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Best content from the best source handpicked by Shyam. The source include The Harvard University, MIT, Mckinsey & Co, Wharton, Stanford,and other top educational institutions. domains include Cybersecurity, Machine learning, Deep Learning, Bigdata, Education, Information Technology, Management, others.

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    3D Computer Chips Could Be 1,000 Times Faster Than Existing Ones




    © Max Shulaker A new method of creating computer chips could provide much faster performance than was previously possible. The new design uses a special material called carbon nanotubes, which allows memory and processor layers to be stacked in three…


    A new method of designing and building computer chips could lead to blisteringly quick processing at least 1,000 times faster than the best existing chips are capable of, researchers say.

    The new method, which relies on materials called carbon nanotubes, allows scientists to build the chip in three dimensions.

    The 3D design enables scientists to interweave memory, which stores data, and the number-crunching processors in the same tiny space, said Max Shulaker, one of the designers of the chip, and a doctoral candidate in electrical engineering at Stanford University in California.

    Reducing the distance between the two elements can dramatically reduce the time computers take to do their work, Shulaker said Sept. 10 here at the "Wait, What?" technology forum hosted by the Defense Advanced Research Projects Agency, the research wing of the U.S. military.

    Progress slowing

    The inexorable advance in computing power over the past 50 years is largely thanks to the ability to make increasingly smaller silicon transistors, the three-pronged electrical switches that do the logical operations for computers.

    According to Moore's law, a rough rule first articulated by semiconductor researcher Gordon E. Moore in 1965, the number of transistors on a given silicon chip would roughly double every two years. True to his predictions, transistors have gotten ever tinier, with the teensiest portions measuring just 5 nanometers, and the smallest functional ones having features just 7 nanometers in size. (For comparison, an average strand of human hair is about 100,000 nanometers wide.)
    The decrease in size, however, means that the quantum effects of particles at that scale could disrupt their functioning. Therefore, it's likely that Moore's law will be coming to an end within the next 10 years, experts say. Beyond that, shrinking transistors to the bitter end may not do much to make computers faster.

    Long commute time

    The main roadblock to faster computers is not flagging processor speed, but a memory problem, Shulaker said.

    Big-data analysis requires the computer to draw some tiny piece of data from some previously unknown spot in truly staggering troves of data. Then, the computer must shuttle that information via an electrical signal back and forth across the (relatively) vast inches of wire between the computer's memory (typically a hard drive) and the processors, facing the speed bump of electrical resistance along the entire path.

    "If you try to run that in your computer, you would spend over 96 percent of the time just being idle, doing absolutely nothing," Shulaker said. "You're wasting an enormous amount of power." While the Central Processing Unit (CPU) waits for a piece of data to make the return trip from the memory, for instance, the computer is still hogging power, even though it's not calculating a thing.
    Solving the memory-CPU "commute time," however, is tricky. The two components can't be put in the same wafer because silicon-based wafers must be heated to about 1,800 degrees Fahrenheit (1,000 degrees Celsius), while many of the metal elements in hard drives (or solid state drives) melt at those temperatures, Shulaker said.

    Carbon nanotubes

    To get around this issue, Shulaker and his advisers at Stanford University, Subhasish Mitra and H.-S. Philip Wong,  looked to a completely different material: carbon nanotubes, or miniscule mesh rods made of carbon atoms, which can be processed at low temperatures. Carbon nanotubes (CNTs) have electrical properties similar to those of conventional silicon transistors.

    In a head-to-head competition between a silicon transistor and a CNT transistor, "hands down, the CNT would win," Shulaker told Live Science. "It would be a better transistor; it can go faster; it uses less energy."

    However, carbon nanotubes grow in a disorderly manner, "resembling a bowl of spaghetti," which is no good for making circuits, Shulaker said. As such, the researchers developed a method to grow nanotubes in narrow grooves, guiding the nanotubes into alignment.
    But there was another hurdle. While 99.5 percent of the nanotubes become aligned, a few stragglers will still be out of position. To solve this problem, the researchers figured out that drilling holes at certain spots within the chip can ensure that even a chip with wayward tubes would work as expected. 

    Another problem is that while most CNTs have the properties of a semiconductor (like silicon), a few act just like an ordinary conducting metal, with no way to predict which tubes will misbehave. Those few conducting tubes can ruin an entire chip, and having to toss even a fraction of the chips wouldn't make financial sense, Shulaker added. As a remedy, Shulaker and his colleagues essentially "turn off" all the semiconducting CNTs, leaving huge jolts of current to circulate through the remaining conducting nanotubes. The high current heats up and breaks down only the conducting nanotubes, which blow like nano-scale fuses, Shulaker said.

    In 2013, the team built a CNT computer, which they described in the journal Nature. That computer, however, was slow and bulky, with relatively few transistors.

    Now, they have created a system for stacking memory and transistor layers, with tiny wires connecting the two. The new 3D design has slashed the transit time between transistor and memory, and the resulting architecture can produce lightning-fast computing speeds up to 1,000 times faster than would otherwise be possible, Shulaker said. Using the new architecture, the team has built a variety of sensor wafers that can detect everything from infrared light to particular chemicals in the environment.

    The next step is to scale the system further, to make even bigger, more complicated chips.

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    Do today’s philanthropists hurt more than they help?



    As philanthropy enters a second golden age, real social change is getting lost in the hype of market-based giving.

    In one of his short stories, “Counterfeit Money,” Charles Baudelaire describes a fictional encounter between two friends who come across a beggar in the street.
    In this short piece, the narrator and friend offer the beggar spare change, but the friend offers a much larger coin. The narrator commends him for his generosity. The friend accepts the compliment and then adds, once they’re out of earshot of the beggar, “It was a counterfeit coin.”
    The narrator is astounded. Not only has his friend duped the beggar on purpose, what’s worse, he feels self-congratulatory for his gift. His satisfaction lies in the fact that the beggar doesn’t realize that he has been duped. The narrator sees that his friend’s “aim had been to do a good deed while at the same time making a good deal; to earn forty cents and the heart of God; to win paradise economically; in short to pick up gratis the certificate of a charitable man.”
    Baudelaire’s story was written in the latter half of the 19th century, a time when industrialists such as Andrew Carnegie and John D. Rockefeller Sr. began channelling their vast fortunes into some of the greatest acts of philanthropy ever known. From Carnegie’s spending on public libraries to Rockefeller’s investment in biomedical advances, their giving helped to shift charity from the dispensing of alms in a largely unsystematic manner to a business in itself, overseen by paid philanthropic advisors.

    Many did not feel grateful for the robber barons’ generosity, however. In his essay, “The Soul of Man Under Socialism,” Oscar Wilde berated the tendency of benefactors to use their charity as a bulwark against redistributive demands.
    “The best among the poor,” Wilde wrote, “are never grateful. They are ungrateful, discontented, disobedient, and rebellious. They are quite right to be so … Why should they be grateful for the crumbs that fall from the rich man’s table? They should be seated at the board, and are beginning to know it.”
    As philanthropy enters a second golden period, with the gifts from benefactors such as Bill Gates and Warren Buffett rivaling those offered toward the end of the gilded age, sceptics are starting to ask: Are Wilde’s and Baudelaire’s concerns still relevant? Are today’s philanthropists knowingly dispensing “false coins?” Are they trying to “pick up gratis the certificate of a charitable man?”
    In most cases, the answer is a firm no. Charity is dispensed in good faith, with empathy toward close and distant strangers. And yet, at the same time, a new trend is growing: philanthrocapitalism, a more muscular philanthropy that seeks to combine profits with poverty alleviation. The effort to do a good deed while at the same time making a good deal is the driving impetus behind the new philanthropy. Another question Baudelaire raised still lingers: Who benefits more from charitable acts, the giver or the receiver?
    At the forefront of the new philanthropy is the effective altruism movement, something upheld as radically different from earlier philanthropic approaches through a purportedly novel emphasis on measuring the results of giving. A pioneer in the movement is Peter Singer, the controversial bioethicist who has praised Buffett and Gates for being “the most effective altruists in history.”
    His praise rests on the magnitude of their giving rather than evidence of their effectiveness. It’s true that in dollar terms, their generosity is jaw-dropping. Joel Fleishman points out in The Foundation that Buffett’s 2006 announcement of a gift of $31 billion to the Gates Foundation represented, in 2006 dollars, more than Rockefeller Sr. and Carnegie gave away combined.
    But as a proportion of the overall U.S. Gross Domestic Product, the size of today’s foundations pales next to their predecessors. The Ford Foundation’s endowment in the early 1960s represented more than double the share of U.S. GDP in comparison to the Gates Foundation 50 years later. Ever since the 1970s, overall charitable giving in the U.S. “as a share of GDP has rarely strayed far from 2 percent,”Suzanne Perry points out in the Chronicle of Philanthropy, “despite the huge growth in the number of charities and fundraisers and periodic crusades to encourage greater giving.”

    Corporations have become far stingier. Mark Kramer and Michael Porter pointed out in the early 2000s that corporate philanthropy as a proportion of corporate profits dropped since the 1980s. Since then it’s sunk even further, from 2.1% of pretax profits in the mid-1980s to 0.8% in 2013.
    Singer’s presumption that Buffett and Gates are any more effective than earlier philanthropists isn’t backed by data. Some of the Gates Foundation’s work has led to measurable gains. Vaccination rates are rising; global child mortality has fallen—the foundation’s work in global health has contributed to these gains. But in comparison to government donors, Gates Foundation grants are a small drop in the global health landscape: The U.S. government has committed over $65 billion to global HIV/AIDs programs alone. That’s double the amount of overall giving by the Gates Foundation toward U.S. education, global health, and global agriculture since its inception.
    To date, there has been far more hype than hard evidence about effective altruism’s achievements; its progress often seems to be measured and underpinned by self-sustaining feedback loops. Donors privilege what critics see as low-hanging fruit: aid projects where measuring the effect is relatively easy to do.
    We hear a lot about the positive effects of different programs, such as the benefits of deworming efforts worldwide that were once thought to have contributed dramatically to education attainment in developing nations, until a recent review from independent health research group Cochrane cast doubt on that link. Far less attention is paid to counterfactuals, such as the cost to welfare programs when tax revenue is lost as a result of philanthropists receiving lucrative tax exemptions for pet projects.
    Today’s philanthropy enthusiasts are never short on hyperbole. An organizer of a recent effective altruism conference at Google’s Quad campus in Mountain View reportedly averred that “effective altruism could be the last social movement we ever need.” But it’s clear that rises in global giving over the past 10 years have not made a dent in reducing economic inequality in rich nations such as the United States or Britain.
    Individual philanthropic foundations have grown at a fast clip in the U.S. over the past 15 years: In that span, the number of individual foundations has doubled from about 40,000 to over 85,000. But this surge hasn’t helped alleviate extreme poverty. A 2012 report from the National Poverty Center at the University of Michigan points out that within the U.S., “the prevalence of extreme poverty rose sharply between 1996 and 2011.”

    One of the biggest ironies facing 19th-century philanthropy was the question of whether growing charity simply exacerbated economic inequality by thwarting demands for better wages and the right to unionize.
    Carnegie published his first “Wealth” essay, in which he urged the rich to share their spoils, just a few years before the Homestead battle of 1892, one of the bloodiest labor standoffs in U.S. history, where he brutally stamped out burgeoning union efforts even while liberally dispensing charity to his workers. “Paradoxically,” David Nasaw, Carnegie’s biographer, has pointed out, “Carnegie … became, if anything, more ruthless in pursuit of profits once he had determined that those profits would be distributed during his lifetime.”
    “In remonstrating that only the millionaire could be trusted to dispense his millions, and that whatever that millionaire thought ‘best’ was best,” Nasaw adds, “Carnegie was promulgating a profoundly antidemocratic gospel, almost feudal in its paternalism.”
    Effective altruists insist that private charity is the best means for improving livelihoods. ‘Today’s philanthrocapitalists see a world full of big problems that they, and perhaps only they, can and must put right,’ Matthew Bishop and Michael Green write inPhilanthrocapitalism: How Giving Can Save the World, a book that’s become something of a bible for the new philanthropists.
    In contrast to claims of novelty, the results-oriented approach of today’s donors is little different than Carnegie or Rockefeller, who were both outspoken about the need to give away their money in an efficient and effective manner.
    And just as in Carnegie’s day, philanthropy is often upheld as justification for gross profiteering.
    “I donated a total of $5,000,000 to various causes recently. Looking forward to telling you all about it,” Martin Shkreli, the CEO of Turing Pharmaceuticals who was vilified for raising the price of Daraprim by 5,000%, tweeted in mid-September.
    This is a prime example of philanthrocapitalism in action: the use of philanthropy to thwart attention to business practices that hamper access to life-saving medicines. And much like in Carnegie’s time, many aren’t buying it.

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    It was enough rock and ice to equal the weight of 33 million pickup trucks. And for an earth-shattering two minutes, it barrelled down a mountain at nearly 200 km/h, pulverizing everything in its path.

    And the Yukon didn’t even know it was there.

    “Most likely it would have been missed,” said Colin Stark, one of two Columbia University geologists who spotted the “catastrophic” event from more than 5,000 kilometres away.

    Expected to rank among the world’s 10 largest landslides for 2015, the slide saw a massive chuck of rock and ice slough off Mount Steele, Canada’s fifth highest peak.

    If the Oct. 11 slide had struck in a populated region of India or China, hundreds would be dead. Even in Canada’s sparsely populated Rocky Mountains, it would have at least blocked a highway or buried a wilderness lodge.

    But it occurred in a remote corner of Kluane National Park, Canada’s Wales-sized contribution to a swath of protected land stretching all the way to Anchorage, Alaska.

    Jennoit/Jenn/Wikipedia

    “That particular area, as the crow flies, is about 70 kilometres to the Alaska Highway; people aren’t back there very often,” said Jeff Bond with the Yukon Geological Survey.

    Quite often, said Bond, the only way remote Yukon landslides are recorded is if some bystander happens to phone it in.

    “We hear about them from helicopter pilots who say, ‘hey, did you guys know about this big slide?’ ”
    In the summer of 2014, for instance, a landslide plowed into a creek within Kluane National Park, violently creating Canada’s newest lake. But it wasn’t until six months later that the change happened to be spotted by an off-duty parks employee who was out for a hike.

    Credit for discovering the Oct. 11 avalanche falls to Stark and his research partner, Göran Ekström.
    Operating out of Columbia University’s Department of Earth and Environmental Sciences, they have pioneered a way of discovering landslides by sifting through data typically used to detect earthquakes.

    In the case of Mount Steele, one of the few witnesses to more than 45 megatons of falling rock and ice was “YUK8,” an unmanned Canadian seismic monitoring station located only 25 kilometres away.

    Confirmation then came in via Landsat 8, a NASA Earth-monitoring satellite that focused in on the remote mountain and noted that vast areas of the surrounding peaks and glaciers had been blackened by debris.

    Jsayre64/Wikipedia Commons

    “The fact that the debris fell on ice contributed to the long debris field,” NASA wrote in a subsequent post.

    Named for Sam Steele, the Yukon’s indomitable top Mountie during the Klondike Gold Rush, Mount Steele has proved to be surprisingly delicate of late.

    In 2007, the mountain first found its way into geology textbooks with a slide that buried an area larger than Vancouver’s Stanley Park, and shook the ground with the force of a 5.2 earthquake.
    That time, the only witnesses were a research team led by glaciologist Garry Clarke, who just happened to be nearby when they heard the distinctive roar of a mountain falling over.
    “They got dusted by the ice avalanche, actually,” Bond said.

    Mount Steele is part of the Saint Elias Mountains, which includes Canada’s highest peak, Mount Logan. Amid regular earthquakes and landslides, it’s also a good candidate for Canada’s most geologically interesting corners.

    Just last year, in fact, a mountain face broke off nearby Mount La Perouse, in Alaska, creating one of North America’s largest known natural landslides.

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    Looking at trends in youth unemployment in high- and low-income countries makes the need for supporting youth entrepreneurship clear Youth unemployment is a critical issue for any country. From the lifelong effect graduating in a recession can have on students’ earnings to the upheaval of the Arab spring, the headlines of the last few years have shown that the ramifications of youth unemployment are deep and far-reaching. Taking a global view of trends in youth employment reveals what’s at the heart of the challenge—and points to the change that needs to be made to address it.

    While youth unemployment rates across geographies vary, they diverge in a fashion that one may not expect. The world youth unemployment rate (ages 15–24) sits at 13.9 per cent, according to the World Bank, increasing by .2 percentage points since 2006. High-income countries—including the United States, Argentina and Kuwait—average an unemployment rate of 18.2 per cent. Middle-income countries—including China, Malaysia and Mexico—average a rate of 13.8 per cent. Low-income countries—including Afghanistan, Nepal and Liberia—a rate of 9 per cent. The key to making sense of what may be a surprising disparity is to ask: What kind of employment do these numbers reflect? That in turn underscores the transformative role youth entrepreneurship can play in both developing and developed economies.

