

What is quantum key distribution?

QKD involves sending encrypted data as classical bits over networks, while the keys to decrypt the information are encoded and transmitted in a quantum state using qubits.

Various approaches, or protocols, have been developed for implementing QKD. A widely used one known as BB84 works like this. Imagine two people, Alice and Bob. Alice wants to send data securely to Bob. To do so, she creates an encryption key in the form of qubits whose polarization states represent the individual bit values of the key.

The qubits can be sent to Bob through a fiber-optic cable. By comparing measurements of the state of a fraction of these qubits—a process known as “key sifting”—Alice and Bob can establish that they hold the same key.

As the qubits travel to their destination, the fragile quantum state of some of them will collapse because of decoherence. To account for this, Alice and Bob next run through a process known as “key distillation,” which involves calculating whether the error rate is high enough to suggest that a hacker has tried to intercept the key.

If it is, they ditch the suspect key and keep generating new ones until they are confident that they share a secure key. Alice can then use hers to encrypt data and send it in classical bits to Bob, who uses his key to decode the information.

We’re already starting to see more QKD networks emerge. The longest is in China, which boasts a 2,032-kilometer (1,263-mile) ground link between Beijing and Shanghai. Banks and other financial companies are already using it to transmit data. In the US, a startup called Quantum Xchange has struck a deal giving it access to 500 miles (805 kilometers) of fiber-optic cable running along the East Coast to create a QKD network. The initial leg will link Manhattan with New Jersey, where many banks have large data centers.

Although QKD is relatively secure, it would be even safer if it could count on quantum repeaters.

What is a quantum repeater?

Materials in cables can absorb photons, which means they can typically travel for no more than a few tens of kilometers. In a classical network, repeaters at various points along a cable are used to amplify the signal to compensate for this.

QKD networks have come up with a similar solution, creating “trusted nodes” at various points. The Beijing-to-Shanghai network has 32 of them, for instance. At these waystations, quantum keys are decrypted into bits and then reencrypted in a fresh quantum state for their journey to the next node. But this means trusted nodes can’t really be trusted: a hacker who breached the nodes’ security could copy the bits undetected and thus acquire a key, as could a company or government running the nodes.

Ideally, we need quantum repeaters, or waystations with quantum processors in them that would allow encryption keys to remain in quantum form as they are amplified and sent over long distances. Researchers have demonstrated it’s possible in principle to build such repeaters, but they haven’t yet been able to produce a working prototype.

There’s another issue with QKD. The underlying data is still transmitted as encrypted bits across conventional networks. This means a hacker who breached a network’s defenses could copy the bits undetected, and then use powerful computers to try to crack the key used to encrypt them.

The most powerful encryption algorithms are pretty robust, but the risk is big enough to spur some researchers to work on an alternative approach known as quantum teleportation.

What is quantum teleportation?

This may sound like science fiction, but it’s a real method that involves transmitting data wholly in quantum form. The approach relies on a quantum phenomenon known as entanglement.

Quantum teleportation works by creating pairs of entangled photons and then sending one of each pair to the sender of data and the other to a recipient. When Alice receives her entangled photon, she lets it interact with a “memory qubit” that holds the data she wants to transmit to Bob. This interaction changes the state of her photon, and because it is entangled with Bob’s, the interaction instantaneously changes the state of his photon too.

In effect, this “teleports” the data in Alice’s memory qubit from her photon to Bob’s. The graphic below lays out the process in a little more detail:

Researchers in the US, China, and Europe are racing to create teleportation networks capable of distributing entangled photons. But getting them to scale will be a massive scientific and engineering challenge. The many hurdles include finding reliable ways of churning out lots of linked photons on demand, and maintaining their entanglement over very long distances—something that quantum repeaters would make easier.

Still, these challenges haven’t stopped researchers from dreaming of a future quantum internet.

What is a quantum internet?

Just like the traditional internet, this would be a globe-spanning network of networks. The big difference is that the underlying communications networks would be quantum ones.

It isn’t going to replace the internet as we know it today. Cat photos, music videos, and a great deal of non-sensitive business information will still move around in the form of classical bits. But a quantum internet will appeal to organizations that need to keep particularly valuable data secure. It could also be an ideal way to connect information flowing between quantum computers, which are increasingly being made available through the computing cloud.

