HBR: How to Help Your Employees Learn from Each Other

“Peer-to-peer learning is also uniquely well suited to the way we learn. People gain new skills best in any situation that includes all four stages of what we call the “Learning Loop”: gain knowledge; practice by applying that knowledge; get feedback; and reflect on what has been learned. Peer-to-peer learning encompasses all of these.” Below is a blog from the Harvard Business Review by Kelly Palmer and David Blake:

How to Help Your Employees Learn from Each Other

When your team wants to learn a new skill, where do they turn first? Google? YouTube? Their corporate training programs? No. According to a study conducted by our company, Degreed, more workers first turn to their peers (55%)—second only to asking their bosses. Peer-to-peer learning can be a powerful development tool that breaks through some common barriers to skill-building — and it has other benefits as well.

Yet many organizations have yet to create a formal structure for peer-to-peer learning. In a McKinsey survey, Learning & Development officers report that while classroom training, experiential learning, and on-the-job application of skills are now in regular use as learning mechanisms, less than half of organizations have instituted any kind of formal peer-to-peer learning. One in three respondents said their organizations don’t even have any systems in place to share learning among employees.

In the research for our book The Expertise Economy, we found that managers are often reluctant to establish formal peer-to-peer learning primarily because of a perception that experts outside the company are more valuable as teachers than those inside it, and because peer-to-peer programs are spaced out over numerous sessions. In this context, sending employees to a single day of intense training from an outside expert is assumed to be more fruitful.

It isn’t. First, peer-to-peer learning taps into the expertise that already exists in your organization. Think of all the smart people that you hire and surround yourself with every day, and how much could be gained if peers shared their expertise with each other to learn and build new skills.

Peer-to-peer learning is also uniquely well suited to the way we learn. People gain new skills best in any situation that includes all four stages of what we call the “Learning Loop”: gain knowledge; practice by applying that knowledge; get feedback; and reflect on what has been learned. Peer-to-peer learning encompasses all of these.

For example, when Kelly was in charge of learning at LinkedIn, her team created a peer-to-peer learning program designed around the company’s key corporate values. One section of the program focused on difficult conversations; each participant was asked to identify a real-life difficult conversation they needed to have at work (especially one they might be avoiding). They were first taught about difficult conversations (stage 1); next they practiced with each other before holding the conversations in real life (stage 2). One of the participants, John, confronted his employee Mark about his missed deadlines, a pattern which had been negatively affecting the team. The conversation did not go well — John felt awkward, and Mark got defensive. When John shared this experience with his peers in the learning group, they openly shared their views and ideas, and their own experiences of similar situations (stage 3). As everyone in the group — not just John — reflected on what they had learned, they concluded that they had all become more confident and armed with ideas about how to better handle a similar situation in the future (stage 4). Later group members indicated that their real-world difficult conversations indeed had become more productive.

Learning

A learner’s development is dependent on a willingness to make mistakes, challenge ideas, and speak up about concerns — as John and his colleagues did in their group. Unlike some learning methods — like tests or exams, or high-pressure demonstrations of skills — peer-to-peer learning creates a space where the learner can feel safe taking these risks without a sense that their boss is evaluating their performance while they are learning. You’re more likely to have candid conversations about areas you need to develop with a peer than with someone who has power over your career and income. In peer-to-peer learning, the dynamics of hierarchy disappear. And unlike other methods — like classroom lectures or online compliance training — peer-to-peer learning provides a structured opportunity to have these discussions to begin with.

A secondary benefit of peer-to-peer learning is that the format itself helps employees develop management and leadership skills. Group reflection conversations help employees master the difficult skills of giving and accepting honest, constructive feedback. Because feedback flows in both directions, participants in peer-to-peer learning tend to put more time and energy into making sure the feedback they provide is meaningful. They think from the perspective of their peer, consider where each is coming from, and try to get specific about what will be most helpful and constructive. This doesn’t happen as often when a boss delivers one-way feedback to employees. Similarly, peer learning gives employees experience in leadership, handling different points of view, and developing skills such as empathy.

Setting Up a Peer Learning Program

Formal peer-to-peer learning programs can take many forms. As a manager, you can hold your program online or in person. Your program could pair participants in one-to-one sessions, create cohorts working together on real work problems over a few months, or involve weekly sessions in which individuals share the latest knowledge they’ve gained with their peers with plenty of time for discussion and reflection.

To make any peer-to-peer learning program successful for your team, we recommend a few best practices:

Appoint a facilitator. Although the structure of peer learning is horizontal rather than hierarchical, it’s important to have a neutral party who is not the team’s manager facilitate the program to keep in on track. This person — ideally a skilled facilitator — should organize sessions, keep everyone on topic, keep conversations moving forward, and maintain a positive atmosphere for participants to learn, experiment, and ask questions.

Build a safe environment. Peer learning only works when participants feel safe enough to share their thoughts, experiences, and questions. They need to be open and vulnerable enough to accept constructive input, and also have the courage to give honest feedback rather than telling people what they want to hear.

