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Networking Myths Dispelled

Harvard business - Tue, 08/14/2018 - 15:18

David Burkus, a professor at Oral Roberts University and author of the book Friend of a Friend, explains common misconceptions about networking. First, trading business cards at a networking event doesn’t mean you’re a phony. Second, your most valuable contacts are actually the people you already know. Burkus says some of the most useful networking you can do involves strengthening your ties with old friends and current coworkers.

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Categories: Blogs

Leap: How to Thrive in a World Where Everything Can Be Copied

Leadershipnow - Tue, 08/14/2018 - 09:44


IN TODAY'S competitive environment, where latecomers can copy almost any product or service, companies can no longer just be good at what they do. Is the displacement of early pioneering companies an inevitable fate in the modern economy? Outlasting copycat competition in any industry is difficult; doing so over decades is nearly impossible—unless you leap.

Howard Yu explains in Leap: How to Thrive in a World Where Everything Can Be Copied, how a business can shield itself from copycats. (The stories are absorbing and alone are worth the price of the book.)

Yu identifies five fundamental principles that allow companies to make a leap and stay successful in the face of such competition.

Principle 1: Understand your firm’s foundational knowledge and its trajectory
Protecting a business begin first by knowing its foundational or core knowledge. Here Yu examines what not to do in the case of Steinway and copycat Yamaha. Steinway & Sons spiraled into decline “in large part due to its myopic obsession with craftsmanship at the expense or technological advancement and automation.” He notes, “As history has proved, what begins as an act of human creativity by a world-class expert usually ends in machine automation.” Steinway allowed its strengths to become its weakness. “In other words, core competencies turned into core rigidities, preventing the firm from responding appropriately to the strategic threat Yamaha posed.”

What is the core knowledge discipline that is most fundamental to your company and how widely available is it?

Principle 2: Acquire and cultivate new knowledge disciplines
Yu examines pharmaceutical companies like Novartis and the soap company P&G to see how they moved across knowledge disciplines to leverage or create new knowledge on how their product was made. “Only by forging ahead, rather than refining what has already been, can a pioneer avoid being caught by copycats.”

Two forces—the unwillingness to cannibalize current sales and the tendency to leverage what we have today—leads firms to give their advantage away to copycats. As P&G chairman William Cooper Proctor said in 1933, “This [synthetic detergent] may ruin the soap business. But if anybody is going to ruin the soap business it had better be Procter & Gamble.”

When making the leap timing is important. Steve Jobs said, “Things happen fairly slowly.” Yu writes, “This is an important lesson. Successful executives often exhibit a bias for action. But it’s even more important to separate the noise from the signal that actually pinpoints the glacial movement around us. Listening carefully to the right signals requires patience and discipline.”

Principle 3: Leverage seismic shifts
Where should we look for opportunities to leap? “We must identify those forces that matter the most in the coming decades and reconfigure our competencies ahead of others.” The two intertwining forces that will propel all companies into the second half of the twenty-first century are the rise of intelligent machines and the emergence of ubiquitous connectivity. We must think about how we can use connectivity to mass-produce solutions and solve complex problems and how to use intelligent machines to automate that process in our own businesses.

Principle 4: Experiment to gain evidence
There are puzzles and there are mysteries. To solve a puzzle, you need the correct data—better intelligence and sharper calculation. Mysteries on the other hand, do not have an answer. The answer has to be invented. It requires a shift in thinking. It requires creativity. “Executives must infuse knowledge work with creativity while automating everything that is routine.”

Ask: “What world am I living in? What are the biggest trends in this world? How do I align my company’s activities so my organization gets the most out of these trends and cushions the worst?”

And while experimentation is good, at some point someone has to pull the trigger. Stop the experimentation process and fully commit to an execution strategy. There is an abundance of ideas but not enough execution.

Principle 5: Dive deep into execution
“The biggest risk that threatens the survival of a large and complex organization lies in political infighting and collective inaction.” Looking at example after example, Yu found that “Every time an organization successfully leaps into a new knowledge base, the senior leaders need to go beyond formulating a strategy and should get their hands dirty during its implementation. Corporate leaders need to absorb career risks…. Success requires an exact combination of knowledge power and positional power.” Maintaining the entrepreneurial spirit is the function of the CEO.

Looking at the successes and failures of startups, the difference “was not that the successful startups got it right the first time but that they learned from their mistakes early enough to shift gears. They had just enough money left over to restart after getting it wrong.”

How do you thrive in a world where everything can be copied? You change the rules of the game. You leap from one knowledge discipline to another. “It turns out that regardless of the industry, it is possible to radically rewrite the rules of the game so as to demand a whole new field of knowledge in support of the change.” We can’t stand on what got us here, we must innovate.

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Categories: Blogs

Managers Think They’re Good at Coaching. They’re Not.

Harvard business - Tue, 08/14/2018 - 09:00
pbombaert/Getty Images

Are you successful at coaching your employees? In our years studying and working with companies on this topic, we’ve observed that when many executives say “yes,” they’re incorrectly answering the question. Why? For one, managers tend to think they’re coaching when they’re actually just telling their employees what to do — and this behavior is often reinforced by their peers. This is hardly an effective way to motivate people and help them grow, and it can result in wasted time, money, and energy.

According to Sir John Whitmore, a leading figure in executive coaching, the definition of coaching is “unlocking a person’s potential to maximize their own performance. It is helping them to learn rather than teaching them.” When done right, coaching can also help with employee engagement; it is often more motivating to bring your expertise to a situation than to be told what to do.

Recently, my colleagues and I conducted a study that shows that most managers don’t understand what coaching really is — and that also sheds light on how to fix the problem. This research project is still in progress, but we wanted to offer a glimpse into our methodology and initial findings.

First, we asked a group of participants to coach another person on the topic of time management, without further explanation. In total, 98 people who were enrolled in an MBA course on leadership training participated, with a variety of backgrounds and jobs. One-third of the participants were female and two-thirds were male; on average, they were 32 years old and had eight years of work and 3.8 years of leadership experience. The coaching conversations lasted five minutes and were videotaped. Later, these tapes were evaluated by other participants in the coaching course through an online peer review system. We also asked 18 coaching experts to evaluate the conversations. All of these experts had a master’s degree or graduate certificate in coaching, with an average of 23.2 years of work experience and 7.4 years of coaching experience.

Participants then received face-to-face training in two groups of 50, with breakouts in smaller groups for practice, feedback, and reflection around different coaching skills. At the end, we videotaped another round of short coaching conversations, which were again evaluated by both peers and coaching experts. In total, we collected and analyzed more than 900 recorded evaluations of coaching conversations (pre-training and post-training), which were accompanied by surveys asking participants about their attitudes and experiences with leadership coaching before and after the training.

The biggest takeaway was the fact that, when initially asked to coach, many managers instead demonstrated a form of consulting. Essentially, they simply provided the other person with advice or a solution. We regularly heard comments like, “First you do this” or “Why don’t you do this?”

This kind of micromanaging-as-coaching was reinforced as good practice by other research participants. In the first coaching exercise in our study, the evaluations peers gave one another were significantly higher than the evaluations from experts. In an organizational setting, you can imagine how a group of executives, having convinced one another of their superior skills, could institutionalize preaching-as-coaching.

Our research also looked at how you can train people to be better coaches. We focused on analyzing the following nine leadership coaching skills, based on the existing literature and our own practical experiences of leadership coaching:

  • listening
  • questioning
  • giving feedback
  • assisting with goal setting
  • showing empathy
  • letting the coachee arrive at their own solution
  • recognizing and pointing out strengths
  • providing structure
  • encouraging a solution-focused approach

Using the combined coaching experts’ assessments as the baseline for the managers’ abilities, we identified the best, worst, and most improved components of coaching. The skill the participants were the best at before training was listening, which was rated “average” by our experts. After the training, the experts’ rating increased 32.9%, resulting in listening being labeled “average-to-good.”

The skills the participants struggled with the most before the training were “recognizing and pointing out strengths” and “letting the coachee arrive at their own solution.” On the former, participants were rated “poor” pre-training, and their rating crept up to only “average” after. Clearly, this is an area managers need more time to practice and work on, and it’s something they likely need to be trained on differently as well. Interestingly, the most improved aspect of coaching was “letting coachees arrive at their own solution.” This concept saw an average increase in proficiency of 54.1%, which moved it from a “poor” rating to a “slightly above average” one.

More generally, multiple assessments of participants by experts before and after the training course resulted in a 40.2% increase in overall coaching ability ratings across all nine categories, on average.

What can organizations learn from our research? First, any approach to coaching should begin by clearly defining what it is and how it differs from other types of manager behavior. This shift in mindset lays a foundation for training and gives managers a clear set of expectations.

The next step is to let managers practice coaching in a safe environment before letting them work with their teams. The good news, as evidenced by our research, is that you don’t necessarily need to invest in months of training to see a difference. You do, however, need to invest in some form of training. Even a short course targeted at the right skills can markedly improve managers’ coaching skills.

Regardless of the program you choose, make sure it includes time for participants to reflect on their coaching abilities. In our study, managers rated their coaching ability three times: once after we asked them to coach someone cold, once after they were given additional training, and once looking back at their original coaching session. After the training, managers decreased their initial assessment of themselves by 28.8%, from “slightly good” to “slightly poor.” This change was corroborated by managers’ peers, who reduced their assessment by 18.4%, from “slightly good” to “neither good nor bad,” when looking back at their original observations of others. In other words, if managers have more knowledge and training, they are able to provide a better self-assessment of their skills. Organizations should allocate time for managers to reflect on their skills and review what they have done. What’s working, and what they could do better?

Our research also supports the idea of receiving feedback from coaching experts in order to improve. The risk of letting only nonexperts help might reinforce and normalize ineffective behaviors throughout an organization. Specifically, coaching experts could give feedback on how well the coaching skills were applied and if any coaching opportunities have been missed. This monitoring could take the form of regular peer coaching, where managers in an organization come together to practice coaching with each other, or to discuss common problems and solutions they have encountered when coaching others, all in the presence of a coaching expert. Here managers have two advantages: First, they can practice their coaching in a safe environment. Second, coaches can discuss challenges they have experienced and how to overcome them.

If you take away only one thing here, it’s that coaching is a skill that needs to be learned and honed over time. Not only does a lack of training leave managers unprepared to undertake coaching, but also it may effectively result in a policy of managers’ reinforcing poor coaching practices among themselves.

Categories: Blogs

To Make Self-Driving Cars Safe, We Also Need Better Roads and Infrastructure

Harvard business - Tue, 08/14/2018 - 08:39
Paul Taylor/Getty Images

The big question around self-driving cars, for many people, is: When will the technology be ready? In other words, when will autonomous vehicles be safe enough to operate on their own? But there has been far less attention paid to two equally important questions: When will the driving environment be ready to accommodate self-driving cars? And where will this technology work best?

Self-driving cars are the most challenging automation project ever undertaken. Driving requires a great deal of processing and decision making, which must be automated. On top of that, there are many unpredictable external factors that must be accounted for, and therefore many ways in which the driving environment must change.

Cars are heavy, fast-moving objects, operating in public spaces. Safety is largely the responsibility of the driver, who must continuously observe, analyze, decide, and act. Not only do drivers have to follow the rules of the road, but they also have to communicate with each other and other road users to navigate ambiguous or contested situations; think about how you wave or nod to someone to signal “You go first.”

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Self-driving systems have to execute all of these functions, and do so accurately, reliably, and safely, across a wide variety of situations and conditions. Currently, the technology is more capable in some situations than in others.

Through sensors and detailed mapping software, the systems build representations of their environments and update them many times a second. They classify the objects they see and predict their likely behavior before selecting appropriate responses. The speed and the accuracy of these systems already surpass human responses in many situations. Lasers can see in the dark. Reaction times can be nearly instantaneous.

But some conditions still constrain them. Cameras are challenged by strong, low-angle sunlight (important for reading traffic lights), and lasers can be confused by fog and snowfall. Unusual, unfamiliar, and unstructured situations (so-called edge cases), such as accidents, road work, or a fast-approaching emergency response vehicle, can be hard to classify. And self-driving systems are not good at detecting and interpreting human cues, such as gestures and eye contact, that facilitate coordination between cars on the road.