China is in the vanguard of the push toward a quantum internet. It launched a dedicated quantum communications satellite called Micius a few years ago, and in 2017 the satellite helped stage the world’s first intercontinental, QKD-secured video conference, between Beijing and Vienna. A ground station already links the satellite to the Beijing-to-Shanghai terrestrial network. China plans to launch more quantum satellites, and several cities in the country are laying plans for municipal QKD networks.

Some researchers have warned that even a fully quantum internet may ultimately become vulnerable to new attacks that are themselves quantum based. But faced with the hacking onslaught that plagues today’s internet, businesses, governments, and the military are going to keep exploring the tantalizing prospect of a more secure quantum alternative.

Article link: https://www.technologyreview.com/2019/02/14/103409/what-is-quantum-communications/?

Just when leaders need fresh thinking and decisiveness, they tend to fall back on tried-and-true ways. Five actions can transform your relationship with uncertainty and help you thrive.

Shutdowns and supply-chain hacks. Hybrid work, remote shopping, settling up via blockchain. The past year has made it abundantly clear, if it wasn’t already, that a volatile and complex world is  serving up change at an accelerating pace.

Individuals and organizations need to be ready. That doesn’t mean reacting to the next challenge that comes our way but rather being prepared to meet it when it arrives. There’s one tool above all others that can help leaders do that: adaptability.

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Adaptability is the ability to learn flexibly and efficiently and to apply that knowledge across situations. It’s not so much a skill as a meta-skill—learning how to learn and being conscious of when to put that learner’s mind into action. By becoming aware of and open to change now, we can maintain control over uncertainty before pressures build to the point where altering course is much more difficult, or even futile.

Our research shows that adaptability is the critical success factor during periods of transformation and systemic change. It allows us to be faster and better at learning, and it orients us toward the opportunities ahead, not just the challenges.

Yet the same conditions that make adapting so important can also trigger fear, making us default to familiar patterns or whatever solutions worked the last time. We call this the “adaptability paradox”: when we most need to learn and change, we stick with what we know, often in a way that stifles learning and innovation. Even positive events, such as receiving a promotion or beginning a new workstream, can turn negative unless we can maintain a learning mindset while under pressure.

But people often don’t put in the hard work of learning and mastering something new unless there is compelling motivation to do so. When that motivation arrives, it’s often accompanied by pressure—to avert failure, for instance, or to attain a high-stakes reward or incentive.¹

To avoid this trap, leaders must work on transforming their relationship with change and uncertainty by building adaptability as an evergreen skill that benefits themselves and their organizations at a deeper level.

This is not a natural skill—even for the most successful among us—but it can be nurtured. And the rewards are worth the effort: companies with strong cultures that emphasize adaptability turn in better financial performance than entities that lack those attributes, research shows.²

In this article, we delve into five steps that leaders can take to become more adaptable, including emphasizing both well-being and purpose, practicing an adaptive mindset, building deeper human connections, and making it safe to learn.

Why building an adaptability muscle is so important

The power of resilience has been amply demonstrated during the COVID-19 crisis. Although resilience and adaptability are linked, they are different in important ways. Resilience often entails responding well to an external event, while adaptability moves us from enduring a challenge to thriving beyond it. We don’t just “bounce back” from difficult situations—we “bounce forward” into new realms, learning to be more adaptable as our circumstances evolve and change.

Learning agility,³ emotional flexibility, and openness to experience are all part of a multidimensional understanding of adaptability.⁴ They help us maintain deliberate calm under pressure and display curiosity amid change. They allow us to respond in ways that are the opposite of a knee-jerk reaction by making thoughtful choices.

Studies have shown that adaptability is also linked to important psychological skills, ranging from coping to personal growth. In the workplace,⁵ higher levels of adaptability are associated with greater levels of learning ability and better performance, confidence, and creative output.⁶ Adaptability is also crucial for psychological and physical well-being and is linked to higher levels of social support and overall life satisfaction.⁷

Now that we’ve enumerated the benefits of adaptability, let’s go through the five ways leaders can invest in it to prepare for a fast-paced and uncertain future.