To build a safe environment, set ground rules. Some suggestions: confidentiality must be honored; feedback should be perceived as a generous gesture that should always be met with gratitude; participants should practice empathy, putting themselves in others’ shoes; and participants should never be mocked or embarrassed for expressing themselves in front of their peers.

Focus on real-world situations. Whenever possible, these sessions should focus on genuine problems to solve. People are more likely to participate, learn, and remember new skills if they are learned in the course of addressing a real-life challenge.

Encourage networking. It helps to set up online social networks around learning, organize networking events for people to discuss their area of expertise, and establish learning groups that meet regularly to discuss ideas. Some organizations build company-wide campaigns in an effort to get everyone involved.

With a well-built peer-to-peer learning program in place as a complement to more traditional learning programs, your team will build lasting skills and relationships that will allow them to bring the skills they learn in those programs into their daily work.

 

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Everwise: Motivating employees close to retirement

“Engaging older employees, particularly in a mentoring program paired with younger workers, can help companies differentiate as they look to attract and retain the best employees, increase engagement and performance, and build a learning culture. More mature workers are a treasure trove of resources, experience, and advice. They can help younger talent grow and develop within the company, setting the stage for a more inclusive culture where talent at all levels and ages can thrive.” Below is a blog from Everwise:

Motivating employees close to retirement

Earlier this month, motivating employees close to retirement surfaced as one of the most popular topics in the Everwise user community of Learning & Development (L&D) professionals and learners. That’s not surprising–employees approaching the traditional age of retirement of 65 are one of the fastest growing segments of the workforce. Approximately 10,000 Baby Boomers have reached this stage every single day since 2011. And by 2035, the U.S. Census Bureau calculates that number will total 78 million. Just because Baby Boomers are nearing retirement doesn’t mean that they will stop contributing to the workplace in a meaningful way. And any employer wanting a skilled and diverse workforce needs to engage this growing – and valuable – segment.

Recognizing the value of older workers

Many employers view older workers as being less motivated and having less growth potential. They assume younger employees invest more time in developing new skills and are generally more excited about their jobs. Older workers, by contrast, are seen as coasting toward retirement and less interested in exploring new ideas and opportunities. As a result, managers feel it is difficult to encourage and manage older employees. They often overlook the benefits that this segment of the workforce can provide.

If you are hanging on to the notions that more mature workers aren’t energetic, eager and useful, your bias is showing. Older employees come to the table with a wealth of contacts, years of skill development, and a track record of experience that illustrates their strengths. After years of navigating the workplace, they understand how the business works, have important people and office skills, and can be a resource for training other employees.

Engaging older workers

Engaging older workers doesn’t need to be a big challenge or initiative. It turns out older workers are still dedicated to their work. A 2010 study found their performance was more stable and less variable from day to day than that of the 20-somethings. And just like with most of today’s employees, older workers value the ability to develop new skills on the job. AARP’s research shows that more than 80 percent of workers ages 45 to 64 view the opportunity to learn something new as an essential element of their ideal job. That means older workers are still very much open to being engaged by your L&D programs and initiatives, so be sure to include them.

To get the best results without gargantuan effort, remember that just like their younger counterparts, older workers want to find purpose in their work and have fun while doing so. It is not just the young who are positive and excited by their work. An AARP retirement study revealed that nearly 1 in 5 between the ages of 65 and 74 say job enjoyment is the single most important reason they still work.

Schedule some fun with social interactions that appeal to all employees. Start with a Friday team lunch or competition sharing and casually quizzing employees’ knowledge about the company or sector. You may find this offers younger and older employees an opportunity to get to appreciate one another as individuals as well as team players.

Recognizing their contributions – use mentoring!

Older employees can be an invaluable source of information and expertise. Recognize them as the experts they are. If you need to change the way things have been done, bring them into the discussion of the best way to implement those changes. That way they can feel a part of the process rather than being pushed aside or forced to change. You may even save valuable time by learning that an approach you’re considering previously failed, or that an approach succeeded and is worth accelerating this time around.

And pairing older employees with younger employees in a mentoring relationship will not only help the older employee feel appreciated but also help transfer knowledge more effectively. There’s no denying that mentoring is an effective way to develop and retain talent. Mentors can help motivate and inspire employees. Mentors provide an essential and experienced sounding board as well as ongoing encouragement and advice. Helping older employees find a larger purpose through mentoring may help them become more engaged and productive as well.

Make it clear that your organization is one where employees can stay, develop skills and achieve their full potential over the long haul. Show appreciation for those employees that have remained committed to a company. Celebrate their efforts at significant milestones. Make every retirement party count as an opportunity to motivate those who are staying and make a statement about the company culture.

In conclusion

Engaging older employees, particularly in a mentoring program paired with younger workers, can help companies differentiate as they look to attract and retain the best employees, increase engagement and performance, and build a learning culture. More mature workers are a treasure trove of resources, experience, and advice. They can help younger talent grow and develop within the company, setting the stage for a more inclusive culture where talent at all levels and ages can thrive.

To learn more from colleagues, experts and industry leaders on this topic and more, join our Everwise community.