Processes and environments that are structured well are much easier to automate than those that are not. Automated systems need to collect, classify, and respond to information, and this is easier to do in a clean, unambiguous environment — which is what many driving environments are not. The designers of self-driving systems simply cannot foresee every possible combination of conditions that will occur on the road. (Though companies are trying: Google’s Waymo team deliberately subjects its cars to “pathological situations” that are unlikely to happen, such as people hiding in bags and then jumping in front of the car.)

Over time, learning will take place and the number of situations that systems cannot recognize will decrease. In fact, learning is likely to be better in an automated system, because once an incident has occurred and is understood, the fix can be rolled out across all vehicles. Currently, learning is largely confined to individual drivers, and is not shared across the system as a whole. But novel combinations of conditions will never be eliminated, and sometimes these will have catastrophic consequences — a pattern seen even in the highly disciplined environment of commercial aviation.

The problem therefore lies in our period of transition. For the technology to improve, it must be exposed to real, on-road conditions. In the early stages of deployment, it sometimes won’t know the best way to respond and therefore will have to hand over control to a human driver. The issue here, however, is that humans zone out when their full attention is not needed. As self-driving cars improve and humans intervene less, driver inattention and the associated problem of quickly reengaging to respond become even bigger problems.

And as the technology becomes more sophisticated, the situations where it requires human assistance are likely to be more complex, ambiguous, and difficult to diagnose. In these cases, a startled human has much less chance of responding correctly. Even in the highly sterile environment of an aircraft cockpit, pilots can be caught by surprise and respond incorrectly when automation has ceded control.

Two fatal accidents involving Tesla vehicles operating on their Autopilot systems demonstrate how this space between semi-automated driving and intermittent human control may be the most dangerous place of all. In the Florida 2016 crash, the driver of the Tesla had his hands on the steering wheel for only 25 seconds of the 37 minutes in which he operated the vehicle in automated control mode. In California in 2018, the driver’s hands were not detected on the steering wheel in the six seconds preceding the crash.

This problem has led companies such as Waymo and Ford to advocate for fully autonomous cars that get rid of the need for handovers. But this requires a leap: With no driver as backup, there is a risk that the technology will be catapulted into environments that are beyond its ability to handle.

Self-driving cars also have to navigate an environment that is shared — with pedestrians who sometimes cross the road without looking, cyclists, animals, debris, inanimate objects, and of course whatever elements the weather brings. Road infrastructure, regulations, and driving customs vary from country to country, even city to city, and are overseen by a multiplicity of bodies. So it’s not clear which institutions have the power and reach to regulate and standardize the driving environment, if they even exist. Roads are very different from airspace, which is governed by powerful global regulatory bodies, has far less traffic, and has very high licensing standards for pilots.

This means that we need to think not just about the onboard technology but also about the environment in which it is deployed. We’ll likely start to see a more standardized and active environment as more smart infrastructure is constructed. Think of radio transmitters replacing traffic lights, higher-capacity mobile and wireless data networks handling both vehicle-to-vehicle and vehicle-to-infrastructure communication, and roadside units providing real-time data on weather, traffic, and other conditions. Common protocols and communications standards will have to be devised and negotiated, as they were with internet communication protocols or the Global System for Mobile Communications (GSM) for mobile phones. This transition will take decades, and autonomous vehicles will have to share the roads with human drivers.

If rapid, radical change to the driving environment is impractical, what is the alternative? The most likely near-term scenario we’ll see are various forms of spatial segregation: Self-driving cars will operate in some areas and not others. We’re already seeing this, as early trials of the technology are taking place in designated test areas or in relatively simple, fair-weather environments. But we may also see dedicated lanes or zones for self-driving vehicles, both to give them a more structured environment while the technology is refined and to protect other road users from their limitations.

We can also expect to see self-driving cars deployed first in relatively controlled environments (such as theme parks, private campuses, and retirement villages), where speeds are lower and the range of situations the vehicles have to deal with is limited. Economics, too, will play an important role in where and how self-driving cars begin to operate. The vehicles will likely appear in environments where it is cost-effective to develop and maintain highly detailed mapping, such as dense urban environments, although of course these also pose other challenges due to their complexity.

Although the cost of self-driving cars will fall once they enter mass production, it is currently very high, from $250,000 to $300,000 a vehicle, according to some estimates. So they will first appear in settings where vehicle utilization rates are high and where the cost of a driver’s time matters — imagine robotaxis or ride-hailing vehicles operating in defined, geo-fenced zones. Trials of these are already under way. Robotaxis also point to a way in which humans can support self-driving technology while avoiding the human zone-out problem by interacting with call centers. A self-driving vehicle that cannot get past an obstruction in the road without acting illegally (crossing a white line, for example) can stop and call a human operator for advice, who can then authorize it to act in a nonstandard way.

In the long run, driverless cars will help us reduce accidents, save time spent on commuting, and make more people mobile. The onboard technology is developing rapidly, but we’re entering a transition stage in which we need to think carefully about how it will interact with human drivers and the wider driving environment. During this period, the key question we should be asking is not when will self-driving cars be ready for the roads, but rather which roads will be ready for self-driving cars.

Categories: Blogs

Mindfulness and Meditation Might Be Bad For Your Company...

Hr Capitalis - Tue, 08/14/2018 - 08:03
There's a great scene in the movie The Matrix i'll use as the intro to talking about mindfulness. It goes something like this - one of the machines (Agent Smith) has captured the leader of the human resistance, and he... Kris Dunn
Categories: Blogs

Designing AI to Make Decisions

Harvard business - Tue, 08/14/2018 - 07:30

Kathryn Hume, VP of integrate.ai, discusses the current boundaries between artificially intelligent machines, and humans. While the power of A.I. can conjure up some of our darkest fears, she says the reality is that there is still a whole lot that A.I. can’t do. So far, A.I. is able to accomplish some tasks that humans might need a lot of training for, such as diagnosing cancer. But she says those tasks are actually more simple than we might think – and that algorithms still can’t replace emotional intelligence just yet. Plus, A.I. might just help us discover new business opportunities we didn’t know existed.

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Categories: Blogs

Why Western Digital Firms Have Failed in China

Harvard business - Tue, 08/14/2018 - 07:00
Paper Boat Creative/Getty Images

Many leading American digital firms, including Google, Amazon, eBay, and Uber, have successfully expanded internationally by introducing their products, services, and platforms in other countries. However, they have all failed in China, the world’s largest digital market.

The widely touted reasons for these failures include censorship by the Chinese government and cultural differences between China and the West. While these factors undoubtedly have played a role, such explanations are overly simplistic. Google, for example, has succeeded in dominating many foreign markets that have radically different political systems and cultures (including Indonesia, Thailand, and Saudi Arabia). And these factors have not stopped Western multinationals from succeeding in China in car manufacturing, fast-moving consumer goods, and even sectors where culture plays a key role, such as beer, coffee shops, fast food, and the film industry. There are deeper reasons behind the systematic failure of Western digital firms in China. (The term “digital firms” refers to those companies that from their inception have focused on digital services enabled by the internet and related technologies, including mobile. It does not include traditional IT firms that rely on sales of hardware or software as their main source of revenue.)

And yet Western digital firms haven’t given up on trying to tap into China’s rapidly growing market. Google is reentering China by setting up new offices and an AI center, signing new deals with retail heavyweights JD.com and Tencent, rolling out new products (including a controversial local mobile search app that would strictly censor results), and investing in promising local startups. Airbnb, LinkedIn, and WeWork are also expanding their presences in China. Amazon is expanding its China business in cross border e-commerce, Amazon Prime, and Amazon Web Services.

The question is, will this be sufficient? What could these firms do differently this time to succeed?

“Death by a Thousand Cuts”

Based on a comprehensive five-year study, my new research paper, published in the Academy of Management Discoveries this year, systematically identifies the reasons behind the failures of major Western digital firms in China. This study uses two rounds of interviewing to identify what the Nobel laureate Daniel Kahneman describes as the “inside view” and the “outside view” of the phenomenon.

First, interviews were conducted with 40 senior business executives from six leading Western digital firms (Google, Yahoo, eBay, Amazon, Groupon, and Uber) and their corresponding direct competitors in China (Baidu, Sohu, Taobao, JD.com, Meituan, and Didi). This was intended to identify the inside view of the phenomenon. The prevailing narrative emerging from these interviews points to a lack of strategic determination and patience by Western digital firms as the main cause of their failure. This is reflected in seven factors:

  • lack of a deep (enough) understanding of the Chinese market
  • poor management of relations with Chinese regulators and the government
  • ill-fated attempts to impose global business models unsuited to the Chinese market
  • failure to cope with the extremely fierce competition in China
  • failure to manage relations effectively with local business partners
  • imposing technological platforms developed for the U.S. market on China
  • overly centralized organizational structure’s leading to slow decision making

Second, 185 seasoned expert observers were interviewed in China to identify the outside view on the phenomenon. These interviews highlighted the failure by Western digital firms to acclimate to China’s business environment as the main cause of their failure. This was described in Chinese as Bujie diqi (不接地气), meaning these firms failed to “keep their feet firmly on the ground.” It led to a series of competitive disadvantages, thereby allowing Chinese digital firms to race ahead in the fight for market share. Specific factors identified included:

  • failure to cope with a very large number of local competitors
  • failure to cope with extremely aggressive and determined local competitors
  • underestimating the major differences between digital business and other industries
  • failure to develop and communicate business strategies effectively
  • ineffective innovation strategies
  • failure to fully embed operations in China

Despite the differences between the inside view and the outside view, these factors have converged in three clusters: (1) poor understanding of the business environment, (2) ineffective strategy making and communication, and (3) underperformance in operation and execution. The Western firms’ failures in China were not due to one specific factor, but rather to the cumulative effects of multiple factors over time. “It’s death by a thousand cuts!” remarked a former senior executive from eBay.

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To date, Western digital firms have failed to capitalize on their perceived competitive advantage in China. They have failed to understand the complex business environment there, adapt their strategies and business models to the Chinese market, and develop new technologies and services to cater to the preferences of Chinese users. They have underestimated the strength and resilience of Chinese competitors and the enormous challenges involved when trying to dominate the largest digital market in the world. Their successes in other international markets have given them a false sense of safety and invincibility in their perceived competitive advantages.

While Western multinationals from other sectors benefit from advanced technologies, established product lines, and global supply chains that may take Chinese firms years of investment to catch up to, digital firms do not. They operate in an environment where the barriers to entry are relatively low and the focus of competition is on product and business model innovations and service delivery, rather than the most advanced technologies.

Can They Get Back in the Game?

Are Western digital firms forever doomed to fail in the Chinese market? The answer, of course, is no. The problems are not insurmountable, but the size and dynamism of the Chinese digital market suggest that any solutions that focus only on those problems are unlikely to be sufficient. The competitive advantages that have served Western digital firms well in other countries need to be recalibrated for the Chinese market. Three lessons here are particularly important.

1. Doing everything right is not enough. China has huge geographical disparities and socioeconomic variations across its regions. Its institutional environment and market preferences evolve rapidly and sometimes even erratically. Dominating and maintaining dominance in China poses unique challenges. Unlike other digital markets, doing everything right in China is often not enough to guarantee success, due to strong competition.

Take Uber. Before entering China, Uber senior leaders did their homework carefully to avoid the mistakes that had derailed many other (digital and not) multinational firms. Uber set up a highly autonomous Chinese subsidiary; partnered with China’s largest search engine, Baidu; committed significant capital and paid out $2 billion in subsidies to win market share; and offered services specially tailored to the Chinese market. Uber’s founder and CEO at the time, Travis Kalanick, took a hands-on role and spent over 20% of his time in China.

Despite all this, Uber wound up retreating from the Chinese market. What went wrong? It is hard to pinpoint any individual failure on Uber’s part. One notable challenge, however, is that for the first time, Uber met a genuine competitor: Didi Chuxing, which was more determined, had a larger cash reserve, and focused exclusively on China at that time. Uber sold its operation to Didi Chuxing. This case suggests that simply addressing each of the known mistakes made by other multinationals in the past is often not enough to guarantee success in the future. A more holistic approach is needed.

