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Friday, June 24, 2016

Team from India to Participate In NASA Competition 06-26






A team of 13 Indian engineering students, including four girls, will participate in NASA's prestigious global competition to build and design remotely operated vehicles from scratch.

The team named 'Screwdrivers' from Mukesh Patel School of Technology Management, Mumbai, will compete against 40 other teams from countries like China, Scotland, Russia, USA, Canada, Ireland, Mexico, Norway, Denmark, Egypt, Turkey, and Poland in NASA's 15th annual international Remotely Operated Vehicle (ROV) competition in Houston from Thursday.


This competition is being organised by MATE (Marine Advanced Technology Education) and Screwdrivers is the only team from India and competing against 40 other teams from countries like China, Scotland, Russia, USA, Canada, Ireland, Mexico, Norway, Denmark, Egypt, Turkey, and Poland.


Competing for a coveted prize as part of NASA's MATE international ROV competition, the team guided by Prof Sawankumar Naik, is all set to represent India at the NASA Johnson Space Canter's Neutral Buoyancy Lab from June 23 to 25.


"Although it is their third visit to the space centre, but this time, with over 40 participating teams from across the globe, the stakes are higher than ever," he told.


Students are expected to build and design their own remotely operated vehicles from scratch.


Chief Technical Officer, Vijayender Joshi said, "The tasks change each year but are always based on ocean engineering.

This year, NASA is going to start a mission to Jupiter's moon, Europa, since the moon also has water, the students would have to create a model, which will not only work underwater but also survive in space.


"The design is completely revamped from the model that went last year, we're told. And with various changes in design, the cost has come up to an approximately $1,000. Made over a span of five months, the robot, which the team calls 'spyder', has two parts - one that can stay above water and another that can go under it," he adds.


Team Screwdrivers has previously been felicitated by late President late APJ Abdul Kalam, Ace Nuclear Scientist Dr Anil Kakodkar, record holding astronaut Sunita Williams and Chief Minister of Maharashtra Devendra Fadnavis for innovative design and cost-effective implementation.




Saturday, June 11, 2016

100 years of global aging, in one GIF 06-11


100 years of global aging, in one GIF











The median age of a Japanese citizen today is about 46.5 years old. In Cameroon, it's just 18.5 years. That's a wide gap, and one that tells us a lot about both countries — and, more broadly, the state of the world today.

To understand what this gap tells us, it helps to look at a global perspective. The following GIF, from Lund University Masters student Aron Strandberg, does this beautifully. Using data from the United Nations World Population Prospects, it traces the median age around the world from 1960 through today. It also uses the UN's projections to estimate how each country's median will likely change over the next 40-odd years:

Immediately, you see two things. First, the median age tends to be significantly higher in wealthy and middle-income countries than in poorer ones. Second, the median age is going up in almost every country worldwide.

These two trends reflect centuries of good news. Rapid technological development and economic growth since the Industrial Revolution have allowed people to live much longer. Basic public health techniques have dramatically reduced infant mortality, and more advanced technologies (like chemotherapy) allow people to live even longer. This progress has been uneven — people in wealthy countries still live longer — but the trend is unmistakable.



That explains why the median age is getting higher basically everywhere, and why it's higher in rich countries than in poor ones. People are just living longer.

But there's a dark side to this trend: Populations can get too old.

An older median age isn't produced merely by people living longer. If fewer babies are being born in a country, then that will raise a country's median age even if it hasn't seen huge increases in life expectancy. According to the UN, "fertility has declined in virtually all major areas of the world" in recent years.

In some places, that's not so bad: Sub-Saharan African countries still had an average of 4.7 children per woman between 2010 and 2015, more than enough to deliver robust population growth. In those countries, a lower birthrate over time would be a good sign, as it tends to correlate with economic development and more education for women.

But in Europe (fertility rate: 1.6), North America (1.86), and Asia (2.2), low birthrate is becoming a serious problem.

As the map shows, the median age in countries like Japan, China, the US, and France will soon reach the 40s and 50s if current trends continue. Imagine a world where the median age in America is 10 years older than it is today, and then think about how many more people will qualify for Social Security versus how many fewer working-age people there will be who can be taxed to pay for it.
This isn't an imminent problem in the United States, and may not be one for some time. But it is in Japan, which has one of the lowest birthrates in the world. The Japanese experience is serving as something of a test case for what happens when a country gets too old.

"The working age population is falling by about 1 percent per year, and the rate of shrinkage will eventually approach 1.7 percent per year, so that even productivity growth of 2% or more will deliver very low aggregate or per capita growth," a recent OECD report concludes. "There will simply be no way to sustain high living standards and quality public standards in a 'super-aging' Japan unless the country is able to achieve much higher rates of productivity growth."

So while it's great news that a lot of countries are getting older, some countries — namely rich ones — are getting too old. This is a solvable problem: Both increased immigration from poor countries and better integration of women into the workplace should raise a country's birthrate. But if rich countries want to stave off serious economic problems down the line, they need to start dealing with their birthrate problems soon.


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Friday, June 10, 2016

An incumbent’s guide to digital disruption 06-11


























Image credit : Shyam's Imagination Library



Incumbents needn’t be victims of disruption if they recognize the crucial thresholds in their life cycle, and act in time.
          
A decade ago, Norwegian media group Schibsted made a courageous decision: to offer classifieds—the main revenue source of its newspaper businesses—online for free. The company had already made significant Internet investments but realized that to establish a pan-European digital stronghold it had to raise the stakes. During a presentation to a prospective French partner, Schibsted executives pointed out that existing European classifieds sites had limited traffic. “The market is up for grabs,” they said, “and we intend to get it.” Today, more than 80 percent of their earnings come from online classifieds.



Our framework for understanding the life cycle of industry disruption.
      
About that same time, the boards of other leading newspapers were also weighing the prospect of a digital future. No doubt, like Schibsted, they even developed and debated hypothetical scenarios in which Internet start-ups siphoned off the lucrative print classified ads the industry called its “rivers of gold.” Maybe these scenarios appeared insufficiently alarming—or maybe they were too dangerous to even entertain. But very few newspapers followed Schibsted’s path.  


