The "events", so to speak, involved no less than a typical decorated delivery truck on one hand (The event where, apparently, his amazon.in CEO called out Jeff as his 'Baap' [try here]). And, on the other hand, there was him meeting with the Indian Prime Minister in Delhi and talking about things (in e-retail in the most promising e-global economy with the world's 3rd largest open internet userbase, of course).#1: What was the hardest moment of your life?
Jeff: My experience of raising the first million dollars to start Amazon.
Nothing over the following two decades of founding Amazon compared to that. I reached out to 80 odd investors and how they thought my idea of selling books over the internet was crazy.
#2: How do you hire people?
Jeff: I look at two things: one, does the person consider himself to be fortunate? And two, how good are they at making decisions without data... I'm biased and I prefer people who consider themselves as very fortunate [...] they will make or do things better because they are thankful to the way their lives are shaping up. The others will waste their lives looking over their shoulder and complain about how life is not satisfactory. “Those kind of people I don’t want on my team”. [...] While data is an extremely important element of decision making, you have to first listen to your gut, what feels right. Usually, the gut is right and you have to substantiate it with data. But you should not start the other way round, where you look at data first and then suppress your instinct and do what the data says. That will not necessarily make you do great things.
#3: Would you hire a philosopher and/or an entrepreneur?
[Jeff pauses for a bit], I would hire a philosopher and not an entrepreneur. [...] a philosopher will take my mind where nobody else has taken it. And then, he will find the entrepreneur to make that into a reality.
#4: What are the fundamental tenets of your business?
Jeff: There are three things -
1. Customers rule: That is an obsession at Amazon. At any meeting that we have, we have a chair for the customer. I say, ‘there’s a customer sitting here, and are we doing things right for the customer?’.
2. An incessant appetite for innovation: This has to be there in every walk of life, and it’s not an annual activity, but an everyday thing: we have to do things better.
3. Operational excellence: When you are running a successful corporation, the fundamental building block is phenomenal operational excellence. Everything will happen the way it is planned to happen and that we actually execute and deliver on the promise.
#5: What next?
Jeff: I’ve only just begun.
(For a perspective, today Amazon ranks #35 in Fortune500 list - compared to Google's #46, and Microsoft's #34).
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| Cheers to Life! |
The Pygmalion effect, or Rosenthal effect, is the phenomenon in which the greater the expectation placed upon people, the better they perform.
On the other hand is the Golem effect, in which low expectations lead to a decrease in performance.
We live in an age of unprecedented opportunity: If you've got ambition and smarts, you can rise to the top of your chosen profession, regardless of where you started out.
But with opportunity comes responsibility. Companies today aren't managing their employees' careers; knowledge workers must, effectively, be their own chief executive officers. It's up to you to carve out your place, to know when to change the course, and to keep yourself engaged and productive during a work life that may span some 50 years. To do those things well, you will need to cultivate a deep understanding of yourself - not only what your strengths and weaknesses are but also how you learn, how you work with others, what your values are, and where you can make the greatest contribution.
Because only when you operate from strengths can you achieve true excellence.Marking a small footnote today as this 10-slides synopsis (below) of Peter Drucker's "Managing Oneself" crosses a sort of a mini milestone on SlideShare with a thousand+ downloads from 26k+ views overall since its first publication.
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| (My junior) |
I see trees of green, red roses too
I see them bloom, for me and you
And I think to myself
What a wonderful world
I see skies of blue, and clouds of white
The bright blessed day, dark sacred night
And I think to myself
What a wonderful world
The colors of the rainbow, so pretty in the sky
Are also on the faces, of people going by
I see friends shaking hands, sayin', "How do you do?"
They're really sayin', "I love you"
I hear babies cryin', I watch them grow
They'll learn much more, than I'll ever know
And I think to myself
What a wonderful world
Yes, I think to myself
What a wonderful world
Oh yeah...
~ Louis Armstrong
[...] Economics is not typically thought of as a global systems problem. Indeed, investment banks are famous for a brand of tunnel vision that focuses risk management at the individual firm level and ignores the difficult and costlier, albeit less frequent, systemic or financial-web problem. Monitoring the ecosystem-like network of firms with interlocking balance sheets is not in the risk manager’s job description.
A parallel situation exists in fisheries, where stocks are traditionally managed one species at a time. Alarm over collapsing fish stocks, however, is helping to create the current push for ecosystem-based ocean management. This is a step in the right direction, but the current ecosystem simulation models remain incapable of reproducing realistic population crashes. And the same is true of most climate simulation models: Though the geological record tells us that global temperatures can change very quickly, the models consistently underestimate that possibility. This is related to the next property, the nonlinear, non-equilibrium nature of systems.