2. Accumulating incremental advantages in the “winner takes all” digital market. While radical innovations in products, business models, and technologies capture the most headlines, due to their importance to the long-term competitiveness of digital firms, what’s often overlooked is that accumulating incremental advantages across different areas of competition over time is also essential for survival.

The digital market is significantly different from other market sectors. Western digital firms had only a short history to establish any inimitable advantages. The focus of digital firms on product and business model innovations, and the relatively low technological entry barriers, allowed a very large number of Chinese competitors to appear. As a culture market, China favors native firms, as they are often better at understanding users and the business environment. Local firms are also more adept at managing relationships with regulatory bodies and thereby influencing and anticipating regulatory changes. The technologies and intellectual property that Western digital firms rely on are often easily imitated and then adapted to local tastes in the digital space.

In the “winner takes all” digital market, where usually only one or two players survive in each market niche, incremental advantages can snowball and have increasing returns to scale. The cumulative effect from any such advantage can become what separates winners from losers.

3. Experimental approaches to strategy and innovation. The enormous uncertainties in the rapidly evolving digital markets call for experimental approaches to both strategy and innovation. New ideas can become obsolete before they are fully implemented, requiring frequent recalibration of the course and destination of business strategy. Innovation through experimentation and improvisation is vital for success. But such experimental approaches are only feasible with strong autonomy by local management, local product and technical teams, and, in many cases, business models tailor-made for the Chinese market.

Winning in the New Digital Economy

Western digital businesses have not given up on China. However, to get back in the game and win, Western digital firms need to bring forward genuine competitive advantages. In addition to customizing their products, platforms, and business models for China, and empowering local management teams to compete for market share, these firms must also learn from Chinese digital firms how to integrate online and offline operations and build new partnerships and ecosystems.

As the digital market in China continues to expand rapidly, a growing number of digital startups have joined the ranks of the largest unicorns in the world. And as Chinese digital firms grow larger and more confident, they are actively pursuing new opportunities in other international markets — India, Southeast Asia, Africa, Europe, and even the U.S. So the clashes between Western and Chinese digital firms will continue to escalate both in China and internationally.

Beyond digital businesses, similar patterns have been observed in cloud services, mobile communications, fintech, and several non-digital sectors (such as solar energy, electric cars, and high-speed trains). Further, new battle lines have been drawn between Western and Chinese firms for artificial intelligence, driverless vehicles, and industries where Western multinationals have traditionally held major technological advantages (say, pharmaceuticals). The ongoing trade dispute between the U.S. and China is likely to further complicate the situation.

To capture a slice of the Chinese market, Western business leaders must recognize and understand the issues highlighted here. These lessons are relevant to more than Western digital businesses in China; they can also shed light on the future competition between Western and Chinese multinationals in other sectors and other international markets.

Categories: Blogs

The Best Way for Netflix to Keep Growing

Harvard business - Tue, 08/14/2018 - 06:05
jakob owens/unsplash

Netflix has a lot to gain by becoming a multisided platform.

Currently, Netflix is in the business of buying or making content, which it sells consumers access to at prices and on terms it fully controls (a monthly subscription). That’s unlike a platform such as YouTube, which enables myriad content providers to sell directly to users at prices they control, with limited intervention by YouTube other than the enforcement of some content guidelines.

Netflix’s model has been undeniably successful to date. However, fighting the blockbuster battle over content acquisition and creation is becoming ever more expensive, and it involves an increasing number of combatants (including Amazon, Apple, Disney, and Google). All these companies already have or will have digital download and streaming services. Furthermore, the growth of Netflix’s subscriber base is slowing down. The company lost more than 15% of its stock market valuation over the past month after its growth numbers disappointed investors.

In this context, it seems obvious that Netflix can and should become a platform, using one of the models described in my 2017 HBR article with Liz Altman. Why? Netflix’s big subscriber base (130 million worldwide) and content-delivery infrastructure are potentially very attractive to many third parties. In addition to video content providers, these third parties include marketers and the developers of cloud gaming or other services. How would Netflix become a platform? Simply by allowing these third parties to sell their products or services within Netflix’s service but outside Netflix’s subscription, on terms controlled by the third parties.

Becoming a multisided platform in this way would allow Netflix to tap a different dimension of growth: selling more stuff to the same subscribers. And the beauty of the platform model is that Netflix can grow without having to buy or produce the new stuff itself. It just has to attract third parties to develop and sell the content, and then it can take (as is common) a share of the revenue or a transaction fee. Moreover, third parties could experiment with new forms of content, which could be very valuable to Netflix’s content acquisition and production efforts. In this way, Netflix would follow in Amazon’s footsteps. That company started as a pure retailer of products it bought from sellers and sold in its own name, before adding a marketplace where customers purchased directly from third-party sellers. Netflix can aim to become a similarly powerful reseller-platform hybrid, except it will have digital content rather than (for the most part) physical products.

Why has Netflix not started on this path already? CEO Reed Hastings and his team must have thought about it. There are only two plausible explanations I can think of: (1) resource allocation and (2) quality control. I don’t find either one very convincing.

The resource-allocation argument would be that, given the resources (financial and human) needed to develop and acquire high-quality content, Netflix simply may not have the bandwidth right now to look at platform opportunities. Well, I’d argue it should create the necessary bandwidth, given the huge potential payoff and the danger of getting stuck in the war over content acquisition and creation. Being a platform for content is much more scalable, valuable, and defensible than being just a content creator and reseller.

The quality-control argument would run as follows. Becoming a platform — allowing third parties to sell content whose quality is not fully controlled by Netflix, and on terms not completely determined by Netflix — runs the risk of letting low-quality content slip through the cracks and alienating customers, who would then hold Netflix responsible. That is a valid concern, but there are many ways in which Netflix can mitigate this risk — as other companies have done when turning their products into platforms (examples include Amazon, Intuit, and Salesforce). I am not arguing that Netflix should move to an open platform model like YouTube’s, where everyone and their cat can post video content. Rather, Netflix can turn its service into a carefully curated platform, with relatively tight governance rules that can be relaxed over time.

My bottom line is that Netflix has little to lose and a lot to gain by shifting from being an aggregator of content under one subscription, to a hybrid aggregator platform on which various content providers sell directly, and at prices of their choosing, to users. Becoming a platform is usually about fear (of competitors) or greed (for new sources of growth and revenues). For Netflix, it should be about both.

Categories: Blogs

Multiplying the Effective Intelligence of Your Organization

Greatleaders hipbydan - Tue, 08/14/2018 - 06:00

Guest post from Robert (Dusty) Staub: 

“Perhaps the only sustainable competitive advantage is increasing your ability to learn faster than your competition.”
 - Arie de Geus, former head of Strategic Planning, Shell Oil Company

Are you getting the best results from the people–the embedded collective intelligence–in your organization? Do you feel that there is something missing in overall performance, or your team and/or enterprise could achieve even more? Most senior leaders with whom I have worked would answer, “We can achieve more and be better if only we could work smarter and more effectively together.” The name of the game today is figuring out how to multiply the Effective Intelligence (E.I.) of your organization. Here is where you can gain a great competitive edge that is sustainable and also leads to more innovative and effective ways of getting things done.
Research and experience demonstrate that the only difference between so-so organizations and high performing ones is the quality of the teamwork and the collaborative networks that exist within an organization. This makes sense if you understand brain physiology. It is not the absolute number of neurons that determines intelligence; it is the number of dendritic connections between neurons that determines overall processing power and intelligence. The greater the number of connections, the higher the level of collaborative networking, which equals greater intellectual capacity to problem-solve and create solutions. The term I have coined to describe this capacity for teams and organizations is “Effective Intelligence.” What great leadership does is to use presence (demeanor an modeling), practices and processes to multiply E.I., thereby increasing the performance and capabilities of a team, a department or an entire organization.

Is your enterprise actually engaging and making the full use of the collective intelligence embedded in the human system (people, team work, relationships) in your organization? Is your organization realizing its potential and performing at its best? Are you multiplying the E.I. of your organization by how you are leading and encouraging the engagement of individuals, teams and departments? Perhaps you share the opinion one CEO gave me recently, “There is truly room for improvement; I just know, good as we are now, that we can do better than we have been doing to date.”

If you see room for improvement, then how can you increase the E.I. of your team, your department and your organization? The answers will sound simple yet applying the insights to multiply effective intelligence will take all three forms of critical leadership capacity: guts, heart and head. It will require that you focus your attention and processes on the following dynamic development as outlined by Wayne Gerber and Staub in Dynamic Focus: Creating Significance and Breaking the Spells of Limitation. Please consider the question at the end of each of the eight process steps below.

Increasing the Effective Intelligence (E.I.) of Your Team and Organization:

1. Expanding perspectives. This means seeing beyond the obvious and challenging conventional thinking. The status quo and old ways of thinking are the enemy of higher order processing, innovation and increased performance. “Good enough” is the death of being even better, let alone great. What are you doing in your leadership and in your workplace to help expand the thinking and to promote a wider strategic picture or way of looking at the business and how work gets done?

2. Clarifying and focusing attention on your core Purpose, your WHY. Astute leaders know that when the people in an enterprise know WHY it exists–in other words, the purpose and mission it serves beyond the usual answer of “making money”–that they perform better and expend more discretionary effort. They are more engaged. (See Simon Sinek’s Start with Why TED Talk.) Do the people in your organization know the fundamental WHY of the business? Do you use that to rally them and challenge them to help everyone step up to more active learning, interactions, collaboration and teamwork?

3. Consciously creating psychological safety in your organization. Google research on the core factor fostering high performance teamwork finds that a sense of “psychological safety” is key. \ This means people feel “safe” offering different opinions, ideas, suggestions and, as outlined in the research and findings in Jim Collins’ book Good to Great, engaging in “vigorous intellectual debate.” If people feel they will be punished, belittled or put down, if they do not feel it is safe to speak up, they won’t and you are then minimizing the E.I. instead of increasing it. How well are you creating a sense of psychological safety for your employees, teams and those around you? Do you have healthy, positive, vigorous intellectual debate around best practices, new ideas and better ways of moving the enterprise forward?

4. Leveraging strengths, focusing on what there is to celebrate. Research in the fields of psychology and sociology have revealed that human systems (from individuals to groups) get stronger by focusing on, leveraging and building upon strengths rather than by fixating on what is wrong. Yet many executives still manage by “exception,” ignoring what is right and working well and spending supervisory time on problems and issues. Are you focusing on strengths, on what is right and working well? What strengths in your people, teams and organization have you been celebrating? How have you been building on or leveraging the top 2 or 3 of these strengths?

5. Failing forward. This means giving reward and recognition for a specific category of mistakes instead of punishing for or treating all mistakes as the same, as if they are all “bad.” Mary Kay Ash of Mary Kay Cosmetics and Soichiro Honda, founder of Honda Motor Company, both subscribed to and taught “failing forward” as a way to promote innovation and growth within their organizations. Most executives and employees do the exact opposite. By treating all mistakes the same and seeing them as “wrong,” the E.I. of an enterprise is diminished instead of increased. Do you know which kinds of mistakes should be rewarded, or do you treat them all the same? Are you using the practice of “failing forward” in your organization?

6. Using Power Questions. Power questions enhance learning and improve performance. A great question is often more valuable than a good answer. The greatest danger you have as an executive is to be blindsided by issues or to miss key opportunities in your organization. One of the ways to minimize this is to make a practice of asking “power questions” – namely, Pareto- based questions that focus on quickly getting to the core or root cause of an issue or opportunity. For example a poor question is asking, “Is there anything here we need to improve?” A better question is “What do we need to improve?” A power question is, “What is the one thing we could do differently here that would make the biggest positive difference?” Asking power questions and teaching those around you to ask them will be a key part of increasing the E.I. of your enterprise. How are you and those in your organization doing with regard to asking power questions of each other, of customers, of key suppliers?

7. Knowing the difference between Symptoms and Root Causes. When you and those in your organization know how to recognize symptoms and use them to focus on root causes, you are helping to multiply the E.I. in your enterprise. For example the following should all be considered symptoms: poor teamwork, low employee engagement, quality issues, unhealthy conflict, customer complaints, lower market share and declining sales numbers. Do you know what the root causes of those kinds of symptoms are? For example, the symptom of low employee engagement has as a root cause a failure in management practices and leadership behaviors. The research shows that people quit supervisors as opposed to quitting companies. How a supervisor treats, talks to, engages, coaches, corrects, supports and otherwise makes an employee feel about the supervisor’s valuation of him or her is a huge determinant of how engaged and motivated that employee is. How effectively do you and your management focus on addressing root causes versus chasing symptoms?