From the vantage point of 2016, when print media lie shattered by a tsunami of digital disruption, it’s easy to talk about who made the “right” decision and who the “wrong.” Things are far murkier when one is actually in the midst of disruption’s uncertain, oft-hyped early stages. In the 1980s, steel giants famously underestimated the potential of mini-mills. In the 1980s and 1990s, the personal computer put a stop to Digital Equipment Corporation, Wang Laboratories, and other minicomputer makers. More recently, web retailers have disrupted physical ones, and Airbnb and Uber Technologies have disrupted lodging and car travel, respectively. The examples run the gamut from database software to boxed beef.

What they have in common is how often incumbents find themselves on the wrong side of a big trend. No matter how strong their ingoing balance sheets and market share—and sometimes because of those very factors—incumbents can’t seem to hold back the tide. The champions of disruption are far more often the attackers than the established incumbent. The good news for incumbents is that many industries are still in the early days of digital disruption. Print media, travel, and lodging provide valuable illustrations of the path increasingly more will follow. For most, it’s early enough to respond. (For a quick guide to assessing your organization's position in the digital disruption journey,
What’s the secret of those incumbents that do survive—and sometimes even thrive?

One aspect surely relates to the ability to recognize and overcome the typical pattern of response (or lack thereof) that characterizes companies in the incumbent’s position. This most often requires acuity of foresight3 and a willingness to respond boldly before it’s too late, which usually means acting before it is obvious you have to do so. As Reed Hastings, the CEO of Netflix, pointed out (right as his company was making the leap from DVDs to streaming), most successful organizations fail to look for new things their customers want because they’re afraid to hurt their core businesses.

Clayton Christensen called this phenomenon the innovator’s dilemma. Hastings simply said, “Companies rarely die from moving too fast, and they frequently die from moving too slowly.”4
We are all great strategists in hindsight. The question is what to do when you are in the middle of it all, under the real-world constraints and pressures of running a large, modern company. This article looks at the four stages of disruption from an incumbent’s perspective, the barriers to overcome, and the choices and responses needed at each stage.

Where you are and what you need

It may help to view these stages on an S-curve (exhibit). At first, young companies struggle with uncertainty but are agile and willing to experiment. At this time, companies prize learning and optionality and work toward creating value based on the expectation of future earnings. The new model then needs to reach some critical mass to become a going concern. As they mature—that is, become incumbents—mind-sets and realities change. The established companies lock in routines and processes. They iron out and standardize variability amid growing organizational complexity. In the quest for efficiency, they weed out strategic options and reward executives for steady results. The measure of success is now delivery of consistent, growing cash flows in the here and now. The option-rich expectancy of future gain is replaced by the treadmill of continually escalating performance expectations.






In a disruption, the company heading toward the top of the old S-curve confronts a new business model at the bottom of a new S-curve. The circle of creative destruction is renewed, but this time the shoe is on the other foot. Two primary challenges emerge. The first is to recognize the new S-curve, which starts with a small slope, and often-unimpressive profitability, and at first does not demand attention. After all, most companies have shown they are very good at dealing with obvious emergencies, rapidly corralling resources and acting decisively. But they struggle to deal with the slow, quiet rise of an uncertain threat that does not announce itself. Second, the same factors that help companies operate strongly toward the top of an S-curve often hinder them at the bottom of a new one. Because different modes of operation are required, it’s hard to do the right thing—even when you think you know what the right thing might be.

This simplified model, of a new S-curve crashing slow motion into an old one, gives us a way to look at the problem from the incumbent’s perspective, and to appreciate the actual challenges each moment presents along the way. In the first stage, the new S-curve is not yet a curve at all. In the second, the new business model gets validated, but its impact is not forceful enough to fundamentally bend the performance trajectory of the incumbent. In the third stage, however, the new model gains a critical mass and its impact is clearly felt. In the fourth, the new model becomes the new normal as it reaches its own maturity.

Let’s step through these stages in sequence and see what is going on.

Stage one: Signals amidst the noise

In the late 1990s, PolyGram was one of the world’s top record labels, with a roster boasting Bob Marley, U2, and top classical artists. But, in 1998, Cornelis Boonstra, CEO of PolyGram’s Dutch parent, Koninklijke Philips, flew to New York, met with Goldman Sachs, and arranged to sell PolyGram to Seagram for $10.6 billion. Why? Because Boonstra had come across research showing that consumers were using the new recordable CD-ROM technology (which Philips coinvented) largely for one purpose: to copy music.

In hindsight, this is a good example of how, in the early stages of disruption, demand begins to “purify” and lose the distortions imposed on it by businesses.


The MP3 format had barely been invented, Napster was a mere gleam in Sean Parker’s eye, and PolyGram was riding at the top of its S-curve—but Boonstra detected the first signs of transformational change and decided to act swiftly and decisively. Within a decade, compact-disc and DVD sales in the United States dropped by more than 80 percent. Similarly, Telecom New Zealand foresaw the deteriorating economics of its Yellow Pages business and sold its directories business in 2007 for $2.2 billion (a nine-time revenue multiple)6 while numerous other telecom companies held on until the businesses were nearly worthless.


The newspaper industry had no shortage of similar signals. As early as 1964, media theorist Marshall McLuhan observed that the industry’s reliance on classified ads and stock-market quotes made it vulnerable: “Should an alternative source of easy access to such diverse daily information be found, the press will fold.” The rise of the Internet created just such a source, and start-ups such as eBay opened a new way for people to list goods for sale without the use of newspaper ads. Schibsted was one of the earliest media companies to both anticipate the threat and act on the opportunity. As early as 1999, the company became convinced that “The Internet is made for classifieds, and classifieds are made for the Internet.”


It’s not surprising that most others publishers didn’t react. At this early stage of disruption, incumbents feel barely any impact on their core businesses except in the distant periphery. In short, they don’t “need” to act. It takes rare acuity to make a pre-emptive move, likely in the face of conflicting demands from stakeholders. What’s more, it can be difficult to work out which trends to ignore and which to react to.