HBR: How to Motivate Frontline Employees

“We’ve written before that why people work determines how well they work — that someone’s motive for doing a task determines their performance. Our work has shown that if a person’s motive is play (for example, excitement from novelty, curiosity, experimentation), purpose (the work matters), and potential (they are improved by the work), then their total motivation and performance increase. But if their motive is emotional pressure (shame, guilt, insecurity), economic pressure (mercenary behavior), or inertia (no motive), then total motivation and performance worsen.” Below is a blog from the Harvard Business Review by Lindsay McGregor and Neel Doshi:

How to Motivate Frontline Employees

One question that has long plagued organizations is how to improve performance among frontline workers, the people who actually drive customer experience. Our work with hundreds of companies offers a clear and simple answer.

To show how it works, we’ll walk you through an example. In 2016 the leadership team of a national retail organization asked us to help boost their frontline performance. They wanted to improve revenue, cost, risk, and customer satisfaction all at the same time. (They reached out to us because we wrote a book describing how these performance outcomes would be improved with an operating model that increases motivation.)

We’ve written before that why people work determines how well they work — that someone’s motive for doing a task determines their performance. Our work has shown that if a person’s motive is play (for example, excitement from novelty, curiosity, experimentation), purpose (the work matters), and potential (they are improved by the work), then their total motivation and performance increase. But if their motive is emotional pressure (shame, guilt, insecurity), economic pressure (mercenary behavior), or inertia (no motive), then total motivation and performance worsen.

The retail organization wanted to see how this applied to its stores. So we ran an experiment: We fully transformed the operating model of four stores (which employed around 60 people) for one year, and then compared their performance with that of the other 750+ U.S. stores.

As we predicted, we saw the performance of our experimental stores increase significantly. Productivity (revenue divided by expense) increased by 20% year over year (far more than the 9% increase in revenue that the control group stores averaged); customer satisfaction increased by 11% (the control group saw it decrease by 4%); and sales increased by 8% (the control group saw only a 2% increase).

We should note that this organization is one of the top performers in its industry, so the baseline performance was already high. But we believe that by taking similar steps, the average organization can improve performance even further.

Focus on Learning, Not Pressure

Prior to this pilot, the operating model of the stores was focused on creating emotional and economic pressure to drive performance. District managers would often hear, “You need to get your team to try harder,” or “This is really not what we would expect from your store,” or “Other stores are doing better.” On occasion, managers would use special rewards or threats to motivate better performance.

This playbook is the norm in most organizations. Based on what we’ve seen, frontline employees are among the lowest in total motivation.

To engage the front line at the retail organization, we implemented a new operating model focused on optimizing play, purpose, and potential while reducing the pressure. This required four major changes:

Reduce the economic and emotional pressure. To ensure this front line could focus on learning, we eliminated high-pressure motivation tactics, including sales commissions, high-pressure conversations, sales-based promotion criteria, and public shaming. We explained to leaders that great leadership isn’t about pressuring people to do their work. Rather, it is about inspiring your people to want to do their work well, so they can perform adaptively.

Incorporate a spirit of play by encouraging experimentation. To drive performance with play instead, we wanted to focus on increasing experimentation. Experimentation fosters curiosity, allows for novelty, and sets the pace of learning — all of which are important components of play.

To encourage experimentation, each store maintained an idea board that tracked the primary challenges the store had to solve, as well as ideas for solutions. For example, in one store, a challenge was how to get more walk-in customers. Colleagues could add any ideas they had, whenever they wanted. The challenges themselves were used to focus ideation on what mattered the most.

Employees were asked to choose an idea on the board and experiment with it. Every person was expected to have at least one experiment that they owned at a given time. They learned about hypotheses and about how to reduce an experiment to its minimum effective dose to get a useful result. Each store also had a weekly 45-minute meeting for teams to review their past performance and experiments, without shame or blame, in the spirit of generating new ideas.

There were rules. Experiments had to be doable on the job using only the budget, tools, and time already allocated to each store. Colleagues learned how to focus on creating low-risk experiments (experiments that were “above the waterline” so as to not sink the ship). Once an experiment ended, lessons were systemically captured and shared. There was no pressure for an experiment to work as long as something was learned. If an experiment didn’t work, the team wouldn’t throw it out, but instead would seek to understand why and launch a different experiment.

Create a sense of purpose around the customer. To build a genuine sense of purpose and meaning, the employees in the experiment stores were taught how to connect every product, process, and policy to the benefit and impact they had on customers. If they couldn’t connect an action to a customer outcome, they were taught that it was safe to ask questions until they understood.

Systematically manage apprenticeship. While experimentation is focused on learning strategic or process improvements, it is equally important to manage the pace of learning through apprenticeship. In a culture of apprenticeship, people receive high levels of on-the-job coaching by others who are higher in skill. And just like the system of experimentation, the system of on-the-job apprenticeship has to be tightly managed.

Here’s what we did: Each store was given a set of 30 frontline skills for employees to learn. This included things such as “generating ideas through sales and service data” and “building advisory relationships with prospective customers.” Everyone was asked to choose the skills that they believed would most improve their performance if they learned them. While leaders would help with this decision, the choice was ultimately up to each individual, with leaders focusing on finding on-the-job moments to learn.

