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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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    Airport Authority of India Executive Recruitment

    AAI Junior Executive Recruitment 2016:

    Apply for 220 posts

    AAI Jr Executive Recruitment 2016:The application process will commence from April 18 and the last date to send the fully completed form is on May 17, 2016

    aai, aai recruitment, aai recruitment 2016,, AAI Jr Executive Recruitment 2016, AAI Jr Executive Recruitment eligibility, aai engineer jobs 2016, aai jr eng vacancy, jobs for graduate, engineering job graduate AAI Jr Executive Recruitment 2016: The CTC would be around Rs 6.9 lakh.

    The Airports Authority of India (AAI) has invited candidates for the post of junior executive in various streams. The selected candidates will fill up around 220 vacancies.

    The application process will commence from April 18 and the last date to send the fully completed form is on May 17, 2016.

    The Airports Authority of India (AAI) ATC is under the Ministry of Civil Aviation.

    Vacancy details

    Jr Executive (Civil): 50 posts

    Jr Executive (Electrical): 50 posts

    Jr Executive (Information Technology): 20 posts

    Jr Executive (Airport Operations): 100 posts

    Salary: Rs 16,400 to Rs 40,500. The CTC would be around Rs 6.9 lakh

    View: PHOTOS: Top government jobs to apply in March-April 2016

    Educational qualifications:

    The candidates should have a minimum 60% marks in degree. The candidates who have appeared for the final year examination can also apply.

    Junior Executive (Civil): BE/ B.Tech in Civil engineering

    Junior Executive (Electrical): B.E/ B.Tech in Electrical engineering

    Junior Executive (IT): B.E/ B.Tech in Computer science/ Computer engineering/ IT

    Junior Executive (Airport Operations): Graduate in science and MBA (regular) or Bachelors degree in engineering. Valid driving license is essential for JE (Airport Operations).

    Age limit: The candidates who had applied should have a maximum age as on 31.5.2016

    General: 27 years

    OBC: 30 years

    SC/ST: 32 years

    View the detailed advertisement

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    Deliberately Developmental

    How workplaces can build success by unlocking the potential of every employee.


    Many workplaces claim to be committed to fostering the personal growth of their employees. But few are deliberately organized to put employee growth at the very center of their mission. After all, when was the last time you worked somewhere that asked you to talk several times a day about your progress on personal-improvement goals, to undergo a formal review in front of colleagues (who discuss your performance with total candor), or to recognize that longtime leaders may be demoted by their peers at any time?

    It may sound shocking. But imagine if, at the same time, your colleagues were excited to celebrate your personal accomplishments, your supervisor was eager to make your development one of her top priorities, your organization's leaders prioritized trust and held themselves to the same standards as others, and that everyone in your workplace was fully committed to the success of both the company and each other?

    Organizations that engage in practices like these — called “deliberately developmental” in a new book exploring the topic — have embraced the “simple but radical” conviction that they will thrive only if and when every one of their employees does.

    And as the authors of An Everyone Culture found, these companies appear to have charted a new and distinctive path to success, one that lays out a new definition of what it means to be at work. In the process, they broaden the notion of a “learning organization,” making the case that any workplace — including, but not limited to, schools — can be a site of deep learning and personal growth.

    The benefits for the three deliberately developmental organizations (DDOs) the book profiles are staggering: increased profitability, improved employee retention, better communication, reductions in employee downtime, less interdepartmental strife, and faster solutions to tough problems, such as how to anticipate crises, create valuable leadership, and realize future possibilities — to name a few.
    These companies offer a model for the rest of us — for organizations and schools seeking to grow, for leaders wanting to make a cultural change, and even for individual employees who may feel stuck, say Lisa Laskow Lahey and Robert Kegan, who wrote An Everyone Culture with fellow Harvard Graduate School of Education faculty Matthew L. Miller and Deborah Helsing and with organizational consultant Andy Fleming.

    It turns out, says Lahey in a recent EdCast interview, that “when you support people’s development, it allows the organization to better and better deliver on its mission.” When employees overcome their barriers to success — facing their vulnerabilities and offering support in kind — organizations clear hurdles, too.

    Five Qualities that Make a DDO

    In their analysis of these DDOs, the authors demonstrate to other organizations how they, too, can maximize their outcomes by helping employees overcome personal challenges and amplify their potential.

    A key finding: Development does not happen on its own. Engrained practices — or specific routines that emphasize growth in every aspect of the workday — are key to ensuring that employees will keep growing.

    What types of practices encourage growth?

    1. Practices that shed light on internal struggles. The DDOs the researchers studied all invited employees to share challenges and goals that, typically, might be considered irrelevant to a professional environment. By helping workers overcome internal or personal struggles, the organizations helped them address longstanding limitations in the way they approached their work.

    2. Practices that connect professional and personal work. This same focus on surmounting personal challenges was not a separate part of the work day, but integrated throughout. For instance, rather than host an annual session on how to receive feedback, the organizations made feedback and coaching a fundamental part of every meeting.

    3. Practices that shift the focus from outcomes to the processes generating those outcomes. All three DDOs were less concerned with correcting an unhelpful behavior than they were with changing the mindset that created that behavior. This perspective helped emphasize the importance of achieving long-term goals above short-term ones.

    Practices that give employees a common language. Each organization wound up with its own “language” used to describe its many practices and norms. While perhaps confusing to outsiders, these languages both built community within each workplace and helped further integrate the developmental practices into the workday. Practices that exist every day, at every level. Personal development was always an essential goal — for entry-level new hires and for the most senior leaders alike, in meetings and on individual assignments, every day of the week.

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    The organizational cost of insufficient sleep

    Sleep-awareness programs can produce better leaders.
    Thou hast no figures nor no fantasies,
    Which busy care draws in the brains of men;
    Therefore thou sleep’st so sound.

    —William Shakespeare, Julius Caesar

    In the passage above, the playwright’s tragic antihero Brutus enviously reflects on the timeless truth that people without worries and anxieties (in this case, his servant Lucius) generally enjoy the most peaceful and uninterrupted rest.

    Some senior business people skillfully and consciously manage their sleep, emerging refreshed and alert after crossing multiple time zones or working late into the night. Yet we all know caffeinated and careworn executives who, after hours of wakeful slumber, struggle to recall simple facts, seem disengaged and uninspired, lack patience with others, and can’t think through problems or reach clear-cut decisions.

    Sleep (mis)management, at one level, is obviously an individual issue, part of a larger energy-management challenge that also includes other forms of mental relaxation, such as mindfulness and meditation, as well as nutrition and physical activity. But in an increasingly hyperconnected world, in which many companies now expect their employees to be on call and to answer emails 24/7, this is also an important organizational topic that requires specific and urgent attention.

    Research has shown that sleep-deprived brains lose the ability to make accurate judgments. That, in turn, can lead to irrational and unjustified claims such as “I do not need sleep” or “I’m doing fine with a couple of hours of sleep.” Our own recent survey of executives (see sidebar “Highlights from our survey of 196 business leaders”) demonstrates how many of them remain in denial on this point. Yet our respondents contradicted themselves by suggesting that companies should do more to help teach leaders the importance of sleep.

    On this point, they are right. Many companies do not do enough to promote healthy sleep, which can have serious consequences. As we will demonstrate, sleep deficiencies impair the performance of corporate executives, notably by undermining important forms of leadership behavior, and can thereby hurt financial performance. This article will demonstrate and explore the link between sleep and leadership behavior before discussing solutions that can improve both individual well-being and organizational efficiency and effectiveness.

    The link to organizational leadership

    The last part of our brain to evolve was the neocortex, responsible for functions such as sensory perception, motor commands, and language. The frontal part of the neocortex, the prefrontal cortex, directs what psychologists call executive functioning, including all the higher-order cognitive processes, such as problem solving, reasoning, organizing, inhibition, planning, and executing plans. These help us get things done.

    It’s long been known that all leadership behavior relies on at least one (and often more than one) of these executive functions and therefore, in particular, on the prefrontal cortex. Neuroscientists know that although other brain areas can cope relatively well with too little sleep, the prefrontal cortex cannot.1 Although basic visual and motor skills deteriorate when people are deprived of sleep, they do not do so nearly to the same extent as higher-order mental skills.

    Previous McKinsey research has highlighted a strong correlation between leadership performance and organizational health,2 itself a strong predictor of a healthy bottom line. In a separate study of 81 organizations and 189,000 people around the world, we have found that four types of leadership behavior are most commonly associated with high-quality executive teams: the ability to operate with a strong orientation to results, to solve problems effectively, to seek out different perspectives, and to support others.3 What’s striking, in all four cases, is the proven link between sleep and effective leadership (exhibit).

    Operating with a strong orientation to results

    To do this well, it’s important to keep your eye on the ball and avoid distractions, while at the same time seeing the bigger picture—that is, whether your company is heading in the right direction. Scientists have found that sleep deprivation impairs this ability to focus attention selectively. Research shows that after roughly 17 to 19 hours of wakefulness (let’s say at 11 PM or 1 AM for someone who got up at 6 AM), individual performance on a range of tasks is equivalent to that of a person with a blood-alcohol level of 0.05 percent. That’s the legal drinking limit in many countries. After roughly 20 hours of wakefulness (2 AM), this same person’s performance equals that of someone with a blood-alcohol level of 0.1 percent, which meets the legal definition of drunkenness in the United States.

    Solving problems effectively

    Sleep is beneficial for a host of cognitive functions—insight, pattern recognition, and the ability to come up with innovative and creative ideas—that help us solve problems effectively. One study has shown that a good night’s sleep leads to new insights: participants who enjoyed one were twice as likely as those who didn’t to discover a hidden shortcut in a task. Likewise, an afternoon nap has been found to aid creative problem solving: subjects who took a nap after struggling on a video-game problem were almost twice as likely to solve it as subjects who had remained awake. Other research has established that creative thinking is especially likely to take place during dream sleep, enhancing the integration of unassociated information and promoting creative solutions.

    Seeking different perspectives

    A wealth of scientific studies have also highlighted the impact of sleep on all three stages of the learning process—before learning, to encode new information; after learning, in the consolidation stage, when the brain forms new connections; and before remembering, to retrieve information from memory. An important consideration for leaders seeking different perspectives is the ability to weigh the relative significance of different inputs accurately, to avoid tunnel vision, and to reduce cognitive bias. Sleep has been shown to improve decision making for tasks that mimic real life, such as complex cognitive–emotional ones which integrate emotional responses by involving financial rewards and punishments. Science supports the commonly heard advice that rather than making an important decision or sending a sensitive email late at night, you should sleep on it.5

    Supporting others

    To help other people, you must first understand them—for example, by interpreting the emotions on their faces or their tone of voice. In a sleep-deprived state, your brain is more likely to misinterpret these cues and to overreact to emotional events,6 and you tend to express your feelings in a more negative manner and tone of voice.7 Recent studies have shown that people who have not had enough sleep are less likely to fully trust someone else, and another experiment has demonstrated that employees feel less engaged with their work when their leaders have had a bad night of sleep.8

    What organizations can do

    How can organizations improve the quality and efficiency of sleep to ensure that their leaders attain—or recapture—the highest performance levels? At McKinsey, we’ve been working on this issue with our own colleagues, as well as with business leaders, over the past year. We offer this menu of possible solutions for companies to consider. As we are the first to admit, our own people do not always practice what we preach. In any case, certain types of organizations cannot implement these ideas without an accompanying change in the underlying culture.

    Training programs

    Interestingly, 70 percent of the leaders in our survey said that sleep management should be taught in organizations, just as time management and communication skills are now. Ideally, such programs should be part of a unified learning program that includes a number of components, such as online assessments, in-person workshops, and a performance-support app offering reminders, short inspirational videos or animations, additional assessments, and opportunities to connect with online communities. (For a selection of healthy sleep habits, see sidebar “Sleep tips.”)

    Companies should embed sleep training in a broader approach to well-being that takes in other topics, notably exercise, nutrition, mindfulness, and energy management. Yet it can be daunting for leaders to go about changing a lot of behavior at once, so it’s important to allow time for new habits to stick.

    Company policies

    Before introducing new policies, businesses should start a conversation among their leaders to determine which ideas will best suit the organization, particularly bearing in mind the fact that working cultures differ.

    Travel. Companies should encourage flexibility—for example, by allowing employees, if possible, to take an earlier plane (rather than an overnight “red eye” flight) to get a good night’s sleep before an important meeting.