Step 1: Practice well-being as a foundational skill

From the beginning of the COVID-19 pandemic, executives have made sure to check on employees’ health. But that may have been putting the cart before the horse: research shows that leaders experienced anxiety and burnout symptoms at unprecedented rates⁸ as they focused on others without restoring their own energy levels.

A Harvard Business Review–sponsored survey conducted in the fall of 2020 gathered feedback from more than 1,500 respondents from 46 countries⁹ —the majority of whom were at or above supervisor level. Eighty-five percent of these respondents said their well-being had declined, while 56 percent said their job demands had increased. Moreover, 62 percent who were struggling to manage their workloads said they had experienced burnout “often” or “extremely often” in the previous three months.

The number of people reporting more symptoms of burnout has increased since then, not only in C-suites but also across organizations. When people are exhausted, they fall into a scarcity mindset (thinking about what they don’t have) and aren’t as adaptable or open to learning. We expect to see these mental-health and well-being challenges continue for at least the next year or two.

The best way to handle demanding situations is by investing in one’s own well-being first. Just like athletes who continually invest in their own physical and mental health—not only before a game or a race—leaders have to be fit to face whatever comes their way and to support others for however long it takes. Leaders should focus on allowing themselves to thrive, and then helping others to be at their physical, mental, and emotional best.¹⁰

The CEO of a global mobility tech company told us that when the pandemic began, he took advantage of not having to travel by restarting a daily running routine. He started at five kilometers a day, using the time and physical activity to reflect and refresh, eventually building his runs to marathon length. After injuring himself, however, he realized that he had begun to approach running as a goal to be achieved rather than as a nurturing practice to enjoy. So he shifted back to his original goal of giving himself time to reflect, which in turn helped him perform and nurture his team.

Research shows that taking deliberate breaks accelerates learning and skill acquisition. For example, a study of violin prodigies¹¹ revealed that students who were quickest to master the instrument took regular and significant breaks, including naps between practice sessions, rather than playing for hours on end. In another study of people trying to perform a task involving new skills, those who took breaks to mentally reset improved much more quickly under performance pressure.¹²

Counter to what leaders may think, attending to one’s own physical well-being is not selfish. Rather, physical and mental health are necessary to build sound decision-making skills amid uncertainty (Exhibit 1).

Many leaders think they have to show their organizations that they are always “on,” never being out of pocket long or taking needed vacations. But research shows that leaders who are role models for well-being can have a positive impact across their organizations. They understand from their own experience that people learn better and faster when they are healthy and well-rested.

A McKinsey survey on employee experience found that taking care of one’s physical and mental health was associated with a 21 percent improvement in work effectiveness, a 46 percent improvement in employee engagement, and a 45 percent improvement in well-being. Organizations that invest in scaling well-being and improving employee experience have seen lower rates of employee turnover, higher ratings on innovation, and even increased Iong-term stock performance.¹³ They are also more frequently cited as great places to work.

Step 2: Make purpose your North Star and define your ‘nonnegotiables’

While learning is normally invigorating, it can feel daunting during challenging times. We often fall into the trap of attending to the most urgent tasks rather than what is the most important. That’s where a sense of purpose comes in: it offers a framework that makes hard work worthwhile and expands tolerance for change. When employees feel that their purpose is aligned with that of their organization, the benefits expand to include stronger engagement and self-efficacy, as well as heightened loyalty.

Purpose starts with exploring what truly matters to you and what you want to spend time on. As your North Star, your purpose can guide you through tough decisions and inspire you to move forward.

While purpose helps define what you hope to gain, it also frames what you don’t want to lose—your “nonnegotiables.” These are the vows you make to yourself that you will not break no matter what: I will coach junior colleagues; I will be home for my child’s birthday; I will take time off to see my parents. Even if they’re sometimes tough to execute, keeping these vows is worth it.

The link between well-being and purpose is strong. People who say that they are “living their purpose” at work report levels of well-being that are five times higher than those who say that they are not. Research shows they are also healthier, more productive, and more resilient. For their part, leaders who link their own purpose to that of their organization in a genuine fashion help their employees do the same, creating stronger relationships over time.