    “What often goes unrecorded in the data on youth unemployment is underemployment, and the negative impact that has on income and quality of life,” says Dr. Ben Oppenheim, Visiting Scholar and Senior Fellow at New York University, whose research focuses on economic development and governance in emerging markets. “Unemployment estimates can also be unreliable, since in many emerging markets, a significant share of labor activity takes place in the informal economy.”

    A dearth of legal, high-paying economic opportunities means populations, including youth, in developing countries are forced to take jobs that expose them to occupational hazards and decrease their overall well-being. A 2012 study, for example, found that people in developing countries are exposed to more than 80 per cent of global occupational hazards.

    In a similar vein, workers in the developed world are witnessing an increased informalization and fragmentation of their work, putting greater strains on youth employment. “What we see today is increasingly informalized labor in wealthy countries,” says Oppenheim. “The rise of the on-demand economy creates both pressures and opportunities for workers in the developed world to piece together income streams, as many people in developing countries do.”

    This global, cross-regional perspective helps to clarify where the focus of combating youth unemployment should be—not just on hitting a number of “employed,” but also on creating quality employment opportunities with a positive impact on the individual and community alike. Fostering youth entrepreneurship may provide one avenue for accomplishing this. “Small and micro enterprises can absorb a lot of labor, and we know how to stimulate those kinds of businesses—for example, through microloans when credit bottlenecks are a critical constraint,” says Oppenheim. While no prescription for fostering youth entrepreneurial activity will be the same across borders, there may be similar through-lines that transect geographies. A key challenge, however, says Oppenheim, is that not everyone is ready to be an entrepreneur, and training and relieving constraints to entrepreneurship can only go so far.

    This highlights that a combination of measures is needed to support a culture of youth entrepreneurship by choice, as opposed to labor-force participation out of hand-to-mouth necessity. While programs like social safety nets can free young would-be-entrepreneurs from subsistence work, getting to the “liftoff” point, where ideas become thriving business realities, takes more than that. That’s why training and mentoring are key. Investing in these resources for youth can have an impact on a country’s social and economic health that goes far beyond today’s topline numbers.

    In the coming weeks, we’ll explore how this central insight is being turned into solutions that are unique to the challenges and opportunities of countries around the world.


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    A Day on Pluto, a Day on Charon

    On approach in July 2015, the cameras on NASA’s New Horizons spacecraft captured Pluto rotating over the course of a full “Pluto day.” The best available images of each side of Pluto taken during approach have been combined to create this view of a full rotation.



    Credits: NASA/JHUAPL/SwRI

    Pluto’s day is 6.4 Earth days long. The images were taken by the Long Range Reconnaissance Imager (LORRI) and the Ralph/Multispectral Visible Imaging Camera as the distance between New Horizons and Pluto decreased from 5 million miles (8 million kilometers) on July 7 to 400,000 miles (about 645,000 kilometers) on July 13. 

    The more distant images contribute to the view at the 3 o’clock position, with the top of the heart-shaped, informally named Tombaugh Regio slipping out of view, giving way to the side of Pluto that was facing away from New Horizons during closest approach on July 14.  The side New Horizons saw in most detail – what the mission team calls the “encounter hemisphere” – is at the 6 o’clock position.

    These images and others like them reveal many details about Pluto, including the differences between the encounter hemisphere and the so-called “far side” hemisphere seen only at lower resolution. Dimples in the bottom (south) edge of Pluto’s disk are artifacts of the way the images were combined to create these composites.


    On approach to the Pluto system in July 2015, the cameras on NASA’s New Horizons spacecraft captured images of the largest of Pluto’s five moons, Charon, rotating over the course of a full day. The best currently available images of each side of Charon taken during approach have been combined to create this view of a full rotation of the moon.






    Credits: NASA/JHUAPL/SwRI

    Charon – like Pluto – rotates once every 6.4 Earth days. The photos were taken by the Long Range Reconnaissance Imager (LORRI) and the Ralph/Multispectral Visible Imaging Camera from July 7-13, as New Horizons closed in over a range of 6.4 million miles (10.2 million kilometers). The more distant images contribute to the view at the 9 o’clock position, with few of the signature surface features visible, such as the cratered uplands, canyons, or rolling plains of the informally named Vulcan Planum. The side New Horizons saw in most detail, during closest approach on July 14, 2015, is at the 12 o’clock position.

    These images and others like them reveal many details about Charon, including how similar looking the encounter hemisphere is to the so-called “far side” hemisphere seen only at low resolution – which is the opposite of the situation at Pluto. Dimples in the bottom (south) edge of Charon’s disk are artifacts of the way the New Horizons images were combined to create these composites.

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    What Kind of Thinker Are You?






    We all aspire to work better together. Technology is making some of that effort easier. But digital tools are only part of the answer. It’s people who ultimately make the difference.

    The problem is that technologies for collaboration are improving faster than people’s ability to learn to use them. What can be done to close that gap? A year ago we set out to find the answer, drawing on the collective experience of dozens of collaborative communities and learning organizations. Here’s what we found.

    In most organizations, there’s a standard set of tools we use to form, lead, and manage teams. These include personality tests, skill profiles, and team roles. When you put a team together, you consider people’s personalities: are they an introvert or extrovert, risk-taker or risk-avoider, analytical or intuitive? You consider their skills: What is their specific area of talent, experience, or expertise? And you consider their potential role on the team: What will their contribution be to the team’s purpose?

    We normally think of roles as being about what people do, such as team leader, project manager, or researcher. When you need a decision, you go to the team leader. When you want a status update, you go to the project manager. When you need something investigated, you go to the researcher.

    But in today’s marketplace, the smartest companies aren’t those that necessarily out-produce the competition. Instead, it’s the organizations that outthink them. And while there are plenty of tools that help us quickly understand what our teammates do, it’s harder to tell how they think. Research shows that it is ultimately how teams think together that most determines their performance.

    We therefore propose that just as team members today have assigned doing roles, there should also be thinking roles. By knowing how other members of your team and organization think — and by others knowing how you think — everyone can be more energized, more engaged, more creative, and more productive.

    One aspect of collaboration is about getting people aligned in what they do. But there is another dimension is about getting people aligned in how they think.

    So how should you evaluate about how you and your team think? There are frameworks for how you personally think or how you influence others one-on-one. But we didn’t find any simple assessments that would help people connect, communicate, and collaborate based on how they think. So after a lot of co-creation and trial-and-error, we developed a three-step method that delivers practical and meaningful results.

    Focus. 

    The first step is to identify the focus of your thinking in a particular context or setting. Do you tend to pay the most attention to ideas, process, action, or relationships? For example, in the morning as you contemplate the day ahead, do you tend to think about the problems you need to solve, the plans you need to make, the actions you need to take, or the people you need to see?

    This isn’t about picking one to the exclusion of the other. It’s about where your focus naturally lands. Just like when you consider watching a movie or reading a book, do you tend to go for action, romance, drama, or mystery?

    Orientation. 

    The next step is to notice whether your orientation in that setting swings toward the micro or the macro — the big picture or the details. A good way to identify this orientation is by thinking about what tends to bother you in meetings. Are you more likely to complain about getting dragged into the weeds or about things being too general and not specific enough?

    These dimensions are complementary to personality, skills, and traditional roles. Some project managers are more inclined to focus on process and others on people. And some extraverts are big picture and others more detail oriented.


    The third step is to combine these two dimensions and see the thinking style at work in whatever context or setting you chose.




    For example, on the big picture or macro orientation:


    Explorer thinking is about generating creative ideas.

    Planner thinking is about designing effective systems.

    Energizer thinking is about mobilizing people into action.

    Connector thinking is about building and strengthening relationships.
    Across the micro or detail orientation:

    Expert thinking is about achieving objectivity and insight.

    Optimizer thinking is about improving productivity and efficiency.

    Producer thinking is about achieving completion and momentum.

    Coach thinking is about cultivating people and potential.

    When you know your thinking style, you know what naturally energizes you, why certain types of problems are challenging or boring, and what you can do to improve in areas that are important to reaching your goals.

    Once you know your style, it helps to share it with others, and have others share theirs with you. In this way, your thinking style becomes a useful tool — a kind of social currency — for the team. Imagine you put together a team to work on a new initiative. Wouldn’t you like to know who is energized by big-picture strategy discussions and who finds them frustrating? Who likes to work on the details of the execution? And who is energized by managing the team dynamics?

    As a real-world demonstration, one company had their entire leadership team identify their thinking styles as managers and leaders. Looking at a heat map of the results, they realized they had a lot of big-picture Explorer thinking and a lot of Action thinking (Energizer and Producer), but very little Process thinking (Planner and Optimizer). The team was strong at coming up with big ideas and mobilizing everyone into action, but weak at working out the details and making things run efficiently.

    With this new information in hand, they started giving more voice to those whose detailed thinking often seemed like a buzz kill to the big picture explorers and energizers. They also shifted the culture and recruiting strategies to create a more balanced and diverse thinking style.

    At an individual level, one specific leader had always operated in idea-rich environments like consulting and marketing. But by identifying her thinking style, she realized that she was more energized by relationships than ideas. Her orientation was more towards Connector thinking than Explorer thinking. She used ideas to nurture relationships, rather than relationships to nurture ideas. This insight led her to shift the focus of her work toward account management and business development, leading to much higher levels of energy and engagement.

    The landscape of business is changing rapidly, and we have to find new and better ways to connect and communicate. We all aspire to work better together; the challenge is actually making it happen. Understanding collaboration through the lens of thinking rather than doing is a practical and powerful step forward.

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    New Growth Projections Predict the Rise of India, East Africa and Fall of Oil Economies

    May 7, 2015

    Growth Projections based on 2013 Global Trade Data
    May 7, 2015

    Rank Country Projected Annual Growth Through 2023 (%)
    1 India 7.89
    2 Uganda 7.00
    3 Kenya 6.74
    4 Malawi 6.54
    5 Tanzania 6.54
    6 Egypt 6.03
    7 Madagascar 5.85
    8 Zambia 5.82
    9 Senegal 5.53
    10 Philippines 5.53
    11 Mali 5.37
    12 Guatemala 5.30
    13 Turkey 5.29
    14 Kyrgyzstan 5.25
    15 Indonesia 5.15
    16 Pakistan 5.13
    17 Zimbabwe 4.93
    18 Vietnam 4.91
    19 Malaysia 4.89
    20 Thailand 4.89
    21 Jordan 4.78
    22 Mozambique 4.63
    23 China 4.56
    24 Ghana 4.50
    25 Yemen 4.45
    26 Mexico 4.43
    27 Ethiopia 4.41
    28 Israel 4.38
    29 Tunisia 4.18
    30 Guinea 4.17
    31 Cote d'Ivoire 4.05
    32 Honduras 3.94
    33 Belarus 3.91
    34 Lebanon 3.87
    35 Serbia 3.87
    36 Korea, Rep. 3.85
    37 Angola 3.71
    38 Slovak Republic 3.69
    39 Romania 3.67
    40 Ukraine 3.65
    41 Bosnia and Herzegovina 3.63
    42 Switzerland 3.62
    43 Brazil 3.62
    44 Uzbekistan 3.62
    45 Spain 3.60
    46 Cambodia 3.53
    47 Paraguay 3.52
    48 El Salvador 3.50
    49 Portugal 3.50
    50 Bulgaria 3.49
    51 Cameroon 3.46
    52 Nigeria 3.44
    53 Morocco 3.43
    54 Poland 3.42
    55 Sri Lanka 3.39
    56 Tajikistan 3.38
    57 United Kingdom 3.36
    58 Mauritania 3.34
    59 Hungary 3.33
    60 Colombia 3.33
    61 Congo 3.30
    62 Bangladesh 3.29
    63 Estonia 3.28
    64 Papua New Guinea 3.27
    65 Lao PDR 3.21
    66 Slovenia 3.19
    67 Croatia 3.19
    68 Finland 3.19
    69 Namibia 3.14
    70 Greece 3.14
    71 Dominican Republic 3.12
    72 Ireland 3.09
    73 Nicaragua 3.07
    74 Canada 3.02
    75 Czech Republic 3.02
    76 Argentina 3.02
    77 Latvia 2.99
    78 Bolivia 2.97
    79 South Africa 2.96
    80 Costa Rica 2.94
    81 Lithuania 2.91
    82 Netherlands 2.84
    83 Mongolia 2.81
    84 Peru 2.77
    85 Moldova 2.76
    86 Belgium 2.74
    87 Denmark 2.73
    88 Saudi Arabia 2.66
    89 Sweden 2.60
    90 United Arab Emirates 2.53
    91 Macedonia 2.53
    92 Russia 2.51
    93 Uruguay 2.41
    94 France 2.37
    95 Mauritius 2.31
    96 Algeria 2.23
    97 Japan 2.13
    98 Ecuador 2.12
    99 Oman 2.10
    100 Kazakhstan 2.09
    101 United States 2.09
    102 Jamaica 2.04
    103 Chile 2.03
    104 New Zealand 2.01
    105 Iran 1.97
    106 Venezuela 1.93
    107 Albania 1.91
    108 Georgia 1.90
    109 Kuwait 1.87
    110 Gabon 1.80
    111 Italy 1.62
    112 Norway 1.61
    113 Austria 1.60
    114 Turkmenistan 1.57
    115 Botswana 1.54
    116 Azerbaijan 1.47
    117 Qatar 1.36
    118 Australia 1.36
    119 Cuba 1.25
    120 Libya 0.69
    121 Trinidad and Tobago 0.67
    122 Germany -1.33
    While the Atlas contains trade data for 128 countries, only 122 countries met the minimum requirements necessary for the methodology behind our growth projections.

     – South Asia and East Africa top the list, while oil-driven economies face the sharpest fall in new growth projections and rankings of productive dynamism for 128 countries, as presented by researchers at the Center for International Development at Harvard University (CID). Using their own measure of economic complexity that captures the productive capabilities embedded in a country’s exports, CID researchers paint a new picture of the economic growth landscape, which foresees growth in emerging markets to continue to outpace developed countries. They also predict important reversals among growth leaders, with India expected to overtake China.
    After decades spent trailing the growth of its northern neighbor and economic rival, India now tops the projections of annual growth rates to 2023. This finding adds to the recent debate over India’s own revisions to its 2014 growth statistics, which showed India’s growth edging out China for 2014.
    Projections of GDP Growth to 2023 Rankings: Selected Top Countries
    Source: The Atlas of Economic Complexity, 2015. Harvard Center for International Development. Note: Rankings out of 128 countries.

    “Our Economic Complexity predictions find India’s disputed upper hand in growth will expand into a widening gap in the medium-term, with growth projections to 2023 predicted to be at 7.9 percent annually, well ahead of the 4.6 percent projected for China,” said Ricardo Hausmann, Professor of the Practice of Economic Development at Harvard Kennedy School (HKS), the leading researcher of The Atlas, and the director of CID.
    Relative to China’s 9.1 percent annual growth of the past quarter century, this growth projection presents an important slowdown for China, but stands just below the 6 percent growth rate in 2020 predicted by the IMF and China’s leadership.
    CID’s projections are also bullish on East Africa. Four East African countries – Uganda, Tanzania, Kenya, and Madagascar – rank in the top ten, with all predicted to grow at least 6 percent annually. The projections also favor Pakistan’s potential, at 5.1 percent predicted growth, presenting a clear picture of South Asia and East Africa’s positive growth outlook. Southeast Asia also includes several high-growth countries, driven by its largest country, Indonesia, which is anticipated to grow at 5.2 percent annually to 2023.
    Outlooks for Europe and the U.S. show little optimism. The U.S. growth rate in 2023 is predicted to be 2.4 percent, while major European players range from 2.3 percent in Italy to 3.7 percent in Spain. Among OECD countries, Turkey holds the greatest optimism, at 5.3 percent growth. Overall, the model predicts significant convergence in global incomes, with significant catch-up in parts of Sub-Saharan Africa and Southeast Asia.
    Economic Complexity Index: Rank of Expected GDP Growth to 2023
    Source: The Center for International Development at Harvard University. Economic Complexity Index. 2015



    “Countries accumulate productive knowledge by developing their respective capacity to make both more products, and products of increasing complexity—this underpins economic growth,” said Hausmann. “Countries like India, Kenya, and the Philippines have made important recent gains in diversifying their exports into more complex products. Historically, these gains in economic complexity have translated into higher incomes, which position them as the frontrunners globally for their growth prospects.”
    CID’s projections are based on newly released 2013 global trade data and The Atlas of Economic Complexity, an online tool which measures a country’s productive knowledge and predicts its rate of growth. Productive knowledge – the knowledge that goes into making products – captures more relevant information as to the drivers of economic growth, to provide a more accurate explanation for why countries are rich or poor. The Atlas shows remarkable accuracy in predicting future economic growth. Relative to the leading measures of governance, competitiveness, and education, The Atlas’ Economic Complexity measures are found to best forecast growth rates—with 10 times greater accuracy than the World Economic Forum’s Global Competitiveness Index.