    Team working. Companies must increasingly be responsive 24/7, but this doesn’t mean that specific people should bear the brunt of the burden single-handedly. IT help desks in many global organizations have shown the way—shifting location every eight hours. Likewise, other groups should work to alleviate the pressure by creating “tag teams” of employees who seamlessly hand over the reins to other teams, in different time zones, at the end of their shifts. Phone calls and home-based videoconferences do run the risk of extending the workday but, used judiciously, can cut unnecessary travel-to-work time. Leaders should set an example by being mindful of local times (and the time preferences of the people involved) when scheduling global calls. Simply knowing the participants’ preferences can help reinforce a sleep-friendly culture.

    Emails. A number of companies have imposed blackout times on work emails. A large European car business, for example, programs the smartphones of its nonmanagement employees to switch off work emails automatically between 6 p.m. and 7 a.m. In many companies, particularly knowledge-based ones, this would be disruptive and counterproductive—but provided there are overrides, such a policy can send a clear signal of management’s intent.

    Work-time limits. Some companies known for a “long-hours culture” have been implementing rules to curb working very late at night. One major financial-services business, for example, specifically required its summer interns to leave the office before midnight each day to ensure that they were not subjected to “all-nighters.” This organization’s full-time employees have been told to stay out of the office from 9 p.m. Friday to 9 a.m. Sunday.

    Mandatory work-free vacations. A US software company gives employees a $7,500 bonus if they follow two rules: (1) They have to actually go on vacation or they don’t get the money. (2) They must disconnect, and hence cannot work, on vacation.

    ‘Predictable time off’ (PTO). Leslie Perlow, a professor at Harvard Business School, introduced a good way to catch up on lost sleep: a planned night off, with no email, no work, and no smartphone. A large global consulting firm found that productivity went up when it tested this approach, which is now the basis for a company-wide program.

    Napping rooms or pods. The image of a sleeping manager is easy to mischaracterize. Research has shown that a short nap of 10 to 30 minutes improves alertness and performance for up to two and a half hours.9 Over half of the leaders in our survey wanted their businesses to imitate the large technology companies and telcos that have already successfully adopted sleep pods and nap rooms.
    Smart technology. Companies should consider supplying (or at least informing their employees about) some of the gadgets and tools designed to improve sleep management. Examples include the f.lux application, which limits blue light on computers and iPhones, thereby boosting reduced levels of the sleep hormone melatonin. Other apps on the market provide individualized jetlag-minimizing schedules.

    Organizations of the future

    Much attention has been focused on the importance of sleep for top-performing athletes, musicians, and even politicians. Expert violinists, for example, have cited practice and sleep as two of the most important drivers of performance. (One study shows that the top performers consistently take a nap and get over half an hour more sleep than their less well-regarded peers do.) Former US president Bill Clinton once admitted, “Every important mistake I’ve made in my life I made when I was tired.” Business people have often lagged behind others in both their willingness to acknowledge the issue and their readiness to act on it.

    A recent Harvard Medical School study surveyed senior leaders and found that 96 percent reported experiencing at least some degree of burnout. One-third described their condition as extreme.10 It’s time for organizations to find ways of countering the employee churn, lost productivity, and increased healthcare costs resulting from insufficient sleep. If it is true that some millennials care less about high salaries and more about work–life integration, the next generation of employees will demand solutions even more strongly.

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    Just How Smart Are Smart Machines? 

    The number of sophisticated cognitive technologies that might be capable of cutting into the need for human labor is expanding rapidly. But linking these offerings to an organization’s business needs requires a deep understanding of their capabilities.

    If popular culture is an accurate gauge of what’s on the public’s mind, it seems everyone has suddenly awakened to the threat of smart machines. Several recent films have featured robots with scary abilities to outthink and manipulate humans. In the economics literature, too, there has been a surge of concern about the potential for soaring unemployment as software becomes increasingly capable of decision making. Yet managers we talk to don’t expect to see machines displacing knowledge workers anytime soon — they expect computing technology to augment rather than replace the work of humans. In the face of a sprawling and fast-evolving set of opportunities, their challenge is figuring out what forms the augmentation should take. Given the kinds of work managers oversee, what cognitive technologies should they be applying now, monitoring closely, or helping to build?

    To help, we have developed a simple framework that plots cognitive technologies along two dimensions. (See “What Today’s Cognitive Technologies Can — and Can’t — Do.”) First, it recognizes that these tools differ according to how autonomously they can apply their intelligence. On the low end, they simply respond to human queries and instructions; at the (still theoretical) high end, they formulate their own objectives. Second, it reflects the type of tasks smart machines are being used to perform, moving from conventional numerical analysis to performance of digital and physical tasks in the real world. The breadth of inputs and data types in real-world tasks makes them more complex for machines to accomplish.

    By putting those two dimensions together, we create a matrix into which we can place all of the multitudinous technologies known as “smart machines.” More important, this helps to clarify today’s limits to machine intelligence and the challenges technology innovators are working to overcome next. Depending on the type of task a manager is targeting for redesigned performance, this framework reveals the various extents to which it might be performed autonomously and by what kinds of machines.

    Four Levels of Intelligence

    Clearly, the level of intelligence of smart machines is increasing. The general trend is toward greater autonomy in decision making — from machines that require a highly structured data and decision context to those capable of deciphering a more complex context.

    Support for Humans

    For decades, the prevailing assumption has been that cognitive technologies would provide insight to human decision makers — what used to be known as “decision support.” Even with IBM Corp.’s Watson and many of today’s other cognitive systems, most people assume that the machine will offer a recommended decision or course of action but that a human will make the final decision.

    Repetitive Task Automation

    It is a relatively small step to go from having machines support humans to having the machines make decisions, particularly in structured contexts. Automated decision making has been gaining ground in recent years in several domains, such as insurance underwriting and financial trading; it typically relies on a fixed set of rules or algorithms, so performance doesn’t improve without human intervention. Typically, people monitor system performance and fine-tune the algorithms.

    Context Awareness and Learning

    Sophisticated cognitive technologies today have some degree of real-time contextual awareness. As data flow more continuously and voluminously, we need technologies that can help us make sense of the data in real time — detecting anomalies, noticing patterns, and anticipating what will happen next. Relevant information might include location, time, and/or a user’s identity, which might be used to make recommendations (for example, the best route to work based on the time of day, current traffic levels, and the driver’s preference for highways versus back roads).

    One of the hallmarks of today’s cognitive computing is its ability to learn and improve performance. Much of the learning takes place through continuous analysis of real-time data, user feedback, and new content from text-based articles. In settings where results are measurable, learning-oriented systems will ultimately deliver benefits in the form of better stock trading decisions, more accurate driving time predictions, and more precise medical diagnoses.


    So far, machines with self-awareness and the ability to form independent objectives reside only in the realm of fiction. With substantial self-awareness, computers may eventually gain the ability to work beyond human levels of intelligence across multiple contexts, but even the most optimistic experts say that general intelligence in machines is three to four decades away.

    Four Cognitive Task Types

    A straightforward way to sort out tasks performed by machines is according to whether they process only numbers, text, or images — the building blocks of cognition — or whether they know enough to take informed actions in the digital or physical world.

    Analyzing Numbers

    The root of all cognitive technologies is computing machines’ superior performance at analyzing numbers in structured formats (typically, rows and columns). Classically, this numerical analysis was applied purely in support of human decision makers. People continued to perform the front-end cognitive tasks of creating hypotheses and framing problems, as well as the back-end interpretation of the numbers’ implications for decisions. Even as analysts added more visual analytics displays and more predictive analytics in the past decade, people still did the interpretation.

    Today, companies are increasingly embedding analytics into operational systems and processes to make repetitive automated decisions, which enables dramatic increases in both speed and scale. And whereas it used to take a human analyst to develop embedded models, “machine learning” methods can produce models in an automated or semiautomated fashion.

    Analyzing Words and Images

    A key aspect of human cognition is the ability to read words and images and to determine their meaning and significance. But today, a wide variety of technological tools, such as machine learning, natural language processing, neural networks, and deep learning, can classify, interpret, and generate words. Some of them can also analyze and identify images.

    The earliest intelligent applications involving words and images involved text, image, and speech recognition to allow humans to communicate with computers. Today, of course, smartphones “understand” human speech and text and can recognize images. These capabilities are hardly perfect, but they are widely used in many applications.

    When words and images are analyzed on a large scale, this comprises a different category of capability. One such application involves translating large volumes of text across languages. Another is to answer questions as a human would. A third is to make sense of language in a way that can either summarize it or generate new passages.

    IBM Watson was the first tool capable of ingesting, analyzing, and “understanding” text well enough to respond to detailed questions. However, it doesn’t deal with structured numerical data, nor can it understand relationships between variables or make predictions. It’s also not well suited for applying rules or analyzing options on decision trees. However, IBM is rapidly adding new capabilities included in our matrix, including image analysis.

    There are other examples of word and image systems. Most were developed for particular applications and are slowly being modified to handle other types of cognitive situations. Digital Reasoning Systems Inc., for example, a company based in Franklin, Tennessee, that developed cognitive computing software for national security purposes, has begun to market intelligent software that analyzes employee communications in financial institutions to determine the likelihood of fraud.

    Another company, IPsoft Inc., based in New York City, processes spoken words with an intelligent customer agent programmed to interpret what customers want and, when possible, do it for them.
    IPsoft, Digital Reasoning, and the original Watson all use similar components, including the ability to classify parts of speech, to identify key entities and facts in text, to show the relationships among entities and facts in a graphical diagram, and to relate entities and relationships with objectives. This category of application is best suited for situations with much more — and more rapidly changing — codified textual information than any human could possibly absorb and retain.

    Image identification and classification are hardly new. “Machine vision” based on geometric pattern matching technology has been used for decades to locate parts in production lines and read bar codes. Today, many companies want to perform more sensitive vision tasks such as facial recognition, classification of photos on the Internet, or assessment of auto collision damage. Such tasks are based on machine learning and neural network analysis that can match particular patterns of pixels to recognizable images.

    The most capable machine learning systems have the ability to “learn” — their decisions get better with more data, and they “remember” previously ingested information. For example, as Watson is introduced to new information, its reservoir of information expands. Other systems in this category get better at their cognitive task by having more data for training purposes. But as Mike Rhodin, senior vice president of business development for IBM Watson, noted, “Watson doesn’t have the ability to think on its own,” and neither does any other intelligent system thus far created.

    Performing Digital Tasks

    One of the more pragmatic roles for cognitive technology in recent years has been to automate administrative tasks and decisions. In order to make automation possible, two technical capabilities are necessary. First, you need to be able to express the decision logic in terms of “business rules.” Second, you need technologies that can move a case or task through the series of steps required to complete it. Over the past couple of decades, automated decision-making tools have been used to support a wide variety of administrative tasks, from insurance policy approvals to information technology operations to high-speed trading.

    Lately, companies have begun using “robotic process automation,” which uses work flow and business rules technology to interface with multiple information systems as if it were a human user. Robotic process technology has become popular in banking (for back-office customer service tasks, such as replacing a lost ATM card), insurance (for processing claims and payments), information technology (IT) (for monitoring system error messages and fixing simple problems), and supply chain management (for processing invoices and responding to routine requests from customers and suppliers).

    The benefits of process automation can add up quickly. An April 2015 case study at Telefónica O2, the second-largest mobile carrier in the United Kingdom, found that the company had automated over 160 process areas using software “robots.” The overall three-year return on investment was between 650% and 800%.

    Performing Physical Tasks

    Physical task automation is, of course, the realm of robots. Though people love to call every form of automation technology a robot, one of Merriam-Webster’s definitions of robot is “a machine that can do the work of a person and that works automatically or is controlled by a computer.”

    In 2014, companies installed about 225,000 industrial robots globally, more than one-third of them in the automotive industry. However, robots often fall well short of expectations. In 2011, the founder of Foxconn Technology Co., Ltd., a Taiwan-based multinational electronics contract manufacturing company, said he would install one million robots within three years, replacing one million workers. However, the company found that employing only robots to build smartphones was easier said than done. To assemble new iPhone models in 2015, Foxconn planned to hire more than 100,000 new workers and install about 10,000 new robots.

    Historically, robots that replaced humans required a high level of programming to do repetitive tasks. For safety reasons, they had to be segregated from human workers. However, a new type of robots — often called “collaborative robots” — can work safely alongside humans. They can be programmed simply by having a human move their arms.

