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.

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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

 

HBR: How to Lose Your Best Employees

“When we are learning, we experience higher levels of brain activity and many feel-good brain chemicals are produced. Managers would do well to remember that.” What are you doing to keep your employees challenged at work? Below is a blog from the Harvard Business Review by Whitney Johnson:

How to Lose Your Best Employees

You want to be a great boss. You want your company to be a great place to work. But right now, at this very moment, one of your key employees might be about to walk out the door.

She has consistently brought her best game to work and has grown into a huge asset. But her learning has peaked, her growth has stalled, and she needs a new challenge to reinvigorate her.

As her boss, you don’t want anything to change. After all, she’s super-productive, her work is flawless, and she always delivers on time. You want to keep her right where she is.

That’s a great way to lose her forever.

This was my situation more than a decade ago. After eight years as an award-winning stock analyst at Merrill Lynch, I needed a new challenge. I’ve always liked mentoring and coaching people, so I approached a senior executive about moving to a management track. Rather than offering his support, he dismissed and discouraged me. His attitude was, We like you right where you are. I left within the year.

This kind of scenario plays out in companies every day. And the cost is enormous in terms of both time and money. But if I had stayed and disengaged, the cost may have been even higher. When people can no longer grow in their jobs, they mail it in — leading to huge gaps in productivity. According to Gallup, a lack of employee engagement “implies a stunning amount of wasted potential, given that business units in the top quartile of Gallup’s global employee engagement database are 17% more productive and 21% more profitable than those in the bottom quartile.”

And yet engagement is only symptomatic. When your employees (and maybe even you, as their manager) aren’t allowed to grow, they begin to feel that they don’t matter. They feel like a cog in a wheel, easily swapped out. If you aren’t invested in them, they won’t be invested in you, and even if they don’t walk out the door, they will mentally check out.

How do you overcome this conundrum? It starts with recognizing that every person in your company, including you, is on a learning curve. That learning curve means that every role has a shelf life. You start a new position at the low end of the learning curve, with challenges to overcome in the early days. Moving up the steep slope of growth, you acquire competence and confidence, continuing into a place of high contribution and eventually mastery at the top of the curve.

But what comes next as the potential for growth peters out? The learning curve flattens, a plateau is reached; a precipice of disengagement and declining performance is on the near horizon. I’d estimate that four years is about the maximum learning curve for most people in most positions; if, after that, you’re still doing the exact same thing, you’re probably starting to feel a little flat.

Take my own career: I moved to New York City with a freshly minted university degree in music. I was a pianist who especially loved jazz. But I was quickly dazzled by Wall Street which, in the late 1980s, was the place to work. I secured a position as a secretary in a financial firm and started night school to learn about investing.

A few years later, my boss helped me make the leap from support staff to investment banker. It was an unlikely, thrilling new opportunity that required his sponsorship and support. After a few years, I jumped again to become a stock analyst, and I scaled that curve to achieve an Institutional Investor ranking for several successive years.

When I began, I was excited to be a secretary on Wall Street. I was also excited to become an investment banker. And I loved being a stock analyst. Though I started in each of these positions at the low end of their respective learning curves, I was able to progress and achieve mastery in all of them.

Eventually, I became a little bored with each job and started looking around for a new challenge to jump to. Most of us follow similar patterns — our brains want to be learning, and they give us feel-good feedback when we are. When we aren’t, we don’t feel so good. The human brain is designed to learn, not just during our childhood school years but throughout our life spans. When we are learning, we experience higher levels of brain activity and many feel-good brain chemicals are produced. Managers would do well to remember that.

Because every organization is a collection of people on different learning curves. You build an A team by optimizing these individual curves with a mix of people: 15% of them at the low end of the curve, just starting to learn new skills; 70% in the sweet spot of engagement; and 15% at the high end of mastery. As you manage employees all along the learning curve, requiring them to jump to a new curve when they reach the top, you will have a company full of people who are engaged.