8. Identifying and Utilizing Essential Behaviors as Core Leadership Practices. To address critical operational as well as human systems issues, make the best use of the seven practices outlined above. You will need to identify which essential behaviors you want to train for, expect, model and reinforce in all levels of your enterprise. Do you have a set of 4 to 6 essential behaviors that you know are clearly outlined, coached for and reinforced from front line supervisors up to the CEO? If you are like the vast majority of organizations and leadership teams, the answer to that will be a resounding no. If you want to really increase the effective intelligence of your enterprise then you will need to have an agreed upon core set of leadership practices, or essential behaviors, that are being used consistently throughout all levels. Do you know which essential behaviors will give you the biggest return on your investment of time, energy and supervisory development? Examples of essential behaviors include: active listening, using power questions, knowing how to design and engage in courageous conversations and making use of systemic-accountability. What are you doing to ensure there is consistent, effective modeling of powerful leadership behaviors? Are you living and modeling those behaviors with your teams and employees?

If you take the eight suggestions above to heart, and if you are working on engaging all of them, you will multiply the effective intelligence of your organization and can expect improved productivity, greater innovation, superior employee engagement, high performing teams, less waste, better quality, more loyal customers, better talent retention and higher profitability. The only barriers are either not following through or a lack of experienced guidance. Are you willing to build a learning-based, higher performing enterprise by multiplying the effective intelligence of your human system? What are you waiting for?

 Robert “Dusty” Staub is an international speaker, best-selling author, and the CEO of Staub Leadership International, a business consulting company that trains executives and teams in creating high-performance outcomes. Staub is the best-selling author of The Heart of Leadership, The 7 Acts of Courage, and Courage in the Valley of Death. In his experienced speaking career, Staub has motivated audiences with his insightful and heartfelt keynote presentations on leadership, excellence, change management, conflict resolution, organizational and team communication, and the relationship between intent, behavior, and results.
Categories: Blogs

4 Reasons Why Organizations Should Focus on Performance

Hr Bartender - Tue, 08/14/2018 - 02:57

Some of you might be thinking, doesn’t every organization focus on performance? Well, I think the answer to that is … maybe.

I know in my career, I’ve worked for companies that spent a huge amount of time focused on goals, only to abandon all of them for some shiny new program. I’ve also worked in situations where achieving the result was the most important thing … and it didn’t matter who was hurt along the way. If you haven’t worked for an organization where this was the culture, it’s possible that a manager or just a department adopted that philosophy.

When I think about it, performance involves both the results and the methods used to achieve those results. And that’s why organizations should focus on performance, because it’s just as much about the pre- and the post- as it is the actions itself. There are four reasons for organizations to focus their efforts on performance:

  1. It creates a way for organizations, departments, and individuals to plan activities. I’m intentionally not saying goals here because performance doesn’t always have a direct goal attached to it. That being said, our performance of small tasks can have a huge impact on goals. It requires some thought and intention at every level.
  1. By focusing on performance, everyone stays on track. This ties a little bit into reason number one above. Regardless of the task or activity we’re asked to perform, we need to do it well. And we should want to do it to the best of our ability. The company is focused on hiring candidates who can perform, training them to perform at their best.
  1. Performance allows for the logical flow of information to stakeholders. When companies focus on performance, then that’s what they talk about during meetings, feedback sessions, and coaching conversations.
  1. It permits organizations to gauge their progress. This is where I think goals and benchmarks might factor into the conversation. When companies are focused on performance, they will want to have some sense of how well they’re performing. This can be reported to stakeholders (see reason #3) and possibly, prompt new direction (see #2).

The business world is very complex and we all have a tremendous amount of data and information to curate each day. By staying focused on performance … from an individual, team, and organizational perspective, it can help us create a filtering system. Do I need this information to perform better? Would this program help the team perform faster? Could this new process allow the organization to perform at the same level of quality while reducing costs? You see the point.

But make no mistake, focusing on performance is hard. If it were easy, everyone would be doing it. It’s easy to get distracted. And when we get too distracted, it’s a challenge to get it back on track. It can be done though, with some honest conversation and a tremendous amount of cultural willpower.

Image captured by Sharlyn Lauby while exploring the Wynwood Art District in Miami, FL

The post 4 Reasons Why Organizations Should Focus on Performance appeared first on hr bartender.

Categories: Blogs

The Simple Question That Can Make or Break a Startup

Harvard business - Mon, 08/13/2018 - 10:00
Jonathan Knowles/Getty Images

There’s an unassuming restaurant in Dallas called Chop House Burger, home to handspun milkshakes, truffle parmesan french fries, and six innovative burgers. It’s an eight-year-old restaurant in an industry where 80% of new entrants fail in the first five years. And stitched into its origin story is a clue to why some products (and businesses) succeed in the market while most wither and die.

The burger place spun out of a The Dallas Chop House, a high-end steakhouse two blocks away. The Chop House was known for its ribeye, filet mignon, and flat iron steaks, dry-aged in the restaurant with Himalayan sea salt. In an effort to diversify their menu, the owners also offered a gourmet burger. Despite how good the steaks were, the burger became one of the most popular items on the menu. So the owners decided to build a restaurant around it.

Most of us aren’t in the restaurant industry. We don’t all have an established business to test ideas in. Yet the value of establishing demand before you launch the business is just as important for us, whether we’re launching a new company or simply a new product.

In February, venture capitalist database CB Insights conducted an extensive review examining what contributes to the failure of new businesses. After analyzing 101 startup post-mortems, the reviewers found that 42% suffered from a lack of demand for the product or service being offered. They used a harsh phrase to describe this cause of failure: “no market need.”

This one flaw harmed significantly more companies than well-known startup challenges such as cash flow (29%), competition (19%), and poor timing (13%), to name a few.

The findings raise the question: How can entrepreneurs or new product developers test their ideas before investing the significant time and capital required to actually bring them to life? How can we spot the ideas that are likely to succeed instead of wasting our efforts on those that are prone to failure?

Here are three strategies worth trying:

Look for successful competitors. When it comes to establishing demand, thriving competitors are a good sign, not the red flag many entrepreneurs view them to be. Being the first mover in a space can produce situational advantages, but showing up late gives you the benefit of added perspective.

Today, if you were to release a new photo editing software, beer, or car rental service, you could be confident your offering would be understood and in-demand at some level. Yes, you would still have to get the attention of your target customers. You would also have to differentiate yourself from competitors. And there would still be plenty of ways your product or business could ultimately fail. But you would at least be in charted territory.

The food delivery industry contains terrific examples of established companies following the demand validated by early movers, such as Seamless and Grubhub. To better leverage its foodie customer base, Yelp purchased Eat24. Uber applied its successful driver model to meals and created UberEats, which is outgrowing the ride sharing service in some markets. And payment platform Square acquired Caviar, giving restaurant owners a simple way to accept credit cards and deliver meals.

Getting outcompeted is the obvious fear associated with entering a space that’s already home to successful companies. It’s a real risk. In the food delivery space, companies differentiated by finding new restaurants to partner with, expanding to new locations, and offering distinct pricing models. But those opportunities won’t exist in every industry.

Ultimately, it’s worth considering the numbers. In the CB Insights study, only 19% of the analyzed postmortems claimed their startup had been outcompeted, less than half the number that blamed failure on a lack of demand.

Check for search traffic. When people are searching for a product to solve a problem they’re facing, they type what they’re looking for into Google. Through keyword research, entrepreneurs can learn what people are searching for and use the findings to gauge demand for a product or service idea.

According to the keyword research tool Ahrefs, 27,000 people per month are searching for “Photoshop alternatives.” 4,000 are searching for “automatic lawn mower.” And 100 are searching for “truckers’ bookkeeping service.”

Each of these terms has similar variations that increase the total number of monthly searches. You could also gauge potential demand by looking for broader searches that don’t focus on a specific solution but prove the existence of a problem you can solve.

For the examples above, “How to edit photos,” “Don’t have time to mow my lawn,” or “Bookkeeping guidelines for truckers” could be searches worth exploring.

There’s no standardized amount of search volume you can use to validate healthy demand. You will have to interpret the data in the context of your specific industry and business goals. But confirming that people are searching for a product or service like yours is a good sign, and through Google AdWords campaigns or SEO, you can work to get in front of these very people if you decide to launch the idea.

Test your marketing promise. People don’t buy products. They buy promises. Generally speaking, customers don’t truly know what it’s like to own a product until after they’ve purchased it. They don’t spend money because of any realized benefits. They’re paying for the benefits promised in the sales copy and testimonials.

This is a crucial insight for anyone looking to test a new product or service because it suggests that you don’t need a finished product to validate demand for an idea.

You can create the marketing copy for your hypothetical offering and test it through surveys or interviews with targeted prospects. Of course, the most accurate test of demand will involve customers getting out their credit cards. Pre-selling models such as Kickstarter are one way to do that.

There’s no perfect system to pre-validate demand for a product or service, but that doesn’t mean you shouldn’t do your due diligence. Business failures are costly. They can result in lost capital, wasted time, and damaged confidence. Some of the challenges uncovered by the CB Insights study will be hard to predict — such as timing, whether you’ve hired the right people, and if you’ll make necessary pivots after launching the business. But demand is one key ingredient you can pre-validate, at least partially.

Had they done a better job of gauging demand in advance, 42% of the companies in the CB Insights study might have chosen to pursue more reliable ideas, which could have better prepared them to avoid business failure and reach success sooner.

After all, the fewer detours we take, the faster we arrive at our goals.

Categories: Blogs

Build Self-Awareness with Help from Your Team

Harvard business - Mon, 08/13/2018 - 09:00
Doug Perrine/Nature Picture Library/Getty Images

There are lots of compelling reasons to build a better team. Great teams deliver stronger results, faster. They’re more innovative. They challenge you to learn more quickly and to be at your best.  And, let’s face it — they’re simply more fun to work with.

Recently, I found a new reason to build a better team — to address the fact that most of us are surprisingly lacking in self-awareness. Researcher and author Tasha Eurich uncovered this disturbing statistic through her multi-year study on the topic of self-awareness: 95% of us think we are quite self-aware, but only about 10-15% of us actually are.

You and Your Team Series Emotional Intelligence

So how can better teams help with our own self-awareness? Here’s the important connection: We need feedback to help match our internal view of ourselves with the external view. And on the best teams, not only are teammates willing to provide feedback to each other, they are required to do so.

On high-performing teams, peers feel accountable for each other’s success, and willingly provide both generous support and candid feedback to help each team member be at their best.

Through years of research on teamwork, I have uncovered four distinct types of teams, from the worst of the worst, “Saboteur Teams,” to the highest-performing, or “Loyalist Teams.” While distrust, politics, infighting, and gossip are hallmarks of Saboteur Teams (or “team hell” ), trust, candor, feedback, shared goals, and joint accountability constitute Loyalist Team behavior.  In fact, compared to Saboteur Teams, Loyalist Team members are:

  • 292 times more likely to spend time debating, discussing problems, and making decisions
  • 125 times more likely to address unacceptable team behaviors promptly
  • 106 times more likely to give each other tough feedback
  • 40 times less likely to have “undiscussables” that the team can’t talk openly about

On Loyalist teams, team members talk honestly and openly about team and individual team members’ strengths and challenges. And, because team members extend trust to each other, they assume positive intent when the tougher conversations happen. Therefore, authentic and candid feedback is more easily heard and valued. It feels okay to be imperfect or to experience setbacks. It is less scary to be vulnerable.

What if you could get honest insights and feedback from coworkers who are truly committed to your success and get to see you in action all the time, on both your best and worst days? You can, and you will, if you build a Loyalist Team. Think of how much faster you could address the unintended consequences of your actions if you were surrounded by people motivated to give you useful feedback.