    Robots have varying degrees of autonomy. Some, such as remotely piloted drone aircraft and robotic surgical instruments and mining equipment, are designed to be manipulated by humans. Others become at least semiautonomous once programmed but have limited ability to respond to unexpected conditions. As robots get more intelligence, better machine vision, and increased ability to make decisions, they will integrate other types of cognitive technologies while also having the ability to transform the physical environment. IBM Watson software, for example, has been installed in several different types of robots.

    The Great Convergence

    Slowly but surely, the worlds of artificially intelligent software and robots seem to be converging, and the boundaries between different cognitive technologies are blurring. In the future, robots will be able to learn and sense context, robotic process automation and other digital task tools will improve, and smart software will be able to analyze more intricate combinations of numbers, text, and images.
    We anticipate that companies will develop cognitive solutions using the building blocks of application program interfaces (APIs). One API might handle language processing, another numerical machine learning, and a third question-and-answer dialogue. While these elements would interact with each other, determining which APIs are required will demand a sophisticated understanding of cognitive solution architectures.

    This modular approach is the direction in which key vendors are moving. IBM, for example, has disaggregated Watson into a set of services — a “cognitive platform,” if you will — available by subscription in the cloud. Watson’s original question-and- answer services have been expanded to include more than 30 other types, including “personality insights” to gauge human behavior, “visual recognition” for image identification, and so forth. Other vendors of cognitive technologies, such as Cognitive Scale Inc., based in Austin, Texas, are also integrating multiple cognitive capabilities into a “cognitive cloud.”

    Despite the growing capabilities of cognitive technologies, most organizations that are exploring them are starting with small projects to explore the technology in a specific domain. But others have much bigger ambitions. For example, Memorial Sloan Kettering Cancer Center, in New York City, and the University of Texas MD Anderson Cancer Center, in Houston, Texas, are taking a “moon shot” approach, marshaling cognitive tools like Watson to develop better diagnostic and treatment approaches for cancer.

    Designing a Cognitive Architecture

    Hardware and software will continue to get better, but rather than waiting for next- generation options, managers should be introducing cognitive technologies to workplaces now and discovering their human-augmenting value. The most sophisticated managers will create IT architectures that support more than one application. Indeed, we expect to see organizations building “cognitive architectures” that interface with, but are distinct from, their regular IT architectures. What would that mean? We think a well-designed cognitive architecture would emphasize several attributes:

    The Ability to Handle a Variety of Data Types

    Cognitive insights don’t just come from a single data type (text, for example). In the future, they will come from combining text, numbers, images, speech, genomic data, and so forth to develop broad situational awareness.

    The Ability to Learn

    Although this should be the essence of cognitive technologies, most systems today (such as rules
    engines and robotic process automation) don’t improve themselves. If you have a choice between a system that learns and one that doesn’t, go with the former.


    Humans and cognitive technologies will be working together for the foreseeable future. Humans will always want to know how the cognitive technologies came up with their decision or recommendation. If people can’t open the “black box,” they won’t trust it. This is a key aspect of augmentation, and one that will facilitate rapid adoption of these technologies.

    A Variety of Human Roles

    Once programmed, some cognitive technologies, like most industrial robots, run their assigned process. By contrast, with surgical robots it’s assumed that a human is in charge. In the future, we will probably need multiple control modes. As with self-driving vehicles, there needs to be a way for the human to take control. Having multiple means of control is another way to facilitate augmentation rather than automation.

    Flexible Updating and Modification

    One of the reasons why rule-based systems have become successful in insurance and banking is that users can modify the rules. But modifying and updating most cognitive systems is currently a task only for experts. Future systems will need to be more flexible.

    Robust Reporting Capabilities

    Cognitive technologies will need to be accountable to the rest of the organization, as well as to other stakeholders. We’ve spoken, for example, with representatives of several companies using automated systems to buy and place digital ads, and they say that customers insist on detailed reporting so that the data can be “sliced and diced” in many different ways.

    State-of-the-Art IT Hygiene

    Cognitive technologies will need all the attributes of modern information systems, including an easy user interface, state-of-the-art data security, and the ability to handle multiple users at once. Companies won’t want to compromise on any of these objectives in the cognitive space, and eventually they won’t have to.

    What’s more, if the managerial goal is augmentation rather than automation, it’s essential to understand how human capabilities fit into the picture. People will continue to have advantages over even the smartest machines. They are better able to interpret unstructured data — for example, the meaning of a poem or whether an image is of a good neighborhood or a bad one. They have the cognitive breadth to simultaneously do a lot of different things well. The judgment and flexibility that come with these basic advantages will continue to be the basis of any enterprise’s ability to innovate, delight customers, and prevail in competitive markets — where, soon enough, cognitive technologies will be ubiquitous.

    Clearly, smart machines are advancing at the things they do well at a much faster rate than we humans are. And granted, many workers will need to call on and cultivate different capabilities than the ones they have relied on in the past. But for the foreseeable future, there are still unlimited ways for humans to contribute tremendous value. To the extent that wise managers leverage their talents with advanced technology, we can all stop dreading the rise of smart machines. 

    View at the original source

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    How social tools can reshape the organization.

    Not all social technologies bring equal benefits. Survey respondents say the most valuable tools make it easier for employees to collaborate—and could even transform the way organizations work

    While social technologies have become ubiquitous in business, not all tools—or the benefits companies  see from their use—are created equal. Indeed, results from McKinsey’s latest survey on social tools suggest that a new generation of tools is enabling employees to collaborate in improved and innovative ways.1 Respondents say improved internal communication is the feature of social tools that has most benefited their businesses. They also expect that, in the coming years, enabling better communication will be  one of the ways these tools could bring about fundamental changes at their organizations.

    The results also suggest that social tools play a critical role in how technology overall can encourage organizational change. We asked executives about their companies’ use of social tools, digital technologies, and big data in 18 different business processes; the clear consensus is that using social begets better use  of these other technologies. When organizations digitize a process’s work flow (which happens most often

    with customer-facing processes), respondents say that using social tools in that same process has  enabled their companies’ overall digital efforts. What’s more, some executives report greater benefits— decreased costs and increased productivity, for example—if they digitize and use social tools in a  given process. Several benefits are greater still if the company uses data collected from social interactions among employees and with customers.

    A new generation of social tools Executives report that the business use of social tools is nearly universal. Ninety-three percent  of respondents say their companies use at least one social technology, continuing an upward trend  (82 percent said so in the previous two surveys).2 And most respondents say employees at their  companies use at least one tool on mobile devices. In addition, 74 percent say social tools are at least somewhat integrated into employees’ work—up from 67 percent in the past two years.

    Although social technologies are more and more commonplace, the results suggest that not all tools are created equal. Specifically, those that can enable collaboration among employees are the most valued— increasingly important, since 80 percent of executives, up from 69 percent in 2014, say their companies use these tools for internal purposes.

    When asked about the most beneficial features of the social tools their companies use, respondents most often cite real-time interactions, the ability to collaborate with specific groups, and cross-platform availability (Exhibit 1). What’s more, respondents believe the same three features will most improve how people work at their organizations in the future.

    View Exhibits 1to 6

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    Equipping the Sustainability Insurgency.

    An environmentalist and an MBA team up to develop a network of sustainability champions.
    Sustainability World Wildlife Foundation.


    As this series has documented, Sustainability Insurgents are professional insiders driven by a higher purpose. While loyally serving their employers, they also pursue a higher ideal: aligning their organizations with a global vision of a peaceful, prosperous, and sustainable world. This article explores how two insurgents, working for dramatically different organizations, partnered to save the planet — and in doing so spread the sustainability insurgency to thousands of individuals and dozens of organizations.

    The unlikely duo is Frances Edmonds, an environmental scientist, and Adrienne Lo, an MBA. They hail from the conservation non-profit WWF and the tech leader HP Canada. But, in a twist increasingly common to the insurgency, the environmentalist works for the business, and the MBA works for the non-profit.

    What brought this odd couple together? A shared belief that saving the planet depends on engaging and rallying as many people as possible to action. Their target audience: Nascent Sustainability Insurgents, whom they call “champions,” in companies around the globe. Champions are employees who see opportunities for positive change, but aren’t tasked by their company’s official CSR function to act.

    Their model of change is peer-to-peer engagement, which they see as the most effective way to support champions and encourage them to take actions that can foster new sustainable norms at work.

    Edmonds and Lo knew from experience that champions operate on a volunteer basis, stepping up to the challenge largely because it makes their job more meaningful and personally fulfilling. This intrinsic motivation is vital because insurgents swim against the organizational current. They get told “no” often.

    It’s not that the companies don’t want to improve their sustainability performance: No executive gets up in the morning and asks, “How can I destroy the planet today?” But, according to Lo, established corporate processes, systems, and policies are difficult to change — and often, no single person or department has the power to act alone. Corralling and convincing all the needed people requires unique skills and organizational knowledge that are not readily available, nor taught in traditional management programs.

    This is where our duo steps in. They wanted a way to provide the know-how and tools champions need to advance the sustainability insurgency in their organizations. But more important, they knew that a supportive peer network of like-minded insurgents would empower champions and give them the courage to persist in the face of inevitable resistance.

    The result of their vision is a web-enabled system launched by WWF Canada called Living Planet @ Work, a free, one-stop-shop that provides insurgents with the resources, inspiration, and support they need to become sustainability champions in their company. The website also works to overcome the dismal rate of charitable giving to environmental causes, which is less than 5% in Canada, by encouraging users to support important WWF campaigns like Arctic conservation (see the video).

    Living Planet @ Work’s online tools include how-to guides for reducing the workplace environmental footprint and advice on engaging colleagues around sustainability. But beyond information, the site fosters an engaged, peer-to-peer network where members support each other in navigating the organizational obstacle course. As Frances puts it, “There is nothing more motivating than knowing that you’re not alone.”

    Since Living Planet @ Work launched 5 years ago, more than 1,200 champions have joined. The website documents examples of insurgents making their offices more energy efficient, reducing the landfill waste, organizing e-waste drives, and more. While these tangible outcomes are important, it is the growing organizational capacity to act on sustainability that ultimately counts. With each successful initiative, champions demonstrate to themselves, their peers, and company executives how corporate social responsibility can have an impact on important managerial issues like employee engagement, operational efficiency, and corporate purpose.

    Living Planet @ Work website captures the vision this way: “We know that meaningful change comes from within an organization, and the more help you can get to build support across teams and employees, the better.” This is where change begins, but the end game of these bottom-up victories must be an executive embrace of sustainability and a commitment to embedding corporate responsibility into every function of the organization. Luckily, with champions like these populating the company, executives will find an established network ready and willing to support a coherent and compelling sustainability strategy.

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    Hardware and software will continue to get better, but rather than waiting for next- generation options, managers should be introducing cognitive technologies to workplaces now and discovering their human-augmenting value. The most sophisticated managers will create IT architectures that support more than one application. Indeed, we expect to see organizations building “cognitive architectures” that interface with, but are distinct from, their regular IT architectures. What would that mean? We think a well-designed cognitive architecture would emphasize several attributes:

    The Ability to Handle a Variety of Data Types

    Cognitive insights don’t just come from a single data type (text, for example). In the future, they will come from combining text, numbers, images, speech, genomic data, and so forth to develop broad situational awareness.

    The Ability to Learn

    Although this should be the essence of cognitive technologies, most systems today (such as rules
    engines and robotic process automation) don’t improve themselves. If you have a choice between a system that learns and one that doesn’t, go with the former.


    Humans and cognitive technologies will be working together for the foreseeable future. Humans will always want to know how the cognitive technologies came up with their decision or recommendation. If people can’t open the “black box,” they won’t trust it. This is a key aspect of augmentation, and one that will facilitate rapid adoption of these technologies.

    A Variety of Human Roles

    Once programmed, some cognitive technologies, like most industrial robots, run their assigned process. By contrast, with surgical robots it’s assumed that a human is in charge. In the future, we will probably need multiple control modes. As with self-driving vehicles, there needs to be a way for the human to take control. Having multiple means of control is another way to facilitate augmentation rather than automation.

    Flexible Updating and Modification

    One of the reasons why rule-based systems have become successful in insurance and banking is that users can modify the rules. But modifying and updating most cognitive systems is currently a task only for experts. Future systems will need to be more flexible.

    Robust Reporting Capabilities

    Cognitive technologies will need to be accountable to the rest of the organization, as well as to other stakeholders. We’ve spoken, for example, with representatives of several companies using automated systems to buy and place digital ads, and they say that customers insist on detailed reporting so that the data can be “sliced and diced” in many different ways.