Step 3: Experience the world through an adaptability lens

Unless the brain learns something new, it will forecast what will happen based on what it has seen and learned before.¹⁴ That is why people default to certain behavioral patterns, especially under stress. Some want to control the situation. Others tend to see themselves as victims, claiming everything is out of their control and shutting down.

Our default patterns may serve to protect us in the moment. But ultimately, they may hinder our ability to adapt and respond in ways that a new situation requires. Often, we realize this is the case only after an interaction in which our default patterns have caused friction in a relationship. These can be missed opportunities to take a proactive approach to the situation.

Underlying these patterns are mindsets and beliefs we hold, often unconsciously, that influence how we perceive reality and make us less flexible and adaptable to changing circumstances. However, if we can recognize that we’re moving to our default mindset for stressful situations—signals such as sweaty palms or other physical reactions to perceived threats—and instead push ourselves to see multiple perspectives, we move into a world that offers more possibilities.

While status quo mindsets may be perfectly reasonable in some routine (or low-stress) situations, they are progressively less useful as circumstances become more complex and we’re under more pressure. What becomes optimal then is for leaders and organizations to shift into adaptable learning mindsets (Exhibit 2).

For leaders, one enemy of the adaptive mindset is a belief that it’s their job to have the “right answers” rather than knowing when to ask the right questions. It’s essentially the same trap that Zen Buddhism warns against falling into, thus urging practitioners to adopt what it calls the beginner’s mind, or shoshin. “In the beginner’s mind, there are many possibilities,” according to this concept. “In the expert’s mind, there are few.”

What we now know is that this beginner’s mind is not a fixed personality trait or a skill available only to Zen masters; it is a learnable skill for everyone. We can build ours through deliberate practice. If leaders shed their “expert” status, they can navigate uncertain situations by collecting information in new and productive ways. By shifting their mindset to encourage learning, curiosity, and openness to change, leaders can display the flexibility to find solutions.

For instance, C-suite leaders at a multinational corporation were struggling with how best to support employees during the pandemic as burnout rates rose. As a practitioner of the “expert mindset,” the CEO felt he should already know the answers and was unable to accept such uncertainty. He was coached to approach the problem by seeking different perspectives—for instance, by turning to team members with nursing, military, and paramedic backgrounds, who had experience dealing with trauma. Making such a journey requires awareness of your default mindsets, understanding when they are not serving you, opening up to what else may be true, and intentionally shifting into a new, adaptable mindset.

Self-awareness and reflection are critical components of adaptability. Ways to build awareness include making a “to be” list—that is, a list of the values we want to embody—and setting your intentions in the morning, ahead of a busy day, or at work when things get challenging. Reflecting at the end of the day about difficult moments also helps build an adaptable “unlocking mindset” for the future. The central issue is not that we experience anxiety or uncertainty—that will happen frequently—but rather whether we respond to those pressures in ways that lead us to do more of the same rather than learning and changing.

Step 4: Build deeper and more diverse connections

Strong interpersonal relationships also bolster adaptability, since human beings need meaningful connections to survive and thrive. These community networks can even affect longevity, research shows.¹⁵

We typically go through our daily work routine actively engaging with tasks and indirectly engaging with colleagues to help us achieve those tasks. But that emphasis is misplaced: inattention to colleagues is actually counterproductive to both our well-being and our productivity at work.

Research has found that deep and diverse connections that provide social support are fundamental elements of the rich tapestry feeding our well-being and learning,¹⁶ especially during periods of uncertainty and heightened stress.

As a leader, there are certain actions you can take to foster deeper connections:

• Pay full attention to the person in front of you. When in conversation, we often let our minds stray, or we multitask by checking our phone or email. Full attention requires tuning our awareness toward the other person and listening deeply, without judgment. When people feel heard, they can also hear you.
• Allow yourself to be vulnerable. Show up as your authentic self and be willing to share your fears, concerns, and imperfections. While it can feel risky to be exposed, this process is always one of deliberate choice.
• Show empathy, but don’t stop there. Empathy alone is not enough. Leaders can learn to channel the right kind of empathy, which involves taking into account the other person’s perspective without being distracted from the situation at hand or, potentially, using up your own energy on unpleasant feelings. Once you understand the other person’s perspective, you become aware of the best course of action.
• Meet others with compassion. If you’ve noticed someone else’s pain—physical, mental, or social—demonstrate your intent to take supportive action. At the same time, be aware that you can never fully understand what they’re going through, so keep an open mind. While general acts of kindness are appreciated, compassion is more nuanced and specific to the needs of the individual.