    New Country Rankings in Economic Complexity

    Along with the growth projections, CID released the new 2013 Economic Complexity Index (ECI). The ECI ranks countries based on the average complexity of their export basket, using the same indicator that generated the growth projections. Of the countries that made the greatest improvements in ECI from 2003-2013, four of the top five are in Sub-Saharan Africa: Zambia, Tanzania, Uganda and Malawi. The region is not uniformly improving, however, as Mauritania, Namibia, and Zimbabwe are among the group with the worst declines in ECI. Policy approaches toward diversification and the management of commodities, like oil, increasingly diverge within regions and underpin differing economic outcomes.
    Biggest Winners and Losers in Economic Complexity: 2003-2013
    Source: The Atlas of Economic Complexity, 2015. Harvard Center for International Development. Note: Rankings out of 128 countries.
    The Economic Complexity growth projections underscore that not all exports are created equal. Rather, moving into greater productive diversity and more complex exports may hold the secret to countries’ growth prospects.
    The countries that slipped the most in the complexity rankings are all commodity-driven economies, including Libya, Venezuela, Namibia, Georgia and Qatar. After a decade that saw oil prices triple to $98 at the end of 2013, oil-based economies translated higher prices into larger export value, becoming some of the fastest growing countries over the 2003-2013 period. This growth is not expected to be sustained; however, as CID’s growth projections show the concentration of exports in oil has come at the expense of greater diversification into other industries not as sensitive to price fluctuations. The dramatic decline in oil prices in mid-2014 bear out these risks: these oil-driven economies have witnessed downward revisions to their official growth projections, with a correction more closely aligned to the CID projections.
    “Resource wealth appears to be rife with pitfalls that inhibit the diversification of productive knowledge into more complex areas, as seen from Libya to Venezuela to Qatar,” said Sebastian Bustos, a lead CID researcher on the project. “But this is not destiny, as Oman and the United Arab Emirates show the scope of what is achievable by focusing on productive capabilities and strategically increasing the complexity of one’s exports, starting from nearby products that rely on similar capabilities to those currently present in the country.”
    The top of the rankings remain largely unchanged, with Japan, Switzerland, and Germany maintaining the greatest diversity in productive knowledge. The United States ranks 12th in the 2013 rankings, slipping four places over the prior decade. South Korea, by contrast, has shown the greatest rise among the leaders, up 13 spots to fourth. Other top risers are China (up 14 spots to 23rd), and Thailand (up 12 spots to 25th). When comparing a country’s ECI rankings to its income per capita over time, the growth projections look favorably on those countries, like Vietnam, that show the capabilities to produce more complex products than expected by its current income level. At 66th globally, Vietnam now outranks countries with significantly higher income per capita, like Chile (67th) and Australia (76th), as predictive of higher income growth in Vietnam. This pattern holds at the other extreme, too, where previous iterations of the rankings showed Greece as an outlier for having a higher income level than expected for its level of complexity, predicting a dip in growth.
    Economic Complexity Index: 2003-2013 Country Rankings – Top 25 Countries
    Source: The Center for International Development at Harvard University. Economic Complexity Index. 2015

    About the Center for International Development

    The Center for International Development (CID) at Harvard University is a university-wide center that works to advance the understanding of development challenges and offer viable solutions to problems of global poverty. CID is Harvard’s leading research hub focusing on resolving the dilemmas of public policy associated with generating stable, shared, and sustainable prosperity in developing countries. Our ongoing mission is to apply knowledge to and revolutionize the world of development practice.

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    A Note on Trump: We Are No Longer Entertained




    Earlier today, the candidate currently leading in the polls for the Republican presidential nomination called for a "total and complete shutdown of Muslims entering the United States." That was, of course, Donald Trump. As Jeffrey Goldberg just tweeted, "Donald Trump is now an actual threat to national security. He's providing jihadists ammunition for their campaign to demonize the US."
    On the heels of Trump's proposed change for America, we will be changing how we cover him at The Huffington Post. Back in July, we announced our decision to put our coverage of Trump's presidential campaign in our Entertainment section instead of our Politics section. "Our reason is simple," wrote Ryan Grim and Danny Shea. "Trump's campaign is a sideshow."
    Since then Trump's campaign has certainly lived up to that billing. But as today's vicious pronouncement makes abundantly clear, it's also morphed into something else: an ugly and dangerous force in American politics. So we will no longer be covering his campaign in Entertainment. But that's not to say we'll be treating it as if it were a normal campaign.
    Our decision in July was made because we refused to go along with the idea, based simply on poll numbers, that Trump's candidacy was actually a serious and good faith effort to present ideas on how best to govern the country. We continue to believe this to be true -- and will continue to let it guide our coverage -- but much has changed.
    Yes, there was certainly no shortage of ugly comments from the beginning, as he kicked off his campaign with outrageous comments about Mexicans. But at first, this over-the-top xenophobia, though disgusting, played as the sour shtick of a washed-up insult comic. Now that Trump, aided by the media, has doubled down on the cruelty and know-nothingness that defined his campaign's early days, the 'can you believe he said that?' novelty has curdled and congealed into something repellent and threatening -- laying bare a disturbing aspect of American politics.
    We believe that the way we cover the campaign should reflect this shift. And part of that involves never failing to remind our audience who Trump is and what his campaign really represents.
    As Jay Rosen recently observed:
    "To an extent unrealized before this year, the role of the press in presidential campaigns relied on shared assumptions within the political class and election industry about what the rules were and what the penalty would be for violating them ... These assumptions were rarely tested because the risk seemed too high, and because risk-averse professionals -- strategists, they're called -- were in charge of the campaigns."
    That is, most politicians knew not to say outlandish and offensive and dangerous things because they knew they'd be punished for it. As Rosen continues, "Those beliefs have now collapsed because Trump 'tested' and violated most of them -- and he is still leading in the polls."
    But that doesn't mean we in the media should in any way let Trump or those who would follow his footsteps off the hook. So as we cover his daily campaign, we'll constantly remind the public of what he stands for, citing references and providing links.
    For example:
    1) His enthusiasm for creating a database of all Muslims in the United States.
    2) His ongoing lies about Muslims in New Jersey celebrating 9/11.
    3) His status as birther-in-chief, cynically sowing doubt about President Obama's legitimacy as the duly elected President of the United States.
    4) His misogyny -- here's just one Huff Post piece on this, but there's no shortage of these.
    5) His xenophobia and scapegoating of immigrants, including his lies about Mexican immigrants and his ardent desire to deport millions of undocumented immigrants.
    6) His unmistakable passion for bullying. Again, there's no shortage of examples, but you could start with his defense of supporters who roughed up a protester at one of his rallies or his ridiculing of a disabled New York Times reporter.
    And we're happy to see we're not alone in our desire to present the unvarnished, un-euphemized Trump. Last week, The Washington Post's Dana Milbank opened a column by writing, "Let's not mince words: Donald Trump is a bigot and a racist." And he went on to back that up, which isn't hard and is the approach any reporter with an interest in telling the truth to his or her readers should adopt.
    So if Trump's words and actions are racist, we'll call them racist. If they're sexist, we'll call them sexist. We won't shrink from the truth or be distracted by the showmanship.
    Of course, Trump isn't the only candidate out there spouting extreme and irresponsible messages, but he's in a unique position in the wall-to-wall coverage, from Meet the Press to SNL, that he elicits. By not calling out Trump's campaign for what it is, many in the media, addicted to the ratings buzz he continues to deliver, have been legitimizing his ugly views.
    As we've seen in the Republican race so far, Trump's worst comments don't occur in a vacuum -- or land without repercussions. They affect the tenor of the conversation, frequently moving the line between what's considered mainstream and what's considered unabashedly extreme and unacceptable.
    So we'll not only be covering the ways Trump's campaign is unique in recent American politics, but also the disastrous impact it continues to have on his fellow candidates -- and the national conversation.

    A Note from Shyam

    Agree with you on everything Arianna Huffington 

    However the unfortunate fact is that He is leading the campaign of Republican candidates. There are good chances of his being nominated as a Presidential Candidate. And who knows he has 50-50 (50%) changes of being the next President of the United States.

    In India too, we have a similar situation. An atmosphere of Intolerance is prevailing among the supporters of the ruling party BJP. They are persecuting the Muslims in all possible manner. Physically, Mentally, and Psychologically. 

    WE ARE NOT TRUE HUMAN BEINGS,IF WE CONSIDER A PART OF OUR RACE UNWANTED. IT IS HIGH TIME WE RELATING TERRORISM TO ISLAM.

    #DonaldTrump, #US_PresidentialElection2016, #PresidentialElection,

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    Shyam's take on HR analytics

    I agree with Vinay on the need for HR analytics in the diverse cross culture environment in India.

    However the accuracy and usefulness of the data depends on the quality of its integration.
    This is possible only when the Data Scientists have also knowledge about HR domain. Otherwise the inference we draw will have a huge margin of error and so will the action on the benefit of it.

    I suggest that, after drawing inference from the data. The HR specialist should interact with the concerned employees to authenticate the results. If personal interaction is not possible, they can send out a questionnaire and prepare reports based on the employee inputs. And  when taking a decision or inferring an opinion, it is suggested that data output along with the Report of the actual interaction with the employee should be taken into account before coming to a conclusion.

    Specially when working on the Predictive analytics, it essential that, the stats are as closer to reality as possible.




    How is HR analytics changing people management?



    It is developing an engaged, agile and flexible workforce by making use of data to obtain valuable insights on the employees.


    How is HR analytics changing people management?          

    In today’s VUCA (volatility, uncertainty, complexity, and ambiguity) landscape, small and big companies are continually facing uncertainty and volatility in their operations. The working environment is increasingly becoming very complex and ambiguous. This has put human resources into a challenging situation in terms of making definitive decisions in the workplace. HR has to look constantly at new tools for making risk-free decisions, and this is where the help of HR analytics comes in.
    HR analytics is the use of statistical methods like factor analysis, correlation and regression and making use of different sources and variables to arrive at meaningful insights. It helps HR understand the dynamics in the workforce.

    One cannot rely on a person’s experience or tacit knowledge to base one’s decisions on, but on real data and numbers to back one’s workplace decisions. This has proved to add value and improve workforce resource utilisation and deployment. HR analytics is not about merely collecting vast amounts of data, but analysing and processing it to provide meaningful insights. These insights are then used to provide the answers sought by the company, to the following questions, among others:

    • Will the predictive attrition model help identify who is going to resign in the next, three, six or 12 months? What is the efficiency factor of this predictive model?

    • Is the new tax-friendly employee compensation and benefits programme driving higher retention?


    • Are the highly engaged employees at the workplace highly productive? Are they spreading positive employer brand in the workplace and social media?


    • Will work from home/flexible working hours lead to better engagement, and to what extent?


    • Which generation of employees (Gen X, Gen Y, Gen Z , Millennial) is contributing more towards profitability?


    • What are the major reasons for attrition? Is the preventive HR intervention effective in controlling attrition?


    • Is there any correlation in employees who are leaving within six months of joining?


    • Is there any relation between employees who stay within 10 km radius and retention?


    • Is the newly designed Employee Fraud Risk Management effective?


    Is there any correlation between frauds committed by habitual noncompliant employees/ disengaged employees?

    Finance function decisions are based on data, such as graphs, charts, etc. However, in HR, it is based mostly on the relationship component and there is always the risk of being judgmental when it’s a person making decisions. Through HR analytics, this risk can be minimised.

    HR can study the behavioural competencies of high-potential employees and share the data with the recruiting team to help them identify potential employees. This data can also be used in training. HR often comes up with various mechanisms intended to achieve employee satisfaction, leading to employee engagement. But today, the mechanism depends on what the employees value more and whether it is going to achieve the outcome.

    Based on the HR analytics data, human resource policies are customised, for example, the recent decision by the Government of Delhi regarding the odd and even number cars taking turns to run on the roads. This has led some companies to offer Delhi metro cards to employees and encourage them to take local public transport instead of using their cars. Some companies are exploring the option of working from home.

    People management is being accomplished with change thanks to evolving HR analytics. It gives a clear view of performances and drives the organisation towards its goals. This has led managers to understand their employees better and contribute towards planning for their training and development. In turn, the employees will be motivated to be more in tune with the culture of the organisation.

    People analytics empowers HR with the ability to identify the gaps between employees and training, which is necessary to be bridged. This is especially important with new hires to help them understand expectations and workflow processes quicker. By digging into insights, HR managers can not only identify which hires will be low but also the high performers.

    Predictive analytics contributes to analysis of the workforce beyond the mere basis of academics. While recruiting, many companies look for candidates with high academic records. But this is not full proof of a candidate’s ability to perform. Some bugging questions come to mind:

    Why does one programmer perform better than the other?

    • Why do some average employees succeed while some perceived as good recruits fail?


    • How much time does it take the new employee to be productive?


    One way to employ the use of HR analytics is acceptance and deployment of HR management systems and cloud storage availability. These make it possible for organisations or companies to store all their data in a manner that can be integrated with other workplace operations.

    Such cloud software today is readily available and affordable. It is time for employers to take advantage of this progress. By deploying HR analytics, companies collect data based on attrition, retention and other HR aspects. These metrics are then used further to look for trends based on ratios and accounts. The data is then vigorously analysed to give Google insight into employee trends.

    These insights could be effectively used to shape the organization’s policies and decisions.

    Businesses have noted that the ability to take initiative is a better indicator of actual performance.
    Companies are deploying predictive analytics to drive their HR strategies. Employee data from all locations is analysed and processed to develop programmes based on age, demography and tenure. Information from predictive analytics/HR analytics is used to attract, retain and manage the right talent. To change the course of the manner in which they deal with employees, data-based information is used like predictive attrition models and exit analyses. This predictive modelling tactic is more handy than trying to figure out later why an employee left.

    The new approach of HR/predictive analytics provides the ability to measure, quantify and qualify employee data. The new method digs into the ‘why’ rather than the ‘what’ to get the better perspective of things.

    HR analytics helps to develop a workforce that is engaged, agile and flexible by using data to gain valuable insights on employees. In the diverse Indian context, the need for HR analytics is felt even more because every company has a broad array of people to manage. Proper management of this varied workforce is a prerequisite for greater synergy and productivity within an organisation. Companies must look towards HR analytics as the new tool to power an organisation’s success through smart people management.

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    The Innovative Power of Criticism.




    The business world is awash in ideas for new products, services, and business models. Thanks to powerful ideation approaches such as design thinking and crowdsourcing, it has become incredibly easy and relatively inexpensive for companies to obtain a vast number of novel concepts, from both insiders and outsiders such as customers, designers, and scientists. Yet many organizations still struggle to identify and capture big opportunities. A division head at a global consumer electronics corporation recently told me, "We have a mass of ideas, but honestly, we don’t know what to do with them. While we’ve tried to explore some unusual avenues, we’ve ended up committing ourselves to ideas that are already familiar." From what I have observed, his company is the rule rather than the exception.

    Why is this the case? Clayton Christensen, of disruptive innovation fame, and W. Chan Kim and Renée Mauborgne, the inventors of "blue ocean strategy," have shown that big changes in society and technology fundamentally challenge the conventional understanding of what is valuable. Those changes render obsolete whatever criteria companies are using to identify customer problems they could address. To see which ideas truly have potential, managers need new assessment criteria.

    From studying and working with 24 companies that have captured big opportunities, I discerned how to create such criteria and synthesized those companies’ individual approaches into one four-step process, which I now advise organizations to employ. (The steps can be useful individually as well.) My process is a complement to Kim and Mauborgne’s "strategy canvas" for coming up with a blue ocean strategy and Christensen’s "jobs to be done" framework for finding disruptions. About a dozen companies are now adopting it, including two major consumer-packaged-goods firms, a high-end fashion company, and a manufacturer of optical cables.

    Unlike design thinking and crowdsourcing, which rely on the art of ideation, my process is rooted in the art of criticism. Instead of soliciting early input from customers and other outsiders, it engages a company’s own employees. It helps them articulate their individual visions and then compare and discuss their contrasting perspectives in order to distill them into a handful of even better proposals. The views of outsiders are sought only at the end.

    The Art of Criticism
    Whether for products, services, processes, or business models, two levels of innovation are possible: improvements and new directions.

    Improvements are novel solutions that better satisfy existing definitions of value. Whether incremental or radical, they address problems that are already widely recognized in the marketplace. Consider residential thermostats. Most companies in this business assume that their main value lies in enabling people to better control the temperature in their homes. Innovation has therefore focused on creating digital thermostats with novel features such as touchscreen displays with multiple menus, day-of-the-week schedules, different room settings, and programmable fans.

    In contrast, new directions arise from reinterpreting the problems worth addressing. They redefine what customers value. In November 2011 Nest Labs came up with a brand-new value proposition for thermostats: to help people be comfortable in their homes without having to fuss with the temperature. Its founders understood that the complexity and unpredictability of family life in America had made it nearly impossible to program a thermostat with a regular schedule. In addition, they saw that the technology of sensors and mobile phones had matured to the point where temperatures could be set through simple interactions, which would appeal to people fed up with complicated interfaces.