    State-of-the-Art IT Hygiene

    Cognitive technologies will need all the attributes of modern information systems, including an easy user interface, state-of-the-art data security, and the ability to handle multiple users at once. Companies won’t want to compromise on any of these objectives in the cognitive space, and eventually they won’t have to.

    What’s more, if the managerial goal is augmentation rather than automation, it’s essential to understand how human capabilities fit into the picture. People will continue to have advantages over even the smartest machines. They are better able to interpret unstructured data — for example, the meaning of a poem or whether an image is of a good neighborhood or a bad one. They have the cognitive breadth to simultaneously do a lot of different things well. The judgment and flexibility that come with these basic advantages will continue to be the basis of any enterprise’s ability to innovate, delight customers, and prevail in competitive markets — where, soon enough, cognitive technologies will be ubiquitous.

    Clearly, smart machines are advancing at the things they do well at a much faster rate than we humans are. And granted, many workers will need to call on and cultivate different capabilities than the ones they have relied on in the past. But for the foreseeable future, there are still unlimited ways for humans to contribute tremendous value. To the extent that wise managers leverage their talents with advanced technology, we can all stop dreading the rise of smart machines. 

    Reproduced from MIT Sloan Managed Review                                           Go to Page !

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    Remember when emerging economies were supposed to save us all? After the 2008 financial crisis, the traditional engines of global growth—the U.S., Western Europe, and Japan—stumbled into recession. To the rescue came the once-poor developing world. China, India, Brazil, and other up-and-comers powered the global economy through the historic downturn. The meek were inheriting the earth.

    Not completely, as it turns out.

    Today, as the U.S. recovery gains steam and even debt-burdened Europe stirs to life, the emerging world has tumbled into trouble. Growth is slowing, currencies are plunging, and investors are fleeing. Fears of a protracted slowdown in China sparked a worldwide stock selloff in August. The turmoil has even resurrected terrifying memories of previous emerging-markets crises, like East Asia’s rout in 1997, igniting jitters that the fragile global economy faces yet another financial debacle.
    But international investors are making a big mistake. The emerging world will be just fine, thank you. The global business community is allowing short-term uncertainty to cloud the long-term reality of the changing global economy: Emerging markets are still our future.

    There are certainly a host of reasons to be down about the developing world at the moment. Hypercharged growth rates have cooled just about everywhere. The International Monetary Fund forecasts that the output of emerging economies will rise only 4.2 percent in 2015, a sharp drop from 7.4 percent five years ago. Brazil and Russia, both proud members of the BRIC group of large developing nations, are in recession. China, the supposed juggernaut of the emerging world, has seen growth drop to its lowest rate in a quarter century.

    China, Brazil, and Russia are struggling, but other developing economies are posting strong growth
    Terrible policy is to blame. Politicians have been complacent about implementing the reforms necessary to keep growth going. China is example No. 1: Its top leaders have done little to overhaul an outdated, investment-heavy growth model. They’re still procrastinating about changes that would unleash the private sector, open markets, and improve productivity—all crucial for prosperity.

    In India, perhaps the only major emerging economy with sound prospects right now, Prime Minister Narendra Modi has yet to prove he can walk his bold talk of deregulating the economy to encourage investment. On Aug. 30, Modi announced he wouldn’t renew a controversial executive order that loosened restrictions on the purchase of land for industrial projects—a major setback to his efforts.
    Then there’s Vladimir Putin, who has strangled his oil-dependent economy by favoring an aggressive foreign policy and isolating Russia from the West, forgoing the investment and technology his country needs to advance.

    All this is happening while the international environment remains uncertain. Although growth in the U.S. and Europe is improving, the developed world may not be strong enough to buy more of the exports of developing nations, sparking a recovery among them. Investors have also been spooked by the expectation that the U.S. Federal Reserve will begin raising interest rates for the first time since the 2008 financial crisis. That could suck cash from developing economies (as U.S. assets become more attractive) and raise their borrowing costs—a potential double whammy for their already subdued growth prospects.

    As a consequence, a torrent of cash has fled the developing world. Investors yanked more than $900 billion from the world’s 19 largest emerging economies over a 13-month period ended in July, according to NN Investment Partners, a Netherlands-based asset-management firm. That’s almost double the amount pulled at the depths of the 2008 financial crisis. Currencies have taken a beating. The Indonesian rupiah and Malaysian ringgit recently touched lows against the U.S. dollar last seen during the late-1990s Asian financial crisis.

    What’s significant is that the developing world has endured such drastic capital outflows without tumbling into a full-fledged economic meltdown, proof of its new resilience. Neil Shearing, chief emerging-markets economist at research firm Capital Economics, deemed predictions of an impending crisis “overblown.” “It is striking,” he wrote in an August report, “that many [emerging-markets] currencies have lost up to half their value over the past couple of years, without triggering widespread financial stress.” Shearing noted that the level of foreign-currency debt of most developing economies is lower than it has been in the past, making them less vulnerable to weakening currencies.

    Other economists point to external surpluses and larger currency reserves in many Asian emerging economies as indicators of their financial strength. Of course, these circumstances don’t ensure a crisis won’t happen, but they make one much less likely.

    Nor should higher U.S. interest rates be as damaging as many investors fear. In a June study, HSBC economist Frederic Neumann and strategist Jessica Wu analyzed previous Fed tightening cycles and discovered they’d left emerging Asia “relatively unscathed,” at least in initial stages.
    Going further, Michele Mazzoleni, vice president at California-based investment manager Research Affiliates, calls the whole notion that rising U.S. rates are automatically bad for emerging economies a “myth.” Historical evidence shows that when interest rates rise on the good news of a strong U.S. economy—the reason behind any Fed tightening now—capital flows into emerging markets. Not only does a healthy U.S. bolster overall global growth, Mazzoleni reasons, it also enhances investors’ appetite for risk. “What is good for the United States and other developed economies is also good for the emerging world,” he believes.

    While high-profile developing countries may be struggling, others continue to excel. Many of today’s better performers sat on the sidelines during the developing world’s big growth surge of the late 20th century and are just joining the party—a sign that the emerging-markets story is becoming broader. The Philippines, long a laggard in supercharged Asia, is expanding at about 6 percent annually. Myanmar, coming out of self-imposed seclusion, is growing at more than 8 percent. Once-dormant African economies are showing promise. Ethiopia, for decades a symbol of poverty, is expected to expand by 8 percent or more through 2017. The IMF forecasts that a large group of low-income countries will grow 5.1 percent in 2015 and 6.2 percent next year.

    None of this is to say that challenges don’t remain. Growth cannot be sustained without painful reforms requiring political will—a critical ingredient that’s been in short supply. In Brazil, for instance, corruption scandals are paralyzing the government of President Dilma Rousseff as growth tanks; in Indonesia, newly installed President Joko Widodo hasn’t yet lived up to his reputation as a reformer; Shearing at Capital Economics says Turkey is a potential trouble spot as well.

    Nonetheless, the long-term story hasn’t changed. The middle class in the U.S. and Europe will continue to be a pillar of the global economy, but the world’s new consumers—and new growth engines—will still be found in developing, not developed, countries. Even if the Chinese leadership fails to shift from investment-dependent to consumption-led growth, consumer spending in China will grow 60 percent over the next decade, according to the Demand Institute, a think tank. In a 2012 study, HSBC researchers prognosticated that almost 3 billion people will enter the ranks of the middle classes by 2050—nearly all in emerging economies. That would create a seismic shift in the world economy: Consumption in emerging countries could account for almost two-thirds of the global total in 2050, a significant increase from only about one-third today.

    Where stock markets, currencies, and growth rates will head in coming months may be unclear. That the meek will eventually inherit the earth is not.

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    The serial entrepreneur reflects on lessons learned during his long and varied career.

    Richard Branson leads a charmed life. Today, the founder of the Virgin Group travels the globe, running his multibillion-dollar empire from his numerous homes and hotel properties.

    “I’ve been fortunate,” Branson said onstage Tuesday at the Tribeca Film Festival’s Imagination Day in New York City.

    Undeniably. But this good fortune didn’t happen by accident. While Branson credits his business success to an innate “screw it, let’s do it” attitude — “my greatest fear,” he said, “is saying ‘no’ to something” — recklessness alone doesn’t build a global brand.

    Most people can take risks. What’s made Branson the bonafide face of entrepreneurship is the ability to try something and, whether it’s a success (as with Virgin Atlantic and Virgin Records) or failure (Virgin Cola), dissect the experience for lessons to use in his next venture.

    The through line so far? “I learned very early on in life that business is simply coming up with an idea that makes other people’s lives better,” he said. “Some of the best businesses come out of initial frustration with the way other people are dealing with you.” Virgin Atlantic was famously born on a whim back in 1984. When British Airways cancelled Branson’s flight to the British Virgin Islands, he rented a plane to fly there himself, filling it up with fellow disgruntled passengers. “The rest,” he said, “is history.”

    While Branson dedicated most of his conversation to general reflections on life and career, he also shared a few concrete pointers he’s picked up along the way. Here’s his case for why entrepreneurs and business leaders should:

    Travel. Particularly for young entrepreneurs, it’s important to visit other countries and experience other ways of life, Branson said. “See what’s happening in France, see what’s happening in England, see what’s happening in China.” If nothing else, the exposure to different strategies to everyday problems may get the creative juices flowing. “If you can’t come up with a great idea yourself, you’ll find there are other great ideas out there.”

    Take notes. Steve Jobs’ legacy may have popularized a style of leadership based on the manipulation of weaknesses, but Branson takes the opposite approach. For him, a leader is someone “who will praise and not criticize” in order to “draw out the best in people.” Along the same lines, his version of leadership is based on the ability listen more than they talk.

    On a practical level, this means taking notes. Because in this regard at least, Branson is a realist: “If you don’t write things down, how are you going to remember half the things the person told you?”

    Hire from within. There are undeniable benefits to hiring an outside candidate as chief executive of a company. An external hire often comes with fresh perspectives and the ability to drive needed change, which helps explain why the practice at large public companies is on the rise.

    Still, Branson tries to avoid it whenever possible. “We don’t often go outside,” he says. Yes, selecting from a company’s existing talent pool means that some boxes remain unchecked, but it also means you’re never exposed to a candidate with glaring, unforeseen weaknesses. Perhaps more importantly, it’s a morale play.

    “The whole company will be pleased that you employ from within; they all have the chance to one day get the top job.”

    Let employees work from home. When Yahoo controversially scrapped its work from home policy in 2013, it argued that requiring employees to come into the office each day would boost productivity and engagement. While the merits of this strategy are still up for debate, one thing is clear: Branson is on the opposite side of the issue.

    On top of its existing work from home policy, in 2014 the Virgin Group adopted an unlimited leave policy. The overall aim is to provide “lots and lots of flexibility,” particularly for new parents.
    Branson knows the importance of flexible schedules firsthand. Throughout his career, his policy has been to work from home — or homes, more accurately — whenever possible. By doing so, “the kids have literally grown up crawling at my feet.” He’s taken meetings while changing a nappy, and wants his employees to have the freedom to do the same.

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    The Rainbow Mountains Of China Are Earth's Paint Palette

    The Rainbow Mountains of China within the Zhangye Danxia Landform Geological Park are a geological wonder of the world. These famous Chinese mountains are known for their otherworldly colors that mimic a rainbow painted over the tops of rolling mountains.

    This is just one example where geology catches our attention and begs the question: What causes the Rainbow Mountains to be colored the way they are? Here I will discuss the diagenetic and mineralogical processes that make up the reds, greens, yellows, and blues.

    The Zhangye Danxia National Park is located in the Gansu province in China’s northwest covering 200 square miles. The site was named a UNESCO World Heritage Site in 2009 and is the destination for many Chinese and international tourists.How Did The Rainbow Mountains Form?
    The Rainbow Mountains are cretaceous sandstones and siltstones that were deposited in China before the Himalayan Mountains were formed. The sand and silt was deposited with iron and trace minerals that provided it with the key ingredient to form the colors we see today.

    What was once a layered horizontal and flat stratigraphy was disrupted by the Indian Plate colliding into the Eurasian Plate approximately 55 million years ago. Much like when two cars get in a wreck and the bumpers fold and break, a similar process folded what was once flat sandstones into the Rainbow Mountains we see today. This process uplifted mountains and exposed sedimentary rocks that were otherwise hidden well below the surface of the earth. Weathering and erosion removed the overlying layers of continental siliciclastic rocks and exposed underlying formations with different mineralogy and chemistry. This causes the striking variation in colors seen across the Rainbow Mountains.