We told leaders to identify and share the strongest skill (the professional “superpower”) of each individual on their team. The point of this was to make it easier for colleagues to seek help with learning skills from their colleagues. For example, one person’s superpower might be “solving complex service problems,” while another’s might be “introducing new products to customers.”

Every week, employees would have a brief development discussion with their leader on how they were progressing on learning their skills. Goals and metrics were transparent to everyone so that nothing was hidden.

As leaders and colleagues focused on skill development, performance problems were no longer met with blame and defensiveness. Instead, if a colleague was struggling to perform, the immediate focus became learning and teaching.

Seeing Performance Results

Only a few weeks after this new model was put into place, the teams’ behaviors started to fundamentally shift.

For example, in one case, one of the most junior members of the store led a successful experiment on how to move customers through the checkout line faster. Another store member conducted an experiment on how to better explain a product’s features to a customer. Another had an experiment on how to improve signage visibility.

At an individual level, colleagues started to open up to their teams on what they wanted to learn. Coaching accelerated. People became far more engaged in their work. At the end of eight months, year-over-year performance at our pilot stores had increased significantly, compared with the control stores. The approach is now being scaled across the organization.

Broadly speaking, in front lines today, productivity growth has stalled, while employees are feeling less engaged and more stressed. Moreover, employee retention on the front line continues to be a problem. Too many organizations are responding to these trends with more pressure and micromanagement, which only worsens the problem and increases risk.

Small increases in productivity and retention can have a significant impact on the bottom line. Our rough calculation suggests that improving retention by one percentage point in a 5,000-person front line results, on average, in $2.5 million in annual benefit. (That number assumes a fully loaded cost of $50,000 per person, and a $50,000 cost to replace a new hire and make up for lost productivity while the new hire is found and trained.)

Now is the time for organizations to invest in workers. By implementing a frontline management system focused on driving performance through total motivation, you can build the ultimate win-win.

The authors give special thanks to the following executives and experts for their advice on this article: Deborah Moe, Mandy Norton, Dan Wilkening, Jamie Warder.

HBR: What to Do When a Good Employee Stops Trying to Grow

“Is it OK if someone you are managing doesn’t seem motivated to take on a new assignment or build new skills? When, like a helium balloon, they’re content to float near the ceiling, doing a perfectly good job but never rising higher? What do we do with the experienced experts who have seemingly hit a ceiling and are totally fine with staying there?” Below is a blog from the Harvard Business Review by Whitney Johnson:

What to Do When a Good Employee Stops Trying to Grow

The best managers know they’re supposed to give the people they lead challenging assignments to keep them interested and engaged. But what do you do when someone you manage gets to the top of their learning curve — and doesn’t really want to be pushed any further?

Is it OK if someone you are managing doesn’t seem motivated to take on a new assignment or build new skills? When, like a helium balloon, they’re content to float near the ceiling, doing a perfectly good job but never rising higher? What do we do with the experienced experts who have seemingly hit a ceiling and are totally fine with staying there?

As a manager, you might feel relieved that someone so valuable seems happy to stay where they are. There is a common mindset that favors leaving high-performing employees in place once they have mastered their domain, indefinitely reaping the rewards of their labor, but it ultimately has a downside.

Think of the difference between a stagnant pond — unmoving, algae-covered, a breeding ground for mosquitoes — and a lively, bubbling stream. In the stream, there’s enough motion to keep the water fresh.

Employees at the high end of their learning curve also require change. They are settling into a comfort zone, and absent the stimuli associated with overcoming challenges and building competence, they can quickly become bored, indifferent, and disengaged. Stagnation can breed entitlement, an environment hostile to creative thinking and innovation.

I see this happen for one of two reasons: the need for a new challenge, or the need for a change.

As managers, we can use this insight to figure out which approach to take. There are really two options here.

Offer a Stretch Assignment

That’s what Sumeet Shetty, product development manager at SAP India, did. Subsequent to a reorganization, he inherited a new team. Some of these people made it clear they were happy right where they were — they were comfortable, settled into their routine. But Shetty saw that they were capable of more.

So he gave them stretch assignments, including an exercise in which they had to rehearse board report speeches over and again. They complained that rehearsing for a board presentation was unnecessary. And their first tries reflected these sentiments — they really weren’t very good. But by the sixth time, the presentations were improving. And when the team reported back at the end of the year on Shetty’s performance, they cited this stretch assignment as the most impactful thing he had done as a manager. Six months earlier he had been desperate to find a way to stop the complaining. And finding a professional solution was not easy, but ultimately ended up being what they needed.

Encourage an Entirely New Learning Curve

If your employees’ current level of skill is high but not growing, suggest a move to a new assignment, new team, or a new project or client — anything to help them jump to a new learning curve. When people hang out at the top, their mastery can prevent others who are ready to grow from doing so.

Be direct and sympathetic as you communicate their successes and growth. They’ve simply outgrown their current position.