Gaining sharper insight, and escaping the myopia of this first stage, requires incumbents to challenge their own “story” and to disrupt long-standing (and sometimes implicit) beliefs about how to make money in a given industry. As our colleagues put it in a recent article, “These governing beliefs reflect widely shared notions about customer preferences, the role of technology, regulation, cost drivers, and the basis of competition and differentiation. They are often considered inviolable—until someone comes along to violate them.”


The process of reframing these governing beliefs involves identifying an industry’s foremost notion about value creation and then turning it on its head to find new forms and mechanisms for creating value.

Stage two: Change takes hold

The trend is now clear. The core technological and economic drivers have been validated. At this point, it’s essential for established companies to commit to nurturing new initiatives so that they can establish footholds in the new sphere. More important, they need to ensure that new ventures have autonomy from the core business, even if the goals of the two operations conflict. The idea is to act before one has to.

But with disruption’s impact still not big enough to dampen earnings momentum, motivation is often missing. Even as online classifieds for cars and real estate began to take off and Craigslist gained momentum, most newspaper publishers lacked a sense of urgency because their own market share remained largely unaffected. And it’s not like the new players were making millions (yet). There was no performance envy.

But Schibsted did find the necessary motivation. “When the dot-com bubble burst, we continued to invest, in spite of the fact that we didn’t know how we were going to make money online,” recalls then-CEO Kjell Aamot. “We also allowed the new products to compete with the old products.”10 Offering free online classifieds directly cannibalized its newspaper business, but Schibsted was willing to take the risk. The company didn’t just act; it acted radically.

Now, let’s openly acknowledge how hard it is for a company’s leaders to commit to supporting experimental ventures when the business is climbing the S-curve. When Netflix disrupted itself in 2011 by shifting focus from DVDs to streaming, its share price dropped by 80 percent. Few boards and investors can handle that kind of pain when the near-term need is debatable. The vague longer-term threat just doesn’t seem as dangerous as the immediate hardship. After all, incumbents have existing revenue streams to protect—start-ups only have upside to capture. Additionally, management teams are more comfortable developing strategies for businesses they know how to operate, and are naturally reluctant to enter a new game with rules they don’t understand.

The upshot: most incumbents dabble, making small investments that won’t flatten their current S-curve and guard against cannibalization. Usually, they focus too heavily on finding synergies (always looking for efficiency) rather than fostering radical experimentation. The illusion that this dabbling is getting you into the game is all too tempting to believe. Many newspapers built online add-ons to their classified businesses, but few were willing to risk cannibalizing the traditional revenue streams, which at this point were still far bigger and more profitable. And remember, at this time, Schibsted had not yet been rewarded for its early action: its results looked pretty similar to its peers.

In time, of course, bolder action becomes necessary, and executives must commit to nurturing potentially dilutive and small next-horizon businesses in a pipeline of initiatives. Managing such a portfolio requires high tolerance for ambiguity, and it requires executives to adapt to shifting conditions, both inside and outside the company, even as the aspiration to deliver favorable outcomes for shareholders remains constant.11 The difficulty is the tendency to protect the core at the expense of the periphery. Not only are there strong, short-term financial incentives to protect the core, but it’s also often painful to shift focus from core businesses in which one has, understandably enough, an emotional as well as a financial investment.

No small part of the challenge is to accept that the previous status quo is no longer the baseline. Grocery retailer Aldi has disrupted numerous incumbents globally with its low-price model. Aldi’s future success was visible while Aldi was still nascent in the market. Yet many incumbent supermarkets chose to avoid the near-term pain of sharpening entry price points and improving their private-label brands. In hindsight, those moves would have been highly net-present-value positive with respect to avoided loss—as Aldi has continued its strong growth across three continents.

Stage three: The inevitable transformation

By now, the future is pounding on the door. The new model has proved superior to the old, at least for some critical mass of adopters, and the industry is in motion toward it. At this stage of disruption, to accelerate its own transformation, the incumbent’s challenge lies in aggressively shifting resources to the new self-competing ventures it nurtured in stage two. Think of it as treating new businesses like venture-capital investments that only pay off if they scale rapidly, while the old ones are subject to a private-equity-style workout.

Making this tough shift requires surmounting the inertia that can afflict companies even in the best of times.12 In fact, our experience suggests stage three is the hardest one for incumbents to navigate. As company performance starts to suffer, tightening up budgets, established companies naturally tend to cut back even further on peripheral activities while focusing on the core. The top decision makers, who usually come from the biggest business centers, resist having their still-profitable (though more sluggishly growing) domains starved of resources in favor of unproven upstarts. As a result, leadership often under invests in new initiatives, even as it imposes high performance hurdles on them. Legacy businesses continue to receive the lion’s share of resources instead. By this time, the very forces causing pressure in the core make the business even less willing and able to address those forces. The reflex to conserve resources kicks in just when you most need to aggressively reallocate and invest.

Boards play a significant role in this as well. Far too often, boards are unwilling (or unable) to change their view of baseline performance, further exacerbating the problem. Often a board’s (understandable) reaction to reduced performance is to push management even harder to achieve ambitious goals within the current model, ignoring the need for a more fundamental change. This only worsens problems in the future.

Further complicating matters, incumbents with initially strong positions can take false comfort at this stage, because the weaker players in the industry get hit hardest first. The narrative “it is not happening to us” is all too tempting to believe. The key is to monitor closely the underlying drivers, not just the hindsight of financial outcomes. As the tale goes, “I don’t have to outrun the bear . . . I just have to outrun you.” Except when it comes to disruption, that strategy merely buys time. If the bear keeps running, it will get to you, too.

The typical traditional newspaper operator, likewise, wasn’t blind to a shift taking place, but it rarely managed to mount a response that was sufficiently aggressive. One notable exception was former digital laggard Axel Springer. The German media company was “a mere Internet midget,” according to Financial Times Deutschland, until it leapt into action in 2005. It went on a shopping spree, acquiring 67 digital properties and launching 90 initiatives of its own by 2013.13 Like Schibsted, it saw the value pools moving to online classifieds and made the leap. The lesson is that incumbents can win even with a late start, provided that they throw themselves in wholly. Today, digital media contributes 70 percent of Axel Springer’s earnings before interest, taxes, depreciation, and amortization. The core has become the periphery.