    So now that you have an idea of how the Rainbow Mountains formed, we will discuss a bit about how they got the color we see today. Precipitated groundwater moves through the sandstone grains and deposits trace minerals in between the grains. This precipitate can build up to a point where there is no longer an pore space between the individual grains, cementing them in place. This process is what imparts the trace minerals mentioned below and allows for the otherworldly coloring of sandstones around the world.

    The primary color is a deep red sandstone, not unlike the Fountain Formation that outcrops in the Flatirons, Red Rocks Park, and the Garden of the Gods all in Colorado. The red coloring is due to an iron oxide coating and cementation, also known as hematite (Fe2O3), between the sandstone grains.

    This is the exact same process that takes place when a piece of metal is left out in the rain and forms a red layer of rust around the outside.Weathering, mixed with water and oxygen oxidizes elemental iron into iron oxide, which is notable for its dark red coloring. The Rainbow Mountains are largely characterized by this iron oxide staining of its sandstone Danxia formation.
    Most of the time iron oxides impart a dark red pigment, however, there are instances where oxides form different colors. For example oxidized limonite or goethite will produce brown or yellow staining of sandstones, magnetite can form black staining of sandstones. If there is iron sulfide present, you will get a metallic yellow color imparted by the sulfur. Meanwhile, green coloring is often due to chlorite or iron silicate clays. These are just some examples of how sandstones can be altered in coloring during diagenesis.

    Luckily for you, you don’t have to travel to northwest China to see this exact same process. Go outside and wander around, looking down and out on the landscape. Try to identify a rock with a red coloring all over and there’s a good chance you’ve identified a iron oxide stained sandstone. Let us know what you’ve found in the comments below.

    Lastly, I’ll leave you with a few more spectacular photos of the Zhangye Danxia Rainbow Mountains.

    View more images of the Rainbow Mounatin

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    A New Approach to Organization Design

    In a time of economic turbulence, disruptive technology, globalization, and unprecedentedly fierce competition, the priority concern for many business leaders is to adapt to the changing conditions in order to boost their company’s performance. For that purpose, they frequently turn to organization design for help. By driving a thorough organizational review and redesign, company leaders can change the trajectory of their business.

    Corporate reorganization is certainly in vogue. In a survey conducted by The Boston Consulting Group, almost 80% of respondent companies reported under-going a recent reorganization exercise—in about half of those cases, a large-scale, enterprise-wide reorganization initiative.
    If only it were that easy. The results have been disappointing: survey respondents rated fewer than half of the reorganization efforts as successful. The underlying reason for such a low success rate: all too often, the companies’ leaders relied on organizational frameworks that have become outmoded and ineffective in today’s business environment.


    In grappling with organization design, company executives tend to draw on two venerable approaches, which can be characterized as the “hard” approach and the “soft” approach.

    The hard approach can be traced back more than a century to the pioneering work of Frederick W. Taylor on the subject of scientific management. The approach rests on two broad assumptions: first, that performance is affected directly and crucially by structures, processes, systems, and financial rewards; second, that people’s behavior is something to be controlled—through structures, processes, and systems and by offering financial incentives based on performance metrics.

    Because performance levels often seemed curiously resistant to the hard approach and the level of control achieved was limited, organizational theorists began supplementing it with the soft approach. This approach involves encouraging positive attitudes and interactions among the workforce by means of team-building activities, workshops emphasizing values, and other “people initiatives.” It can be traced to the work of Elton Mayo in the 1920s and the subsequent human relations school of management. The new thinking was, very roughly, as follows: performance is heavily influenced by interpersonal relationships, which are largely determined by mind-sets, which can be changed—not by financial incentives but by improved communication and emotional and social reassurance. The underlying purpose here, as with the hard approach, is control. The main difference is that the mechanism used to achieve it is psychological rather than economic.

    Both approaches underplay the importance of individual autonomy and rationality. First, people are less likely to behave in the way we want if coerced or manipulated into such behavior than they are if the choice is their own. (And in any case, the kind of work they now generally do is not really amenable to control: in a knowledge economy, workers need to apply their own judgment rather than simply follow a set of rules.) Second, workers—being rational—act in their perceived own best interests. So, the modern approach to organization design should not be to seek control but rather to create the right context for the workforce, by aligning their own best interests with the mission of the organization. Once that context is suitably conducive, the workers will change their behavior of their own accord and will act together, as a team, to carry out the organization’s mission.

    (This account is adapted from the book Six Simple Rules: How to Manage Complexity without Getting Complicated, by Yves Morieux and Peter Tollman, Harvard Business Review Press, 2014.)

    A Call to Action

    The business world of the early 21st century is radically different from that of the early 20th century, in two key respects.

    First, organizations now have to operate in a vastly more complex environment—one of globalization, hypercompetition, revolutionary technologies, and elaborate regulation. Such complexity implies an increased number of performance requirements for companies (for instance, to satisfy customer needs, address competitive pressures, or comply with the ever-increasing labyrinth of regulation). If you then assign to each requirement its own structural solution (which is the essence of the “hard approach,” described in the sidebar) you end up with an extremely complicated and unwieldy organization.

    Second, in most companies the nature of work has changed: from algorithmic work—that is, clerical or manual labor—to knowledge or heuristic work. Knowledge workers differ from clerical or manual workers in that their role is not merely to follow rules and perform specific tasks but also to use their own initiative to further the organization’s mission. They have to interpret the rules, adjust to the changing realities, and make trade-offs among conflicting requirements in order to arrive at the optimal solution.

    All of that requires judgment. Judgment in turn involves creativity and full engagement on the part of the workforce. For algorithmic work (and in the hard approach to organization design), variation is discouraged and minimized—people need to follow the rules. Knowledge work and creative engagement, however, actually embrace variation and flourish in proportion. What’s more, heuristic workers on the front line, in order to make the most reliable and creative judgments possible, must master and monitor local conditions. So, in this respect, they are now the experts: they know more about this aspect of the trade-offs than their superiors do and, accordingly, need greater autonomy and empowerment.

    If reorganization efforts continue to overlook these two major changes in the world of work, they will continue to fail. A new approach is needed, one that is better suited to the realities of the world in which companies now operate. BCG has developed such an approach, called Smart Design for Performance—or just Smart Design—drawing on the principles of Smart Simplicity. (See “Smart Design, Smart Simplicity.”) The approach has been battle tested and has shown great success in raising company performance, mastering complexity, and enhancing employee engagement.


    Smart Design is based on BCG’s Smart Simplicity model of how to design organizations for performance. Two of the framework’s key tenets are as follows:

    A company’s performance is a direct consequence of its people’s behavior, which in turn is a response to the contexts in which these people find themselves. The performance of any organization is driven by the behaviors of the individuals in that organization: the decisions they make, the activities they undertake, and their interactions. These behaviors are rational—a rational reaction to a particular situation; they are not “hyper-rational,” as the behaviors of a computer algorithm might be. Rather, they represent the individuals’ perceived best strategy in the situation. To change these behaviors, and hence raise the organization’s performance level, you have to make a new set of behaviors rational; to do that, you have to change the situation, or context.

    The new context must encourage cooperation. Company performance improves strongly when organizations raise the level of cooperation among the individual actors and align individual goals more closely with company goals. Cooperation, in this sense, occurs when one individual takes action to improve the performance of another; it brings synergy, such that everyone’s efforts combine in the most effective way and benefit the whole group. Cooperation is therefore the essence of teamwork; the whole is greater than the sum of the parts.

    The Basis of a New Approach

    A holistic view of organization design would encompass numerous components: structural elements, roles and responsibilities, individual talent, and enabling mechanisms such as core enterprise decision-making processes, performance management, and talent management. These are the key levers for organizational change, and they are obviously crucial—but their relevance is indirect. To change a company’s performance is to change what happens in the company. And what happens in a company is not directly a matter of organizational levers (such as structures, processes, and systems) but one of behavior—that is, what people do: how they act, interact, and make decisions. Workforce behavior is what determines company performance.

    All of the various organizational levers act together to affect behavior, and that in turn affects company performance. But the traditional approaches assume, incorrectly and damagingly, that the organizational levers act directly and proportionately on company performance.

    (See Exhibit 1.)

                                                                          View enlarged image

    The new approach to redesigning an organization, far more appropriate for the new business environment, has behavior at its core. It involves identifying and explaining the current behaviors of the workforce, defining the desired behaviors—those that would improve company performance—and generating the new behaviors by creating contexts that are conducive to them.

    What’s So Smart About Smart Design?

    BCG’s Smart Design approach involves three main steps—the why, what, and how (see Exhibit 2):
    • Define the purpose of the reorganization (the why).
    • Determine the behaviors that will support that purpose and design the organization in such a way as to promote those behaviors, using a broad range of design elements (the what).
    • Make it happen (the how).

    Define the Purpose of the Reorganization

    By redesigning the organization, your company can resolve many stubborn issues of strategy and execution. But before embarking on the redesign, make sure to identify clearly the company’s current performance shortfall (that is, the gap between the company’s current performance and its target performance) and hence the precise aims of the reorganization effort—with regard to competitive advantage, strategic priorities, or organizational pain points.

    There are various ways to approach such an assessment. (For a summary of one of them, see “BCG’s Complicatedness Survey.”)


    Organizations today operate in an environment of unprecedented complexity, owing to factors such as competitive intensity, globalization, high technology, tighter regulation, and customer empowerment.

    But that does not mean that the organizations themselves have to be characterized by complicatedness—by having needless KPIs or excessive managerial layers, for example. Complicatedness is a consequence of misguided organization design. Whereas complexity can be a source of advantage if managed effectively, complicatedness impairs the functioning of an organization by restricting management’s agility and reducing the workforce’s engagement.

    BCG has developed a complicatedness survey for client organizations. The online survey contains a standardized set of questions to gauge not just the overall level of complicatedness in an organization but also the specific level of each of seven context dimensions. And it captures not just the facts but—almost equally important—the beliefs or perceptions of key stakeholders. By highlighting the organizational pain points in this way, the survey helps to identify the aspects that would most benefit from redesign. (See the exhibit below.)

    Determine the Target Behaviors and Design the Organization Accordingly

    In this second step, you define the behaviors required to achieve the purpose. That will, in turn, lead to a set of design principles to be used for guidance as you shape the four key design elements, which are the building blocks for producing the desired behaviors. These elements are organizational structure, roles and responsibilities, individual talent, and organizational enablers. Note that they affect one another in many ways, and they act in combination to alter the context for individuals and encourage behaviors that drive high performance. So, instead of dealing with each of the four elements independently, you need to consider them jointly and align them.

    Organizational Structure. Organizational structure refers to the hierarchy of management reporting—who reports to whom with regard to executing the strategy. These reporting lines establish the organization’s geometry: the spans of control and the number of layers.

    Organizational structure can affect behavior profoundly. That is because the reporting relationship is an important basis of power: a line manager has power over his or her subordinates by virtue of being able to influence things that matter to them—notably, their assignments, remuneration, and career paths.

    “Power and Related Concepts.”

    In any team or company, the work done by one person affects the ability of others to do what they have to do. That creates interdependencies. And interdependencies create a need for cooperation.

    Cooperation is the essence of teamwork: it involves more than just collaboration and coordination; it consists of behavior by individuals that increases the effectiveness of a group in pursuit of a shared goal. When you as an individual cooperate, you take into account—in your decisions and your actions—the needs and situations of your colleagues, rather than simply pursuing your own preferences.

    Cooperation is not as easy as it sounds, nor as common. Don’t assume that it happens automatically in your organization. Individuals are, by nature, self-interested and value their autonomy, so they often resist cooperation, because it requires a personal sacrifice, or adjustment cost, from them. This adjustment cost might be professional, emotional, reputational, or, of course, financial.

    If an individual avoids cooperating by refusing to make the adjustment cost, then the cost is incurred elsewhere—by others in the team or organization (in the form of underperformance, perhaps), or by the team or organization as a whole (in the form of lower productivity), or by people external to the organization—such as customers (through defects, delays, or higher prices) or shareholders (through lower returns).

    An important way to secure cooperation within a group is for the group leader to exercise leadership (that means getting people to do things that they wouldn’t do spontaneously) and for that purpose, he or she needs appropriate power (power rather than just status).