We have worked with leaders who have changed how they connect with people by considering the ways described above. For instance, the head of plastic surgery at a major hospital in North America was enlisted to sponsor one of the hospital’s new cohorts. During a live coaching exercise, he was unhappy that a team member waited until the end of a three-week consultation process before opposing new safety protocols the group wanted to implement.

Initially frustrated, he asked why she had waited until the last minute. As he reflected more, though, he realized that he had failed to create a safe enough environment for this team member to raise her concerns. He realized he had tried to convince everyone to take a specific action but had failed to create an atmosphere in which people could discuss their views openly.

His mindset then shifted to “What can I do differently to make sure that these voices speak up earlier?” He debriefed the team, held himself accountable, and worked with others to set new norms. By creating these deeper connections, he allowed team members to bring their whole selves to work and feel valued enough to contribute honestly.

Step 5: Make it safe to learn

Healthy team dynamics also foster adaptability. Working in teams influences the extent to which we prioritize learning, especially from setbacks and failures. The absence of conflict and the appearance of compliance may not reflect that dynamic, however. Teams can have cultures in which setbacks and failures go unacknowledged or, worse, are punished, or they can have cultures that seize setbacks as opportunities from which to learn and grow.

Leaders can have a unique influence on which team culture is adopted depending on the degree to which they foster psychological safety. This is a shared belief held by team members that interpersonal risk taking is safe—that ideas, questions, concerns, or mistakes will be welcomed and valued.¹⁷

Experiencing safety is an essential ingredient for higher performance, creativity, and improved well-being. It invites full, authentic participation from every member, fosters constructive debate and creative problem solving, and allows teams to learn quickly. For such a climate to be successful, leaders should be aware of and model the requisite behaviors and deliberately support team members. Put simply, by creating psychological safety, leaders simultaneously demonstrate their own adaptability and create an environment where adaptability can flourish for their teams. This is very different from a leader who believes, “I know best and the team should follow me.”

Here are four practices that can help leaders foster psychological safety:

• Reframe “failures.” Failure is emotionally difficult, since we are primed to succeed. Leaders can help frame failure as a way to learn from missteps and build future successes. This emphasis helps reinforce an adaptable environment in which people feel comfortable being honest and vulnerable; it also invites curious, open, and growth mindsets.
• Encourage team voice. A diversity of perspectives pushes us to be innovative and elevates our performance. Leaders can strive to invite team input into decision making and use more dialogue to encourage discussion. Reinforce “messenger” behavior by appreciating all ideas and thanking those who share them, even if that message is not ultimately acted on. If the idea is dismissed, be sure to explain why, and seek to “unmute” the voices of those who are silent.
• Appreciate others. To drive full participation, team members need to feel valued for their contributions. Leaders can avoid generic congratulations or only recognizing results. Instead, they can reward members’ efforts, making recognition for their contributions part of the team’s vernacular.
• Coach team members to support one another. As a contributor to psychological safety, team climate is more than twice as important as leadership style, we’ve found. Coaching, role modeling, mentoring, and setting up structures are critical to creating an environment that feels safe.

Recently, we had a conversation with a leadership team at an international relief organization that wanted to build healthier dynamics. The team was preparing to welcome a new CEO though during the previous transition, there was a lot of unhelpful history that got in the way of performance.

The new CEO decided to go on a journey with this team to transform that challenging history into a story of hope and opportunity. He engaged external coaches to help encourage team learning, feedback, curiosity, and mindsets open to transformation. Over time, the group went from a collection of individuals lacking mutual trust to a close-knit team that is much stronger today, despite bumps along the road. The CEO’s focus on building trust, along with his growth mindset and willingness to appear vulnerable, made it possible for a fresh culture of psychological safety to arise.