Recently, one of my coaching clients had this very conversation: They encouraged a good employee to leave the team. Now, this was a valued employee, who had been in the organization for over a decade. My client wasn’t going to kick him to the curb. But it had become clear — to both my client and the employee — that the employee had stalled in his current role. It was a tough conversation, but both the employee and his boss walked away with a huge sense of relief. The employee, no longer feeling stuck, ultimately jumped into a highly entrepreneurial endeavor for two years, then chose to retire. He got his swan song and a strong finish.

Managing this way isn’t easy. Shanna Hocking, associate vice president of development at the Children’s Hospital of Philadelphia, speaks highly of her former boss Pam Parker, VP for Advancement at the University of Alabama. Parker was tough, and she pushed Hocking on to new learning curves and helped her know when needed to leap to a new challenge.

Now Hocking is the boss and hopes to emulate Parker’s style. She’s realized that investing in employees involves parting with something — her time, effort, and mental energy. It won’t work for people who are focused on instant gratification and whose strategy doesn’t encompass anything beyond the next quarterly report. The dividends will come, but true human resource development doesn’t happen in days or months; it can take years and sometimes even decades.

When we have experts on our teams, it’s not about stepping back and letting them “float.” It’s time to offer an assignment that really stretches them, or else to encourage them to move on. Instead of dreading these types of difficult conversations, think of them as a great time to express your appreciation and encouragement. Every employee, however long they’ve worked for you, wants to know they matter. Nothing says that quite like giving them the opportunity to grow.

 

HBR: A 5-Part Process for Using Technology to Improve Your Talent Management

“There is a lot of fear about the speed and scope of technological change, and it’s perhaps most acutely felt by the middle-management survivors of years of corporate layoffs. Fear does not make people more open to experimenting; rather it leads us to put all our energy and ingenuity toward protecting ourselves — and that is lethal for innovation. That’s why the critical task for leaders in a world in which machines will do more and more of their routine work is to enable a shift, from valuing being right, knowing the answers, or implementing top-down changes, to valuing dissent and debate, asking good questions, and iterating to learn.” Below is a blog from the Harvard Business Review by Herminia Ibarra and Patrick Petitti:

A 5-Part Process for Using Technology to Improve Your Talent Management

At the law firm Allen & Overy, the idea of replacing traditional, annual performance appraisals with a technology-enabled continuous feedback system did not come from human resources. It came from a leader within the practice. Wanting something that encouraged more-frequent conversations between associates and partners, the senior lawyer read about what companies like Adobe were doing, and then asked his firm to help him create a new approach. When the new system, Compass, was rolled out to all 44 offices, the fact that it was born of a problem identified by internal staff helped accelerate the tool’s adoption across the firm.

In an era of transformative cognitive technologies like AI and machine learning, it’s become obvious that people, practices, and systems must become nimbler too. And because organizational change tends to be driven by those who most acutely feel the pain, it’s often line managers who are the strongest champions for “talent tech”: innovations in how firms hire people, staff projects, evaluate performance, and develop talent.

But as we have observed in our research, consulting work, and partnerships with dozens of Fortune 500 companies and top professional services firms, the transition to new and different ways of managing talent is often filled with challenges and unexpected hurdles. Gaining the most from talent tech, we find, depends on the adopting firm’s ability to confront, and ultimately reinvent, an often outdated system of interlocking processes, behaviors and mindsets. Much like putting a new sofa in the living room makes the rest of the décor look outdated, experimenting with new talent technologies creates an urgency for change in the rest of the organization’s practices.

While the jury is still out on the long-term impact of many of the talent tech experiments we have witnessed, we have observed five core lessons from those firms that seem to be positioning themselves most effectively to reap their benefits:

  1. Talent tech adoption must be driven by business leaders, not the C-suite or corporate functions.
  2. HR must be a partner and enabler — but not the owner.
  3. Fast-iteration methodologies are a prerequisite, because talent tech has to be tailored to specific business needs and company context and culture.
  4. Working with new technologies in new and nimbler ways creates the need for additional innovation in talent practices.
  5. The job of leaders shifts from mandating change to fostering a culture of learning and growth.

Let’s look at these one by one.

  1. Talent tech adoption must be owned and driven by business leaders.

Many business leaders we have spoken with have stressed: It’s not about the technology, it’s about solving a problem. It’s no surprise then, as we have observed, that talent tech projects have a greater likelihood of succeeding and scaling when they are driven by the business line — and not by top management or functional heads in HR or IT. Because operational managers are closer to the action, they have better insights into specific business challenges and customer pain points that can be addressed by new technologies.

As a VP charged with talent tech innovation at a large consumer products company told us: “We started our digital transformation top-down, creating a sense of urgency and cascading it down. Now it’s much more bottom-up because you have to experiment, you have to do things that are relevant in the field. The urgency has to come from inside the individual instead of top management.” The company organized a series of road shows that exposed high-potential managers to new developments in AI and enabled them to propose and run with projects of their own.

Putting responsibility for innovation in the hands of those who are closest to customers, and reducing layers of control and approval, increases the likelihood that the talent technologies will be fit for purpose. But for a generation of senior managers and functional heads raised on a steady diet of “visionary leadership,” this more adaptive approach does not always come naturally.