To generate the acceleration needed at this stage of the game, incumbents must embark on a courageous and unremitting reallocation of resources from the old to the new model—and show a willingness to run new businesses differently (and often separately) from the old ones. Perhaps nothing underlines this point more than Axel Springer’s 2013 divestment of some of its strongest legacy print-media products, which accounted for about 15 percent of its sales, to Germany’s number-three print-media player, Funke Mediengruppe. These products, such as the Berliner Morgenpost, owned by Axel Springer since 1959, were previously a core part of the corporate DNA and emblems of its journalistic culture. But no more. They realized that the future value of the business was not just about the continuation of today’s earnings but rather relied on the creation of a new economic engine.

When incumbents lack the in-house capability to build new businesses, they must look to acquire them instead. Here the challenge is to time acquisitions somewhere between where the business model is proved but valuations have yet to become too high—all while making sure the incumbent is a “natural best owner” of the new businesses it acquires. Examples of this approach in the financial sector include BBVA’s acquisition of Simple and Capital One’s acquisition of the design firm Adaptive Path.

Stage four: Adapting to the new normal

In this late stage, the disruption has reached a point when companies have no choice but to accept reality: the industry has fundamentally changed. For incumbents, their cost base isn’t in line with the new (likely much shallower) profit pools, their earnings are caving in, and they find themselves poorly positioned to take a strong market position.

This is where print media is now. The classifieds’ “rivers of gold” have dried up, making survival the first priority, and sustainability and growth the second. In 2013, the CEO of Australia media company Fairfax Media told the International News Media Association World Congress, “We know that at some time in the future, we will be predominantly digital or digital-only in our metropolitan markets.”14 True, some legacy mastheads have created powerful online news properties with high traffic, but display advertising and paywalls alone are for the most part not enough to generate a thriving revenue line, and social aggregation sites are continuing to drive unbundling. Typical media firms have had to undertake the multiple painful waves of restructuring and consolidation that may be needed while they seed growth and look for ways to monetize their brands.

For the incumbents who, like Axel Springer and Schibsted, have made the leap, the adaptation phase brings new challenges. Having become majority digital businesses, they’re fully exposed to the volatility and pace that comes with the territory. That is, their adaptation response is less a one-time event than a process of continual self-disruption. Think of Facebook upending its business model to go “mobile first.”15 You can’t be satisfied with the first pivot—you have to be prepared to keep doing it.

In some cases, incumbents’ capabilities are so highly tied to the old business model that rebirth through restructuring is unlikely to work, and an exit is the best way to preserve value. Eastman Kodak Company, for example, may have been better off leaving the photography business much faster, because its numerous strategies all failed to save it. When a business is built on a legacy technology that is categorically different from the new standard, even perfect foresight of the demise of film or CDs would not have solved the core problem that the digital replacement is fundamentally less profitable.

The simple fact is that new profit pools may not be as deep as prior ones (as many newspaper publishers have come to believe). The challenge is to adapt and structurally realign cost bases to the new reality of profit pools, and accept that the “new normal” likely includes far fewer “rivers of gold.”



The reality is, most industries are still in stages one, two, and three. That’s why the early experiences of media, music, and travel companies can prove so valuable. These first industries to transition to a digital reality highlight the social and human challenges that by their nature apply to companies in most every industry and geography.

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Tuesday, May 31, 2016

Indian PSUs, still far from a digital deluge in Technology. 06-01


Indian PSUs, still far from a digital deluge in Technology

































Public sector undertakings (PSUs) are the nation builders of India. Over the past couple of decades, they’ve catapulted the country onto the world stage in sectors from energy and finance to agriculture and transportation. Now they face a new challenge: digital, a force that’s impacting PSUs from the corner office to the factory floor. New digitally savvy rivals are gaining on traditional turf. The question becomes: Are PSUs ready to build the workforce of the future?


Maharatna. Navratna. Miniratna. The jewels of India’s public sector undertakings continue to shape the competitive landscape of India, contributing an impressive 25 percent of the overall gross domestic product.1 They represent some of the most trusted brands for consumers, and coveted employers for workers. Like other leading companies around the world, PSUs are investing in technology. Particularly digital innovation that will put them ahead of competitors, making them more agile and competitive.


But to date, one critical element of PSUs’ digital strategy has been overlooked: the workforce. It’s as if the prevailing thought is, “We’ll invest in the technology and our people will be digital by default.” But gaining the agility required to compete in the age of disruption goes beyond systems. It requires a deep shift for PSUs: in leadership, recruitment and organization. The current PSU culture is not well suited to such sweeping changes. Accenture Strategy research has identified the top ten attributes that correlate to successful culture change.


PSUs are on par with non-PSUs in only half of those attributes.2 PSUs rank in the bottom quartile for the remaining attributes, including talent management, adaptability and confronting conflict. In addition, current PSU employees are more skeptical about their organization’s readiness to leverage digital advances. Fewer than half (47 percent) of PSU employees, versus 56 percent of non-PSU employees, expect to derive productivity improvements or drive innovation from digital transformation.3 It’s a challenging starting point, but the direction is clear. PSUs in India need to embrace digital or witness their long-held national dominance quickly evaporate.


Accenture Strategy research has identified the top ten attributes that correlate to successful culture change. PSUs are on par with non-PSUs in only half of those attributes.


Digital has upended many traditional business models, philosophies and processes. One of those concerns the idea that leadership is practiced only at the top levels of the organization, by leaders who advanced through the ranks of an organization based largely on seniority. It was a system that worked well in an environment that was much less volatile and more predictable. Where skills like organization and delegation were paramount. While those skills are still important, there are other, more critical ones in the digital age.