You and every person on your team is a learning machine. You want the challenge of not knowing how to do something, learning how to do it, mastering it, and then learning something new. Instead of letting the engines of your employees sit idle, crank them: Learn, leap, and repeat.

HBR: How to Motivate Yourself When Your Boss Doesn’t

Do you request feedback from your peers and/or managers? What do you do to motivate yourself? Below is a blog from the Harvard Business Review by Julie Mosow:

How to Motivate Yourself When Your Boss Doesn’t

Let’s face it: some bosses are not inspiring. They don’t motivate us to perform at our best — let alone improve our skills. What should you do if your boss is too hands-off, ambivalent, or downright demotivating? How can you keep your engagement up and your own professional goals on track? Is it possible to motivate yourself?

What the Experts Say

The good news is that while your boss has a lot of influence over how engaged you are at work, you can put yourself in the driver’s seat. “Employees have more control than they realize over their ability to build and sustain motivation in the workplace,” says Heidi Grant Halvorson, a motivational psychologist and author of Nine Things Successful People Do Differently. There are many factors that influence motivation, but “the most significant one is a sense of progress,” says Monique Valcour, professor of management at EDHEC Business School in France, citing Teresa Amabile and Steven Kramer’s book, The Progress Principle. “And that comes from the feeling that we are doing work that is meaningful to ourselves, to our colleagues, to the organization, and to the world at large.” Halvorson adds: “Changing your mindset and habits can drive a more fulfilling, more motivated approach to work no matter who your manager is.” Here’s how to motivate yourself when your boss doesn’t.

Understand what makes you tick

If your manager doesn’t motivate you or, even worse, undermines you, it’s important to figure out what drives you personally and professionally. In The Progress Principle, Teresa Amabile and Steven Kramer stress that motivation stems from three things: love of the work itself, the desire to receive recognition, and a sense that our work matters and connects us to others. So ask yourself: When was the last time you felt a sense of meaning and purpose at work? What were the conditions that allowed those feelings to flourish?

Set your own goals

Valcour points out that many people feel they’re sprinting in place with no extra time to tackle anything other than their day-to-day responsibilities. However, it’s important to step back and look at the big picture. Make an individual career plan to help you track your projects and results and set goals for your own development. While some of these goals may be directly related to your current role, others may be geared toward learning and exploring areas of interest outside your job description. Even though it’s tempting to set demanding goals for yourself, Halvorson cautions against going overboard. “Although it’s counterintuitive, setting unrealistic or overly ambitious goals can actually be demotivating because there’s so much on the line,” she says. Instead, set goals with smaller milestones so that you can celebrate your progress each step along the way.

Use if-then planning

Once you’ve decided on your goals, Halvorson recommends using “if-then” planning to stay on track or to handle setbacks. “Accepting that challenges are a part of life and being prepared to deal with them is critical to long-term motivation,” she says. For example, if your goal is to finish a presentation, but you find yourself getting distracted by conversations with colleagues, you might say, “If I haven’t finished the presentation by the end of the day on Wednesday, then I will come in early on Thursday to finish up while it’s quiet.” Or you might use if-then planning to move past a low point. For example, “If we don’t receive funding for this project, then I will rewrite the business plan and approach the partners again.” By anticipating obstacles, you’re less likely to get stuck.

Evaluate your own performance and ask for feedback

One way that poor managers undermine motivation is by not giving sufficient feedback. “Seeking feedback is important,” Valcour confirms, “even if we sometimes hear things we’d rather not.” Halvorson believes that most managers are willing to offer feedback if you ask. You might request the feedback directly and in the moment by saying something like, “How did you think the meeting went? Is there anything I might do differently next time?” You might also look to peers for an objective assessment of your performance. Ask people who will be candid with you and whose opinions you trust. Another option is self-evaluation. “We’re more capable than we realize of generating meaningful feedback about our professional accomplishments,” Halvorson says. “Look critically at your own work and ask yourself the same questions you would use to evaluate the work of others. For example, consider if you’re moving fast enough or if the quality of your work is what it should be.”