  1. HR must be a partner and enabler — but not the owner.

Not only are line managers closely connected to business imperatives, but they are also eager to move fast in technology adoption. They want to seize on the promise of AI, machine learning, and people analytics to improve business results and enhance their career prospects. But their priorities can conflict with other parts of the business.

At one of the companies we worked with, a young, ambitious manager experimented successfully with an on-demand talent platform for staffing employees on projects. But the experiment raised questions, for example, about what latitude bosses had in deciding who’d be allowed to take on extra projects and about whether performance on these extra projects could or should count toward an employee’s annual appraisal and compensation. HR was not involved early enough, was more attuned to the risks than the opportunities, and opposed scaling the project further. Only after a lot of stakeholder management and leadership intervention did the pilot get back on track.

The ramifications of reimagining work are far-reaching, necessitating talent strategies built on the ability to access the right people and skills at the right time and then put them to work in flexible ways for which they will be coached and rewarded. But if middle managers wind up caught in bureaucratic procedures and rule-enforcement mindsets, implementations will falter. That’s why getting buy-in from HR early in the process is so important — and necessary for scaling up when pilots yield promising results.

  1. Knowing how to use lean, self-managing team methodologies is a prerequisite.

Because AI-powered tools like on-demand talent platforms and project staffing algorithms are not simply “plug and play,” it can be helpful to use methods such as rapid prototyping, iterative feedback, customer-focused multidisciplinary teams, and task-centered “sprints” — the hallmarks of agile methodologies — to determine their usefulness.

For example, one large industrial company needed a better way to get people on cross-functional projects. Information about people’s skills and capabilities was dispersed across siloed business lines. Rather than attempting to build out a comprehensive system to identify and match employees across all the projects (and the silos), the company piloted the idea with only a few projects and a carefully selected pool of employees. Starting small allowed extremely fast learning and iteration, broader scaling, and more-complex uses of the system.

We have worked with a range of companies that are experimenting with technology platforms that catalogue projects that need doing, match project needs to skill supply, and then source appropriate talent. In each case, significant modifications were needed to adjust to specific requirements. And in most cases the data necessary to run the new systems existed in different formats residing in silos. Companies that lacked experience with lean methodologies had to be trained to operate as agile teams in order to define a specific use case for the technology. This learning curve is often the culprit behind implementation processes that take significantly longer than managers expect.

  1. Talent tech raises urgency for further talent innovation.

Much has been made of the scarcity of AI engineers, along with the fact that the precious few are quickly snapped up at huge salaries by the usual suspects — Amazon, Apple, Google, and Facebook. Beyond the hype, many firms are finding that they cannot hire the talent they need (because the top experts prefer to be free agents or already work for competitors) and that the skills and capacities they need evolve rapidly or are best sourced externally. These trends are fueling a strategic shift from acquiring talent to accessing talent on an as-needed contract basis; yet the cultural hurdles to staffing externally can be as, if not more, challenging than the technological ones.

One organization we worked with did not have a good mechanism in place for prioritizing the work requested of its shared internal consulting services. Its highly skilled consultants were responding on a first-come, first-served basis and fielding more demands than they could handle. Often they were also the wrong demands. When the team didn’t have the right people on the team for the work, they’d either do their best to complete it themselves or abandon it altogether. An analysis revealed that a good portion of the work could be better done externally by highly skilled contractors, and in fact the team could dramatically increase its ability to provide value across the organization if it could access a specific set of external expertise. But implementing the change was a challenge because the unit’s internal clients felt “safer” working with internal employees.

Once one part of the people system changes significantly, the pressure is on to change related processes. Companies that have shifted to more-agile ways of working have also found that they can no longer evaluate people once or twice a year on their ability to hit individual targets; they now need to look at how people perform as team members, on an ongoing basis. All of this is driving a shift from annual performance assessments to systems that provide feedback and coaching on a continuous basis, as firms ranging from Allen & Overy to Microsoft have found.

  1. Leaders must foster a culture of learning.

One CTO we spoke to tells a story about an AI project that “hit the wall” despite a sequence of green lights. “It was over-administered,” she explained. “We had specified detail into 2019.” As reality on the ground began to diverge from the plan, the people in charge of executing the plans failed to speak up and the project derailed. Without people who feel an “obligation to dissent,” she concluded, it’s hard to innovate.

Across industries and sectors, practitioners and academics seem to agree on one thing: Successfully piloting new technologies requires shifting from a traditional plan-and-implement approach to change to an experiment-and-learn approach. But experiment-and-learn approaches are by definition rife with opportunities for failure, embarrassment, and turf wars. Without parallel work by senior management to shift corporate cultures toward a learning mindset, change will inch along slowly if at all.

When Microsoft CEO Satya Nadella took charge, for example, he saw that fear — and the corporate politics that resulted from it — was the biggest barrier to capturing leadership in cloud computing and mobility solutions. A convert to Carol Dweck’s idea of a growth mindset — the belief that talent is malleable and expandable with effort, practice, and input from others — he prioritized a shift from a “know it all” to a “learn it all” culture as a means to achieving business goals. Today, not only does Microsoft rank among the top firms in cloud computing, but the company is also “cool” again in the minds of the top engineering talent it needs to compete.