If you want candid feedback, trust, and support from your teammates, try these five tips:

  1. Assume positive intent. Give your teammates the benefit of the doubt. Assume they are providing feedback not to judge you but to make you better.
  2. Talk to your teammates, not about them. You can’t solve problems with gossip. Venting without follow-up action ensures that you are building cliques and solidifying rifts. It takes courage, but talking directly and respectfully with teammates when something goes wrong can solve many misunderstandings without creating drama or bringing others into it.
  3. Care about your teammates’ success. Start by taking an interest in your teammates’ success. Ask questions about their concerns, know what their goals are, help where you can, and be a good listener and collaborator. You can’t be a Loyalist teammate if you don’t know what drives others’ success.
  4. Push your teammates to do their best work and vice versa. On Loyalist Teams, team members challenge each other to reach their goals. Loyalists don’t spend energy watching their own backs, so they take risks and reach higher. Start by asking your teammates to challenge you. Bring them ideas and ask for input. Ask for feedback on your plans. Embrace the idea that your teammates make you better.
  5. Ask for personal feedback. Before offering feedback, ask for it first. Ask your teammates what you could do to better support their success. Ask peers for suggestions on one behavior you could work on to become a better teammate. Give permission for teammates to share feedback by asking for it regularly and listening openly. Thank others for giving you feedback.

To build greater self-awareness, work to create a team of Loyalists around you, people who trust you, support you, and challenge you to be your best. Surround yourself with people who will speak their truth, even when it’s hard. And then listen. When you do, you will see an amazingly positive impact — on you, on them, and on the overall success of your team.

Categories: Blogs

What’s the Purpose of Companies in the Age of AI?

Harvard business - Mon, 08/13/2018 - 08:00
Tintan/Getty Images

Recent advances in artificial intelligence (AI) and computer technology are causing us to think again about some really basic questions: what is a firm?  What can firms do better than markets?  And what are the distinctive qualities of firms in a world of smart contracts and AI?

While there has been a lot of discussion about “what’s left for humans?” as AI improves at exponential rates — the customary answer is that humans need to focus on the things they are uniquely good at, such as creativity, intuition, and personal empathy — I think we now have to ask, “what’s left for firms?”

In many ways this is an old question, because it takes us back to the arguments of Nobel Laureates Ronald Coase and Oliver Williamson that firms exist to coordinate complex forms of economic activity in an efficient way.  If computer technology has the capacity to simplify and streamline transaction costs, more and more work can be done through these smart-contract arrangements, making traditional human-managed firms obsolete.  For example, when you say to Alexa “order more dog food,” a chain of activities is initiated that leads to the delivery of a fresh supply of Kibble 24 hours later, with little or no human intervention. This work is coordinated by a single firm, Amazon, but it often involves third parties (makers of dog food, delivery companies) whose systems interact seamlessly with Amazon’s.

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But is this coordination logic, this ability to internalize transactions to make them more efficient, really the raison d’etre of firms? I would argue that it is just one among many reasons that firms exist. And as computer technology simplifies and reduces transaction costs further, it is these other things that firms do uniquely well that will come more to the forefront. Here are four areas where firms excel.

1. Firms create value by managing tensions between competing priorities. 

In today’s parlance, firms have to exploit their established sources of advantage (to make profits today) while also exploring for new sources of advantage (to ensure their long-term viability).  However, getting the right balance between these two sets of activities is tricky because each one is to a large degree self-reinforcing. Hence the notion of organizational ambidexterity — the capacity to balance exploitation and exploration.

Artificial intelligence is evidently helping many firms to exploit their existing sources of advantage — whether through process automation, improved problem-solving or quality assurance.  Artificial intelligence can also be useful in exploring new sources of advantage: in the famous case of AlphaGo, the winning “strategy” was one that no human player had ever come up with; and computers are increasingly writing new musical scores and painting Picasso-like landscapes.

But AI is not helpful in managing the tension between these activities, i.e. knowing when to do more of one or the other.  Such choices require careful judgment — weighing up qualitative and quantitative factors, being sensitive to context, or bringing emotional or intuitive factors into play. These are the capabilities that lie at the heart of organizational ambidexterity and I don’t believe AI can help us with them at all right now. IBM’s recently-announced Project Debater is a case in point: it showed just how far AI has come in terms of constructing and articulating a point of view, but equally how much better humans are at balancing different points of view.

2. Firms create value by taking a long-term perspective.

As a variant of the first point, firms don’t just manage trade-offs between exploitation and exploration on a day to day basis, they also manage trade-offs over time. My former colleagues Sumantra Ghoshal and Peter Moran wrote a landmark paper arguing that, unlike markets, firms deliberately take resources away from their short-term best use, in order to give themselves the chance to create even more value over the long term.  This “one step back, two steps forward” logic manifests itself in many ways — risky R&D projects, pursuing sustainability goals, paying above-market wages to improve loyalty, and so on. We actually take it for granted that firms will do many of these things, but again they involve judgments that AI is ill equipped to help us with.  AI can devise seemingly-cunning strategies that look prescient (remember AlphaGo) but only when the rules of the game are pre-determined and stable.

An example:  the “Innovator’s Dilemma” is that by the time it’s clear an invasive technology is going to disrupt an incumbent firm’s business model, it’s too late to respond effectively. The incumbent therefore needs to invest in the invasive technology before it is definitively needed. Successful firms, in other words, need to be prepared to commit to new technologies in periods of ambiguity, and to have a “willingness to be misunderstood,” in Jeff Bezos’s terms.  This isn’t an easy concept for AI to get used to.

3. Firms create value through purpose — a moral or spiritual call to action.

There is a second dimension to long-term thinking, and that is its impact on individual and team motivation. We typically use the term purpose here, to describe what Ratan Tata calls a “moral or spiritual call to action” that leads people to put in discretionary effort — to work long hours, and to bring their passion and creativity to the workplace.

This notion that a firm has a social quality — a purpose or identity — that goes beyond its economic raison d’etre is well established in the literature, from March and Simon through to Kogut and Zander.  But it still arouses suspicion among those who think of the firm as a nexus of contracts, and who believe that people are motivated largely through extrinsic rewards.

My view is that you just need to look at charities, open source software movements, and many other not-for-profit organizations to realize that many people actually work harder when money is not involved. And it is the capacity of a leader to articulate a sense of purpose, in a way that creates emotional resonance with followers, that is uniquely human.

Successful firms, in other words, institutionalize a sense of identity and purpose that attracts employees and customers. Ironically, even though blockchain technology is — by definition — about building a system that cannot be hacked, or misused by a few opportunists, people still prefer to put their faith in other people.

4. Firms create value by nurturing “unreasonable” behavior.

There are many famous cases of mavericks who succeeded by challenging the rules, such as Steve Jobs, Elon Musk, and Richard Branson. With apologies to George Bernard Shaw, I think of these people as unreasonable — they seek to adapt the world to their view, rather than learn to fit in. And if we want to see progress, to move beyond what is already known and proven, we need more of these types of people in our firms.

Unreasonableness is antithetical to the world of AI. Computers work either through sophisticated algorithms or by inference from prior data, and in both cases the capacity to make an entirely out-of-the-box leap doesn’t exist. Consider the case of investment management, where robo advisors are not just making trades, they are also providing investment advice to investors, and at a fraction of the cost of human financial advisors. But as the Financial Times said last year, “when it comes to investing, human stupidity beats AI.”  In other words, if you want to beat the market, you need to be a contrarian — you need to make investments that go against the perceived wisdom at the time, and you need to accept the risk that your judgment or your timing might be wrong.  Both qualities that — at the moment — are distinctively human.

So one of the distinctive qualities of firms is that they nurture this type of unreasonable behavior.  Of course, many firms do their best to drive out variance, by using tight control systems and punishing failure. My argument is that as AI becomes more influential, though the automation of basic activities and simple contracts, it becomes even more important for firms to push in the other direction — to nurture unorthodox thinking, encourage experimentation, and tolerate failure.

In a recent Fast Company article, Vitalik Buterin described how all the elements of Uber’s ride-sharing service could be provided through Ethereum-based applications that worked seamlessly with one another:  “the whole process is basically as before, but without the middleman [Uber].”  This is may be true, but it doesn’t necessarily follow that a computer-mediated service is the better option.

For example, in 2016 a distributed autonomous organization (DAO) was launched on Ethereum. This idea was that it would run without human intervention, using pre-established rules and blockchain technology to operate seamlessly. But it had a small technical flaw, which allowed an un-named user to siphon of $55 million of the money raised in a matter of days.   Faced with the meltdown of their entire creation, the founding fathers of Ethereum intervened, creating a so-called hard fork in the blockchain that allowed investors to get their money back, and for the development of Ethereum applications to continue.

No matter how powerful the technology, sometimes a little human judgment is necessary to keep things moving in the right direction. 

Categories: Blogs

There’s Only One Way to Break into China’s Crowded Retail Market

Harvard business - Mon, 08/13/2018 - 07:00
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China’s two retailing powerhouses, online commerce pioneer Alibaba and social media-gaming pioneer Tencent, have systematically established a duopoly of record proportions in record time. Combined, they have spent more than $20 billion in the past 12 months alone to change the way people in China shop. (The precise value of their investments cannot be determined, given that many of them are undisclosed or private deals. This figure, along with some others in this article, are drawn from a Bain analysis.)

It started when online retailer Alibaba made the seemingly counterintuitive expansion into the brick-and-mortar world. To do this, they invested heavily in everything from Lianhua supermarkets to Intime department stores to electronics retailer Suning. Alibaba is now working to connect China’s millions of mom-and-pop stores with their internet-based distribution network, an initiative called Ling Shou Tong. It has opened futuristic Hema Xiansheng supermarkets, where consumers use the Alipay app to order groceries or prepared food for delivery to their homes—in many places, within 30 minutes.

Tencent took a different path to becoming China’s other retail leader. It began life as a social networking services company, and then added gaming, electronic payments, media content, cloud computing and devices. With successive investments into Chinese e-commerce company JD.com, it has become China’s No. 2 online retailer only four years after entering the retail industry. It invested in Yonghui, one of the fastest-growing Chinese grocery chains, and partnered with Carrefour and Walmart (which also owns 12% of JD.com). Among many other advances, with JD it created the fresh-food supermarket chain 7Fresh and invested in social commerce app Pinduoduo, a rising e-commerce company targeting the country’s booming smaller cities.

Alibaba and Tencent each is valued at around $500 billion on public markets, and both act as the SoftBank or Berkshire Hathaway of the new Chinese economy, investing in hundreds of companies at all stages. With their mounting arsenals of digital and physical assets, each has created its own closed-loop opportunity capture as much information as possible about a consumer — all day and night, at any browsing or buying moment. They gain invaluable data that fuels everything from hyper-targeted marketing to store locations to product assortment to pricing. Now, with a combined 80% market share of the world’s largest e-commerce market and stakes in  four of the top five hypermarket and supermarket chains in China, a fundamental question looms: Is there space for anyone else?

China’s retail landscape has room for companies to elbow their way in. However, in China there are two decisions that guide any retailer. The first one is choosing sides: Do you want to align with Alibaba or go with Tencent? For any retailer hoping to earn its slice of China’s expanding retail pie, at least for now, there is no alternative but to play alongside one team or the other — and there are pros and cons with each.

The second decision involves the partnership model. When partnering with China’s leaders, you can choose from three basic strategies: Do you want to use the big partners as a way to test and learn in this vast market or to enhance a core business or to fully integrate?

Let’s consider the first decision, whether to go with Alibaba or Tencent. Alibaba prefers to integrate all data, marketing, and logistics of acquired companies. For its part, Tencent allows each retailer the choice of connecting and upgrading its existing business activities. The next consideration: What types of data do you need to complement your own? Tencent will have more data on social media behavior while Alibaba will have more purchasing behavior data. Finally, what kind of expertise do you require? For example, unless the partnership is in conjunction with JD, Tencent does not really have core retail expertise in areas like supply chain and logistics.

The second decision — choosing a partnering strategy — depends on your starting point and your ultimate goals.