Expand your internal and external networks

If your manager isn’t motivating you, it’s essential to look for support elsewhere — not only to boost your confidence but also to increase your visibility. Find mentors within your own company to give guidance and perspective, and, if possible, develop an in-house peer group designed to help all of you move forward. You can also seek out and develop external relationships. Valcour is a strong proponent of online networking. “Particularly for people who live far away from their colleagues, LinkedIn, Twitter, and other networking sites provide a sense of connectedness to a larger professional community that might otherwise be difficult to maintain.” Even for someone in a major metropolitan area with many opportunities to connect, online networking is an effective way to stay in touch with colleagues and to keep abreast of industry-wide developments.

Focus on learning

By shifting the focus of your work from performing perfectly to consistently learning and improving, you create the conditions for both heightened motivation and success. “Research suggests that this change in mindset reliably results in better performance,” Halvorsen says. “When it comes to achievement, attitude and persistence are often more important than innate abilities.” Her advice: break the habit of kicking yourself when things don’t go perfectly and replace it by telling yourself that you’ll learn from your mistakes, move on, and do better next time. “No matter your manager’s approach, breaking away from results-oriented thinking is one of the most powerful things you can do to boost your own motivation.”

Principles to Remember

Do:

  • Determine your own personal and professional motivators ­— you can’t rely on your boss to get ahead
  • Ask for feedback from your colleagues
  • Build a support system inside ­— and outside ­— your company

Don’t:

  • Set unreachable goals that stall your sense of moving forward ­— keep your goals manageable and celebrate your progress along the way
  • Underestimate the value of self-evaluation — look critically at your own work
  • Dwell on your mistakes ­— it’s more important to keep learning

Case Study #1: Cultivate a supportive, effective network

A vice president of human resources in the financial services industry, Lisa Chang* has had five different bosses during the past two years. The revolving door of managers proved to be very demotivating. So she looked elsewhere for support and decided to create an internal network beyond her team. Lisa developed relationships with three senior women in the organization: a woman who was briefly her supervisor before taking a role elsewhere in the company, another who is a leader in the client group she serves, and the chief human resources officer. “It’s unusual to have such a candid, open relationship with someone so senior, Lisa explains. “The chief human resources officer has given me opportunities at every turn in addition to being someone I can go to for advice.”

Lisa has looked to her peers as well but she feels that these mentorship relationships have been a far more effective way for her to stay motivated. “My peers and I are all in the same boat, so most of them wouldn’t have been a great help to me. By looking to more senior employees at the company, I’ve been able to create the kinds of relationships I might have had if I had been working with a great boss.”

While the lack of consistent, managerial support is not what Lisa would’ve hoped for, the situation has provided Lisa with the opportunity to learn from company leaders she otherwise wouldn’t have met. She says: “I’ve been able to seek feedback, challenge myself through new opportunities, and perform effectively in my role despite the leadership vacuum.”

Case Study #2: Stay focused on your own growth and development

Mark Barnaby* has risen through the ranks at several different investment banks, but with a string of managers who were either completely hands off or overly involved, staying motivated hasn’t always been easy. He coped by staying focused on his own ambitions. “Focusing on my manager’s faults just distracted me from my own goals, so I made it my priority to find ways to help him succeed while learning myself.”

He figured out what his bosses weren’t good at and stepped into the gap. “One of my bosses was a big picture thinker, but her approach wasn’t the right one for our work. I helped her by drilling down into fine points of regulatory policy, providing much needed detail in meetings, and being an in-house resource for her. Doing all of this helped me develop the subject matter expertise I needed to continue to move forward professionally.” Developing and meeting his own objectives kept Mark going even when his bosses didn’t.

Early on, Mark knew his growing interests would serve him well. “There is enormous demand for this kind of knowledge,” he explains. “During the past decade, regulatory policy has emerged as a critical focus of the banking industry.” Even though Mark admits that helping managers who weren’t helping him was frustrating, he acknowledges that it was the right decision for him and for everyone involved to approach each situation with a positive, goal-oriented attitude. He advises, “No matter what, never make an enemy of your boss.”

*not their real names