 Leaders today need to thrive at building crossorganization and industry connections that lead to new sources of innovation. They need to influence all levels of the organization but without the authoritarian approach that marks traditional management. They also need to grasp new technologies and their impact on growth and gain the ability to experiment quickly and move on if the desired results aren’t achieved. PSUs need to open their organizations to feedback and ideas that lead to innovation. And flatten hierarchies, cutting out the layers and processes that impede agility. An influx of young talent signals a truth about PSUs in the digital age: old school leaders cannot lead digital transformation alone. They need to build mentors throughout the organization. And push out decision making to the edges by developing a pool of leaders with high digital quotient. Leading at the edge


The requirements of digital—to tap sources of innovation across functional boundaries and industries—means a change in the way PSUs are managed. Digital is horizontal. Traditional is vertical. While PSUs have invested in new systems and hardware to connect their operations, they have overlooked a critical element: the workforce. 73 percent of PSU employees recognize that digital will seriously transform the nature of their work over the next three years.4 They won’t be “digital by default.” Employers must rise to the challenge and change their current talent pools. Retraining them to handle new challenges and attracting a much more diverse new team. Let’s take energy as an example, an industry that is increasingly deregulated and privatized. As the industry shifts to a profit-driven business model, companies will need to recruit new skills like analytics, and sophisticated customer relationship capabilities. This will require expanding beyond the usual degrees in fields like IT and engineering, to backgrounds in statistics and internet marketing. In some instances, PSUs may want to tap into non-traditional sources of specialized skills such as on-line talent exchanges, or third-party partnerships.


Your workforce is not “digital by default”


73 percent of PSU employees recognize that digital will seriously transform the nature of their work over the next three years.


4 | Indian PSUs


To keep the sparkle in Maharatna, Navratna and Miniratna there are three things PSUs can do now to lead in digital: Define a disruptive business model Because of their traditional reach, and long-established marketplace presence, it used to be that no other rival could match the strength of a PSU. But digital allows startups to forgo brick and mortar infrastructure and rapidly achieve new levels of scale unheard of even a handful of years ago. Consider the Bank of India and ICICI Bank. In under two decades time, ICICI Bank has catapulted from startup status to competing neckand-neck with the PSU.5 How? By early on developing an aggressive online strategy that includes virtual banking and next generation mobile banking apps, among other digital moves. The message: it’s time for PSUs to get serious about digital investment. They need to take an ‘equity investor’ approach and incubate digital plays. That requires redesigning the organization for speed to leap ahead of competition instead of treating digital as adjunct to their current strategies. Leaders should learn from juniors With the long tradition of command-and-control leadership style, this flies in the face of management wisdom for most PSUs. But to survive in a digital world, senior leadership needs to turn to younger counterparts to gain a digital edge. This requires “reverse mentoring” where senior leaders learn from their younger counterparts. This learning goes beyond the basic skills like using apps and internet devices to learning about the internet of things, leveraging social networks for employee / customer engagement, and seeing opportunities where earlier none were apparent. PSUs are taking heed: in the general insurance sector, a raft of young officers were fast-tracked to the position of general manager in companies including National Insurance, New India Assurance and United India, among others. As a result, PSUs are starting to infuse new blood into their highest echelons.6 It’s a shot across the bows to PSUs that aren’t moving far, or fast enough.


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Rewrite the value proposition to create competitive advantage To attract and retain the kind of talent digital requires, PSUs need to craft value propositions that include benefits to society as well as opportunities for personal growth. Previous generations of Indians were focused on climbing the socioeconomic ladder of success. Now that many have “arrived,” the focus of newer generations is giving back. PSUs, by the nature of their services, are about contributing to the good of the country. Companies need only to underscore that in their value propositions to attract new pools of talent looking for reward through social contribution. PSUs also need to emulate the offerings of their non-PSU competitors. Consider National Thermal Power Corporation.7 This PSU launched an innovative plan to attract and retain young talent at their often remote locations. They developed the concept of “PUPS,” which stands for providing urban facilities at projects. Included in the new facilities are cafes, libraries, Wi-Fi hotspots and other trappings of city living.


Brilliance of the jewels

Thanks to Accenture for the content.

Monday, May 30, 2016



The Psychological Quirk That Explains Why You Love Donald Trump





The popularity of the GOP front-runner can be explained by the Dunning-Kruger Effect.


Many commentators have argued that Donald Trump’s dominance in the GOP presidential race can be largely explained by ignorance; his candidacy, after all, is most popular among Republican voters without college degrees. Their expertise about current affairs is too fractured and full of holes to spot that only 9 percent of Trump’s statements are “true” or “mostly” true, according to PolitiFact, whereas 57 percent are “false” or “mostly false”—the remainder being “pants on fire” untruths. Trump himself has memorably declared: “I love the poorly educated.”

But as a psychologist who has studied human behavior—including voter behavior—for decades, I think there is something deeper going on. The problem isn’t that voters are too uninformed. It is that they don’t know just how uninformed they are.

Psychological research suggests that people, in general, suffer from what has become known as the Dunning-Kruger Effect. They have little insight about the cracks and holes in their expertise. In studies in my research lab, people with severe gaps in knowledge and expertise typically fail to recognize how little they know and how badly they perform. To sum it up, the knowledge and intelligence that are required to be good at a task are often the same qualities needed to recognize that one is not good at that task—and if one lacks such knowledge and intelligence, one remains ignorant that one is not good at that task. This includes political judgment.

We have found this pattern in logical reasoning, grammar, emotional intelligence, financial literacy, numeracy, firearm care and safety, debate skill, and college coursework. Others have found a similar lack of insight among poor chess players, unskilled medical lab technicians, medical students unsuccessfully completing an obstetrics/gynecology rotation, and people failing a test on performing CPR.

This syndrome may well be the key to the Trump voter—and perhaps even to the man himself. Trump has served up numerous illustrative examples of the effect as he continues his confident audition to be leader of the free world even as he seems to lack crucial information about the job. In a December debate he appeared ignorant of what the nuclear triad is. Elsewhere, he has mused that Japan and South Korea should develop their own nuclear weapons—casually reversing decades of U.S. foreign policy.