    Power can be defined as influence over things that are important to others: it is not necessarily correlated to one’s position in the hierarchy. A line manager coordinating a large project, for example, will have power over direct reports (via influence over their salaries or promotion prospects) but not necessarily over nondirect reports, and so might be unable to secure cooperation among them—a sure sign of a dysfunctional organization and the need for an organization redesign or at least an adjustment.

    The overall architecture of a company tends to reflect the company’s priorities. If the priority is functional excellence, for instance, then the company will usually be organized functionally; if the priority is customer intimacy, then the company will likely be structured according to customer type.

    The problem is that almost all companies need to address multiple, often conflicting, priorities in order to be competitive in today’s environment. For example, in a functional organization, the emphasis might still be on serving customers or on organizing optimally to develop new products. Structure alone is not the answer. If a company neglects other ways of influencing behavior, and concentrates on making multidimensional or overly sophisticated structural changes (or just continues to add new structures) in order to cater to its conflicting priorities, the result is complicatedness and extra bureaucracy. Which is where Smart Design comes to the rescue.

    Another way that organizational structure affects behavior is through geometry: the more layers the structure accommodates, the longer the chain of command becomes, and that can have counterproductive consequences—slower decision making, managers hampered by an overly narrow span of control, a tendency for units to work in silos, and uncooperative or disruptive behaviors by frustrated workers.

    The trend in recent decades has been for organizations to reduce the number of layers within their hierarchies. Yet overlayering persists, for two reasons.

    First, the layers are often generated as a reflex response to business complexity: if a growing company opts to create a new regional structure, for instance, it would understandably be tempted to create a new layer in the organizational hierarchy to accommodate the regional heads.

    The second possible reason is that if the organization is poor at inspiring its workforce to perform, it might overuse a particular incentive: the prospect of promotion. New layers might then be needed to accommodate the various employees who are being “rewarded” in this way. The new positions seldom add much value, and the roles involve little or no power. The effects of these extraneous layers and narrow spans of control include slower decision making, silo behavior, and subdued productivity.

    In contrast, a smart and effective organization is lighter and flatter in structure, allowing for flexibility and agility. It specifies fewer and bulkier management roles with broad spans of control and motivates the employees in those roles to use their own initiative and to exercise their creativity in finding solutions.

    Roles and Responsibilities. Roles and responsibilities clarify who does what and who is accountable for what. For the staff to adjust their behavior in a more cooperative direction, they need to understand their own responsibilities and those of their colleagues. They also need to know how these responsibilities are to be discharged, what decision rights and key capabilities are needed, and how to measure success. To foster performance and cooperation, the roles and responsibilities should be sharply focused on what matters most; they should be defined more in terms of the what than the how; and there should be sufficient overlap to ensure that all the bases are covered but not so much overlap that work would be duplicated or rivalries would emerge.

    An effective way to design roles and responsibilities is through the process of “role chartering.” Each role is defined—on a single sheet of paper each time—in six related aspects:.
    • Desired leadership markers for the role—the values, characteristics, and “style” best suited to the role, such as a bias toward action, a sense of urgency, or candor and openness.
    • Key capabilities required

    • for fulfilling the purpose o
    • f the role.
      • Individual and shared accountabilities—that is, responsibilities for the completion of tasks.
      • Decision rights needed for carrying out the accountabilities.
      • KPIs for measuring the performance of these accountabilities.
      • Mission-critical cooperation requirements—what each person can do to make others more effective at accomplishing their accountabilities, and what others can do in return
    The charters, if effectively designed, will help to foster cooperative behaviors and add value accordingly.

    The challenge is not just to define a person’s independent responsibilities but also to define his or her shared responsibilities with regard to the work of others, in light of interdependencies. So too for metrics: how is success to be measured? (If you cannot measure it accurately, you cannot reward it appropriately, and if you cannot reward it appropriately, you cannot easily incentivize people to engage in it. The metrics might show that each silo is performing strongly, while the performance of the organization as a whole might be weak.) Cooperation cannot be measured, at least directly or quantitatively—hence the need for managerial supervision of key interactions and for spelling out the mission-critical cooperation requirements.

    The key is to align the charters of those people who especially need to cooperate with one another. If your own role charter, thanks to a systematic alignment process, chimes well with those of your supervisors and your peers, that should both clarify individual and shared accountabilities and facilitate productive and cooperative behavior.

    Note again the important role played here by power (that is, influence over things that are important to others). It is power that determines your capacity for gaining cooperation from others and hence for dealing with business complexity. One way for a company to empower you is by incorporating into your role charter a new “stake” for others (something that matters to them). Suppose, for example, that your role charter authorizes you to select various colleagues for a desirable task or to submit an assessment report on them to their line manager when their promotion prospects come under review: in each case, your role charter is empowering you—these colleagues would now have an incentive to listen to you and cooperate with you, and you would be in a position to influence their behavior. Or suppose that your role charter gives you the decision right over a policy that some of your colleagues wish to introduce or over budget allocations for a project of theirs: again, that would serve as an extra source of power for you, encourage cooperation from your colleagues, and make it easier for you to fulfill your shared accountability.

    All in all, by devising role charters for key positions in the organization, a company can accomplish several aims: clarify the individual and shared accountabilities, establish how to align roles and responsibilities horizontally and vertically with the desired behaviors, secure from everyone involved the necessary buy-in for behavioral change, and increase power and alignment in the organization, in order to enhance autonomy and cooperation and thereby cope better with complexity.
    Individual Talent. Individual talent is needed for filling the roles and discharging the responsibilities. To be a good match for a given role, the individual obviously must have (or be able to acquire) the right skill set and the motivation. That way, the role is performed effectively, the individual is engaged rather than disaffected, and the individual’s colleagues are therefore undistracted and likely to behave productively and not disruptively.

    To achieve the right match, proceed in a methodical way. Begin by reviewing each key role and specifying the talent it needs; then choose the most promising candidate, regardless of current seniority, salary level, or contract type (external resourcing is one of the options).

    If necessary, the company will aim to “upskill” the candidate for a new role, via mentoring, training, or other development opportunities. This upskilling is particularly important around the time of a reorganization effort. Consider the example of a senior role holder: during preparations for the reorganization, he or she might need to learn new ways of designing a team or of managing difficult conversations. And after the reorganization has taken place, he or she might need to acquire new managerial skills in such areas as leading a new team, resolving conflicts across units, and managing a broader span of control. Once equipped with the appropriate talent or skill sets again, the role holder is in a position to fulfill his or her new responsibilities.

    However, that might still not be enough. The individual also needs the motivation to apply these skills, specifically in a cooperative way. When companies are struggling to execute a strategy, they often lay the blame on skill gaps when the real culprit is rather different: a shortage of cooperation. The solution is to make adjustments to the context, in such a way that a committed fulfillment of the responsibility becomes a rational and personally beneficial behavior for the role holder.

    Any new organization design should not only deploy and leverage existing talent to the full but also aim to attract, retain, and develop future talent. One strategy in this regard is to create and foster roles that offer great learning experiences or enhanced career paths. Once again, make sure to create a conducive context for such roles—one that gives an ambitious and talented individual the right amount of exposure, for example, and provides him or her with the right opportunities to move on after a while.

    Organizational Enablers. Finally, organizational enablers provide further help in creating the coherent organizational context that encourages the desirable behaviors. The main enablers are enterprise-level decision processes and their support systems, performance management, and talent management.

    Among the enterprise-level decision processes are strategic planning, product and portfolio planning, budget allocation, and major capital investments. Decision making within organizations often becomes slow and contentious, and when a company tries to improve the situation by imposing formal guidelines and new processes, it often just complicates things and makes matters worse.

    Once again, the right approach is to create a conducive context: the major stakeholders can then cooperate with one another to generate effective and timely decisions for the company’s benefit. As an additional resource for sharpening their decision-making abilities, the stakeholders have access to a support system, including IT platforms and data analytics. This system needs to be well designed, however, and the analytics need to be relevant as well as practical. Failing that, the system could actually prove counterproductive, and weaken rather than strengthen the quality of decisions made within the organization.

    Performance management is conducted through staff evaluations. The evaluations would ideally involve a combination of KPIs and judgment-based assessments. The company should ensure that those conducting the performance management are properly equipped to do so. They need to acquire the requisite skills, by means of training, if necessary—how to recognize cooperative and uncooperative behaviors, for instance, or how to provide feedback candidly but constructively.
    If executed well, performance management can help to enhance workplace behavior—but it is liable to misuse. All too often, companies deploy performance assessment criteria to link operational failures to specific roles or individuals. The clearer the link, the more strongly the company believes it has the right assessment system—only to find that these direct attributions have the effect of making matters even worse and prompting suboptimal or even counterproductive behavior. A smart organization understands that performance requirements can be highly complex and often conflicting and accepts that problems of execution arise for many reasons. It also understands that frequently the best way to solve these problems is to increase cooperation, and that means reducing the payoff for those people or units engaging in uncooperative behavior, even if the problem does not take place directly in their own domain, and to increase the payoff for everyone when everyone cooperates in a beneficial way.

    As for talent management (through appointments, promotions, or a new career path, for example), it too can have a powerful effect on the way that people behave. One technique is to carefully assign people the role—perhaps as a temporary transfer—of someone affected by their behavior. By getting them to walk in another’s shoes in this way, you alert them to the “shadow of the future”—that is, you make them aware of the problems that their current behavior might create for their future selves. This technique is particularly effective when the outcomes of their behavior lie very far in the future. (In biopharma R&D, for example, the time lag between decision and outcome is so great that the decision maker might never be personally affected by the outcome.) By reminding people that what happens tomorrow is a consequence of what they do today and making them accountable for it, you give them an incentive to optimize their current behavior.

    Both performance management and talent management need careful designing to create the right context for behavior. It is all too easy to misalign them with target behaviors and thereby actually encourage the counterproductive behaviors that you are setting out to eradicate.

    Make It Happen

    Reorganization is undertaken not for its own sake but in order to successfully execute strategy and boost performance (in each case, by modifying the behavior of the workforce). So the implementation phase is crucial. It has two main aspects: establishing the right context throughout and enhancing the capabilities of leaders and top talent. And it can be accomplished most efficiently through a process with three features: cascaded design, rigorous program management with multilayered communication, and capability building.

    Cascaded design, or “layer-by-layer, team-by-team design,” involves role chartering by each employee successively down the organization, in consultation with his or her colleagues and line manager. This cascading process helps to refine and publicize each role—clarifying the interdependencies and the way they affect one another—as well as speeding up decision making and reinforcing strategic goals throughout the organization.

    Rigorous program management involves creating, tracking, and course correcting a portfolio of change initiatives. If conducted properly, it maximizes the visibility of the change program and ensures that members of the workforce understand and feel the consequences of their actions. Through feedback loops, it indicates, encourages, and reinforces the desired behaviors. One of its major components is multilayered communication—at all levels of the hierarchy, senior managers hold one-on-one conversations with their subordinates and conduct pulse checks or surveys to monitor how their subordinates are progressing and how they feel. In that way, they can gain insights into the effects of the new context and make adjustments to it as needed.

    Capability building, or enablement, drives performance and hence value. Organization design provides a unique opportunity for companies to boost capabilities in this way, provided that the company’s leaders and top talent learn the necessary skills: first, how to execute the organization redesign smoothly, then how to lead within the new organizational context and help their subordinates to adapt, and then how to drive business objectives and value in their new roles. To ensure sustainable outcomes in each of these requisites, companies often benefit from a tailor-made leadership- and talent-development program.

    When it comes to applying Smart Design to actual situations, the details obviously differ from case to case, according to the purpose of reorganization, its scope and scale, and the company’s current organizational capabilities. Some reorganization initiatives clearly need all three components of the enhanced organization-design program; for others, just one or two of the components might be enough. (For two instructive case studies, see “Smart Design in Action.”)


    Two case studies provide insight into the power of the Smart Design approach.
    Making a New LoB-and-Hub Matrix Work

    A multibillion-dollar financial institution in the US was underperforming, and a serious reorganization was indicated. A redesign initiative duly got under way, with the aim of transitioning the organization from a predominantly line-of-business

    (LoB) structure to a matrix of LoBs and hub centers. The upshot was exacerbation of the drivers of underperformance:

    ⦁ Decision making became slower and more contentious.

    ⦁ Cross-functional efforts proved increasingly disappointing.

    ⦁ The brand LoBs avoided collaborating with the hubs, citing various concerns involving the hubs’ capabilities and processes.