There is a lot of fear about the speed and scope of technological change, and it’s perhaps most acutely felt by the middle-management survivors of years of corporate layoffs. Fear does not make people more open to experimenting; rather it leads us to put all our energy and ingenuity toward protecting ourselves — and that is lethal for innovation. That’s why the critical task for leaders in a world in which machines will do more and more of their routine work is to enable a shift, from valuing being right, knowing the answers, or implementing top-down changes, to valuing dissent and debate, asking good questions, and iterating to learn.

 

HBR: Automation Will Make Lifelong Learning a Necessary Part of Work

“We see retraining (or “reskilling” as some like to call it), as the imperative of the coming decade. It is a challenge not just for companies, which are on the front lines, but also for educational institutions, industry and labor groups, philanthropists, and of course, policy makers, who will need to find new ways to incentivize investments in human capital.” Below is a blog from the Harvard Business Review by Susan Lund, Jacques Bughin, Eric Hazan:

Automation Will Make Lifelong Learning a Necessary Part of Work

President Emmanuel Macron together with many Silicon Valley CEOs will kick off the VivaTech conference in Paris this week with the aim of showcasing the “good” side of technology. Our research highlights some of those benefits, especially the productivity growth and performance gains that automation and artificial intelligence can bring to the economy — and to society more broadly, if these technologies are used to tackle major issues such as fighting disease and tackling climate change. But we also note some critical challenges that need to be overcome. Foremost among them: a massive shift in the skills that we will need in the workplace in the future.

To see just how big those shifts could be, our latest research analyzed skill requirements for individual work activities in more than 800 occupations to examine the number of hours that the workforce spends on 25 core skills today. We then estimated the extent to which these skill requirements could change by 2030, as automation and artificial technologies are deployed in the workplace, and backed up our findings with a detailed survey of more than 3,000 business leaders in seven countries, who largely confirmed our quantitative findings. We grouped the 25 skills into five categories: physical and manual (which is the largest category today), basic cognitive, higher cognitive, social and emotional, and technological skills (today’s smallest category).

The findings highlight the major challenge confronting our workforces, our economies, and the well-being of our societies. Among other priorities, they show the urgency of putting in place large-scale retraining initiatives for a majority of workers who will be affected by automation — initiatives that are sorely lacking today.

Shifts in skills are not new: we have seen such a shift from physical to cognitive tasks, and more recently to digital skills. But the coming shift in workforce skills could be massive in scale. To give a sense of magnitude: more than one in three workers may need to adapt their skills’ mix by 2030, which is more than double the number who could be displaced by automation under some of our adoption scenarios — and lifelong learning of new skills will be essential for all. With the advent of AI, basic cognitive skills, such as reading and basic numeracy, will not suffice for many jobs, while demand for advanced technological skills, such as coding and programming, will rise, by 55% in 2030, according to our analysis.

The need for social and emotional skills including initiative taking and leadership will also rise sharply, by 24%, and among higher cognitive skills, creativity and complex information and problem solving will also become significantly more important. These are often seen as “soft” skills that schools and education systems in general are not set up to impart. Yet in a more automated future, when machines are capable of taking on many more rote tasks, these skills will become increasingly important — precisely because machines are still far from able to provide expertise and coaching, or manage complex relationships.

While many people fear that automation will reduce the number of jobs for humans, we note that the diffusion of AI will take time. The need for basic cognitive skills as well as physical and manual skills will not disappear. In fact, physical and manual skills will remain the largest skill category in many countries by hours worked, but with different importance across countries. In France and the United Kingdom, for example, manual skills will be overtaken by demand for social and emotional skills, while in Germany, higher cognitive skills will become preeminent. These country differences are the result of different industry mixes in each country, which in turn affect the automation potential of economies and the future skills mix. While we based our estimates on the automation potential of sectors and countries today, this could change depending on the pace and enthusiasm with which AI is adopted in companies, sectors, and countries. Already, it is clear that China is moving rapidly to become a leading AI player, and Asia as a whole is ahead of Europe in the volume of AI investment.

We see retraining (or “reskilling” as some like to call it), as the imperative of the coming decade. It is a challenge not just for companies, which are on the front lines, but also for educational institutions, industry and labor groups, philanthropists, and of course, policy makers, who will need to find new ways to incentivize investments in human capital.

For companies, these shifts are part of the larger automation challenge that will require a thorough rethink of how work is organized within firms — including what the strategic workforce needs are likely to be, and how to set about achieving them. In our research, we find some examples of companies that are focusing on retraining, either in-house — for example, Germany’s SAP — or by working with outside educational institutions, as AT&T is doing. Overall, our survey suggests that European firms are more likely to fill future staffing needs in the new automation era by focusing on retraining, while US firms are more open to new hiring. The starting point for all of this will be a mindset change, with companies seeking to measure future success by their ability to provide continuous learning options to employees.

The skill shift is not only a challenge, it is an opportunity. If companies and societies are able to equip workers with the new skills that are needed, the upside will be considerable, in terms of higher productivity growth, rising wages, and increased prosperity. M. Macron’s point about technology being a force for good will become a self-fulfilling prophecy. Conversely, a failure to address these shifting skill demands could exacerbate income polarization and stoke political and social tensions. The stakes are high, but we can already see the outlines of what needs to be don — and we have a little time to work on solutions.