A test-and-learn strategy is most suitable if you do not already have a presence in China and would like a non-capital-intensive way to test the market — to learn what customers want and how well your products would sell, for example. No physical stores are required, and if the arrangement doesn’t go well it is relatively easy to exit the market. Costco, the U.S.-based store, took this approach, using Alibaba as a way to test its offerings and learn about China before fully committing. In 2014, it opened an online warehouse store on Tmall Global, Alibaba’s cross-border e-commerce channel. That move helped it take advantage of a special government program that allows retailers to sell specific goods (with favorable tax status) without being granted a license to operate in China. It also helped Costco gain widespread name recognition. By the following year, Costco had made it into the top 10 sellers on Tmall Global during the 11/11 Singles Day sales promotion.

In 2017, Costco obtained a license to open a flagship store on Tmall and began moving toward its goal of offering nearly 800 SKUs to Chinese consumers. These online steps paved the way for Costco to obtain permission to open physical stores, the first of which is expected to greet customers next June in Shanghai. Costco’s China stores will operate differently than its outlets elsewhere in the world. For example, they will rely on Alibaba’s data-heavy approach, using the past four years of consumer data gleaned on Tmall to determine product assortment and influence operations.

Say you already have a presence in China but want access to a leader’s data and technology without losing control of your brand or operations — and without giving up ownership control. In that case, consider another option: using the partnership to enhance your existing core business in China. That’s the approach taken by Walmart. Through a strategic partnership, it now uses Tencent’s technology to both upgrade Walmart’s in-store customer experience and help it learn more about its customers. Among the innovations: the WeChat Scan & Go mobile payment option, which gives the U.S. retailer access to consumption data from customers paying with the WeChat mobile app. It is data that will help Walmart build more sophisticated consumer profiles. However, there is a downside to this approach that will lead some retailers to take a pass. You have to share a lot more information with your chosen partner to make the partnership really work.

Finally, some companies opt to integrate fully with one or the other. It allows a retailer to gain full access to a leader’s user base, insights, data and technology. It also opens up opportunities to gain scale benefits or share processes such as purchasing. The drawback is that the leader becomes more involved in the operations of the store. Hou Yi, a former leader at JD Logistics, took this path after launching Hema Xiansheng, the online-to-offline fresh food supermarket concept that has since become the most tangible example of what is being referred to as “new retail.” Mr. Hou serves as Hema’s CEO and oversees the rapid expansion that ensued after Alibaba invested in and funded the company — and made Hema a part of its powerful ecosystem.

Now, even as they carve up China, both Alibaba and Tencent are poised for global expansion. When that happens, retailers on other continents may find themselves with the same set of options: choosing a partner and determining their own best partnership strategy if they hope to play in this high-speed game.

Categories: Blogs

When Will the U.S. Finally Act Boldly on Paid Family Leave?

Harvard business - Mon, 08/13/2018 - 06:05
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When I gave birth to my daughter over a year ago, I worked for an employer that provides no paid parental leave: the U.S. government. I was able to cobble together vacation and sick time with unpaid leave for four months. But I did not feel ready to go back to work, physically or emotionally, until my daughter was closer to seven months old — when she was sitting up, investigating new toys, eating pureed solids, and getting ready to scoot around her daycare room.

It is time for the U.S. to join the rest of the developed world in providing paid parental leave. Politicians on both sides of the aisle are finally starting to recognize that the current system places American parents in an impossible position. None of them would provide what I think is adequate: six months of paid leave per parent. (Six months is the recommendation of the president of the American Academy of Pediatrics as well.) But one proposal — the Family and Medical Insurance Leave (FAMILY) Act, a bill introduced last February whose primary sponsor was Senator Kirsten Gillibrand, Democrat of New York — would be a major step forward.

It would create a new office within the Social Security Administration to run a paid leave program funded by a new payroll tax. It would cover all family-related caregiving for up to 12 weeks, so almost all workers contributing to the program could eventually benefit from it. Today, more than 43 million Americans provide unpaid caregiving for elderly parents, ill spouses, new children, and other loved ones — often to the detriment of their household finances.

There are other legislative options on the table as well. A tax credit for employers offering at least two weeks paid family leave, first introduced by Senator Deb Fischer, Republican of Nebraska, was included in last year’s tax reform effort. But two weeks does not even cover the typical physical recovery time of labor and delivery, let alone the mental and emotional stress of caring for a weeks-old newborn. And because this is a “carrot approach,” as the senator describes it, and not a program that all families can rely on, the proposal does not go far enough.

Nor does the legislation introduced on August 2 by Senator Marco Rubio, Republican of Florida. Drawing from a policy developed by the Independent Women’s Forum (IWF), a think tank, the bill would allow only new parents to draw benefits early from the Social Security program and defer their retirement benefits accordingly. The proposal does not address other types of family-related caregiving.

The plan’s proponents say that their program would be budget-neutral and voluntary, giving individuals the choice to participate without placing additional burden on employers and those without children. They say it would offer an option to many families who currently lack one, wouldn’t force anybody to pay a tax, wouldn’t cause additional government bloat, and wouldn’t impose a regulatory mandate on employers. They say if a worker’s retirement is deferred — possibly by a couple years if a family has multiple children — it’s a trade-off the individual and her family will have to make.

But they are missing the point. When working parents lack support, our economy and society both suffer the consequences. We Americans all carry this burden, whether we have children or not. We should not be asking people to compromise their financial security later in life in order to take care of their children today.

Borrowing against your future retirement benefits is not a good financial deal for anyone, but it particularly hurts the working poor. “It’s a pretty small loan of effectively a few thousand bucks, and you’re paying interest on it for potentially 40 or more years,” according to Melissa Favreault, an Urban Institute researcher who has done financial modeling of the Social Security proposal.

What kind of person is going to take that option? “Somebody who’s desperate,” Favreault told me. “Somebody who doesn’t have any savings, who doesn’t have a wealthy family or a wealthy spouse. The person who is going to take this is a person who does not have many alternatives.” By placing the responsibility on the individual parent to borrow against their Social Security benefit for near-term financial support, we are telling new parents they are on their own.

Lauren Smith Brody, author of The Fifth Trimester, points out that policies set cultural norms. “We’re saying it’s your fault, and you have to pay for the choice you make to be a working person and also have a child,” she told me. “But whether or not you have children, you were once a child, and you benefited from your parents who brought you up and the economy that you lived in.”

We are losing the full economic potential of much of the population because our country still hasn’t figured out how to support working families. This hurts women the most because women bear the brunt of family caregiving. But this has has a wider impact as well. Researchers have found that paid family leave increases the number of hours that new mothers work. When more women stay at work through their childbearing years, wages rise across the board, household income grows, and the GDP is likely to increase. One recent study found that if the American female workforce participation had grown at the same pace as other developed countries like Norway, our economy would be $1.6 trillion larger. Equitable family leave policies that encourage male participation in caregiving can address this problem. We can’t afford to get this wrong.

This is an opportunity to do what is right for our families, including those who are most vulnerable: our babies, our elderly, our sick or disabled family members and neighbors. It is time for the U.S. to decide whether it values families as a collective. If so, lawmakers must create policies that reflect those values.

Categories: Blogs

Employee Engagement Is a Financial Strategy

Hr Bartender - Sun, 08/12/2018 - 02:57

We spend a lot of time talking about creating employee engagement. The rationale being that engaged employees are highly productive. And productivity fuels the business.

In creating employee engagement, we need to think about employee satisfaction. I don’t see how a dissatisfied employee becomes engaged. It seems like their dissatisfaction with the company, their manager, their work, etc. is a barrier to engagement. On the other hand, employees who are satisfied with their organization, team, manager, work, etc. have opened the door to engagement. While it’s not a guarantee, they’re one step closer than the dissatisfied employee.

So, the question becomes, how do organizations achieve employee satisfaction? According to Jacob Morgan’s book “Employee Experience Advantage”, it’s about creating an outstanding employee experience. His research indicates companies that invest in the employee experience are four times as profitable as those that don’t and have more than two times the average revenue.

This research is supported in the Globoforce white paper “The Financial Impact of a Positive Employee Experience.” Their research reported that organizations that score in the top 25 percent on employee experience have nearly three times the return on assets compared to organizations at the bottom of the list.

My takeaway from these two pieces is that companies making investments in employee experience and engagement are doing so for more than feel-good feedback. The employee experience and employee engagement are key components of the company’s financial strategy. And senior managers not only need to thinkabout it that way but talkabout it that way.

For a moment, think about the other components of your organization’s financial strategy. Or your own personal financial strategy for that matter. It probably includes things like sticking to a budget, making investments in the future, and having an emergency fund. These are excellent strategies whether you’re a global corporation, small business, or an individual. And they are about more than money.

Organizations need to create compensation and benefit programs that are internally fair and externally competitive. The conversation about employee satisfaction and engagement isn’t about throwing money at employees. It’s about delivering value.

Companies should invest in employee’s futures with training and development opportunities. Employees want to know they have a career with the company. They want to know that managers support their career goals. Companies need to set aside a budget for employee development.

Finally, organizations need to realize that sometimes stuff just happens. And they have to spend money they didn’t budget. Sometimes organizations need to open their wallets and do the right thing like buy an employee a nice office chair when theirs breaks. Or have a celebration when they score a big account.

Years ago, there was this trend to rename human resources as human capital because “employees are the company’s greatest asset”. Some people balked at the idea saying that employees aren’t assets because … well, they’re human. In this case, we’re not saying that employees are the same as furniture, fixtures, and equipment. Because they’re not.

But employee satisfaction and employee engagement have value. Measurable financial value. And organizations need to recognize that … or they run the risk of leaving money on the table.

Image captured by Sharlyn Lauby while exploring the streets of Boston, MA

The post Employee Engagement Is a Financial Strategy appeared first on hr bartender.

Categories: Blogs

How Self-Care Became So Much Work

Harvard business - Fri, 08/10/2018 - 11:01

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The United States is no stranger to self-improvement, from the meditation and essential oils of the 60s to the Jane Fonda aerobics tapes of the 1980s and the fat-free-everything 1990s. “Nothing can bring you peace but yourself,” wrote Ralph Waldo Emerson in 1841, sounding a bit like a modern SoulCycle instructor. From these deep roots, the $11 billion self-improvement industry has grown.

Today, like so much around us, that industry is heavily influenced by tech. Our focus is shifting away from the actual self — our bodies, minds, and spirits — and toward data about the self. With iEverythings around us at all times, we expect our steps to be enumerated, our REM cycles to be recorded, and our breathing patterns to be measured. It’s not enough to just feel better — we need our devices to affirm that we are doing the work.

This dogged self-improvement quest is not the antidote. We are approaching the pursuit of work-life balance with the same obsessive (and oppressive) energy as we do our careers. Although the American Psychiatric Association reports that 39% of U.S. adults feel more anxious than they did a year ago, we continue to glamorize being overworked, busy, and stressed. Numerous studies support this — for example, the Journal of Consumer Research has published research showing that Americans associate busyness and stress with prestige and status. This might explain why counting our steps and recording our exhales are satisfying ways to measure the success of our self-care routine once we leave the office. But in this context, our high anxiety becomes just another thing to “work on.”

This raises the question: Are we genuinely interested in feeling healthier and happier? It seems likely that the values driving us to be workaholics in the first place are also encouraging us to “optimize” ourselves by using metric-driven “hacks.”

For type-A overachievers in particular, self-improvement bears a closer resemblance to work than to leisure. As a freelance journalist, I have also subsidized my life in New York City as a copywriter, editor, and consultant for a range of clients in the wellness space. I have led focus group discussions about meditation apps and created websites and content campaigns for prominent skin care lines, juice cleanse companies, and mental health apps. One of my clients recently told me her goal to start a meditation practice had short-circuited due to her tendency to turn everything — including self-care — into a chore. After trying out a 20-minute daily routine, she found that meditation ultimately caused more stress than it alleviated, which, in turn, made her feel guilty and bad about herself. Despite the fact that mindfulness meditation is now popular enough to be a billion-dollar business, the science behind it remains a work in progress. In a 2017 review of meditation studies from the past two decades, author and psychologist David Creswell, who directs the Health and Human Performance Laboratory at Carnegie Mellon University, examined the methodological limitations of recent mindfulness studies. He dispels the misconception that mindfulness is a proven panacea for anxiety, depression, chronic pain, stress, and more. Still, he points out some impressive findings: Mindfulness can reduce activity in the amygdala, the brain region responsible for the fight-or-flight response. Mindfulness meditation has also been shown to reduce levels of interleukin-6, a biomarker in the blood that is elevated in high-stress groups.