Four ways to build adaptability at scale

The power of adaptability grows when the entire organization reinforces these cultural norms and behaviors. From our experience with both virtual and in-person capability building, we have identified a few ingredients as particularly important. As they enter a new chapter of hybrid work, organizations must seize the opportunity to integrate these elements with the more traditional in-person immersive experience. Here are four ways leaders can scale adaptability building.

Use bite-size training as practice. The prevailing belief has been that deeper awareness and habit-shifting work was possible only through immersive in-person experiences. But as with so many other paradigms, the COVID-19 pandemic changed that view. Many organizations have rolled out short digital training modules coupled with the use of behavioral-reinforcement tools, such as nudges. This content focuses on teaching simple adaptability concepts that participants can practice in their day-to-day lives, which can accelerate learning and behavior changes.

We’ve seen this approach help companies undergoing upheaval—for instance, at a global company that went through a complex merger before the pandemic hit. To improve adaptability, it designed a fully digital program to train 5,000 of its top people managers. The program offered a dozen 20- to 30-minute modules delivered over three months, accompanied by weekly emails to reinforce adaptability behaviors.

At the end of the program, it found that participants who engaged with most of the content (four to six hours over three months) saw 2.7 times the improvement in adaptability behaviors (learning skills, empathy and compassion, and fostering psychological safety and greater self-awareness) and 3.0 times the improvement in outcomes (performance, well-being, adapting to change, and developing new skills) as the control group. Even participants who engaged for just 20 to 30 minutes per month saw meaningful increases in adaptability and outcomes, at 1.4 times and 1.9 times the control group, respectively.

Create learning communities. Virtual learning can reach more people faster, engaging larger cohorts in shared experiences. This helps create networks across the organization and a deeper sense of belonging, both of which support adaptability.

During the pandemic, the hospital system we mentioned earlier created formal learning communities for leaders who had graduated from a virtual learning program. These groups continue to meet regularly, applying the lessons they learned to challenges including scheduling patients or clinical personnel, solving conflicts, and supporting a grieving colleague. Such cohorts provide a unique resource to combat feelings of isolation and augment a shared sense of belonging.

Role model at all levels, including visible sponsors at the top. Virtual learning can help senior leaders connect meaningfully with more people faster. At the hospital system, one of the sponsors of the learning program was a well-respected plastic surgeon. He was coached live, in front of the group, encouraging his cohort to share learning stories and generate engagement. He told us that being a sponsor was the best leadership-development training he had ever done, helping him to adopt a leadership mindset in which his role was to serve and support his staff, rather than the other way around. The impact was also positive for participants, who started to build more trust with senior management.

Create enabling mechanisms to build enduring capabilities. To build adaptability into a skill that becomes part of the organization’s core, it’s important to track progress frequently and meticulously. For instance, organizations can use a multirater feedback tool—a digital platform that assesses the effectiveness of the adaptability learning journey for employees. It also shares aggregate data with leaders and tracks when course corrections are necessary.

By investing in measures that emphasize well-being, purpose, mindset shifts, deeper connections, and team learning, leaders become better equipped to meet the challenges ahead. Applying these lessons throughout their organizations makes for healthier and more responsive teams.

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Leaders should understand that adaptability is a skill that is mastered with continual practice—the ability to “learn how to learn” does not materialize overnight. Those who have the courage and humility to do this work can summon their adaptability skills right when they are needed most. In a world of constant flux, that is a crucial skill set indeed.

Article link: https://www.mckinsey.com/business-functions/organization/our-insights/Future-proof-Solving-the-adaptability-paradox-for-the-long-term

ABOUT THE AUTHOR(S)

Jacqueline Brassey is a global director of learning in McKinsey’s Amsterdam office and affiliate leader of McKinsey’s Center for Societal Benefit through Healthcare; Aaron De Smet is a senior partner in the New Jersey office; Ashish Kothari is a partner in the Denver office; Johanne Lavoie is a partner in the Calgary office; and Marino Mugayar-Baldocchi is a research science specialist in the New York office, where Sasha Zolley is a solution associate partner.

The authors wish to thank Kate Lazaroff-Puck and Laura Tegelberg for their contributions to this article.

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This article was edited by Barbara Tierney, a senior editor in the New York office.