    Nest’s Thermostat


    It learns the habits of a home’s inhabitants and automatically sets the temperature. Nest’s founders saw that the unpredictability of family life, exasperation with complicated interfaces, and technological advances had made possible a new value proposition.



    Users switch the thermostat on or off with its straightforward rotary interface or a smartphone; the device requires no programming. Equipped with sensors that detect whether people are in the house, it automatically adjusts the temperature to save energy when no one is home. In a few days, the thermostat learns the habits of the household and takes care of the temperature settings itself. The software platform is open, allowing third parties to build complements for the thermostat. Although Nest does not release sales figures, it claims to have sold millions of its thermostats, which retail for about $210 to $250. In 2014 Google bought the company for $3.2 billion.

    It is highly unlikely that Nest’s geeky founders, who initially had vague ambitions to create a "smart home," would have pursued their thermostat if they had relied on currently popular methods of innovation. Generating lots of ideas works well for improvements, but it doesn’t help to spot new directions. If companies don’t change the lens through which they assess ideas, they won’t be able to identify the outsiders they should seek, know what questions to ask them, and recognize their most valuable input. As a result, they will tend to pick customers and other outsiders who support their current directions and dismiss ideas that lie off the beaten path. Indeed, most of the ideas incorporated in the Nest thermostat were already known to the industry, but none of the existing players recognized their potential.

    In order to find and exploit the opportunities made possible by big changes in technology or society, we need to explicitly question existing assumptions about what is good or valuable and what is notand then, through reflection, come up with a new lens to examine innovation ideas. Such questioning and reflection characterize the art of criticism.

    "Criticism" comes from the Greek word krino, which means "able to judge, value, interpret." Criticism need not be negative; in this context it involves surfacing different perspectives, highlighting their contrasts, and synthesizing them into a bold new vision. This is a significant departure from the ideation processes of the past decade, which treat criticism as undesirablesomething that stifles creativity. Whereas ideation suggests deferring judgment, the art of criticism innovates through judgment.

    In my four-step process, individuals question their assumptions and come up with new interpretations of customer problems that their company could solve. Then people work together in pairs to refine their visions before moving into a larger group for discussion. Finally, the best ideas are tested by users and by internal and external experts in a wide range of fields. Because none of the original 24 companies behind the method employed all the steps, I will illustrate it with several cases, including Vox, a mid-size furniture manufacturer in Poland; Nest; Microsoft; and Alfa Romeo.

    Individual Reflection
    Imagine that you’re a manager who perceives major transitions under way and big opportunities emerging. How can you spur innovation so that your company can capture those opportunities? Piotr Voelkel, the founder and chairman of Vox, faced this question. He was concerned by major changes in customer demographics, particularly the aging of the European population. He felt that in order to prosper in the future, Vox needed a novel interpretation of what furniture should be. To come up with it, Voelkel chose 19 people in his organization, including himself, and asked each to reflect on how Vox could create a new offering for an aging population. He was careful to assemble a heterogeneous group: Some held senior positions; others were promising young talent. Some had long experience in the industry; others had come from outside it. They represented a variety of departments, including sales, marketing, product development, manufacturing, design, and branding. Some were more analytical by nature; others were more intuitive. What they had in common was that their roles in the company or their personal interests were likely to have led to insights.

    After a briefing, Voelkel asked the members of the group to spend time thinking about one or more proposals for products or services or business models. To ensure that they would focus on new directions rather than mere improvements, he gave them a strict directive: Solutions should be based on brand-new concepts of value. To make the new direction explicit, each proposal should contain an arrow indicating the change from the existing value proposition to the proposed one.

    This approach differs from popular innovation methods in several ways. First, Voelkel did not ask his people to start with the insights of customers or other outsiders; he asked them to start with their own. We all sense changes in our environment, and we all have hunches, both conscious and subconscious, about how the world might become better. We often keep these personal hypotheses private. Voelkel understood this, so he asked the members of the group to make their hypotheses explicit. Once made explicit and then challenged, those intuitions would become precious raw material for creating new visions. And the process would combat the natural tendency of individuals to let their subconscious intuitions affect how they perceive the insights of others. Voelkel realized that participating in the exercise himself would enable him to more clearly see and objectively consider visions that would ultimately have been proposed to him.

    Second, Voelkel asked everyone to reflect alone rather than as a team. This allowed people to dig deep into their own insights and not dilute or withhold them, as they might in a group brainstorming session. It gave each person freedom to perform the task as he or she saw fitrelying on a particular analytical framework, on data, or simply on intuition. This increased the likelihood that the 19 would propose diverse directions.

    Third, he gave people one month for reflection. They were expected to keep performing their regular jobs, but the time was sufficient for each individual to sketch out thoughts, let them percolate for a few days, and then refine them and add new ones. This is especially important for coming up with provocative or outlandish hypothesesthose that are often so blurred in the early stages that they can be quickly dismissed.

    One person suggested that Vox think about bedroomsthe focus of only minor innovation in recent decades, but a place where elderly people spend a significant amount of time, especially when sick. He suggested transforming bedrooms fromplaces for rest into places that contribute to health: For example, the beds might contain devices that the elderly could use to do simple exercises. Inspired by projections of decline in the birth rate as well as growth in the elderly population, another participant imagined a day when grandparents would compete for time with their rare grandchildren. She envisioned a change in home furniture from being decorative and functional to being a means of socializing with relativesfor example, tables that could be easily converted into spaces for cooking, painting, or playing. When the month was up, the 19 people had envisioned 90 possible directions (seven of them Voelkel’s).

    Sparring Partners
    In the second step each person subjects his or her vision to the criticism of a trusted peer. The peer acts like a sparring partner, providing a protected environment in which the person can dare to share a wild or half-baked hypothesis without being dismissed.

    A relationship like this was instrumental in the creation of Nest. Tony Fadell and Matt Rogers, the company’s founders, had previously worked together at Apple. In an interview with Derek Andersen, of Startup Grind, a community of entrepreneurs, Rogers described how the two had shared early visions at a lunch meeting. Rogers had begun by saying, "Tony, I want to start a companyand I want to start a company with you."

    "What do you want to do?" Fadell replied.

    "I want to build a smart-home company."

    Fadell was building a new house at the time and was privately contemplating a similar rough idea. But he said, "You’re an idiot. No one wants to buy a smart home. Smart homes are for geeks."
    The conversation could have stopped there. But because the two liked, respected, and felt safe with each other, they continued to talk, dug deeper into each other’s ideas, and eventually decided to focus first on the thermostat.

    In his book Collaborative Circles: Friendship Dynamics and Creative Work, Michael P. Farrell shows that pairs have been the foundation of many breakthroughs in art and society, especially when the definition of "good art" was challenged. He explains that working in pairs creates an environment of "instrumental intimacy" in which people can sympathetically and constructively criticize each other.
    The first daring experiments in impressionism, for example, were conducted in pairsby Claude Monet and Frédéric Bazille and by Pierre-Auguste Renoir and Alfred Sisley, and later by Monet and Renoir. Farrell also mentions the authors J.R.R. Tolkien (The Hobbit, The Lord of the Rings) and C.S. Lewis (The Chronicles of Narnia), who discovered that they shared an interest in what Lewis called "Northern-ness."

    Trusted peers provide a protected environment for sharing half-baked ideas.

    Recent history is full of pairs who created legendary companies: Steve Jobs and Steve Wozniak, Sergey Brin and Larry Page, Bill Gates and Paul Allen, to name a few. I’ve found that pairs can also play a key role in the innovation process at established organizations. An example is Microsoft’s successful 1999 venture into the game-console market with the Xbox. Previously Microsoft had focused on software, most notably productivity applications. A move into hardware, young consumers, and entertainment was a radical departure; furthermore, it involved creating an operating system that was incompatible with Windowsan act that would once have been considered heresy.
    What triggered the Xbox effort was Sony’s announced plan to introduce its PlayStation 2 game console. Bill Gates realized that it posed a serious threat to Microsoft: Households could be enticed to enter the world of computing through consumer-friendly game consoles instead of PCs. He issued a call for fresh ideas about what Microsoft should do.

    Microsoft’s Xbox

    COURTESY OF MICROSOFT

    The system sprang from a vision in which gaming would be regarded as high art, game developers would be the artists, and Microsoft would provide developers with technology to freely express themselves.



    There are always people in large established companies who silently develop theories about how unfolding changes in the world might redefine markets. Microsoft is no exception. Four radicals at the company were Jonathan "Seamus" Blackley, a recent hire with significant experience in digital-game technologies; Kevin Bachus, a product marketing manager for DirectX, Microsoft’s software tool for designers who developed games for the PC; Otto Berkes, a DirectX programming whiz; and Ted Hase, a manager in the developers relations group. Although they worked in different parts of the company, they shared a rudimentary vision: a world in which gaming would be regarded as high art, game developers would be the artists, and Microsoft would provide them with the most powerful technologies available so that they could freely express themselves. This would require a platform designed explicitly for game artists.

    If someone had suggested such a thing in a workshop where various ideas were discussed, it might well have been dismissed or reframed and diluted to fit the existing way of doing business. But that’s not what happened. The four renegades met for a few weeks. They alternated between working in pairs (Blackley with Bachus and Berkes with Hase) and as a quartet. Blackley and Bachus became so close that others dubbed them "Laurel and Hardy." During their sessions together, Bachus worked to strengthen the business case for Blackley’s proposal.

    In Dean Takahashi’s book Opening the Xbox: Inside Microsoft’s Plan to Unleash an Entertainment Revolution, he recalled: "I refocused it. I said, ‘Let’s think about what kind of consumers we’re building this for, and how to get game publishers onboard.’" Through this process, the four transformed their vague notions into a robust vision that eventually withstood the harsh skepticism of others at Microsoft, including some senior executives.

    How can you find a sparring partner who shares your general vision? You needn’t have had a previous relationship, as Fadell and Rogers did. Nor must companies rely on serendipity (Blackley had been hired just a few weeks before he started to collaborate with Bachus and the others). The odds can be improved with a sort of speed-dating process whereby people with similar visions can find each other and agree to work together to polish their ideas. After step one, in which individuals reflect independently on possible directions, invite them to a meeting and ask them to briefly illustrate their ideas, which can be posted on a wall. Then have each person choose another’s idea that he or she would like to explore. If more than one person chooses the same direction, ask them to indicate a second and, if necessary, a third choice. Voilà, you have your pairs.

    Radical Circles
    In step three these promising hypotheses are subjected to deeper criticism through discussion in a group of 10 to 20 people who have envisioned other new directions. I call this group a radical circle. Its purpose is not to decide which hypotheses are right or wrong; it is to judge why and how they are different, what important underlying insights might have been overlooked, and whether a value proposition even more formidable than all the hypotheses might be found.

    This exercise, which can be held in an intense two- or three-day workshop or over the course of four weeks, needs to be conducted carefully so that it is constructive, not destructive. Clashes should push people to dig deeper and identify more innovative spaces, and shouldn’t constrain thinking or compromise good ideas.

    The circle should include people with a variety of backgrounds, perspectives, and personalities—like those of the 19 people at Vox. At Microsoft, about a half-dozen managers joined Blackley, Bachus, Berkes, and Hase in plotting the company’s gaming path. Blackley and Bachus had the most radical vision: Abandon Windows and don’t make game makers pay royalties. The vice president of Microsoft’s hardware division wanted to create something that was compatible with Windows. In the middle was James "J" Allard, a respected figure within the company who had successfully championed big transitions in the past, including Microsoft’s embrace of the internet in the mid-1990s.




    You can keep the process positive and creative by having the radical circle focus initially on where everyone believes the company should not go and who its enemies are. Often members can converge more easily on what they dislike than on what they like, and a common enemy is a powerful incentive to come together and articulate a new direction. Although the members of Microsoft’s radical circle had different visions, they agreed that the enemies were Sony and its new PlayStation 2 console, along with their own company’s strategy of pursuing a generic, PC-based approach to games. (The team named the Xbox endeavor Project Midway, after the sea battle between the U.S. and Japanese navies that was a turning point in World War II.)


    Then contrast the visions and try to combine them, two at a time. Are there places where they overlap? Are there strong elements of the individual visions that didn’t occur to others? At Vox, after the 19 had independently developed their hypotheses, they got together for a three-day workshop. The strategy that the company ultimately pursued grew out of a combination of the two unrelated directions mentioned above: an active role for bedrooms, and home furniture that offered possibilities for socialization. It was called the "living bedroom," a central space in a house where the elderly could pleasurably spend time with relatives and friends. One product, launched in 2012, is a bed that incorporates a large bookshelf, space for visitors to put their shoes, and a folding screen for projecting movies. As of this writing, Vox had sold nearly 3,600 of these beds in Poland and neighboring countries, and unit sales were growing at 88% a year.


    Alfa Romeo, too, created a vision. The brand has a legendary history: It was the first to win a Formula One race, and it produced such famous models as the Spider Duetto convertible driven by Dustin Hoffman in the movie The Graduate. But for a couple of decades the company struggled to compete in the premium segment, which German manufacturers dominate. To address this challenge, Alfa Romeo launched an innovation project in 2010 that involved a radical circle of about 20 people. One proposal was to move from the prevailing notion that people buy premium cars to display their wealth (cars as luxury goods) to a concept of premium cars as a means for people to express their passion for driving. Another was that a car’s agility and responsiveness to the driver’s commands—rather than a superpowerful engine and a high maximum speed—would be critical elements of the value proposition.


    Alfa Romeo’s 4C Sports Car





    Courtesy of Alfa Romeo FCA COURTESY OF ALFA ROMEO FCA


    To compete in the premium segment, the company came up with a new concept: a car that would allow people to express a passion for driving, rather than their wealth, and would be agile and responsive, rather than superfast and superpowerful.



    The team combined the two ideas and proposed that the company focus on building responsive cars for skilled, passionate drivers. One member used a helpful metaphor, comparing the premium car industry to the Michelin Red Guide, which recommends luxury restaurants to inexpert tourists. The vision that emerged was likened to the Lonely Planet guide, which passionate expert travelers use to find restaurants off the beaten path.


    An instantiation of the resulting strategy is the Alfa Romeo 4C, launched in 2013. Compared with many other sports cars on the market, it is less expensive, has a small engine, and is light—thanks in part to an extensive use of carbon fiber and stripped-down equipment (for example, the car has neither an assisted-steering system nor carpets). But its power-to-weight ratio is comparable to that of much more expensive sports cars, such as Ferraris. The concept was a hit: Within a few weeks of the car’s release to the market, the entire first year of production had been booked by consumers.


    Outsiders


    A radical circle may converge on one or a few possible directions, which should then be subjected to the criticism of outsiders—step four. Remember that, unlike open innovation approaches, involving outsiders is not intended to generate new ideas. Rather, it is meant to raise good questions—to challenge the innovative direction you propose in order to help you strengthen it. In addition to targeted users, outsiders should include experts from far-flung fields with novel perspectives. I call them interpreters, because of their ability to find meaning in trends that might not occur to the product’s users.


    After considering more than a hundred candidates, Alfa Romeo tapped 14 interpreters of the travel experience. Most came from outside the auto industry’s typical networks: Among them were, for example, a maker of leather goods, the CEO of a high-end resort, a manufacturer of fitness equipment, and a theater director who had just written an irreverent piece about how modern wealthy people perceive themselves. The Alfa team briefed them on the hypotheses underlying its novel vision and then met with them to discuss and challenge those assumptions.


    Similarly, when Philips Electronics was developing its Ambient Experience for health care, a breakthrough application for reducing the anxiety that patients often experience when they undergo medical scans, it tapped a wide range of interpreters—both the usual suspects (doctors, hospital managers, engineers of medical equipment, marketing experts) and people from unusual domains (architecture, psychology, contemporary interior design, LED technology and video projection, interaction design, interactive hardware and software). A child psychologist refined Philips’s vision by addressing anxiety not only during the exam but also in the waiting room beforehand. And in Vox’s bed project, a spa and aromatherapy specialist advised against designing the bed explicitly for elderly people and suggested making it attractive to all kinds of customers. In addition to expanding sales to other market segments, this idea increased the bed’s appeal for the elderly. In "Designing Breakthrough Products" (HBR, October 2011), I describe how to find good interpreters.


    A common enemy is a powerful incentive for people to find a new direction.


    Classic strategy-analysis tools, such as Kim and Mauborgne’s strategy canvas and Alexander Osterwalder and Yves Pigneur’s business model canvas, are another means of challenging new directions. So is the large amount of data available from the web—for example, on customer preferences. You might consider assembling two data analytics teams, one to find data that supports the hypotheses of a new direction and the other to find data that undermines them, and then determine which results are more compelling.