Many commentators have pointed to these confident missteps as products of Trump’s alleged narcissism and egotism. My take would be that it's the other way around. Not seeing the mistakes for what they are allows any potential narcissism and egotism to expand unchecked.

In voters, lack of expertise would be lamentable but perhaps not so worrisome if people had some sense of how imperfect their civic knowledge is. If they did, they could repair it. But the Dunning-Kruger Effect suggests something different. It suggests that some voters, especially those facing significant distress in their life, might like some of what they hear from Trump, but they do not know enough to hold him accountable for the serious gaffes he makes. They fail to recognize those gaffes as missteps.

Here is more evidence. In a telling series of experiments, Paul Fernbach and colleagues asked political partisans to rate their understanding of various social policies, such as imposing sanctions on Iran, instituting a flat tax, or establishing a single-payer health system.

Survey takers expressed a good deal of confidence about their expertise. Or rather, they did until researchers put that understanding to the test by asking them to describe in detail the mechanics of two of the policies under question. This challenge led survey takers to realize that their understanding was mostly an illusion. It also led them to moderate their stances about those policies and to donate less money, earned in the experiment, to like-minded political advocacy groups.

Again, the key to the Dunning-Kruger Effect is not that unknowledgeable voters are uninformed; it is that they are often misinformed—their heads filled with false data, facts and theories that can lead to misguided conclusions held with tenacious confidence and extreme partisanship, perhaps some that make them nod in agreement with Trump at his rallies.

Trump himself also exemplifies this exact pattern, showing how the Dunning-Kruger Effect can lead to what seems an indomitable sense of certainty. All it takes is not knowing the point at which the proper application of a sensible idea turns into malpractice.

For example, in a CNBC interview, Trump suggested that the U.S. government debt could easily be reduced by asking federal bondholders to “take a haircut,” agreeing to receive a little less than the bond’s full face value if the U.S. economy ran into trouble. In a sense, this is a sensible idea commonly applied—at least in business, where companies commonly renegotiate the terms of their debt.

But stretching it to governmental finance strains reason beyond acceptability. And in his suggestion, Trump illustrated not knowing the horror show of consequences his seemingly modest proposal would produce. For the U.S. government, his suggestion would produce no less than an unprecedented earthquake in world finance. It would represent the de facto default of the U.S. on its debt—and the U.S. government has paid its debt in full since the time of Alexander Hamilton. The certainty and safety imbued in U.S. Treasury bonds is the bedrock upon which much of world finance rests.

Even suggesting that these bonds pay back less than 100 percent would be cause for future buyers to demand higher interest rates, thus costing the U.S. government, and taxpayer, untold millions of dollars, and risking the health of the American economy.

This misinformation problem can live in voters, too, as shown in a 2015 survey about the proposed Common Core standards for education. A full 41 percent claimed the new standards would prompt more frequent testing within California schools. That was untrue. Only 18 percent accurately stated that the level of testing would stay the same. Further, 35 percent mistakenly asserted that the standards went beyond math and English instruction. Only 28 percent correctly reported that the standards were constrained to those two topics. And 34 percent falsely claimed that the federal government would require California to adopt the Common Core. Only 21 percent accurately understood this was not so.

But what is more interesting—and troubling—were the responses of survey takers who claimed they knew “a lot” about the new standards. What these “informed” citizens “knew” trended toward the false rather than the true. For example, 52 percent thought the standards applied beyond math and English (versus 32 percent who got it right). And 57 percent believed the standards mandated more testing (versus 31 percent who correctly understood that it did not). These misconceptions mattered: To the extent that survey takers endorsed these misconceptions, they opposed the Common Core.
My research colleagues and I have found similar evidence that voters who think they are informed may be carrying a good deal of misinformation in their heads. In an unpublished study, we surveyed people the day after the 2014 midterm elections, asking them whether they had voted. Our key question was who was most likely to have voted: informed, uninformed, or misinformed citizens.

We found that voting was strongly tied to one thing—whether those who took the survey thought of themselves as “well-informed” citizens. But perceiving oneself as informed was not necessarily tied to, um, being well-informed.

To be sure, well-informed voters accurately endorsed true statements about economic and social conditions in the U.S.—just as long as those statements agreed with their politics. Conservatives truthfully claimed that the U.S. poverty rate had gone up during the Obama administration; liberals rightfully asserted that the unemployment rate had dropped.

But both groups also endorsed falsehoods agreeable to their politics. Thus, all told, it was the political lean of the fact that mattered much more than its truth-value in determining whether respondents believed it. And endorsing partisan facts both true and false led to perceptions that one was an informed citizen, and then to a greater likelihood of voting.

Given all this misinformation, confidently held, it is no wonder that Trump causes no outrage or scandal among those voters who find his views congenial.

But why now? If voters can be so misinformed that they don’t know that they are misinformed, why only now has a candidate like Trump arisen? My take is that the conditions for the Trump phenomenon have been in place for a long time. At least as long as quantitative survey data have been collected, citizens have shown themselves to be relatively ill-informed and incoherent on political and historical matters. As way back as 1943, a survey revealed that only 25 percent of college freshmen knew that Abraham Lincoln was president during the Civil War.

All it took was a candidate to come along too inexperienced to avoid making policy gaffes, at least gaffes that violate received wisdom, with voters too uninformed to see the violations. Usually, those candidates make their mistakes off in some youthful election to their state legislature, or in small-town mayoral race or contest for class president. It’s not a surprise that someone trying out a brand new career at the presidential level would make gaffes that voters, in a rebellious mood, would forgive but more likely not even see.

But the Dunning-Kruger perspective also suggests a cautionary tale that extends well beyond the Trump voter. The Trump phenomenon may provide only an extravagant and visible example in which voters fail to spot a political figure who seems to be making it up as he goes along.
But the key lesson of the Dunning-Kruger framework is that it applies to all of us, sooner or later. Each of us at some point reaches the limits of our expertise and knowledge. Those limits make our misjudgments that lie beyond those boundaries undetectable to us.