    ⦁ Talent development continued to deteriorate.

    When BCG was invited to help resolve these issues, our Smart Design team began by analyzing exactly what was happening and why. The team studied the key actors, identified the undesirable behaviors, and established why those behaviors were rational in the given context. The team then developed a suite of solutions that would make a new set of behaviors rational—that is, more cooperative and productive. Finally, the team developed a change program for implementation.

    The company was then able to resume its redesign initiative, but on a proper footing this time. It redefined roles and revised the rewards system in such a way as to reinforce the hubs and attract the right talent to the right positions. Further effects included reduced waste, increased cooperation, clearer accountability, higher levels of employee engagement—and overall improved performance.

    Thanks to the quick course correction, a reorganization effort that had been heading for the rocks was diverted into a favorable current, and the company’s prosperous voyage continues.
    Fixing the Issues Affecting New CoEs

    In a major strategic initiative, a global chemical company embarked on a radical reorganization: the old structure, which was based on business units, was to be replaced by a new matrix structure, with centers of excellence (CoEs) for key shared functions such as analytics, customer insights, marketing excellence, and sales operations. The goal was twofold: to improve efficiencies by building scale in these areas and to boost capabilities to the point of excellence.
    To the transformation team’s surprise, the new organization design floundered. The twin goals seemed further away than ever.

    The broad problem was that in creating the CoEs, the company had pressed the structural levers but neglected all the other levers. Roles and responsibilities remained unclear. The talent assigned to the CoEs was ill considered—generalists rather than appropriate specialists. And the talent management was poorly conducted: career paths were considered “second class,” turnover was high, and top performers refused to transfer from brand teams to CoEs.

    In short, redesign had not been accompanied by corresponding changes to the context.

    With BCG’s support, the company set about mapping clearer career paths for those assigned to the CoEs, redefining and rechartering roles to make them more compelling, clarifying decision rights, and adjusting the mix of staff in order to generate real expertise within teams. Within three months of the “redesign of the redesign,” employees registered a hugely improved understanding of their roles and a general rise in satisfaction.

    Subsequent assessments have shown that the organization is now much more scalable, and performance is markedly higher than before.

    As mentioned earlier, BCG conducted a survey on reorganization, polling corporate executives in a wide range of industries. The survey identified six factors as the strongest contributors to the success of reorganization efforts: aligning design with strategy, clarifying roles and responsibilities, deploying the right leaders and the right capabilities, designing layer by layer (not just from the top down), executing optimally by minimizing risk factors, and reorganizing during a period of strength rather than crisis. The findings of the survey were illuminating, to say the least: companies that embraced all six success factors within their reorganization effort enjoyed vastly greater success than companies that did not. With each additional factor, the success gained further impetus. (See Exhibit 3.) Subsequent case experience has confirmed the importance of these factors.

    These findings are consistent with our expectations. In Smart Design, the emphasis is less on perfecting each element and more on creating the context in which the elements can work most effectively together to drive the target behaviors and enhance performance. So, when business leaders commit to an organization redesign, they should take a holistic approach rather than treat each factor individually. (For a more detailed account, see Flipping the Odds for Successful Reorganization, BCG Focus, April 2012.)

    Smart Design is premised on the recognition that company performance is a function of employee behavior. So to improve performance, the trick is to modify behaviors appropriately. And to do that, you must first study the existing behaviors—the good, the bad, and the absent—and then comply with the other success factors listed in the middle column of Exhibit 3. As the final column shows, a conscientious approach to reorganization can make a striking difference to its chances of success.
    Successful reorganization is often the most promising route for companies to regain their former sparkle, consolidate their strengths, or gain a competitive advantage. But taking that route requires steady nerves and bold measures. Many corporate executives are sufficiently bold to authorize a thoroughgoing organization redesign, but not to break with the conventional approaches to it. The trouble is, the conventional approach has produced uninspiring results in recent years, and in many cases has actually made matters worse. 

     It is simply inadequate in the present-day business environment: the circumstances have changed, and the approach needs to change as well. To drive productive behaviors, you must create broader and more conducive contexts for them and then implant the new contexts, layer by layer, deeply into the organization. Smart Design is a comprehensive end-to-end approach that is specifically adapted to the new circumstances and precision-engineered for boosting performance and engagement. It has produced outstanding results with minimal disruption: companies applying Smart Design have seen a revival of employee motivation and engagement and a surge in company performance. If reorganization initiatives often offer the best hope for troubled companies, Smart Design offers the best hope for reorganization initiatives.

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    This Word Has Zero Meaning—Yet, You Probably Already Used it Today


    A few weeks ago, I was sitting in a brainstorming meeting. After one particularly important idea was mentioned, someone responded with “That’s a really interesting point.” And then, crickets.
    OK, not exactly, but it definitely brought the conversation to a halt—until one person took the long silence as an opportunity to speak up.

    What she said surprised me:

    “I’m sorry, I just have to ask. What do you mean by interesting? Break that down for me.”
    What did he mean by “interesting?” I sure didn’t know—and neither did he really. And in that brief moment, as I watched this person try to explain why he found this interesting, I realized just how meaningless the word was.

    I find myself using “interesting” all the time. That was an interesting movie.I’m interested to hear what you think.I think it’s interesting that…

    I use it when I don’t want to say something (for fear of retaliation), when I don’t even know how to put my thoughts into words, or when I don’t want to confront how I really feel inside.

    But from this conversation, I realized that this word not only contributes nothing to the conversation, but it made it seem that the person who said it didn’t want to be involved with what we were all sitting there trying to accomplish. It was the perfect neutral—not too mean, not too encouraging, not too deep that he’d have to jump in and take initiative. In fact, it could have been taken as an insult: I don’t really care either way, so I’ll just acknowledge that you spoke and move on. Just think, have you ever felt elated that someone said your thoughts were “interesting?” I didn’t think so.

    After this experience, I decided to swear off the word altogether (except for writing this article, of course). The reason is simple: I like honesty. Honesty is productive—it shows that you actually listened to someone, then took the time to think through what he or she said in order to craft a thorough and useful response.

    Ever since I swore it off, I’ve become more in tune with my emotions and have had more meaningful and productive interactions in which I was able to learn something new about myself and others around me—a.k.a., I gained some serious emotional intelligence.

    Now, I present my challenge to you: Let’s take more conversation risks and start to break down what we mean by “interesting”—rather than using it as a scapegoat. Do you mean that it’s surprising, or maybe something you really hadn’t thought of before? Do you believe that it’s a good idea, but not practical right now? Or, do you absolutely love the concept but aren’t sure if other people agree?
    Say those things! And, if you truly don’t have a response, that’s OK too—just saying “I’m not sure how I feel about that” can be a great way to further discuss what about it confuses, upsets, or bugs you. But when things remain ambiguous, nothing gets done.

    The next time the word “interesting” pops up in your head, I dare you to try to process it and figure out what you’re really thinking before saying it out loud. You’d be surprised how many better, stronger, and more exciting phrases there are out there—I can tell you from practice that it is one word you can definitely live without.

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    1st-Grader With No Hands Wins National Handwriting Contest  

    Here's a great story that's inspiring people across the country.

    A seven-year-old girl born without hands has won a national handwriting contest.

    Anaya Ellick, from Chesapeake, Virginia, does not use prosthetics. Instead, she uses her forearms to

    The first-grader reportedly beat out 50 other competitors to win the special-needs category prize at the Zaner-Bloser National Handwriting Contest.

    The category consists of students with intellectual, physical or developmental disabilities, and Anaya's impressive handwriting was picked to be the best of the bunch.

    "There is truly very little that this girl cannot do," Tracy Cox, Anaya's principal at Greenbrier Christian Academy, told ABC News.

    "She is a hard worker," Cox said. "She is determined. She is independent. She is a vivacious and a

    no-excuses type of young lady."

    For winning the contest, Anaya received $1,000 and a trophy, according to Zaner-Bloser.
    Her school was also awarded with a gift certificate to purchase print and digital resources for students and teachers.

    Way to go, Anaya!

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    America as 100 College Students

    America’s postsecondary student population is more diverse than ever. Many students attend school while working part- or even full-time. Some are raising children while in school. And, in many cases, they’re financially independent.

    There’s no one-size-fits-all path to (or through) college – and we need to plan our education policies accordingly.

    What would America look like as 100 college students?

    Gender: National Center for Education Statistics, Digest of Education Statistics. Table 

    Age: National Center for Education Statistics, Digest of Education Statistics. Table

    Type of School: National Center for Education Statistics, Digest of Education Statistics. Table 303.70.

    Race: National Center for Education Statistics, Digest of Education Statistics. Table 306.10.

    Enrollment: National Center for Education Statistics, Digest of Education Statistics. Table 303.70.

    Employment: U.S. Department of Education, Demographic and Enrollment Characteristics of Undergraduate Students. Table 8.

    Financial Aid: National Center for Education Statistics. Integrated Postsecondary Education Data System.

    Housing: American College Health Association. National College Health Assessment.

    Children: U.S. Department of Education, Demographic and Enrollment Characteristics of Undergraduate Students. Table 1.

    Learning Environment: National Center for Education Statistics, Digest of Education Statistics. Table 311.15.

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    Where are the world’s population hot-spots?

    From a population of a little over 170m in 1 C.E., the world’s population is forecast to exceed 9.5 billion by 2050.

    An interactive map created by Population Connection charts this growth, highlighting recent rapid population increases, as well as concentrations of people around the world.
    Charting over 2,000 years of history, the map offers an insight into our life on earth.

    How has the population changed?

    2,000 years of human history has seen a significant expansion in the global population, with the world population in 2015 put at 7.3 billion people.

    The following two maps show this change from 1 C.E. (the same point as 1 A.D.) to the present day.

    The dots represent population hotspots of over a million people. Where this population is spread out, the dot is placed in the middle of the approximate range. So, as this first map shows, in 1 C.E. the global population was concentrated in Europe, and particularly the Far East.

    The 2015 map highlights the spread in the population around the globe, from Africa to South America. The timeline also shows the rapid population expansion since the Industrial Revolution, with the population remaining below 1 billion until 1800.

    Where is the population concentrated?

    Europe and the Far East remain major hotspots today, as they were in 1 C.E.. Hotspots have also emerged in India, Japan and coastal areas of the Americas.

    There are also large population concentrations across much of central Africa and part of the Middle East. You can even see a hotspot down the Nile in Egypt.

    At the other end of the scale, large areas continue to have much lower concentrations. The Sahara, the outback of Australia and much of Canada and Russia have very few dots.

    What does it mean?

    Population expansion puts a strain on resources and the environment, presenting challenges for the world as a whole. This strain is most keenly felt in population hotspots, and also in areas which have seen the most rapid expansion.

    This interactive map offers an important insight into global population trends and patterns, which can help policy-makers tackle these challenges.

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    How an Ecosystem Mindset Can Help People and Organizations Succeed

    Greg Gopman has had an interesting two and a half years. In December 2013 he was an up-and-coming young San Francisco entrepreneur and CEO of an incubator, when he posted an offhand comment on Facebook about homelessness in his city. In part, he wrote:
    In other cosmopolitan cities, the lower part of society keep to themselves. They sell small trinkets, beg coyly, stay quiet, and generally stay out of your way. They realize it’s a privilege to be in the civilized part of town and view themselves as guests. And that’s okay.
    Gopman’s post quickly went viral, was blogged about endlessly at media sites such as Gawker’s now-defunct Valleywag, and he became a poster child for everything wrong with the tech industry in the Bay Area. Overnight, his career came to a complete standstill.

    But what Gopman did next was the interesting part: he threw himself at the task of actually trying to fix the homeless problem in San Francisco with the typical zeal of a startup entrepreneur.

    Gopman’s journey is a great illustration of how to adopt what I call an ecosystem mindset: an understanding that the keys to new value and growth likely do not reside within one’s current boundaries but beyond them, and that success involves forging new connections to solve problems and create new value as a team. It’s a mindset that very few big companies and individuals have, but need.

    Gopman’s first step was to conceive and create a product to solve the problem, a set of “I love SF” wristbands. The idea was that homeless people could sell them and help support themselves. Nobody called him for a resupply.

    Next, he spent months researching current approaches, going out and talking to local organizations working with the homeless. His idea was to host a Town Hall to End Homelessness, bringing to bear his own expertise in organizing hackathons.