    When seeking new solutions to existing problems, criticism may hamper the ideation process. But if it’s properly applied in discovering new problems and redefining value, criticism is an engine of innovation. By finding a new direction, a company can make sense of the myriad ideas for offerings and business models and recognize the handful that will really make a difference.



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    Intelligence ‘networks’ discovered in brain for the first time




    Scientists from Imperial College London have identified for the first time two clusters of genes linked to human intelligence.

    Called M1 and M3, these so-called gene networks appear to influence cognitive function which includes memory, attention, processing speed and reasoning.

    Crucially, the scientists have discovered that these two networks which each contain hundreds of genes are likely to be under the control of master regulator switches. The researchers are now keen to identify these switches and explore whether it might be feasible to manipulate them. The research is at a very early stage, but the scientists would ultimately like to investigate whether it is possible to use this knowledge of gene networks to boost cognitive function.

    Dr Michael Johnson, lead author of the study from the Department of Medicine at Imperial College London, said: "We know that genetics plays a major role in intelligence but until now haven’t known which genes are relevant. This research highlights some of genes involved in human intelligence, and how they interact with each other.

    What’s exciting about this is that the genes we have found are likely to share a common regulation, which means that potentially we can manipulate a whole set of genes whose activity is linked to human intelligence. Our research suggests that it might be possible to work with these genes to modify intelligence, but that is only a theoretical possibility at the moment we have just taken a first step along that road."

    In the study, published in the journal Nature Neuroscience, the international team of researchers looked at samples of human brain from patients who had undergone neurosurgery for epilepsy. The investigators analysed thousands of genes expressed in the human brain, and then combined these results with genetic information from healthy people who had undergone IQ tests and from people with neurological disorders such as autism spectrum disorder and intellectual disability.
    They conducted various computational analyses and comparisons in order to identify the gene networks influencing healthy human cognitive abilities. Remarkably, they found that some of the same genes that influence human intelligence in healthy people were also the same genes that cause impaired cognitive ability and epilepsy when mutated.

    Dr Johnson added: "Traits such intelligence are governed by large groups of genes working together like a football team made up of players in different positions. We used computer analysis to identify the genes in the human brain that work together to influence our cognitive ability to make new memories or sensible decisions when faced with lots of complex information. We found that some of these genes overlap with those that cause severe childhood onset epilepsy or intellectual disability.

    "This study shows how we can use large genomic datasets to uncover new pathways for human brain function in both health and disease. Eventually, we hope that this sort of analysis will provide new insights into better treatments for neurodevelopmental diseases such as epilepsy, and ameliorate or treat the cognitive impairments associated with these devastating diseases."

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    A  Look Ahead:  Employee Engagement Trends for 2016




    Here’s an understatement for the year ahead: The workplace is changing and engagement strategies are changing along with it.  Anyone involved in employee engagement knows that conventional wisdom has been turned on its head by a newly plugged-in and  charged-up generation of workers.

    How well do you know the people who come to work every day and how will you effectively engage  them in the next 12 months?

    Here’s a roundup of top-trending strategies  from BI WORLDWIDE to help make 2016 your most engaged and productive year ever.

    TREND: Focus on happiness Organizations have been trying to “sell” employees on engagement but what employees really want is happiness, pure and simple. Instead of declaring undying loyalty or planning long-term career intentions, employees want to enjoy their work, find meaning in it, be recognized when they do well and feel a sense of achievement.


    What can you do?

    Acknowledge contributions and effort. Go beyond the cookiecutter recognition program and create unique recognition tailored  to employees’ passions. • Recognize service. Don’t wait for the traditional five-year anniversary. Celebrate milestones early and often, including at  one month and one year. •

    Enhance your culture. Work should be somewhere employees want to be, not have to be. Don’t be afraid to give them opportunities to thrive.

    TREND: Ask more from managers Of course it’s true that the standard practice is to acknowledge contributions made across every level of the organization. But still, there’s an added zing when an immediate supervisor or manager notices—and recognizes—excellent work. Managers might need some help in spotting and rewarding desired behaviors but the effort will pay off in the long run.


    What can you do? 

    Train them. Let managers know why recognition is important  and the value it plays in reinforcing key behaviors. • Empower them. Research shows that when managers have recognition budgets to use at their discretion, employee tenure increases. • Communicate, then measure, then do it all again. Spread the word and keep checking back to make sure goals are being met.

    TREND: Make work meaningful In a market that’s increasingly shifting in job-seekers’ favor, employees are looking for more than “just a job” and are seeking work that’s personally meaningful.


    If employees aren’t using their skills and being challenged, they’ll move on. Hiring managers might be seeking someone to complete specific tasks immediately but they must also make sure even entry-level jobs provide opportunities to learn, contribute and grow. What can you do? • Ask, don’t tell. Instead of doling out an assignment and dictating the process to team members, challenge them to find improvements and recognize them at every step in the process. • Delegate a project that would not otherwise get done. Offer team members the opportunity to run with an idea that you haven’t had the chance to explore. Give them basic parameters to follow, then make them fearless by removing any consequences for failing.

    Let them lead. Turn over an existing project and let your team members manage everything, from strategy development through project management to leadership presentations. Hold the team accountable to the budget and timelines while letting them know you’re there for support.

    TREND: Lead with compassion Research by Dr. Brad Shuck, an internationally respected researcher on the psychology of engagement, and Maryanne Honeycutt-Elliott, expert in leadership development and executive coaching, has shown higher levels of engagement from employees who work for a compassionate leader—one who is authentic, present, has a sense of dignity, holds others accountable, leads with integrity and shows empathy. In fact, 74% of employees who work for compassionate leaders say they are unlikely to leave their current organization in the next five years.


    What can you do? • Translate strategic goals into individual goals. This requires authentically listening to others and working to leverage their strengths, as well as having a willingness to be flexible and adaptable. • Develop others. Focus outward–not inward–in a way that develops the skills, competencies and abilities of others. • Give and receive helpful feedback. Listen deeply and communicate well, and you will create credibility, trust and influence.

    TREND: Meet them where they are Innovative technologies allow employees to speak and be spoken to with relevance, and relevance leads to better results. They’re accustomed to pulling out their mobile devices whenever they have a spare minute and crave instant, easy access to news, apps, pictures, videos, statuses – all on their terms. They expect the same of their recognition program.

    What can you do? 


    See it, believe it and live it. Start with a clear direction that includes what you’re communicating and use multiple channels and touchpoints. • Make it easy. Give employees the ability to recognize each other on devices with which they’re comfortable. Incorporate social elements like news feeds, comments and sharing, built using responsive design or in a native app. • Mix it up. Offer multiple ways to communicate to employees, including traditional methods like company intranets as well as mobile, social recognition platforms and data visualization boards  in areas where employees gather, such as break rooms.

    TREND: Train more, with less Research shows that today’s learner is overwhelmed, distracted and impatient. Two thirds say they don’t have enough time to do their jobs properly. In fact, employees say they can only devote one percent of their time to learning and career development—just minutes in an average work week.


    What can you do? 

    Make it short and sweet. Break eLearning into Learning  Snacks–two to three-minute bites of learning about a single topic  or task. Learners receive Learning Snacks only when they’re needed and don’t need to “check out” of work for multiple hours just to complete training. • Be multi-device savvy. Millennials are now the largest generation in  the world and the largest generation in the workforce.

    Be aware that they almost unerringly reach for their mobile phones first. Make it seamless by delivering training to all major devices from a single version. • Custom tailor learning. One size fits all? Not anymore. Each of your learners has previous knowledge and expertise, as well as specific gaps in knowledge and skills. Use data to dynamically configure the learning experience for individual learners. 

    Keep an eye on culture. Chances are good that your learning audience is now a global audience, so be sure to deliver all course languages in a single version, using streamlined translation processes available through the cloud. Tweak translations to be relevant to the in-country culture, needs and limitations.

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    Children who sleep more get better grades.



    Sleep plays a fundamental role in the way we learn. Emerging evidence makes a compelling case for the importance of sleep for language learning, memory, executive function, problem solving and behaviour during childhood.

    A new study that my colleagues and I have worked on illustrated how an optimal quantity of sleep leads to more effective learning in terms of knowledge acquisition and memory consolidation. Poor quality of sleep caused by lots of waking up during the night has also been reported to be a strong predictor of lower academic performance, reduced capacity for attention, poor executive function and challenging behaviours during the day.

    Many adolescents are sleep-deprived as they gain less sleep than the average recommended level around nine hours for this group. But due to school commitments, teenagers are required to wake up early at a set time even if they have not achieved the optimal number of hours sleep.

    Along with these early start times, teenagers also experience pubertal phase delay meaning pubertal teenagers will sleep even less due to biological factors. Combined with late night activities, this can have a significant negative effect on the quality of sleep and therefore their behaviour during the day.
    Insufficient and poor quality of sleep appear to be pervasive during adolescence. These can have various consequences such as an excessive daytime sleepiness, poor diet and in turn impairments in cognitive control, risk-taking behaviour, diminished control of attention and behaviour, as well as poor emotional control.

    More sleep versus better sleep

    In a recent study involving 48 students between 16 and 19-years-old recruited through an independent sixth form college in central London, my colleagues and I at the Lifespan Learning and Sleep Laboratory at UCL examined the link between sleep, academic performance and environmental factors.

    Our results showed that the majority of the teenagers achieved just over seven hours of sleep, with an average bedtime at 11.37pm. Our study showed that a longer amount of sleep and earlier bedtimes measures of sleep quantity were most strongly correlated with better academic results obtained by the students on a number of tests taken at school. In contrast, measures that were indicative of sleep quality were mostly linked with students’ performances on verbal reasoning tests and on grade point averages on tests at school.

    So it appears from our results that "longer sleep" is more closely related to academic performance, while "good night sleep" is more closely related to overall cognitive processing.

    Why teens are getting less and less sleep

    Our study also confirms findings from previous research showing that teenagers are getting at least two to three hours less sleep than is needed for their optimal brain development and a healthy lifestyle.

    There are several modern lifestyle factors that have shown to impact on sleep. We found that consumption of energy drinks and coffee, and social media use half an hour before habitual bedtime were strongly associated with poorer sleep.

    Our study has also shown that the negative impact of poor sleep on academic functioning is not always matched by a realisation of this fact by students themselves, therefore they may have little motivation to alter bad sleep habits. Unlike for adults, adolescence is a crucial time because of continual changes in the brain so sleep is particularly important for a teenager’s health.

    Conditions that can impact sleep

    There is an added complexity to the sleep patterns of children with developmental disorders, despite the fact that they are more likely to suffer from sleep problems. So far, we have examined sleep, and cognitive and behavioural functioning in children with Down Syndrome, Williams Syndrome and ADHD. All our studies show that sleep has a very important impact on cognitive and daytime functioning of children with these conditions.

    When we examined levels of sleep biomarkers melatonin and cortisol in children with Williams syndrome, a rare genetic disorder, it revealed that they had elevated levels of cortisol and dampened levels of melatonin. High cortisol and low melatonin levels before bedtime were strongly linked with delayed sleep onset taking around 50 minutes in comparison to the typical 20 minutes to fall asleep.
    Since cortisol is often described as a stress hormone, high levels of this hormone before bedtime may potentially cause sleep problems including difficulty in relaxing and falling asleep. This is an important result to consider before a child is prescribed a melatonin supplement which might not be necessary to help solve their actual sleep problem.

    The effects of the sleep disturbances extend beyond the individual. Parents of children with developmental disorders often experience heightened levels of stress and sleep problems because they are kept awake by their children.

    All this shows how crucial it is for teenagers to get the right amount of sleep otherwise it could have long-term impacts on their health and on their grades.

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    Study: People four times more likely to order dessert when their server is overweight





    "In a novel approach, we showed that diners can be influenced by their surroundings in general and furthermore by their social interactions in particular," Tim Döring and Brian Wansink wrote in their study. "This study suggests that it does not take profound interactions between individuals to alter their eating behavior."


    The study was published online December 28 in the scientific journal Environment & Behavior.
    A team of research assistants visited 60 restaurants, where they observed a total of 497 interactions between diners and servers. While visiting the restaurants, the research assistants recorded the estimated body characteristics of both the diners and the servers. They also recorded how much food and drink was ordered.

    A statistical analysis of this data found that a server’s body mass index (BMI) a simple measure of body fat based on height and weight influenced how much their customers ordered and ate. The higher a server’s BMI, the more meals the diners ordered, regardless of their own body type.
    Diners were four times more likely to order dessert and ordered 17.65 percent more alcoholic drinks when their server had a BMI that was over 25. A BMI greater than 25 is considered overweight by most health experts.

    The relationship between the server’s BMI and their customers’ eating behavior remained significant even after accounting for ethnicity, gender, weight, height, and age.

    "Diners may order and eat more food and beverages in the presence of a heavy person because a heavy person sets a social norm," Döring and Wansink said.

    Some restaurants, such as the chain Hooters, have faced lawsuits for discriminating against overweight employees. But this research suggests forcing waiters and waitresses to be slim is bad for business. "If anything, heavy wait staff might increase sales," Döring and Wansink noted.

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    Fighting the “Headquarters Knows Best” Syndrome

    Shyam's take on this symdrome.

    In my long innings as a management professional, I suffered because of this syndrome at the headquarters.

    Even a clerk cum typist or a management assistant would carry airs of being knowledgeable.
    I found this attitude more with the newly recruited management trainees.

    However when I moved into the C-suite, I tried my best to counsel the staff at the headquarters to respect the skills and Knowledge of the people at the regional and other offices and allow the decisions to be taken at the Regional level.

    BEING AT THE REGIONAL OFFICE DOES NOT MAKE YOU A LESSER SOUL THAN THE ONES AT THE HEADQUARTERS.

    I also agree to the view that when the Headquarters does too much, the people at regional offices begin to shun responsibilities and pass on the buck to the headquarters for all decision making and problem solving. then the Headquarters have to delegate back to the Regional office involving a huge waste of time and loss of revenue.

    Regional problems are best solved at Regional levels. Similarly Regional strategies are best planned and executed and monitored at Regional level.

    The organizations should recruit managers at Regional level, people who in their view have the ability to make decision and solve problems. People having experience of working in cross culture environment can be trusted for these positions. It is not always possible to get local talent steeped in the organization culture.











    When subsidiary managers at global organizations are ignored or constrained by a parochial mindset at headquarters, the whole company can suffer. Here’s how one company set out to change that dynamic.


    In 2007, Irdeto B.V., a Netherlands-based developer of security software for digital media providers, was eager to increase its market share in the Asian market. The company had been in China for nearly a decade and boasted a substantial regional office in Beijing. But its market share in China was under attack from Chinese competitors, including China Digital TV, which held a 40% market share compared to Irdeto’s 22%. Despite frequent visits by then-CEO Graham Kill and the sales director, the company worried that it would miss out on the anticipated market growth in China and other parts of Asia.



    In Kill’s view, one of Irdeto’s problems was that too much power was concentrated in the head office in the Netherlands. Managers there conducted themselves as if they knew best, and branch offices and subsidiaries tended to defer to Amsterdam. Such dynamics undermined the company’s ability to understand remote markets, learn from them, and adapt to them. We call this malady the “headquarters knows best” syndrome.



    In our experience, similar narrow-mindedness holds back many organizations in their efforts to turn global presence into a real source of competitive advantage. In this article, we explore the manifestations and costs associated with this way of thinking — and ways companies have addressed the problem. Many of the things companies have done are fairly predictable, such as decentralizing global responsibilities, changing the reporting relationships, internationalizing senior management, and creating cross-national teams.



    In Irdeto’s case, the company tried a more extreme remedy: It created two headquarters, one in the Netherlands and the other in China. While this was expensive — and something Kill’s successor ultimately did away with in 2015 — our study of the company indicated that the decision to operate out of dual headquarters provided an effective way to realign the focus of the company, and it had significant positive effects on Irdeto’s performance. (See “About the Research.”) We offer a broad set of recommendations to help executives overcome the “headquarters knows best” syndrome and position themselves more effectively for global growth.




    • Limited Upward Influence for Distant SubsidiariesEven when decisions concern them, executives in less-established markets complain that they “feel at the end of a long rope.” Their requests and ideas are unheeded and their ways of operating aren’t considered. Feeling neither involved nor trusted, many subsidiary executives lack the motivation and self-confidence needed to pursue independent initiatives.


    • Horizontal dynamics also can be problematic:

      • Insufficient Exchange Among SubsidiariesHeadquarters and subsidiaries often maintain a hub-and-spoke pattern of interaction. While the satellites compete for attention fromheadquarters, they maintain little contact with each other unless it’s orchestrated by the center. There isn’t much discussion of, or support for, efforts in other parts of the world, particularly between core subsidiaries and those on the periphery.

      • Weak Links With Key Stakeholders Outside its home region, the company is perceived as “alien” by the local business partners and stakeholders.3 Its seat of power is remote. Also, executives at local operations lack the autonomy or status to engage meaningfully with senior local decision makers.