Regardless of whether future scientific findings confirm the benefits of mindfulness, it’s important to remember that there is no one-size-fits-all approach for stress relief. If meditation feels like “work,” it can become a restrictive, rather than expansive, practice. Treating meditation as a step needed to achieve the elusive goal of work-life balance keeps us dialed into the linear mindset of “checking things off our list.” If we rigidly commit to a meditation practice without considering how we might react on days when we don’t have time or aren’t in the mood for it, we might end up mired in guilt or self-criticism. This is not to say that if meditation feels difficult, you should just give up. But it’s important to see how this ancient tradition is being commodified by our culture as a tool for improvement. If your to-do-list mentality is a major source of stress in the first place, why add to it? The goal is to create space for yourself, to experience curiosity and explore without pressure. Take a few conscious breaths during your commute, or set an intention for your day before you leave the house. Remember: There is nothing inherently virtuous about torturing yourself (which, for the record, is an intention I frequently set for myself).

In more extreme cases, self-improvement can become an obsession. The rise of wearable devices like Fitbit that track our steps and sleep cycles can feed perfectionistic tendencies. UK-based marketing professors Rikke Duus and Mike Cooray conducted a study analyzing the effects of wearing a Fitbit on a group of 200 women. The women said the devices made them feel guilty whenever they fell short of their goals: 79% felt pressured to reach their daily targets, 59% went so far as to say they felt “controlled” by their devices, and nearly 30% referred to their Fitbits as “an enemy.” Although knowing our daily step count may provide the illusion of control in our lives, quantifying the “work” we are doing on ourselves (and ostensibly for ourselves) not only reinforces the idea that self-care should be work but also presents excessive opportunities for self-criticism. With a progress report available to us at all times — whether related to steps, sleep, breathing, gait, or calorie consumption — quantified self-improvement encourages us to fixate on the moments we fall short of our most granular expectations. And while beating ourselves up often seems like the most effective way to crack the whip, self-criticism has been shown to preoccupy us with failure and contributes to symptoms of depression, anxiety, substance abuse, and negative self-image.

Given how readily self-care can turn into self-criticism in this landscape, social media is a vicious trigger. Instagram in particular pressures us to share our personal victories and turn them into opportunities for self-marketing. The intoxication of getting likes on that photo of your colorful salad or post-workout selfie is a powerful source of motivation. A 2016 study out of UCLA found that getting likes on Instagram posts activates a part of the brain called the nucleus accumbens, which is also activated when eating chocolate or winning money. Yet, at the same time, this culture of compulsory sharing is what prompts us all to compare ourselves with everyone else. As I write this, I find myself comparing my daily routine with over 5 million Instagram posts invoking the hashtag #selfcare. These posts exhibit a range of photographed activities, from candlelit bubble baths to meal prep to inspirational quotes against monochrome backgrounds (“Say yes to you”). For all the buzz about #selfcare on Instagram, it isn’t actually increasing our well-being. In fact, a recent study calls Instagram “the worst” social media platform for mental health, showing that it heightens users’ feelings of inadequacy and anxiety by creating unrealistic expectations and instilling what the researchers call an attitude of “compare and despair.” Or, as a friend said to me, “Vacation pictures make me feel poor. Gym pics make me feel out of shape. Food pics make me hungry, and anything well-curated makes me nervous that I don’t pay enough attention to detail.”

Of course, engaging in rituals of self-discipline for the purposes of “improvement” is an ancient pastime. Self-denial through fasting or extreme dietary restrictions exists at the core of most major religions, often as a means to achieve spiritual purity, atonement, or enlightenment. Even now, our attempts to exert control on our bodies and minds remain underpinned by a moral charge. Yet what’s different in today’s world of solutionism and tech is that prioritizing self-care — specifically with the aid of consumer goods like wellness apps and health food — is not just a testament to one’s self-discipline or moral virtue. It is an emblem of success and cultural know-how. Last year, journalist Amy Larocca wrote an article titled “The Wellness Epidemic,” in which she argued that, in the world of luxury meditation studios, ayurvedic cleanses, and sober morning raves, the mythical goal of wellness is only available to the rich, who have the time and resources to spend diagnosing their “maybe-kind-of-celiac disease” and purchasing $1,000 skin care protocols. “Spend a little time in the wellness world, and it seems like everyone has an official diagnosis,” Larocca writes. Part of the irony of wellness culture is that it requires us to focus constantly on the specter of illness, as it’s fueled by the (im)possibility of perfection. With green juice at $9 a pop, and luxury spin classes at $35+, the more aspirational self-improvement activities of our day are out of reach for most people. This further circumscribes self-care with values of conformity and achievement, as well as their shadow sides — feelings of inadequacy and self-criticism.

There are infinite opportunities for personal growth, self-care, and genuine stress relief that don’t require money or clenched fists, but instead enable us to take a genuine break from goal-oriented and metric-driven thinking. What about cutting ourselves some slack on the days we don’t get as much done as we had planned? Or reminding ourselves that laughter is healing? We may idealize the actions we are able to document and share, or the data we can collect and track, but there are plenty of times when what we need to do to feel better — and actually get better — is less. For better or for worse, there is no app or amount of money that can help with that.

Categories: Blogs

How B2B Software Vendors Can Help Their Customers Benchmark

Harvard business - Fri, 08/10/2018 - 09:30

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Knowing which organizations perform the best on any particular dimension used to require subjective surveys or painstaking research. Today, the data to answer those questions exists — it’s captured by the software-as-a-service firms whose services companies use to run their businesses. Mainstream software companies are beginning to hold “data mirrors” up to their customers, allowing scoring and benchmarking of their customers’ strategies. We’ve already seen that it’s possible to use external data to evaluate firms on what business models they are employing, and what those business models mean for their valuations.  Those analyses rely on publicly available data sources, but software providers have accumulated growing amounts of private data on almost every aspect of their customers’ technology, operations, people, and strategies. It’s time that these data accumulators begin to share insights back to the creators of all this data, and several firms are beginning to do so.

The most likely software firms to have such data are those that provide transactional capabilities to their customers using a subscription-based SaaS model. SAP, for example, has data on a variety of transactional domains, from customer orders to vacation balances. One of its business units, Fieldglass, provides insights and benchmarks to customers on external workforce management. ADP, a leading provider of payroll capabilities, allows customers to use its DataCloud tool to compare themselves to other firms not only how much employees are paid, but also metrics like their average job tenure, attrition rates, how much they invest in retirement accounts, and at what age they retire. Neustar’s MarketShare software makes it possible for customers to measure the effects of their marketing programs and compare them to other firms. It is even possible to hold up the data mirror to individual technology users. Microsoft, for example, has a program called MyAnalytics that informs customers of its Office productivity software about how much time they spend on various tasks, and the size and strength of their communications networks.

At the same time that data mirrors and scoring have emerged in the corporate world, capital markets are becoming increasingly interested in the analysis of alternative data sets. Active investors such as hedge funds seek to outperform the market and index providers. Stock index giant S&P bought AI-based boutique analytics firm Kensho for just this reason: to get better at using AI to improve investment decisions, and to diversify the kind of data used to make those decisions. (Kensho uses not just raw financial data but data from all sorts of ‘alternative’ sources.)

Software and other companies that develop data mirrors and scores can grow their top and bottom lines with little or no marginal costs by building investable indices that correlate their unique insight and data to investor returns. These can be marketed and monetized via the capital markets in partnership with exchanges and ratings firms.

We believe there are many more opportunities for software companies to adopt this approach—gathering data, relating it to desired outcomes, and returning it to their customers. Salesforce.com, for example, could let its customers assess themselves on their ability to move sales prospects down the pipeline. Workday could provide even more detailed analyses and benchmarking comparisons than ADP or SAP Fieldglass on the workforce. Oracle could let companies know how their average cost of issuing a purchase order, or its average accounts payable levels, compare to other firms.

Allowing a single company to compare itself to other firms on specific attributes is valuable, but an even greater opportunity to create value from data is to assign customers scores based on data and analytics about how they compare to their peers on broad functions or processes, and provide paths to improve their operations and transform their organizations to become digital leaders. The FICO score is an excellent example; the company reduces a consumer’s complex credit history to a single three-digit score that both creditors and debtors can understand. Imagine if all manufacturers had, for example, a supply chain efficiency score, or all companies had a leadership development score. This would provide motivation to leaders to improve their scores, and allow capital markets to make better decisions about the capabilities of companies in which they invest. The appeal of widespread nonfinancial performance measures for assessing companies has been discussed for several decades, but never achieved—despite continuing growth in assets and priorities poorly measured by GAAP accounting.

Of course, there are several steps that software companies need to take in order to make data mirrors possible. Here are some of the key considerations:

  • It’s essential to make sure that your company owns this data or has permission to use it. Many software licensing agreements already allow the use of such data for analysis and comparison purposes, but not all do.
  • Aggregate the data and use it to allow comparisons to other customers (or at least averages) so that your customers and prospects know where they stand (analogous to the running and cycling leader boards from Strava.com or RunKeeper).
  • Software firms may want to display the data only in anonymized form in order to preserve customer confidentiality. Of course, that lowers the value of the data and inhibits the ability to monetize it. If a company is attempting to provide value for investors, anonymity doesn’t work—but the customers of software firms may find it challenging to get customers to agree to be named. In such situations, the use of publicly available external data can be used for scores and rankings.
  • Companies may need some capabilities with artificial intelligence to make data mirrors work, particularly if the score or index is being related to financial performance. Machine learning is the ideal technology for creating a set of predictive scores from a collection of data. Other AI technologies can also be used to extract data from transactional systems, or to analyze and quantify textual data.
  • Just as companies like Credit.com provide personalized recommendations for how to improve a credit score, companies need prescriptive analytics and recommendations for how to improve their scores on whatever measure being assessed. Machine learning and natural language generation can provide such recommendations—just as they do so now for investing recommendations at companies like Morgan Stanley.

Almost all of the companies we researched, written about, and have advised are at the early stages of this movement, and gaining momentum.  They increasingly appreciate the potential value of ranking and optimizing a customer’s operations and resources with low-touch recommendations. We’ve referred to this phenomenon as corporate robo-advisers, and we see more of them all the time. But software companies are perhaps better-equipped than any other type of firm to offer them.

This data-first approach obviously opens up a variety of issues related to data ownership and privacy, products vs. services, interpretation of data, monetization strategies, and the power of platform monopolies.  But we expect that data-mirror-builders and the scoring systems that they are creating will change numerous industries, processes, and functions. There is so much internal and external data available now it seems inevitable that at least some of it will be used to assess the current and future growth and prosperity of commercial enterprises.

Categories: Blogs

New Supply Chain Jobs Are Emerging as AI Takes Hold

Harvard business - Fri, 08/10/2018 - 08:35

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Companies are cutting supply chain complexity and accelerating responsiveness using the tools of artificial intelligence. Through AI, machine learning, robotics, and advanced analytics, firms are augmenting knowledge-intensive areas such as supply chain planning, customer order management, and inventory tracking.

What does that mean for the supply chain workforce?

It does not mean human workers will become obsolete. In fact, a new book by Paul Daugherty and H. James Wilson debunks the widespread misconception that AI systems will replace humans in one industry after another. While AI will be deployed to manage certain tasks, including higher-level decision making, the technology’s true power is in augmenting human capabilities — and that holds true in the supply chain.

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In this new environment, both machines and humans are essential: By collaborating in roles such as supply chain planning and inventory management, the combined power of humans and machines will create new sources of value for businesses. We’ve explored the nature of the new value-enhancing roles that will emerge and identified three new categories of AI-driven jobs:

Trainers who help AI systems learn how to perform, which includes everything from helping natural language processors and language translators make fewer errors, to teaching AI algorithms how to mimic human behaviors.

Explainers who interpret the results of algorithms to improve transparency and accountability for AI decision making and processes.

Sustainers who ensure intelligent systems stay true to their original goals without crossing ethical lines or reinforcing bias.