As such, if we find ourselves worried about the apparent gullibility of the Trump voter, which may be flamboyant and obvious, we should surely worry about our own naive political opinions that are likely to be more nuanced, subtle, and invisible—but perhaps no less consequential. We all run the risk of being too ill-informed to notice when our own favored candidates or national leaders make catastrophic misjudgments.

To be sure, I don’t wish to leave the reader with a fatal hesitation about supporting any candidate. All I am saying is trust, but verify.

Thomas Jefferson once observed that “if a nation expects to be ignorant and free in a state of civilization, it expects what never was and never will be." The Trump phenomenon makes visible something that has been true for quite some time now. As a citizenry, we can be massively ill-informed. Yet, our society remains relatively free.

How have we managed so far to maintain what Jefferson suggested could never be? And how do we ensure this miracle of democracy continues? This is the real issue. And it will be with us far after the Trumpian political revolution or reality TV spectacle, depending on how you see it, has long flickered off the electronic screens of our cultural theater. 

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Wednesday, May 25, 2016

Tech Savvy: How Blockchains Could Transform Management 05-25



What’s happening this week at the intersection of management and technology.

























Re-architecting the firm with blockchain: Is Craig Wright really Satoshi Nakamoto, the mysterious creator of Bitcoin? Who knows — and really, who cares? The bigger issue is blockchains, the distributed ledgers that underpin cryptocurrencies like Bitcoin.
Blockchain technology has so many uses that trying to summarize them can make veteran tech experts sound like PR hacks. “As such, it holds the potential for unleashing countless new applications and as yet unrealized capabilities that have the potential to change everything,” write Don Tapscott and his co-author and son Alex Tapscott in their new book, Blockchain Revolution:


How the Technology Behind Bitcoin is Changing Money, Business, and the World.

That might sound like hyperbole, but it seems like everywhere you turn these days you run into blockchains. Banks are trying to harness blockchain before its blows up their business models. IBM is betting on blockchains to give its revenues a bump. Disney has a blockchain team doing … well, who knows what.


What we haven’t heard very much about is how blockchain could fundamentally change how companies are managed and operate. That’s a good reason to take a closer look at Blockchain Revolution, in which the Tapscotts devote a chapter to the topic. “Blockchain technology is enabling new forms of economic organization and new portfolios of value,” they write. “There are distributed models of the firm emerging — ownership, structure, operations, reward, and governance — that go far beyond enhancing innovation, employee motivation, and collective action.”


Intrigued? If you’d like read more about how blockchains might change the everyday operation of a business, check out the excerpt from the chapter, reprinted with permission, below.
The innovation hub — same as it ever was? The Internet has wrought significant changes in how we work, but some things — innovation hubs, for example — remain remarkably durable. “For hundreds of years,” writes freelance journalist Emily Sohn in Nature, “regions developed specialities that often arose from access to a natural resource, but then intensified as people moved to the regions to be among the expertise. The Internet was supposed to change all that. Around-the-clock connectivity that allowed researchers and entrepreneurs to collaborate from anywhere at any time meant that distance would no longer be an issue, predicted popular economic theory of the early 2000s. A decade later, it hasn’t panned out that way.”


Sohn reports that global connectivity seems to have stimulated the growth of innovation hubs, like Silicon Valley, rather than shrunk them. “Innovators and PhD students are now clumped together in fewer places, often in big cities,” she says. “And collaborations are more likely to happen between researchers who live, or have lived, close to each other.”


New and existing companies can’t afford to buck this finding. Locating in innovation hubs gives them greater access to talent. It also boosts their performance: Sohn cites studies that show start-ups located in hubs are more likely to survive, and firms in hubs are more likely to file patents than companies outside hubs.


It turns out that no matter how easy it is to collaborate at a distance, proximity remains an essential element in stimulating innovation. It sets the stage for serendipitous meetings. Face-to-face interaction also creates feel-good reactions in our brains that promote trust and more effective collaboration.


It’s not that digital connectivity inhibits innovation. Far from it, reports Sohn. Rather, it stimulates the enhanced innovation that is already taking place within innovation hubs — in effect, supercharging it. It’s a finding worth keeping in mind that next time your company is considering where to locate a new business unit or research facility.


Putting data to work with knowledge graphs: A brief story popped up in The Seattle Times last week: A data analytics company named Maana announced it had raised $26 million in Series B funding from the investment arms of Saudi Aramco and Shell. In these (waning) days of billion-dollar start-up valuations, $26 million isn’t especially jaw-dropping. But the company does have has an interesting approach to data analytics, which uses “enterprise knowledge graphs.”
There are a couple of problems with data in big companies. First, there’s lots of it, and it’s often stashed in separate silos. “A single division could have over 60 different information systems that they work with,” CTO Donald Thompson told tech reporter Rachel Lerman. Second, you need to turn the data into useful insights and recommendations. Third, you have get those into the hands of people who can use them to enhance results.


Bearing in mind that I’m a layman at best, here’s how Maana approach works: Instead of placing the company’s data into a common pool, it sends out a search engine to crawl the various data silos in your company. Then, instead of simply delivering a list of results, it uses analytics and machine learning to construct knowledge graphs — kind of like the ones that Google introduced a few years back — that provide actionable recommendations based on the goals and needs of the business and delivers them to line-of-business applications. Maana has used cases on its website that show how this approach works and the results it has produced in operational settings in industrial and oil and gas companies.





Reproduced from MIT Sloan Management Review



Managing Tensions Between New and Existing Business Models05-25


The search for new business models forces established companies to experiment with organizational designs — and leads to tensions that should be anticipated and carefully managed.






Image credit : Shyam's Imagination Library
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Exploring new business models is a recognized way for mature companies to renew their competitive advantage. Companies explore new value propositions, deploy value propositions in new segments, change the value chain, or experiment with alternative revenue models — all in a search for a different logic for value creation and capture. Sometimes this exploration goes far beyond the existing business model and requires the creation of a new business unit.

A sometimes unexpected consequence is the difficulty of fitting this new business unit into the existing organizational structure. While business model experimentation may be the raison d’être of many startup ventures, established companies typically face strong organizational rigidities that lead to tensions. Predicting these tensions and being open to experimentation with organizational structure can be the keys to a smoother business model exploration process. In this article, we report on a study of the European postal industry, in which we examined the organizational challenges that affect incumbent organizations in mature industries as they react to disruptive changes in their environment by seeking new business models.