        The net result is that the belief that headquarters knows best can be damaging to the long-term success of a company operating in global markets. Among other things, it results in missed sales leads, the loss of talented employees working in subsidiaries due to a lack of career advancement opportunities, an overinvestment in initiatives that are close to the headquarters, and an underinvestment in innovation and entrepreneurship in far-off markets.


        Although headquarters executives may have the best of intentions, their actions produce stunted offspring in the form of subsidiary executives who lack confidence, motivation, and autonomy. This places companies at a serious disadvantage, especially when they are competing against rivals with truly global mindsets.

        A Common Condition


        Our surveys of more than 500 executives working in the subsidiaries of multinational corporations reveal that most endure a domineering headquarters. When we asked executives to take a diagnostic quiz assessing the degree to which their companies experience “headquarters know best” syndrome, barely 10% of executives gave their companies a score that indicates the company isn’t at risk of “headquarters knows best” syndrome. The vast majority of executives gave their organizations scores suggesting that their companies are either prone to the syndrome or have an acute case of it. (See “Diagnosing the ‘Headquarters Knows Best’ Syndrome.”)



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        How To Raise A Billionaire: An Interview With Bill Gates' Father





        Bill Gates at age six with his father, Bill Gates Sr. (photo courtesy of the Gates family)


        What was the  Microsoft founder and philanthropist like when his own operating system was still in development? His father, Bill Gates Sr., reminisces.

        What sort of child was Bill?

        Just about every kind of book interested him–encyclopedias, science fiction, you name it. I was thrilled that my child was such an avid reader, but he read so much that Bill’s mother and I had to institute a rule: no books at the dinner table.

        Did Bill ever talk about what he wanted to do or be when he grew up?

        As part of a homework assignment in fifth grade, Bill had to fill out a form about what he wanted to be when he grew up.  The form included a list of occupations – things like doctor, fireman and cowboy – with check boxes next to each. The expectation was that the student would pick one from the existing list. Although Bill did check the box for “astronaut,” he also drew in an additional box, checked it and wrote “scientist.” Growing up, he was very curious to know how the world worked, and he had his own thoughtful ideas about business, life, international affairs, and what the future might hold. At the time, it would have been hard for me to believe that the frequently argumentative boy across the dinner table would one day be my boss, but here we are.



        When did he first get interested in computers?

        Very early on. An opportunity came at his school when the mothers raised money to pay for a device that connected to a computer over the phone line. The intention was that the teachers would use it, but they made a few mistakes and got scared of it. Bill was part of a group of math students who were invited to use the system and learn how it worked. By about 13 years old he was hooked.

        Did he have jobs before college?

        When he was a senior in high school, Bill took a break from classes to do programming at a power plant in North Bonneville, Wash. Bill’s mother and I spoke to his high school headmaster, and we were all in agreement that the job would be a practical way to apply his skills and interests. I recall Bill telling me that he and Paul Allen, who worked there with him, would stay up working on code for the electrical grid management system.

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        Why Bajirao Mastani has upset two families,

        Sanjay Leela Bhansali's Bajirao Mastani has ruffled quite a few feathers among the descendants of the Peshwa and his Muslim wife.



        Sanjay Leela Bhansali's passion project has faced many a hurdle. Bajirao Mastani, the self-indulgent film maker's take on Bajirao I and princess Mastani Begum, was envisioned with publicised excitement some 12 years ago. It quickly came to a dead end after lead pair Salman Khan and Aishwarya Rai developed off-screen differences. When the idea was dusted off much later - this time with Ranveer Singh, and - the film found it shared its release date (December 18) with Shah Rukh Khan's Dilwale. Another blow came more recently as the film's songs caused an outcry among the descendants of the warrior and his lover, who found them objectionable.

        There is concern and dismay in the Bhansali camp, crew members admit. In the manner of most ventures under his banner,
        Bajirao Mastani is a costly affair: co-produced with Eros, it has reportedly been made for Rs 200 crore. The period story has all the trappings of a Bhansali product: forbidden romance, drama, scale and lots of finery. Some of that is glimpsed in the songs revealed so far: Pinga, a dance-off between Padukone and Chopra, and Malhari, a celebratory jig by Singh.

        The tracks betray a thirst for mass appeal, but the ample use of catchphrases and the flamboyant dance moves have not gone down well with members of Bajirao's clan - his descendants from Mastani, the Nawabs of Banda, have filed petitions in the courts of Jabalpur and Indore, and his heirs from his first wife, Kashibai, spoke out in the media.

        The families want Bajirao to be remembered as a peerless war strategist. He was born into a Chitpavan Brahmin family in 1700 and took over from his father as the Peshwa at the age of 19. He is known to have fought 41 battles without a single loss. According to historian Mandar Lawate, his strength was speed. For example, he struck by capturing the enemy's water bodies and fields, or pre-emptively hit the opposition's capital while they were making their way to his. Biographer Jayraj Salgaokar says he was instrumental in expanding the guerilla warfare techniques developed by Shivaji.
        was docile and personable. She suffered from arthritis and tuberculosis, which her descendants note would make it hard to dance fluently.

        When Bajirao saved Bundela warrior Chhatrasal's territory from Muhammad Khan Bangash, he was rewarded with land and the hand of Mastani in marriage around 1730.

        There are various stories about Mastani, who is also believed to have been a poet and Krishna devotee. The Begum, members of the Banda family say, was not a courtesan of Chhatrasal but a daughter from his Persian wife Ruhani Bai. Despite resistance from his mother and brother, Bajirao is said to have married her out of love.

        History retold
        Terms like vaat lavli (slang for destroyed) and rhyming words like chatak matak vatak cannot have been in the vocabulary of a warrior King in the 18th century, reckons Mahendra Peshwa, a consulting engineer and ninth-generation descendent of Bajirao, referring to the song Malhari.

        Thus, open letters were written to Bhansali, demanding that he do his homework. The wives in royal families would never dance in public, notes Mahendra, especially not in midriff-baring saris. "They would be clothed from head to toe in those days. In front of strangers, they were required to cover their heads and wear shawls."

        For the families, who feel they are uncared for in general, this seems to have been an opportunity to come to the fore. Standing in the ruins of Shaniwarwada, the Peshwas' ancestral home and headquarters in Pune, Mahendra and his wife, Sucheta, wonder if their cause will find political support. They are enthused by what they dub as hints of discomfort in the film maker. "Another song titled
        Fituri has offensive lyrics too but they have withheld the video so far, probably out of fear," he says, with a laugh. "They have not yet come to Pune for promotions either."

        The Peshwas maintain that while
        has been adequately glorified for his contributions to Maharashtra, Bajirao hasn't been remembered enough. "In the 40 years of his life and 20 years of his career as the Peshwa, Mastani was a part of the last decade. Why focus so much on the love story and not his laurels as a battle strategist," Mahendra's uncle, Udaysing, asks over the phone.
        History retold
        Equally incensed are Mastani's progeny, who are spread across Sehore, Indore and Bhopal in Madhya Pradesh and work as social workers, teachers and government servants. "If some love story of historic figures fascinates the celluloid world, we have no problem. But should someone take liberties to insult those great people," asks an angry Tamkeen Ali Bahadur, sitting at his modest home at Sehore, some 50 km from Bhopal.

        "
        was not an ordinary dancer but a poet and war strategist who accompanied Bajirao on many occasions," adds Afaque Ali Bahadur, who recently retired as additional-CEO of the District Council. They are the descendants of Shamsher Ali, the son of Mastani, who became the Nawab of Banda. The family lost its riches when Nawab Ali Bahadur II fought against the British along with Laxmibai of Jhansi.

        The family lives modestly, but its syncretic royal past shows up at times. While they are fond of Urdu poetry and the rare Nawabi delicacy ratan kalia, young Umar Ali Bahadur, who leads the charge in preserving the family history, also likes to chant Sanskrit couplets and carries a pocket-sized
        Gita in his bag.

        Some years ago, Umar attended college in Pune and simultaneously made efforts to restore the grave of Mastani Begum at Pabal village near the city. Tamkeen too remains busy digging up government records of his family's property, belongings and jewellery impounded by the British.

        Members of both the families jointly addressed the press in Mumbai some days ago. To allay their concerns, the film's makers declared they would include a disclaimer saying it is a work of fiction where any resemblance to real characters was coincidental. Still, the families have demanded a look at the script and the movie before release. "It is not a ban we are seeking but removal of what is objectionable. How can you disclaim it, when the names of all the characters are the same as in real life?" says Udaysing.

        While it may not be firmly rooted in historical fact, the film's making did entail research. The film is based on fictional work
        Rauu, which draws from Bajirao's life but focuses on his love for Mastani. The writers, Bhansali and Prakash Kapadia, reportedly also consulted historian Ninad Bedekar. Research brought members of the crew to the two-storeyed Raja Dinkar Kelkar Museum in Pune's crowded Shukrawar Peth. They visited twice, says the museum's director, Sudhanva Ranade, whose grandfather and founder of the establishment, D G Kelkar, wrote poems in admiration of Bajirao.

        The museum's collection ranges from objects of everyday use to royal artifacts from the 18th to 20th centuries. Parts of the Mastani Mahal, believed to have been built by the Peshwa for his beloved, have been preserved here and became a reference point for the film's makers. It is a useful peek into the decor of that era: ornamental columns, arches, windows and seating areas all carved in dark brown wood as well as chandeliers and lamps.

        Kapadia, who has the voice and inflection of a movie narrator, talks emotionally about the effort behind the film. In the years since its conception, multiplexes sprung up and audiences preferred shorter, youthful tales. His three-hour script was shortened to two hours. He combined the novel
        Rauu with knowledge from other books, maps and lectures by historians, cutting himself off from people for ten months to write the story.

        Kapadia says he consciously stayed away from depicting the intricacies of Maharashtra culture that would have to be explained. Hints of it will be in the costumes and dialogues. "We wanted a universal flavour because this story could be anywhere. The focus is on the tremendous inherent conflict - a married Brahmin man's love for an outsider with Muslim roots."

        Designer Anju Modi created around 80 saris for the film after studying museums in Mumbai and Pune, and visiting smaller towns like Paithan, Chanderi and Maheshwar. Along with
        on a trip to Nashik, she learnt how to fashion and drape traditional dhotis. In a remote area of Pune, Modi says she found a local to create typical turbans. She had two distinct styles to draw from - Maratha for Bajirao and his first wife, Kashibai, and Islamic for Mastani.

        Another rich source of inspiration for Modi was Maratha paintings that helped her internalise the period. Paintings of Ravi Varma helped make-up artist Uday Shirali decide on a look for little-known Kashibai. He kept make-up to a minimum, using under-eye cream and foundation to give Chopra a younger look since women married early in those times.

        If nothing else, Bhansali's films are known for their sets. Sriram Iyengar first heard of Bhansali's plan for a film on the Peshwas 12 years ago. Between assignments, Iyengar began studying Maratha forts and put together preliminary drawings of various sets. When the period film was revived, someone else was named art director. But a few meetings and twists of fate later, Iyengar and business partner Sujeet Sawant were taken onboard. Saloni Dhatrak joined them to offer expertise on Mughal architecture. Together they recreated Shaniwarwada with Kashi's villa and a mirror chamber.

        Traditionally, the Marathas built simple forts with smaller rooms but Bhansali wanted everything to be scaled up. "He said he cannot have his protagonists in
        kholis," says Iyengar.

        Bhansali is famously idiosyncratic. Bajirao's descendants point out that they were not approached in the run-up to the film and during most of the shooting. The Peshwas were invited on set once. Tamkeen says he tried to contact Bhansali to express his concerns over the depiction but received a lukewarm response, compelling him to move the courts for justice. Some aspects like an animated teaser on Bajirao were encouraging but the songs drew their ire.

        The families are involved in regular fields like education and mechanics but routine lives have hardly dulled their pride in the laurels of ancestors. The Peshwas have to now buy Rs 5 tickets to see Shaniwarwada, a heritage site under the Archaelogical Survey of India. When it closes at 6 pm and they are herded out with other visitors, Mahendra laughs at the irony of being asked to leave "his own home".

        Our anger must reach Bhansali, say both the families. This curious battle has allowed Bajirao's descendents to discover a dormant warrior spirit, at the receiving end of which is a headstrong Bollywood director.




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        Only 8% of Leaders Are Good at Both Strategy and Execution




        In a 2013 survey of nearly 700 executives across a variety of industries, our firm asked respondents to rate the effectiveness of the top leaders of their companies. How many excelled at strategy? How many excelled at execution? The results are shown in the chart below. These responses are sobering: Only 16% of top leaders were rated very effective at either strategy or execution. Only 8% were very effective at both, while 63% were rated neutral or worse on at least one dimension.




        But there is heartening news in one finding. More than half of the leaders who are effective in either strategy or execution (that group of 16% in the top row and right-hand column) are skilled in both strategy and execution. This finding suggests that among the rest of us, those who become better strategists (those who can develop compelling answers to those fundamental strategic questions) will probably gain skill at execution as well, and vice versa.

        In our research, we’ve found five leadership acts that help companies close the strategy-to-execution gap. The five acts of unconventional leadership also provide an opportunity for deep and powerful leadership development. Think of them as a chance to create an engine of growth for you personally and for the company:

        Commit to an identity. As a leader, you can become a symbolic figure, a model of commitment. You have something powerful to sell: a message about identity and the need to stay with that identity over time. As you demonstrate the courage of those convictions, you develop the influence and impact needed to build an extraordinary company.

        Translate the strategic into the everyday. Although you occupy a top executive position, you also “get your hands in the mud,” as Starbucks CEO Howard Schultz puts it in his book Pour Your Heart into It. You become the architect of the capabilities you need, the chief of builders. In these roles, you operate at a fine-grained level of detail so that you can see, sense, and touch the details of everyday activity. But you also raise your view high enough that you clearly see — and show others — how all your global capabilities fit the value you offer customers. You need two kinds of perspectives, nearsighted and farsighted, simultaneously, and you can only develop them this way.

        Put your culture to work. As a leader, you are infused with your company’s culture. You are a primary champion of emotional commitment. You practice mutual accountability; everyone’s success is important to you. Through teaching and learning, you devote yourself to the cultivation of collective mastery. You do all this in a way that matches the unique cultural attributes of your company, which are grounded in its capabilities system. You don’t act like you come from a remote corner office; you act like you are one with the company’s culture.

        Cut costs to grow stronger. Your company consistently allocates its resources with an eye toward strategic priorities. As a leader, you do the same with your personal resources, particularly your time and attention. Are you devoting enough to the most critical capabilities and the value proposition they support? Or are you squandering too much time and attention on immediate demands, responding to everybody else’s idea of what is important?

        Shape the future. As a leader, you are one of the first to experience the constant challenge of external change. You can muster the fortitude (and humility) to recognize when change in yourself is required. You build an extremely capable team, knowing that ultimately the future will depend on developing the next generation of leaders.

        Nearly every CEO we’ve met has great aspirations to change the game, move beyond the constraints that his or her organization faces, and build a legacy that leaves years and years of growth. Living these five acts of leadership can help. They build your confidence, and that of your company, and increase your ability to close the gap between strategy and execution.

        View at the original source

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        Leading in the Age of Super-Transparency




        Thanks to social media and an increasing flood of data, the capacity to generate causes and controversies almost instantly has become the new norm in today’s “super-transparent society.” Most business leaders have not yet come to grips with the new reality — and what it means for their organizations.

        When Martha Payne, a 9-year-old student in Argyll, Scotland, started a blog in April 2012, she had no idea of the stir she would soon cause. The lunches her school offered offended her youthful sense of justice, and she saw no reason to keep her thoughts to herself. So she began blogging under the name “Veg” (short for “veritas ex gustu,” which means “truth from tasting”). With tech support from her dad, Martha photographed and rated the school lunches and posted her reviews to a blog she christened “NeverSeconds.”

        Soon Martha was adding new material regularly. The small portions were an early concern. “I’d have enjoyed more than 1 croquet[te],” she wrote, in a post from the first month. “I’m a growing kid and I need to concentrate all afternoon and I can’t do it on one croquette. Do any of you think that you could?”

        Readers were supportive. “My toddler eats more than that,” one observed. Other blog posts questioned the food’s nutritional value, using words like “pathetic,” “rubbish,” and “disgraceful.” When celebrity chef Jamie Oliver tweeted in support of Martha’s project, newspapers picked up the story. Riding a wave of publicity, NeverSeconds logged

        2 million hits in its first six weeks. Martha donated to a nonprofit that provides free school meals in poor parts of the world.


        But the initiative soon screeched to a halt. As Martha explained in a blog entry titled “Goodbye,” her head teacher had removed her from math class, escorted her to the office, and told her to stop taking photos of school lunches. In a separate entry, Martha’s father noted that Martha’s charity efforts, which had raised nearly £2,000 at the time, would end, and thanked the school for being supportive. The decision to shut down NeverSeconds, he explained, came from the local area council.