    At the end of the event, Gopman met a man who had recently been made homeless after a stroke left him unable to work. The two started meeting regularly and trading notes, the man telling Gopman about what homeless camps actually needed. Gopman went to visit homeless encampments with his new colleague, and even spent a night sleeping in one.

    The two launched a small business based on mutual observations of what people in these camps spend their time doing. The business fared much better than the wristband idea, but they eventually shut it down.

    Finally, Gopman began hosting meetings for a group of activists, civic workers, and homeless people. They devised a plan for homeless encampments that would operate more like cooperatives, and would include case managers, vocational schools, showers, wifi, a dining hall, and wellness programming while operating at a profit. They named it A Better San Francisco.

    While the internet continually paints Gopman as yet another shallow Silicon Valley tech bro looking to salvage his reputation, I believe Gopman’s story perfectly embodies the journey away from a closed Organism Mindset toward a more open Ecosystem Mindset.

    The journey is one that everyone, individuals and organizations alike, can benefit from: start from a self-centric position, and meet, talk, and fail your way outwards. Along the way, partner with others, try small tests, and learn.

    So how do you undertake this journey — either as an individual or as an organization? Let’s look at GE as an example.

    Build new connections. Nobody can truly understand the ecosystem they operate in without getting out and wading in it. Take Beth Comstock, Vice Chair at GE. Comstock now oversees GE Ventures, so it is her job to grow GE’s ecosystem and to make money doing it, but long before she took on that role, she was always meeting people, traveling from city to city, and hosting events. She knows that getting out and building new connections is the way to build value for her company.

    Establish channels between possible partners. These channels do not need to be — should not be — business deals per se. They should be created with the intent to understand how collaboration can happen. GE and GE Ventures, for example, actively seek and develop channels rather than simply looking for budding new companies to invest in. They’ve established Open Office Hours with senior-level experts at partner offices in Redwood City, panel discussions at like-minded accelerators in Boston, and similar initiatives in hotspots of new value creation around the country.

    Partner with others. GE and their Ventures arm are also constantly on the lookout for new partners. The organization currently counts 61 startups in their portfolio in fields as diverse as energy, healthcare and manufacturing. They partner as well with mature organizations, such as Santa Clara University’s Miller Center for Social Entrepreneurship, to find and accelerate new solutions and add value through training and mentoring.

    Of course, sometimes these partnerships end badly, as with the much-celebrated partnership between GE and Quirky, a New York manufacturing startup. Last year, Quirky declared bankruptcy last year and GE claimed that Quirky hurt its reputation with customers. Occasional outcomes like these are table stakes in the game though, and should not deter one from pushing forward with new partnerships across the ecosystem — and GE Ventures has pushed on accordingly.

    Foster sustained action. GE invests time, money, and resources to create sustained, active relationships with accelerator programs in an array of fields and locations, from Energy Excelerator in Honolulu to Robotics Hub in Pittsburgh. The result for GE and its partners is an ongoing, complex exchange of ideas, value, and initiatives, which often dovetail with each other since everyone involved sustain contact and pass information back and forth. The result, for each player in the ecosystem, is certainly no worse than if they were pursuing their goals on their own, and potentially much greater because of their interconnection.

    As Greg Gopman’s story shows, you don’t need to have a separate venture arm like GE with a huge budget to make this all work. It’s really just about applying the principles of the Ecosystem Mindset with whatever means you have: reach out, set up channels, partner, bring people from different parts of the ecosystem together for your cause, and go forward. If you do this, you’ll find that your solutions will take on new life. They’ll be more complex, more distributed across the ecosystem, more resilient, and more suited to survival in the modern world of increasing complexity and change.

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    Cloud computing has been named the technology most likely to shape the future, according to an IBM survey.

    The poll questioned C-level executives from 70 countries on which technologies they thought would be particularly important in the next three to five years. The following chart, produced by Statista, shows the percentage of CxOs (C-level executives) who identified a particular technology as influential.

    Of all the respondents, 63% said cloud computing and related services would have the biggest impact by 2020. Next on the list was mobile solutions – named by more than three in five CxOs. The top three is completed by the internet of things, with over half the respondents considering it likely to be important in the next three to five years.

    Other technologies on the list include cognitive computing, bio-engineering and innovations relating to energy.

    They are all technologies with the potential to have a positive impact on societies, from mobile banking in the developing world to the solutions we need for tackling climate change, and also meeting our energy needs. The World Economic Forum’s Emerging Technologies Report highlights the most innovative solutions to the world’s toughest challenges.

    Competitors now look and feel so much different. No industries are immune to digital disruption. It’s starting to change the way entire industries are thinking about things. If you focus only on the thing that you know, you will miss the thing that’s coming at you from the left or the right. You have to be willing to be disruptive. Learn fast, scale rapidly. You have to make big strategic bets.

    Is my strategy ambitious enough? What do I do to make sure that I’m fit for the future? How do I actually execute? Outthink Boundaries.

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    Padmasree warrior on her move to Next Ev

    NextEv, a Chinese electric car company potentially taking on Tesla and Faraday Future, has tapped Padmasree Warrior for the U.S. CEO position. Warrior will also head up software development and the user experience globally for the Shanghai-based company.

    According to Warrior, NextEv has already pulled in half a billion dollars of the $1 billion it plans to raise from the likes of Sequoia Ventures, Joy Ventures, Tencent Holdings and Hillhouse Capital – with plans to grow the business and hire in the hundreds under her leadership in the near future.
    The company launched out of stealth today and plans to ship an electric vehicle model rivaling Tesla in late 2016 – including a model that will reportedly match Tesla’s “Ludicrous” speed (0 to 60 mph in 2.8 seconds). The vehicles will first roll out to Chinese consumers and then to other parts of the world, including the U.S.

    Warrior tells TechCrunch she was picked for the role because of her strong tech background. She spent the last seven years as the chief technology and strategy officer at Cisco and 23 years before that as the CTO at Motorola. Warrior also sits on the board of several tech companies such as Box and Microsoft. She left her Cisco position in May of this year, according to her LinkedIn profile and considered many career moves – including a possible appointment as Twitter’s CEO– before landing the position at NextEv.

    This is her first startup gig and the first time she’s ventured into the automotive industry. Warrior came into the TechCrunch studios today to speak with me about her about plans for the future of the NextEv and why she made the move into electric vehicle.  

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    Are economic statistics in danger of becoming irrelevant?

    Reliable economic statistics are a vital public good. They are essential to effective policymaking, business planning, and the electorate’s ability to hold decision-makers to account.

    And yet the methods we use to measure our economies are becoming increasingly out of date. The statistical conventions on which we base our estimates were adopted a half-century ago, at a time when the economy was producing relatively similar physical goods. Today’s economy is radically different and changing rapidly – the result of technological innovation, the rising value of intangible, knowledge-based assets, and the internationalization of economic activity.

    In light of these challenges, UK Chancellor of the Exchequer George Osborne asked me ten months ago to assess the United Kingdom’s current and future statistical needs. While my research focused on the UK, the challenges of producing relevant, high-quality economic statistics are the same in many countries.

    Recent technological advances have radically altered the way people conduct their lives, both at work and at play. The advances in computing power underpinning the digital revolution have led not only to rapid quality improvements and product innovation, but also to new, connectivity-driven ways of exchanging and providing services.

    One particular challenge for economic measurement stems from the fact that an increasing share of consumption comprises digital products delivered at a zero price or funded through alternative means, such as advertising. While free virtual goods clearly have value to consumers, they are entirely excluded from GDP, in accordance with internationally accepted statistical standards. As a result, our measurements may not be capturing a growing share of economic activity.
    Consider the music industry. Downloads and streaming services have now largely replaced CDs, the dominant medium in the 1990s. And yet the money has not followed; the industry’s revenues and margins have both plummeted. As a result, its contribution to GDP (as we currently measure it) may be falling, even as the quantity and quality of services are increasing.

    Two methods can give us a rough estimate how much digital economic activity we are failing to capture in our measurements. We can use average wages to estimate the value of the time people spend online using free digital products, or we can adjust telecommunication services output to account for the rapid growth in Internet traffic. Both approaches suggest that accounting for these types of activities could add between one-third and two-thirds of a percentage point to the average annual growth rate of the UK economy over the past decade.

    The digital revolution is also disrupting traditional business models. The reduced search and matching costs offered by a range of online platforms are unlocking the market for skills (known as the “gig economy”) and the market for underutilized assets (known as the “sharing economy”). This, too, causes conceptual and practical measurement challenges for established GDP calculus. The traditional statistical distinction between productive firms and consuming households leaves little room to account for households as value creators.

    Measuring GDP, it turns out, is like trying to hit a moving target. The digital revolution is likely to be followed by yet another wave of disruptive technology, including advances in materials science, artificial intelligence, and genetic engineering. As the economy evolves, so must the frame of reference for the statistics we use to measure it.

    Consequently, internationally agreed statistical standards will almost always be somewhat out of date or incomplete, as they are bound to lag behind changes in the economy. National statistical offices should explore measurement issues that go beyond the prevailing standards, rather than use compliance as an excuse for their failure to innovate.

    One solution would be to establish a continuing program of research into the measurement implications of emerging economic trends, conducting one-off studies at first to gauge their potential quantitative importance. This could then guide the development of experimental statistics capturing the new phenomena.

    New techniques of collecting and analyzing big data, such as web scraping, text-mining, and machine learning, provide an opportunity for statisticians. Governments already hold some administrative data, but their use for statistical purposes often requires legislative changes. Unlocking this trove of information would extend statistical samples to near-census size, increase their timeliness and accuracy, and reduce the respondent costs to businesses and households.

    Ensuring that data accurately reflect a changing economy is one of the hardest tasks faced by national statistical institutes worldwide. Success requires not only understanding the limitations of traditional measurements, but also developing a curious and self-critical workforce that can collaborate with partners in academia, industry, the public sector, and other national statistical institutes to develop more appropriate methods.

    The UK is by no means alone in facing these challenges. But we need to act quickly. Otherwise, the speed of economic change will render our statistics irrelevant to modern life.

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    World Bank Funding For India’s Rooftop Solar Mission

    India’s solar ambitions have received a major boost with the World Bank approving a US $625 million loan to support the installation of rooftop solar power systems across the country.
    The Government of India’s National Solar Mission has set a goal of installing 100 GW of solar capacity by 2022, 40 GW of which is designated for rooftop solar.

    The World Bank loan is aimed at financing at least 400 MW of new Grid Connected Rooftop Solar Photovoltaic (GRPV), buttressed by a co-financing loan of US $120 million and a US $5 million grant from the Climate Investment Fund, to help the Indian market overcome teething problems which have hampered uptake in rooftop solar.

    Despite an estimated potential of 124,000 MW, rooftop solar in India has been sadly neglected in favour of larger scale solar plants. Energy consultancy firm Bridge to India’s latest Solar Handbook (PDF) says the 40 GW target for 2022 seems “a very remote prospect” without more focused policy support and an effective net metering program from government.

    India remains a heavy coal-consuming nation, but is one of the lowest per capita consumers of energy on the world; with over 200 million people living off-grid. According to the World Bank, power shortages force manufacturers and industrial users to rely on expensive and polluting diesel-based back-up power supplies.

    “India is endowed with huge solar energy potential, and the World Bank is strongly supportive of the government’s plans to harness this potential and increase India’s solar PV capacity to 100 GW,” said Onno Ruhl, World Bank Country Director in India.

    “This project will support this target, by providing financing to some of the 40 GW of solar PV which will be placed on rooftops.”

    In January this year, as the country announced it had reached an overall solar capacity of 5.6 percent, the Indian Cabinet Committee on Economic Affairs increased the budget for GRPV programs by more than 8-fold, in an effort to install 4200 MW of rooftop solar power systems throughout the country out to 2019-20.

    The World Bank project will be implemented by the State Bank of India (SBI), and will support a range of rooftop solar options; including commercial and industrial PV systems. With many citizens unable to afford upfront ownership of systems, the SBI Rooftop PV Program will include third-party ownership, leasing, rooftop rental, as well as direct end-user ownership.

    “Today, the only available option for those who want to install solar PV is to pay the entire cost up-front. The variety of financing mechanisms on offer under this program will represent a major innovation for the rooftop market,” said Mohua Mukherjee, Senior Energy Specialist and World Bank’s Task Team Leader for the project.

    “Most importantly, the scope of the project will go beyond simply making finance available, it will also improve the investment climate for solar PV, and increase the `Ease of Doing Rooftop Business”.

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