Although the Romans had a type of postal service, the European postal industry as we know it today has existed for the past 500 years or so — one of the oldest, in Portugal, traces its history to 1520. For close to two centuries, established operators have been using essentially the same business model, pioneered in 1837 in the United Kingdom. In that model, senders pay a postal operator (usually through the purchase of a stamp) to bring a piece of mail or a parcel from A to B, with pricing dependent on some combination of distance, size, and weight. However, the postal industry has recently faced a rapid decline in physical mail as a result of digital substitution, while regulatory liberalization has boosted the level of competition in postal markets. Many postal operators have reacted by exploring new opportunities in the digital marketplace.

By interviewing managers and reviewing relevant information, we studied Danish, Portuguese, and Swiss postal operators to find out how they have dealt with the challenge of exploring new business models since the turn of the millennium. The organizations we studied strived to maintain their core business while at the same time incubating new ventures. Managers at all of the organizations felt there were potential new business models that they could benefit from developing, but when exploring the building blocks of these business models, they found that tensions emerged in their organizations. It required a separate process of organizational experimentation to find out how to organize for business model exploration.

Managing the Tensions

Our research points to three key areas of tension almost any existing business will face if it attempts to discover entirely new business models. Whether management succeeds in handling those tensions will determine their success in identifying and implementing new business models.

1. Don’t settle too quickly on structure. Top management is typically trained to see organizational structure as a means of executing strategy. As the business historian Alfred D. Chandler put it, “structure follows strategy.” In the case of business model exploration, however, our research suggests it’s a mistake for management to settle too quickly on a strategy and structure for the new business. In 2006, the Danish postal service, Post Danmark A/S, acquired Strålfors, an information logistics company, and subsequently positioned some of the company’s other innovative ventures within this subsidiary. It was thought there were possible synergies in merging products, but the fit was less than perfect, and as one manager put it, ultimately the business units “moved a bit around over the years.” The Danish and Swedish posts subsequently merged to form a new company, now called PostNord AB. PostNord at one point signaled to the market that Strålfors was for sale but then, in the fall of 2015, announced that it would retain ownership of Strålfors, after all. A manager from another postal operator offered a similar account of the struggle with how to fit a new venture into an old company, pointing out how that operator had to “constantly learn and modify … how we organize ourselves.”

The lesson for any organization wanting to explore new business models is to not settle too quickly on a structure for the new business. In fact, the organizational structure can more usefully be thought of as one of the essential building blocks of the business model — that is, as an aspect of the new business that needs to be fully explored and experimented with before you can learn what works best.
2. Balance top management support and experimentation. Exploring new business models is a strategic decision aimed at adapting the company’s activities to an evolving business landscape and discovering new revenue streams. At the postal operators we studied, this involved numerous initiatives. For example, the Swiss Post decided there might be an opportunity to expand its partnerships with online retail businesses beyond picking up and delivering parcels. The Swiss Post could leverage its established, trusted brand by selling secure sockets layer (SSL) certificates, digital signature solutions, and email certificates to online retailers and other businesses. However, setting up the new business unit involved the creation of new capabilities, both on the IT and the sales sides. It was recognized that this new business unit would be very different from the organization’s existing core business. The solution involved acquiring a startup that had developed some core solutions in this space and then building the business with a mix of management and staff hired from outside as well as transferred from the core business.

Management clearly identified a need to protect the fledgling business from above. The new business unit was a strategic initiative and as such needed to be shepherded by top management. As one manager told us, “We really managed to make sure that from the top … these organizations were protected. You need to have ownership by the CEO; otherwise, this is destroyed extremely quickly.” However, it was also gradually recognized that top management should not try to steer the new business unit. As one manager said, “It is clearly an advantage if people [in the new business unit] are a little bit remote of the headquarters. The headquarters has an existing way of doing business … you develop much more successfully if you give these people space and distance to the core.” This implies a balancing act for top management between protecting and coaching, on the one hand, and leaving the new business unit to experiment, on the other.

3. Expect a power struggle for resources. Any new business model has to grow and coexist with existing business models that may be stagnating but still provide the lion’s share of revenues for the company. Managers of such existing business models can be powerful and may have turf to protect in the internal struggle for resources. They and their employees may feel threatened if the new business unit becomes too successful. Furthermore, the new business model may not be profitable for a long time, leading to the risk that needed investments are diverted from more profitable parts of the business. One manager told us that this “has perhaps been the biggest barrier — that we are competing and working to get access to the same IT resources within the company.”

Top management needs to manage this potential competition for resources between the new business and the old core business. One way to achieve this is to accept multiple business logics, as well as multiple performance management and measurement systems. As one manager explained, “We quite successfully managed to convince the internal management that, for the moment, revenue streams shall not be the most important performance indicator.” Alternative metrics could include the estimated market potential, for example.

A point to consider is the importance of communicating across the company why it is engaging in business model exploration and how this will benefit the company in the long term. Conflicts for scarce resources within the organization cannot be avoided completely, but they can be softened if employees across business units build a shared understanding of the objectives of the business model exploration.

The Organizational Dimension

The business model canvas framework developed by Alexander Osterwalder and Yves Pigneur has become a very popular way to understand the potential building blocks of business models. The canvas highlights nine such building blocks: customer segments, value propositions, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. However, organizational designs and the associated organizational tensions that emerge during the process of business model exploration are not well addressed by the existing tools. Companies exploring new business models may not fully recognize that these tensions will almost inevitably emerge and thus may be ill-prepared to manage them.

Understanding these tensions should help in managing the challenges of concurrent business models.
The tensions we highlight imply that the design of an organizational structure that accommodates both new and older business models needs to be considered an intricate part of business model innovation. Organizational design has to be questioned and experimented with as part of the exploration. A top management team that is prepared for such exploration and aware of the organizational dimension of business model exploration may well be more likely to succeed at business model innovation.