AI, combined with advanced analytics, will enable supply chain planners to make more forward-looking, strategic decisions and spend less time on reactive problem solving. These planners will lead the charge in moving away from a traditional supply chain operating model, which is inflexible and slow, to a new dynamic model with true end-to-end segmentation. That means planning multiple supply chains that meet the needs of specific customer micro-segments as well as managing business relationships and exceptions. Concurrently, a new digital engineer role will emerge: a highly analytical, digitally savvy data scientist who manages, models, and tweaks the algorithms, alert protocols, and parameters guiding the automated decision-making planning systems. The importance of strong analytical skills will grow with the demand for human workers with a digital engineer’s skill set.

Leading companies recognize this change is coming and are starting to evolve their supply chain workforces. According to Accenture Strategy research, 90% of executives believe this workforce will become adept at digital technologies such as augmented reality, 3D printing, and automation. And 92% of executives surveyed said supply chain workforces will be upskilled and enabled to interact and work with machines seamlessly.

In other words, supply chain workers are already beginning to adjust to work effectively with a range of intelligent technologies — from cobots to robots to virtual agents — to get tomorrow’s jobs done. For example, these technologies can help reinforce correct procedures on the shop floor, monitoring how employees execute tasks and coaching them to do it the best way. Thyssenkrupp is overcoming skill mismatches through AI. The industrial services giant equips its elevator technicians to consult subject-matter experts through Microsoft HoloLens, an augmented reality headset.

Supply chain leaders need to ready their people for this inevitable shift that is already under way. That means making the commitment to reskill and move people to other areas of the business where they can add value. A major consumer goods company applied machine learning to complement more-traditional techniques for forecasting, which increased accuracy for forecasts and inventory management and made unnecessary the manual reviews and calculations that previously took almost 80% of the time. As a result, the company refocused human workers to provide valuable market intelligence.

Here are other ways supply chain leaders can continue this momentum and enable human workers to work together with AI in the most effective way:

Attract the future workforce. Now is the time to identify exceptional talent by looking outside of the supply chain. Data scientists, risk managers, and business development leads are among the types of employees that can bring significant value to the supply chain. Companies should also ensure their workplaces reflect the ethos of the new supply chain by integrating mobility, technology, and collaboration tools and by reinforcing new behaviors and mindsets throughout the talent development life cycle. Recruitment, performance metrics, and career advancement all need to be viewed through a lens of technology-driven innovation.

Remove the robot from the human. Prioritize and define both immediate and longer-term opportunities for AI, based on specific roles and tasks. AI systems will only continue to evolve and get smarter in their decision-making abilities. Consequently, it’s imperative to redirect and reskill human workers to focus on high-value initiatives such as customer experience and innovation.

Place your innovation bets. Think big but start small by mapping opportunities to integrate AI with existing technology solutions. Until now, robots, big data, analytics, and other technologies have been used in parallel with people, but in isolation. Their role: improve process efficiencies. Now, with AI systems that can sense, communicate, interpret, and learn, all that changes. AI can help businesses move beyond automation to elevate human capabilities that unlock new value.

The supply chain is and always has been a people business. We’re moving toward a world where humans and machines are collaborating, not just coexisting. The result will be an efficient, sustainable supply chain that delivers better business outcomes.

Categories: Blogs

Research: Having a Black Doctor Led Black Men to Receive More-Effective Care

Harvard business - Fri, 08/10/2018 - 07:42

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In the U.S., racial and ethnic minorities have higher rates of chronic disease, obesity, and premature death than white people. Black patients in particular have among the worst health outcomes, experiencing higher rates of hypertension and stroke. And black men have the lowest life expectancy of any demographic group, living on average 4.5 fewer years than white men.

A number of factors contribute to these health disparities, but one problem has been a lack of diversity among physicians. African Americans make up 13% of the U.S. population, but only 4% of U.S. doctors and less than 7% of U.S. medical students. (Of active U.S. doctors in 2013, 48.9% were white, 11.7% were Asian, 4.4% were Hispanic or Latinx, and 0.4% were American Indian or Alaska Native.) Research has found that physicians of color are more likely to treat minority patients and practice in underserved communities. And it has been argued that sharing a racial or cultural background with one’s doctor helps promote communication and trust.

A new NBER study looks at how changing this ratio might improve health outcomes — and save lives. Researchers set up an experiment that randomly assigned black male patients to black or nonblack male doctors, to see whether having a doctor of their race affected patients’ decisions about preventive care. They found that black men seen by black doctors agreed to more, and more invasive, preventive services than those seen by nonblack doctors. And this effect seemed to be driven by better communication and more trust.

Increasing demand for preventive care could go a long way toward improving health. A substantial part of the difference in life expectancy between white and black men is due to chronic diseases that are amenable to prevention. By encouraging more preventative screenings, the researchers calculate, a workforce with more black doctors could help reduce cardiovascular mortality by 16 deaths per 100,000 per year — resulting in a 19% reduction in the black-white male gap in cardiovascular mortality and an 8% decline in the black-white male life expectancy gap.

A Field Experiment in Oakland

The researchers — Drs. Marcella Alsan of Stanford University, Owen Garrick of Bridge Clinical Research, and Grant C. Graziani of the University of California, Berkeley — wanted to conduct a community-based study, so they recruited black men from 20 barbershops and two flea markets in Oakland, California. “These are very special places in the black community,” Dr. Garrick told me. “There’s a wide income, educational, and age range. If you have hair, you’re going to visit the barbershop every week or two.”

They were able to enroll more than 1,300 black men to participate. First, the participants received a monetary ($25) incentive to complete a baseline survey, which asked about socio-demographics, health care, and medical mistrust. Then they received a coupon for a free health screening for blood pressure, BMI, cholesterol, and diabetes at a clinic. They were offered another incentive ($50) to go, as well as a ride if they needed one.

The researchers couldn’t find a freestanding clinic with a mix of black and nonblack doctors to partner with, so they created one themselves. They hired 14 male doctors (eight nonblack and six black) to provide these screenings, telling them that the study — officially called the Oakland Men’s Health Disparities Project — aimed to improve the uptake of preventive health screening services for black men. What they didn’t tell the doctors was that their race was being randomized.

About half of the participants showed up to the clinic for a screening. Those who did tended to be older, have lower self-reported income and health, be unemployed, have less education, and not have a primary care doctor. Once participants got to the clinic and to their private patient room, they were given a tablet showing a photo of their (randomly assigned) doctor, his name, and a list of the services they could select. They saw that two of these screenings, for diabetes and cholesterol, required a finger prick of blood. Then they saw that they could get a flu shot, and some were randomly assigned to see an incentive of $5 or $10 to agree to it.

Participants then talked to their doctor. Doctors were only allowed to provide these five preventive services — all highly recommended, cost-effective interventions — and were told to encourage patients to agree to all of them. During the consultation, patients could revise their selections and have the services done. After the visit, patients filled out a feedback form. Then researchers compared the services provided with the services the men chose before talking to the doctor.

The results were fascinating. In the first stage, before meeting their doctor, participants selected the same number of preventive services, regardless of whether the doctor they saw on the tablet was black. “We hypothesized that if there was aversion, like ‘I just don’t like a doctor of this type,’ that would be elicited at this stage. Because you don’t actually interact with someone yet,” Dr. Alsan said.

But in the second stage, after talking to their doctor, men who met with black doctors elected to receive more preventive services — especially more invasive services that required a blood sample or injection — than men who met with nonblack doctors. This held even controlling for duration of the visit and physician characteristics. “We can only speak to our study and our population. But it was a very striking and strong finding,” Dr. Alsan said.

For example, participants assigned to black doctors were more likely to have their blood pressure and BMI measured than those who saw nonblack doctors. And for invasive tests, only men who saw a black doctor agreed to take up more services than they had initially selected. A participant who saw a black doctor was 20 percentage points (47%) more likely to agree to a diabetes screening and 26 percentage points (72%) more likely to accept a cholesterol screening than those who saw a nonblack doctor.

Men were 10 percentage points (56%) more likely to agree to the flu shot if their doctor was black. “Even among men who had been offered the opportunity to get a $5 or $10 incentive to say yes to the flu shot, some of those men had turned that money down, saying, ‘No, I really don’t want a flu shot. I just don’t want a flu shot,’” Dr. Alsan said. “The African-American doctors were able to convince some of those men who had turned down the money to obtain a flu shot.”

The researchers also found that the effects were most pronounced for men with greater mistrust of the medical system. They were the most reluctant to have services done in the beginning, and they were the most likely to change their minds after talking to a black doctor and to have more services done. This is meaningful, as other research has found that black men are more likely to distrust the U.S. health care system than white men, and that this distrust leads to delayed preventive care and worse outcomes.

Trust and Communication

Why would black men choose more services after seeing a black doctor? Looking at doctor notes, patient feedback, and data from a separate survey, the researchers point to a few pieces of evidence suggesting that better trust and communication between black doctors and black patients was what made the difference.

First, because the study was focused on offering preventive care, as opposed to curative care treating illness, the role of the doctor was mostly limited to explaining the benefits of the preventive services and then providing them. Participants knew this, but they were 10 percentage points (29%) more likely to talk about other health or personal issues with black doctors than with nonblack doctors. And black doctors also wrote longer notes about their patients than nonblack doctors.

Second, the researchers gathered additional data by surveying a similar sample of 1,490 black and white men on doctor preferences. Respondents saw a set of black, white, and Asian male doctors, and selected which doctor they thought was most qualified, which they’d feel more comfortable with, and which was most accessible to them.

Both white and black men thought that doctors of their race were about as qualified as other doctors. There wasn’t a clear sign of preference. “But when it came to communication, when we asked, Which doctor would you feel more comfortable with? Which doctor would understand you the best? That’s when we saw a shift.” Dr. Alsan said. Nearly 65% of black respondents and 70% of white respondents reported that a doctor of the same race would understand their concerns best.

“A lot of our job as doctors is to talk to people, and to understand where they’re coming from,” Dr. Alsan said. “They’re sharing some of the most intimate regions of their lives and their concerns with you.”

Of course, the precise mechanisms here are difficult to pin down, and the researchers acknowledge that other factors besides communication and trust could be at play. They didn’t script doctors’ interactions and weren’t in the room to observe differences in their care. Perhaps black doctors were somehow better-quality, or maybe discrimination played a role. But the evidence they did have doesn’t support these interpretations — on feedback forms, for instance, patients rated both black and nonblack doctors equally positively.

“We think [better communication] is a mechanism behind our results, and we have suggestive findings that support that interpretation. But it would be a great follow-on study to figure out what type of communication [mattered],” Dr. Alsan said. “Seeing what can be taught and what one can learn would be a wonderful next-generation study.”

How Diversity Can Improve Care

This study supports the push to increase diversity in the health care workforce. Many racial and ethnic minority patients seek out doctors of the same background — but access is an issue. The survey found that white men were 20 percentage points more likely than black men to say they could access a doctor of their race.

But the researchers and others advise against interpreting these results to mean that black patients should be treated by black doctors preferentially. “We certainly don’t want people to take away from this that, hey, if you’re not black, you can’t relate to black patients,” Dr. Garrick said. “If anything, you might think, what may I be missing here?”

Dr. Anupam Jena, a physician at MGH and an economist affiliated with NBER, who was not associated with the study, urged similar caution. However, he said, “We should be aware that empathy and understanding of your patient, perhaps through shared experiences, might have an important causal impact on health,” he said.

Dr. Jena noted that what he liked most about the study was that it was so ambitious — it randomized across a large number of patients and set up a separate clinic. He also pointed out that because it focused on preventive care, it’s hard to know whether the findings would generalize to care that is provided to sick patients in need of treatment.

But black men are less likely to seek routine and preventative care than other groups, and increasing their uptake could yield significant health benefits. “Prevention is the unsung hero of medicine,” Dr. Alsan said. “The amount of premature mortality that you can save or spare is quite remarkable with comprehensive preventive intervention.”

And it’s not just prevention. “It’s also much earlier diagnosis and awareness if there is disease,” Dr. Garrick said. “If you look at lower life expectancy for African-American men, there’s a lot of late diagnosis of disease, from prostate cancer to cardiovascular disease. And getting these preventative services doesn’t just help prevent the diseases, in the case of vaccines, but it also serves as more of an early detection, an early warning system, which is one of the big factors impacting minority health and health equity.”

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