 

HBR: Learning Is a Learned Behavior. Here’s How to Get Better at It.

“The good news from all of this — for individuals and for companies looking to help their employees be their best — is that learning is a learned behavior. Being a quick study doesn’t mean you’re the smartest person in the room. It’s that you’ve learned how to learn. By deliberately organizing your learning goals, thinking about your thinking, and reflecting on your learning at opportune times, you can become a better study, too.” Below is a blog from the Harvard Business Review by Ulrich Boser:

Learning Is a Learned Behavior. Here’s How to Get Better at It.

Many people mistakenly believe that the ability to learn is a matter of intelligence. For them, learning is an immutable trait like eye color, simply luck of the genetic draw. People are born learners, or they’re not, the thinking goes. So why bother getting better at it?

And that’s why many people tend to approach the topic of learning without much focus. They don’t think much about how they will develop an area of mastery. They use phrases like “practice makes perfect” without really considering the learning strategy at play. It’s a remarkably ill-defined expression, after all. Does practice mean repeating the same skill over and over again? Does practice require feedback? Should practice be hard? Or should it be fun?

A growing body of research is making it clear that learners are made, not born. Through the deliberate use of practice and dedicated strategies to improve our ability to learn, we can all develop expertise faster and more effectively. In short, we can all get better at getting better.

Here’s one example of a study that shows how learning strategies can be more important than raw smarts when it comes to gaining expertise. Marcel Veenman has found that people who closely track their thinking will outscore others who have sky-high IQ levels when it comes to learning something new. His research suggests that in terms of developing mastery, focusing on how we understand is some 15 percentage points more important than innate intelligence.

Here are three practical ways to build your learning skills, based on research.

Organize your goals

Effective learning often boils down to a type of project management. In order to develop an area of expertise, we first have to set achievable goals about what we want to learn. Then we have to develop strategies to help us reach those goals.

A targeted approach to learning helps us cope with all the nagging feelings associated with gaining expertise: Am I good enough? Will I fail? What if I’m wrong? Isn’t there something else that I’d rather be doing?

While some self-carping is normal, Stanford psychologist Albert Bandura says these sorts of negative emotions can quickly rob us of our ability to learn something new. Plus, we’re more committed if we develop a plan with clear objectives. The research is overwhelming on this point. Studies consistently show that people with clear goals outperform people with vague aspirations like “do a good job.” By setting targets, people can manage their feelings more easily and achieve progress with their learning.

Think about thinking

Metacognition is crucial to the talent of learning. Psychologists define metacognition as “thinking about thinking,” and broadly speaking, metacognition is about being more inspective about how you know what you know. It’s a matter of asking ourselves questions like: Do I really get this idea? Could I explain it to a friend? What are my goals? Do I need more background knowledge? Or do I need more practice?

Metacognition comes easily to many trained experts. When a specialist works through an issue, they’ll often think a lot about how the problem is framed. They’ll often have a good sense of whether or not their answer seems reasonable.

The key, it turns out, is not to leave this sort of “thinking about thinking” to the experts. When it comes to learning, one of the biggest issues is that people don’t engage in metacognition enough. They don’t stop to ask themselves if they really get a skill or concept.

The issue, then, is not that something goes in one ear and out the other. The issue is that individuals don’t dwell on the dwelling. They don’t push themselves to really think about their thinking.

Reflect on your learning

There is something of a contradiction in learning. It turns out that we need to let go of our learning in order to understand our learning. For example, when we step away from a problem, we often learn more about a problem. Get into a discussion with a colleague, for instance, and often your best arguments arrive while you’re washing the dishes later. Read a software manual and a good amount of your comprehension can come after you shut the pages.

In short, learning benefits from reflection. This type of reflection requires a moment of calm. Maybe we’re quietly writing an essay in a corner — or talking to ourselves as we’re in the shower. But it usually takes a bit of cognitive quiet, a moment of silent introspection, for us to engage in any sort of focused deliberation.

Sleep is a fascinating example of this idea. It’s possible that we tidy up our knowledge while we’re napping or sleeping deeply. One recent study shows a good evening of shut-eye can reduce practice time by 50%.

The idea of cognitive quiet also helps explain why it’s so difficult to gain skills when we’re stressed or angry or lonely. When feelings surge through our brain, we can’t deliberate and reflect. Sure, in some sort of dramatic, high-stakes situations, we might be able to learn something basic like remember a phone number. But for us to gain any sort of understanding, there needs to be some state of mental ease.

The good news from all of this — for individuals and for companies looking to help their employees be their best — is that learning is a learned behavior. Being a quick study doesn’t mean you’re the smartest person in the room. It’s that you’ve learned how to learn. By deliberately organizing your learning goals, thinking about your thinking, and reflecting on your learning at opportune times, you can become a better study, too.

Original Page: https://hbr.org/2018/05/learning-is-a-learned-behavior-heres-how-to-get-better-at-it