        However, the story didn’t end there — a firestorm ensued. Within 24 hours, there were 2,416 new reader comments on NeverSeconds, most expressing outrage at the local council that had issued the directive. The local council’s website was bombarded with negative comments, and critics launched a petition drive to save the blog. NeverSeconds logged another 1 million hits. The Twitter hashtag #MyLunchforMartha trended, and a dedicated Facebook page amassed comments. Half a world away, Wired magazine published a story on its website headlined “9-Year-Old Who Changed School Lunches Silenced by Politicians.”

        The local council quickly reversed its decision. The council explained that, rather than trying to stifle discussion, it had merely been trying to be sensitive to the feelings of cafeteria workers. Just as the clampdown had been roundly criticized, the news of the reversal was greeted with celebration. Martha appeared on television with Jamie Oliver, and her fundraising and campaign for better lunches resumed.

        The pattern that underlies this story has become common. Every day, images or events with the potential to incite passions get captured digitally, get posted to the Web, and “go viral.” In Martha’s case, it started with her lunch photos, but it could just as easily have been an audio recording of a rude customer service rep on a phone call (as happened when a customer called Comcast in 2014) or a video capture of police seeming overly aggressive in arresting a man for alleged jaywalking (as happened in Austin, Texas, not too long ago). With social media, people share their experiences with friends or followers, who then share with more people. Within a short space of time, incidents can strike a nerve with a nascent virtual community. And some unsuspecting party — such as the council in the area where Martha Payne lives — must respond to a dicey new problem.

        Evocative images and events have always propelled causes and controversies, but not always from such obscure, unexpected, or geographically remote sources — or with such speed. In the past, controversies brewed when people came together, and they were transmitted, if the controversies grew active enough, by a limited number of media outlets, which also served as gatekeepers. Today’s controversies, by contrast, spring to life in myriad, overlapping online communities and get distributed via networks of unaccountable independent agents sharing information in real time. The capacity to generate causes and controversies almost instantly is perhaps the most salient aspect of what we call the “super-transparent society,” which has rapidly become a new norm. Because it has formed so recently, most people, especially leaders of organizations, have not yet come to grips with how much the world has changed or with the benefits and risks of living and leading in an era of super-transparency.

        Our research explores the causes of these changes, the nature of the new reality that results, and the implications for organizations and their leaders. (See “About the Research.”) In aggregate, the changes amount to a fundamental shift in what is commonly known and knowable that invalidates some assumptions and practices we’ve previously relied upon. Executives need to understand this shift and how it changes the rules with regard to competitive markets, their company’s relationships with customers, the broader political contexts in which they operate, and beyond.

        From Data Puddles to Data Floods

        From childhood, most of us know that puddles of water form on the ground after it rains. Consequently, we understand how puddles and the water they contain behave. We know, for example, that water can be moved between puddles, but that it does not move by itself. We can move water by creating a channel between puddles or by using a bucket or a cup to move water from one puddle to another. We can even splash water from one to another, intentionally or not. But until the puddle dries up, our most basic assumption about puddles of water echoes a law of physics: Water in a puddle tends to remain in that puddle, provided that no other action is taken to change it.

        Information used to behave similarly. Historically, only the people in Martha’s hometown in Scotland paid attention to the local goings-on, and information tended to remain within “information puddles.” When information moved beyond a particular puddle, it was due to deliberate action: Some identifiable person or organization moved it. If you wanted to be certain that information didn’t move, you built a barrier that kept the information contained (within an organization, say). Over the years, leaders have invested in building firewalls to restrict the flow of information. To this day, prevailing assumptions about puddles inform our understanding of how information behaves.

        What, exactly, has changed? First and foremost, the amount of information. The volume of new digital data created every year is increasing exponentially. Individuals are the source of most of this data; 75% of all digital data is now created by consumers, much of it via handheld devices we carry around with us.2 By 2019, the technology company Cisco Systems Inc., which knows a thing or two about data traffic, forecasts that mobile data movement will total 24.2 exabytes (an exabyte is equal to 1 billion gigabytes) per month, after expanding at a compound annual growth rate of 57%.

        Put simply, our information puddles have overflowed and become floods. In a flood, water doesn’t behave in ways that are easy to understand. It doesn’t stay in place and is difficult to contain. Although there still can be boundaries separating reservoirs, increasing amounts of pressure behind them makes them more prone than ever to leak.

        In many parts of the world, most people have smartphones in their possession most of the time. These devices not only generate huge volumes of new data; they also represent new channels of information flow that bypass intentionally constructed barriers. However much your company has invested in firewalls, a quick photo and transmittal of the information displayed on a computer screen (perhaps by a disgruntled or not very security-minded employee or contractor) can render such safeguards useless. Well-meaning and conscientious employees can also fall prey to tricks. For example, at a


        French company we know, a junior employee received an email requesting that important
        information be sent to an external address. She knew enough not to respond. But five minutes later, she received a phone call from someone who identified himself as a “vice president” (who spoke perfect French with exactly the right regional accent), asking her for information so the company could keep a customer happy. She complied. But it turned out to be a clever ploy and competitive information went out into the world, bypassing the company’s digital protections.

        Your success in maintaining the integrity of your data depends on your ability to imagine all of the different ways information might flow in a flood. In late 2014, when protestors in Hong Kong feared that the government might shut off cellular networks, they started using FireChat, a smartphone app that connects mobile phones in a “mesh network” (a phone-to-phone relay that can route information without using cellphone towers).

        Wander into a Brookstone store and ask about Brookstone’s video camera pen; although it looks like a normal pen, it’s actually a video capture device that connects to a USB port and can easily dispatch data to the cloud. When direct routes to the Internet are blocked, people can use smart pens, watches, or USB sticks, as Edward Snowden did when he carried an estimated 1.7 million classified documents out of the U.S. National Security Agency, one of the most secure organizations on earth.5 SanDisk offers a 128GB micro SD card for less than $60;6 a two-terabyte card isn’t far off. The technology just keeps getting more sophisticated and cheaper.

        When Martha Payne, a 9-year-old student in Argyll, Scotland, started a blog in April 2012, she had no idea of the stir she would soon cause. The lunches her school offered offended her youthful sense of justice, and she saw no reason to keep her thoughts to herself. So she began blogging under the name “Veg” (short for “veritas ex gustu,” which means “truth from tasting”). With tech support from her dad, Martha photographed and rated the school lunches and posted her reviews to a blog she christened “NeverSeconds.”

        Soon Martha was adding new material regularly. The small portions were an early concern. “I’d have enjoyed more than 1 croquet[te],” she wrote, in a post from the first month. “I’m a growing kid and I need to concentrate all afternoon and I can’t do it on one croquette. Do any of you think that you could?”

        Readers were supportive. “My toddler eats more than that,” one observed. Other blog posts questioned the food’s nutritional value, using words like “pathetic,” “rubbish,” and “disgraceful.” When celebrity chef Jamie Oliver tweeted in support of Martha’s project, newspapers picked up the story. Riding a wave of publicity, NeverSeconds logged 2 million hits in its first six weeks. Martha donated to a nonprofit that provides free school meals in poor parts of the world.

        But the initiative soon screeched to a halt. As Martha explained in a blog entry titled “Goodbye,” her head teacher had removed her from math class, escorted her to the office, and told her to stop taking photos of school lunches. In a separate entry, Martha’s father noted that Martha’s charity efforts, which had raised nearly £2,000 at the time, would end, and thanked the school for being supportive. The decision to shut down NeverSeconds, he explained, came from the local area council.

        However, the story didn’t end there — a firestorm ensued. Within 24 hours, there were 2,416 new reader comments on NeverSeconds, most expressing outrage at the local council that had issued the directive. The local council’s website was bombarded with negative comments, and critics launched a petition drive to save the blog. NeverSeconds logged another 1 million hits. The Twitter hashtag #MyLunchforMartha trended, and a dedicated Facebook page amassed comments. Half a world away, Wired magazine published a story on its website headlined

        “9-Year-Old Who Changed School Lunches Silenced by Politicians.”

        The local council quickly reversed its decision. The council explained that, rather than trying to stifle discussion, it had merely been trying to be sensitive to the feelings of cafeteria workers. Just as the clampdown had been roundly criticized, the news of the reversal was greeted with celebration. Martha appeared on television with Jamie Oliver, and her fundraising and campaign for better lunches resumed.

        The pattern that underlies this story has become common. Every day, images or events with the potential to incite passions get captured digitally, get posted to the Web, and “go viral.” In Martha’s case, it started with her lunch photos, but it could just as easily have been an audio recording of a rude customer service rep on a phone call (as happened when a customer called Comcast in 2014) or a video capture of police seeming overly aggressive in arresting a man for alleged jaywalking (as happened in Austin, Texas, not too long ago).1 With social media, people share their experiences with friends or followers, who then share with more people. Within a short space of time, incidents can strike a nerve with a nascent virtual community. And some unsuspecting party — such as the council in the area where Martha Payne lives — must respond to a dicey new problem.

        Evocative images and events have always propelled causes and controversies, but not always from such obscure, unexpected, or geographically remote sources — or with such speed. In the past, controversies brewed when people came together, and they were transmitted, if the controversies grew active enough, by a limited number of media outlets, which also served as gatekeepers.

        Today’s controversies, by contrast, spring to life in myriad, overlapping online communities and get distributed via networks of unaccountable independent agents sharing information in real time. The capacity to generate causes and controversies almost instantly is perhaps the most salient aspect of what we call the “super-transparent society,” which has rapidly become a new norm. Because it has formed so recently, most people, especially leaders of organizations, have not yet come to grips with how much the world has changed or with the benefits and risks of living and leading in an era of super-transparency.

        Our research explores the causes of these changes, the nature of the new reality that results, and the implications for organizations and their leaders. (See “About the Research.”) In aggregate, the changes amount to a fundamental shift in what is commonly known and knowable that invalidates some assumptions and practices we’ve previously relied upon. Executives need to understand this shift and how it changes the rules with regard to competitive markets, their company’s relationships with customers, the broader political contexts in which they operate, and beyond.

        From Data Puddles to Data Floods

        From childhood, most of us know that puddles of water form on the ground after it rains. Consequently, we understand how puddles and the water they contain behave. We know, for example, that water can be moved between puddles, but that it does not move by itself. We can move water by creating a channel between puddles or by using a bucket or a cup to move water from one puddle to another. We can even splash water from one to another, intentionally or not. But until the puddle dries up, our most basic assumption about puddles of water echoes a law of physics: Water in a puddle tends to remain in that puddle, provided that no other action is taken to change it.

        Information used to behave similarly. Historically, only the people in Martha’s hometown in Scotland paid attention to the local goings-on, and information tended to remain within “information puddles.” When information moved beyond a particular puddle, it was due to deliberate action: Some identifiable person or organization moved it. If you wanted to be certain that information didn’t move, you built a barrier that kept the information contained (within an organization, say). Over the years, leaders have invested in building firewalls to restrict the flow of information. To this day, prevailing assumptions about puddles inform our understanding of how information behaves.

        What, exactly, has changed? First and foremost, the amount of information. The volume of new digital data created every year is increasing exponentially. Individuals are the source of most of this data; 75% of all digital data is now created by consumers, much of it via handheld devices we carry around with us.2 By 2019, the technology company Cisco Systems Inc., which knows a thing or two about data traffic, forecasts that mobile data movement will total 24.2 exabytes (an exabyte is equal to 1 billion gigabytes) per month, after expanding at a compound annual growth rate of 57%.

        Put simply, our information puddles have overflowed and become floods. In a flood, water doesn’t behave in ways that are easy to understand. It doesn’t stay in place and is difficult to contain. Although there still can be boundaries separating reservoirs, increasing amounts of pressure behind them makes them more prone than ever to leak.

        In many parts of the world, most people have smartphones in their possession most of the time. These devices not only generate huge volumes of new data; they also represent new channels of information flow that bypass intentionally constructed barriers. However much your company has invested in firewalls, a quick photo and transmittal of the information displayed on a computer screen (perhaps by a disgruntled or not very security-minded employee or contractor) can render such safeguards useless. Well-meaning and conscientious employees can also fall prey to tricks.

        For example, at a French company we know, a junior employee received an email requesting that important information be sent to an external address. She knew enough not to respond. But five minutes later, she received a phone call from someone who identified himself as a “vice president” (who spoke perfect French with exactly the right regional accent), asking her for information so the company could keep a customer happy. She complied. But it turned out to be a clever ploy and competitive information went out into the world, bypassing the company’s digital protections.

        Your success in maintaining the integrity of your data depends on your ability to imagine all of the different ways information might flow in a flood. In late 2014, when protestors in Hong Kong feared that the government might shut off cellular networks, they started using FireChat, a smartphone app that connects mobile phones in a “mesh network” (a phone-to-phone relay that can route information without using cellphone towers).

        Wander into a Brookstone store and ask about Brookstone’s video camera pen; although it looks like a normal pen, it’s actually a video capture device that connects to a USB port and can easily dispatch data to the cloud. When direct routes to the Internet are blocked, people can use smart pens, watches, or USB sticks, as Edward Snowden did when he carried an estimated 1.7 million classified documents out of the U.S. National Security Agency, one of the most secure organizations on earth.5 SanDisk offers a 128GB micro SD card for less than $60;6 a two-terabyte card isn’t far off. The technology just keeps getting more sophisticated and cheaper.

        Excitable Networks

        Last winter the New York Times described how an off-the-cuff message sent into the cloud by a public relations executive just before boarding an 11-hour flight cost her her job.7 People interpreted her tweet as racist (although, as the Times writer pointed out, it could be interpreted otherwise) and shared it via Twitter, provoking a storm of criticism. Similar examples are common in the super-transparent world: awkward jokes or out-of-context comments, captured and transmitted, can produce unexpectedly immense reactions as information moves from an information puddle and into a chaotic flood. We refer to this information flow as “amplification.”

        Amplification describes the tendency of certain images, stories, or other forms of information to resonate and travel widely. A precondition seems to be interconnectedness and overlapping networks of a certain density. The interactive nature of connections and the fact that posted information induces multifaceted reactions — a provocative post on Facebook might draw others into an argument, for example — causes information to feed back upon itself. People are drawn in not only by the original message but also by reactions to it (and reactions to reactions).

        But connections and interactions don’t fully explain the phenomenon. Certain events seem to have greater capacity to stir passions. An obvious injustice willfully committed, captured in a video and posted for the world to see, is a classic and recurrent motif within viral causes. As the NeverSeconds story illustrates, certain events have compelling plotlines that can be highlighted by the way the events are presented or framed. In May 2013, a Reuters photographer captured an image of a woman, Ceyda Sungur, wearing a red dress and carrying a white bag just as she was being pepper sprayed by Turkish riot police; the “lady in red” photo became, as the online publication the Verge put it, “the symbol of Turkey’s unrest” for reasons that seem largely aesthetic:

        With her stance relaxed and face downturn, Sungur, through Orsal’s lens, is the epitome of passive resistance … [The police officer’s] gas mask and crouched stance seem almost comically disproportionate to his target. With a barricade of shields framing the action with ominous uniformity, she stands alone and absorbs the spray.
        The composition of this visual information and the way the photographer’s craft frames and captures it lends itself to amplification. It is a powerful form of artistry, akin to poetry or moviemaking. Inexpensive but sophisticated tools for information capture and editing such as Adobe’s Photoshop and Apple’s iMovie make it more likely that someone “out there” will cast events that involve your organization in a surprising, passion-inciting plotline.

        Agents of deliberate amplification work within the cloud, reinforcing and repeating items or interpretations of information. “Shamers” use all sorts of techniques to keep a furor from dying down. When the previously mentioned PR executive pursued other jobs, shamers took to social media again to continue to criticize her. Even bystanders become part of plots that become amplified; a joke whispered privately to a colleague can be tweeted or posted by someone who overhears it.

        Although amplification is often negative, there can also be positive effects. Sometimes enhanced transparency and amplification mean that injustices that might have remained hidden get called out and punished. Sometimes the shamed person or organization deserves it, and the credibility of the information is beyond refute. Transparency is often a good thing, and the word carries favorable connotations for this exact reason.

        And of course “going viral” can in some cases be harnessed for marketing purposes. But even for marketers, it’s unsettlingly easy to underestimate or misjudge the chaotic behavior of flows within a flood: You can launch messages into the flood, but you cannot control where they go or what others do with them. For example, SodaStream, an Israeli company that sells a countertop device that turns water into seltzer, launched a marketing campaign in 2013 extolling the environmental virtues of its reusable bottles — only to find itself at the center of criticism for locating one of its production facilities in the disputed West Bank.
        Sometimes enhanced transparency and amplification mean that injustices that might have remained hidden get called out and punished.

        Trails of “Digital Exhaust”

        Dan Geer, a computer security and risk management expert, points out that individuals and organizations inadvertently reveal things about themselves in many ways. People generate huge amounts of data as by-products of everyday behaviors, such as Web searching and social media posting. Even if you have not revealed things about yourself, odds are that someone else has. Someone else has posted your photo on Facebook and probably tagged it with your name. What’s more, your appearance can be identified at a distance with pattern recognition software, using databases gleaned from social media. Your way of walking, detectable using the accelerometer in your smartphone, also can identify you. And if you can be identified, you can be tracked, revealing where you are and where you’ve been. Other data you generate divulges a lot about what you’re doing. Individuals and organizations produce a voluminous, mostly involuntary, “digital exhaust,” which reveals much more about them than they think it does.

        Add “big data” to this mix and marketers, policy analysts, and others can conclude or predict things from this digital exhaust that they could not in the past. It’s possible to predict flu outbreaks from patterns in the symptoms people search for on Google, and for a company to know a young woman is pregnant before she has told family members (to cite two well-publicized examples).The ability to crunch data cheaply and rapidly leads to even greater transparency. Cross-referencing one dataset with another — “putting two and two together” — allows analysts to discover things about you and your organization that you have not disclosed. Researchers have shown, for example, how supposedly anonymized data about customer purchases can be de-anonymized by cross-referencing.

        You might think this capability is limited to sophisticated analysts, but it goes further. Motivated individuals with modest skills and a moderately powerful computer can deduce a lot. Moreover, the so-called “power of the crowd” enables ordinary people to accomplish sophisticated feats of transparency-producing analysis.In February 2009, a masked figure posted a video on YouTube that showed him abusing a cat. The video prompted collaborative detective work by cat sympathizers. The cat sympathizers cross-referenced the YouTube video with others and with photos on Facebook, noting similarities in carpets, walls, and flags. Using a process worthy of crime scene investigators, they identified the masked figure and reported him to police. “Dusty the cat” was rescued and his abuser cited for cruelty to animals.

        In addition, the much-vaunted “Internet of things” has already invaded our homes and businesses, and unbeknownst to many people, it has the potential to transmit lots of data about what we do or what we say. For example, in a two-hour Internet scan, HD Moore, chief research officer at Rapid7 LLC, a Boston-based Internet security company, found 5,000 “wide-open” corporate boardrooms, equipped with videoconferencing equipment with inadequate security.17 IP-enabled heating systems can tell people who know how to read them whether you’re home or away — and let’s not forget the data generated by cars.18 In our pursuit of convenience through network-connected devices, we are creating streams of bundled personal data that can make us more and more transparent.

        The Rise of Cyber-Snoopers

        Regardless of one’s views about the impact of WikiLeaks, as an organization it is committed to setting information free as a matter of first principle. The vast majority of the emails that hackers stole from Sony and that were recently released by WikiLeaks contained no evidence of injustices, only information that has attracted mostly prurient interest (for example, rude comments movie execs have made about movie stars). Nevertheless, some advocates argue that there shouldn’t be secrets — that information needs to be free.

        The past few years have seen the rise of what some refer to as “hacktivists,” entities that take up causes and use computer skills in ways that are sometimes either borderline or outright illegal. In recent years, hactivists operating as a loose community under the umbrella name “Anonymous” have compelled law enforcement organizations to reopen cases and companies to change their ways of doing business. They do this by disclosing information Anonymous obtains by unnamed means and sometimes by threatening to release the names and addresses of allegedly guilty insiders. Anonymous has no stable membership, and “members” generally don’t know each other except by screen names.

        However, like many cause-motivated communities, Anonymous groups coalesce when needed.
        Anonymous has targeted many kinds of organizations, even hospitals, whose leaders have taken actions someone did not like, often with impressive effect. In 2011, for example, Anonymous went after HBGary, an IT security firm. Aaron Barr, the then-head of the company’s federal division, had attempted to infiltrate Anonymous, which had attacked MasterCard and Visa websites (reportedly because the companies had stopped processing donations to WikiLeaks).

        But Barr may have overreached when he told a Financial Times reporter that he was closing in on his prey. Soon after publication of the Financial Times article, Anonymous took control of the HBGary Federal website, stole and leaked company emails, and deleted company data; the group also took over Barr’s Twitter account.

        The people involved were eventually caught, and they were not master criminals. Two were in their 20s, and three were teenagers. They had access only to modest computers and tools, and had succeeded not only with online skills but also by “social engineering” — a low-tech version of a well-known con where outsiders convince people within companies to disclose information that should be kept private. Some of the problem, then, was simply bad judgment or carelessness on the part of employees. Cybercriminals, often equipped with some expertise and resources, add to this troubling mix. Unlike other forms of hackers, criminals don’t brag about their exploits — they keep them secret so they can use the techniques again.

        Managing in a Super-Transparent World

        Our research suggests several steps that managers can take to meet the new expectations for transparency.

        Examine your assumptions about how you can keep information contained. You can no longer count on information boundaries, either those that occur naturally or ones that you construct. Systematically identify unrealistic assumptions — the points at which you might be unwisely assuming that you can contain information. You might be able to keep some secrets, but it will be more expensive and difficult than it was in the past. And there’s always a risk that your efforts won’t work.

        Review your strategy for dealing with vulnerability to unintended transparency. To what extent does your organization’s strategy depend on containing information flows? If the answer is “a lot,” consider moving to strategies that are not sensitive to unexpected information flows and your ability to keep secrets: strategies that are based on what your company can uniquely do as opposed to what it knows. Many organizations can successfully reduce their degree of vulnerability.

        Review your organization’s operations for issues that might be problematic if revealed. How many companies have been embarrassed in recent years by revelations about their operations in a distant country that also surprised leaders back at headquarters? The fact is that many companies are vulnerable to attackers who have a specific axe to grind. Consider hiring external, supply chain, public relations, or security consultants to investigate your operations and fix problems preemptively. Identify managers and management practices that might be problematic. Rather than hunting potential leakers, which might cause people to speculate that you have something to hide, the goal should be to identify questionable behaviors or practices that might prompt leaking.

        Assume that others will put out information about your organization for their own reasons and that you won’t be able to prevent it. The “Streisand effect” describes what happened when singer Barbra Streisand used lawyers to try to get an aerial photo of her house deleted from a photo collection on the Web — and in the process brought more publicity to the photo. When the prime minister of Turkey tried to “rip out the roots” of Twitter to prevent sharing of recordings of phone conversations with his son, the tech community almost immediately created workarounds, and traffic on Twitter within Turkey increased.

        Managing your image has become a new game, and being prepared to respond quickly, especially to information that is incorrect, is a big part of it. You won’t be able to stop malicious falsehoods from ripping through social media. Fringe media outlets, riding the sensation, may even try to avoid your corrections to keep a great plotline alive. But as you deposit accurate information into the cyberspace “record” and provide responsible people with facts that can be verified, you’ll eventually put the brakes on irresponsible claims. Most companies are much too slow to respond.

        Recognize that new information flows change what people consider to be fair. When information that was not previously accessible becomes easily accessible, something changes: People often feel that the information now should be accessible. And when information flows in new ways, how people look at business activities changes. One software company manager told us that the discounts his company had previously offered only to prospective customers became problematic once existing customers learned about them; the existing customers became indignant and demanded similar discounts.

        There’s a parallel here to what happened to the music industry in the late 1990s, when the bits and bytes that record companies owned flowed freely across the Web. Viewing themselves as victims, record companies took legal action against downloaders — only to discover that they themselves had become the bad guys in many people’s eyes. Because digital content could be easily downloaded, many people begrudged those who tried to limit free downloads. In the new information era, it became seen as unfair to ask consumers pay $20 for a complete CD when many people just wanted one or two songs. Apple’s iTunes single-song pricing model was a response to the new customer view of fairness.

        In many ways, today’s emerging super-transparent reality is the music industry’s late-1990s problem writ large. It will force changes in the way a broad set of companies operate. It goes beyond music flowing in surprising and uncontrollable ways and extends to the contents of our lives, captured by personal, portable digital data devices. In addition to smartphones, increasingly it includes an array of other devices (smart pens, watches, wearables, etc.). And just as the music business never regained its balance, we, too, will increasingly find our realities as individuals, organizations, and managers permanently changed.

        In a super-transparent world, it’s important to be on the lookout for shifts in what your customers and the broader public consider reasonable. You won’t anticipate all of them. Expect to be caught wrong-footed when customers or the public suddenly sees something that your organization does in a surprisingly different light. The shift in interpretations of what you do as a manager — and how your organization behaves — will require you to make changes. Even if you can’t be ready for the all the challenges, you’ll be better off if you begin preparing now.

        Reproduced from MIT SLOAN Management Review


        0 0

        A Refresher on Regression Analysis


















        You probably know by now that whenever possible you should be making data-driven decisions at work.

        But do you know how to parse through all of the data available to you? The good news is that you likely don’t have to do the number crunching yourself (hallelujah!) but you do need to correctly understand and interpret the analysis created by your colleagues. One of the most important types of data analysis is regression.

        To better understand this method and how companies use it, I talked with Tom Redman, author of Data Driven: Profiting from Your Most Important Business Asset. He also advises organizations on their data and data quality programs.

        What is regression analysis?

        Redman offers this example scenario: Suppose you’re a sales manager trying to predict next month’s numbers. You know that dozens, perhaps even hundreds of factors from the weather to a competitor’s promotion to the rumor of a new and improved model can impact the number. Perhaps people in your organization even have a theory about what will have the biggest effect on sales. “Trust me. The more rain we have, the more we sell.” “Six weeks after the competitor’s promotion, sales jump.”

        ⦁ Regression analysis is a way of mathematically sorting out which of those variables does indeed have an impact.

        It answers the questions: Which factors matter most? Which can we ignore? How do those factors interact with each other?

        And, perhaps most importantly, how certain are we about all of these factors?

        In regression analysis, those factors are called variables. You have your dependent variable — the main factor that you’re trying to understand or predict. In Redman’s example above, the dependent variable is monthly sales. And then you have your independent variables — the factors you suspect have an impact on your dependent variable.

        How does it work?

        In order to conduct a regression analysis, you gather the data on the variables in question. (Reminder: you likely don’t have to do this yourself, but it’s helpful for you to understand the process your data analyst colleague uses.) You take all of your monthly sales numbers for, say, the past three years and any data on the independent variables you’re interested in. So, in this case, let’s say you find out the average monthly rainfall for the past three years as well.

        Then you plot all of that information on a chart that looks like this:



























        The y-axis is the amount of sales (the dependent variable, the thing you’re interested in, is always on the y-axis) and the x-axis is the total rainfall. Each blue dot represents one month’s data—how much it rained that month and how many sales you made that same month.


        Glancing at this data, you probably notice that sales are higher on days when it rains a lot.

        That’s interesting to know, but by how much?

        If it rains 3 inches, do you know how much you’ll sell? What about if it rains 4 inches?

        Now imagine drawing a line through the chart above, one that runs roughly through the middle of all the data points. This line will help you answer, with some degree of certainty, how much you typically sell when it rains a certain amount.

























        This is called the regression line and it’s drawn (using a statistics program like SPSS or STATA or even Excel) to show the line that best fits the data. In other words, explains Redman, “The red line is the best explanation of the relationship between the independent variable and dependent variable.”
        In addition to drawing the line, your statistics program also outputs a formula that explains the slope of the line and looks something like this:





        Ignore the error term for now. It refers to the fact that regression isn’t perfectly precise. Just focus on the model:




        What this formula is telling you is that if there is no “x” then Y = 200. So, historically, when it didn’t rain at all, you made an average of 200 sales and you can expect to do the same going forward assuming other variables stay the same. And in the past, for every additional inch of rain, you made an average of five more sales. “For every increment that x goes up one, y goes up by five,” says Redman.

        Now let’s return to the error term. You might be tempted to say that rain has a big impact on sales if for every inch you get five more sales, but whether this variable is worth your attention will depend on the error term. A regression line always has an error term because, in real life, independent variables are never perfect predictors of the dependent variables. Rather the line is an estimate based on the available data. So the error term tells you how certain you can be about the formula. The larger it is, the less certain the regression line.

        The above example uses only one variable to predict the factor of interest — in this case rain to predict sales. Typically you start a regression analysis wanting to understand the impact of several independent variables. So you might include not just rain but also data about a competitor’s promotion. “You keep doing this until the error term is very small,” says Redman.

        “You’re trying to get the line that fits best with your data.” While there can be dangers to trying to include too many variables in a regression analysis, skilled analysts can minimize those risks. And considering the impact of multiple variables at once is one of the biggest advantages of regression.
        How do companies use it?


        Regression analysis is the “go-to method in analytics,” says Redman. And smart companies use it to make decisions about all sorts of business issues. “As managers, we want to figure out how we can impact sales or employee retention or recruiting the best people. It helps us figure out what we can do.”

        Most companies use regression analysis to explain a phenomenon they want to understand (e.g. why did customer service calls drop last month?); predict things about the future (e.g. what will sales look like over the next six months?); or to decide what to do (e.g. should we go with this promotion or a different one?).

        A note about “correlation is not causation”

        Whenever you work with regression analysis or any other analysis that tries to explain the impact of one factor on another, you need to remember the important adage: Correlation is not causation. This is critical and here’s why: It’s easy to say that there is a correlation between rain and monthly sales. The regression shows that they are indeed related. But it’s an entirely different thing to say that rain caused the sales. Unless you’re selling umbrellas, it might be difficult to prove that there is cause and effect.

        Sometimes factors are correlated that are so obviously not connected by cause and effect but more often in business, it’s not so obvious. When you see a correlation from a regression analysis, you can’t make assumptions, says Redman. Instead, “You have to go out and see what’s happening in the real world. What’s the physical mechanism that’s causing the relationship?” Go out an observe consumers buying your product in the rain, talk to them, and find out, what is actually causing them to make the purchase. “A lot of people skip this step and I think it’s because they’re lazy. The goal is not to figure out what is going on in the data but to figure out is what is going on in the world. You have to go out and pound the pavement,” he says.

        Redman wrote about his own experiment and analysis in trying to lose weight and the connection between his travel and weight gain. He noticed that when he traveled, he ate more and exercised less. So was his weight gain caused by travel? Not necessarily. “It was nice to quantify what was happening but travel isn’t the cause. It may be related,” he says, but it’s not like his being on the road put those extra pounds on. He had to understand more about what was happening during his trips. “I’m often in new environments so maybe I’m eating more because I’m nervous?” He needed to look more closely at the correlation. And this is his advice to managers. Use the data to guide more experiments, not to make conclusions about cause and effect.

        What mistakes do people make when working with regression analysis?

        As a consumer of regression analysis, there are several things you need to keep in mind.
        First, don’t tell your data analyst to go out and figure out what is affecting sales. “The way most analyses go haywire is the manager hasn’t narrowed the focus on what he or she is looking for,” says Redman. It’s your job to identify the factors that you suspect are having an impact and ask your analyst to look at those. “If you tell a data scientist to go on a fishing expedition, or to tell you something you don’t know, then you deserve what you get, which is bad analysis,” he says. In other words, don’t ask your analysts to look at every variable they can possibly get their hands on all at once. If you do, you’re likely to find relationships that don’t really exist. It’s the same principle as flipping a coin: do it enough times, you’ll eventually think you see something interesting, like a bunch of heads all in a row.

        Also keep in mind whether or not you can do anything about the independent variable you’re considering. You can’t change how much it rains so how important is it to understand that? “We can’t do anything about weather or our competitor’s promotion but we can affect our own promotions or add features, for example,” says Redman.

        Always ask yourself what you will do with the data. What actions will you take? What decisions will you make?

        Second, “analyses are very sensitive to bad data” so be careful about the data you collect and how you collect it, and know whether you can trust it. “All the data doesn’t have to be correct or perfect,” explains Redman but consider what you will be doing with the analysis. If the decisions you’ll make as a result don’t have a huge impact on your business, then it’s OK if the data is “kind of leaky.” But “if you’re trying to decide whether to build 8 or 10 of something and each one costs $1 million to build, then it’s a bigger deal,” he says. The chart below explains how to think about whether to act on the data.




        Redman says that some managers who are new to understanding regression analysis make the mistake of ignoring the error term. This is dangerous because they’re making the relationship between something more certain than it is. “Oftentimes the results spit out of a computer and managers think, ‘That’s great, let’s use this going forward.’” But remember that the results are always uncertain. As Redman points out, “If the regression explains 90% of the relationship, that’s great. But if it explains 10%, and you act like it’s 90%, that’s not good.” The point of the analysis is to quantify the certainty that something will happen. “It’s not telling you how rain will influence your sales, but it’s telling you the probability that rain may influence your sales.”

        The last mistake that Redman warns against is letting data replace your intuition.

        “You always have to lay your intuition on top of the data,” he explains. Ask yourself whether the results fit with your understanding of the situation. And if you see something that doesn’t make sense ask whether the data was right or whether there is indeed a large error term. Redman suggests you look to more experienced managers or other analyses if you’re getting something that doesn’t make sense. And, he says, never forget to look beyond the numbers to what’s happening outside your office:

        “You need to pair any analysis with study of real world. The best scientists — and managers — look at both.”

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