Most engineered devices, consisting of mechanical springs, transistors, and the like, are built to be stable. That is, if stressed from rest, or equilibrium, they spring back. Many simple ecological models, physiological models, and even climate and economic models are built by assuming the same principle: a globally stable equilibrium. A related simplification is to see the world as consisting of separate parts that can be studied in a linear way, one piece at a time. These pieces can then be summed independently to make the whole. Researchers have developed a very large tool kit of analytical methods and statistics based on this linear idea, and it has proven invaluable for studying simple engineered devices. But even when many of the complex systems that interest us are not linear, we persist with these tools and models. It is a case of looking under the lamppost because the light is better even though we know the lost keys are in the shadows. Linear systems produce nice stationary statistics—constant risk metrics, for example. Because they assume that a process does not vary through time, one can subsample it to get an idea of what the larger universe of possibilities looks like. This characteristic of linear systems appeals to our normal heuristic thinking.
Nonlinear systems, however, are not so well behaved. They can appear stationary for a long while, then without anything changing, they exhibit jumps in variability—so-called “heteroscedasticity.” For example, if one looks at the range of economic variables over the past decade (daily market movements, GDP changes, etc.), one might guess that variability and the universe of possibilities are very modest. This was the modus operandi of normal risk management. As a consequence, the likelihood of some of the large moves we saw in 2008, which happened over so many consecutive days, should have been less than once in the age of the universe.
Our problem is that the scientific desire to simplify has taken over, something that Einstein warned against when he paraphrased Occam: “Everything should be made as simple as possible, but not simpler.” Thinking of natural and economic systems as essentially stable and decomposable into parts is a good initial hypothesis, current observations and measurements do not support that hypothesis—hence our continual surprise. Just as we like the idea of constancy, we are stubborn to change. The 19th century American humorist Josh Billings, perhaps, put it best: “It ain’t what we don’t know that gives us trouble, it’s what we know that just ain’t so.”
Among these principles is the idea that there might be universal early warning signs for critical transitions, diagnostic signals that appear near unstable tipping points of rapid change. The recent argument for early warning signs is based on the following: 1) that both simple and more realistic, complex nonlinear models show these behaviors, and 2) that there is a growing weight of empirical evidence for these common precursors in varied systems.
A key phenomenon known for decades is so-called “critical slowing” as a threshold approaches. That is, a system’s dynamic response to external perturbations becomes more sluggish near tipping points. Mathematically, this property gives rise to increased inertia in the ups and downs of things like temperature or population numbers—we call this inertia “autocorrelation”—which in turn can result in larger swings, or more volatility. Another related early signaling behavior is an increase in “spatial resonance”: Pulses occurring in neighboring parts of the web become synchronized. Nearby brain cells fire in unison minutes to hours prior to an epileptic seizure, for example.
The global financial meltdown illustrates the phenomenon of critical slowing and spatial resonance. Leading up to the crash, there was a marked increase in homogeneity among institutions, both in their revenue-generating strategies as well as in their risk-management strategies, thus increasing correlation among funds and across countries—an early warning. Indeed, with regard to risk management through diversification, it is ironic that diversification became so extreme that diversification was lost: Everyone owning part of everything creates complete homogeneity. Reducing risk by increasing portfolio diversity makes sense for each individual institution, but if everyone does it, it creates huge group or system-wide risk. Mathematically, such homogeneity leads to increased connectivity in the financial system, and the number and strength of these linkages grow as homogeneity increases. Thus, the consequence of increasing connectivity is to destabilize a generic complex system: Each institution becomes more affected by the balance sheets of neighboring institutions than by its own. [...]
"From the observable data and experience we select some and affix meaning to it. This forms the basis of our assumptions. And then we come to conclusions which in turn influence our beliefs. Our beliefs are the basis of our actions which bring more data and experience from which we select some, affix meaning and so on. We tend to believe that we affix meaning to the observable data, oblivious of the selection we always make. In a similar way we believe that we draw conclusions by clear reasoning, while we actually always apply some assumptions."Beliefs and Capabilities:
"It suddenly struck me that that tiny pea, pretty and blue, was the Earth. I put up my thumb and shut one eye, and my thumb blotted out the planet Earth. I didn’t feel like a giant. I felt very, very small." — Neil Armstrong
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| [Source: wikimedia.org] |
“Act only according to that maxim whereby you can, at the same time, will that it should become a universal law.” - Immanuel Kant (Categorical Imperative. try here)In this rather short video clipped from the BBC documentary - "Justice: A Citizen's Guide to the 21st Century", Prof. Michael Sandle picks up an ethical dilema from a real-life kidnapping case that took place in Germany in 2002, and bounces it off to a Kantian activist and journalist, and to Peter Singer, the utilitarian Bioethics professor at Princeton University.
Theoretical Physicist Dr. Sheldon Cooper Sc.D. has hardly anything to do with this post except for an optimistic allusion toward his positive delight at throwing a monologos tantrum such as this in any of The Big Bang Theory episodes preferably not named as the same suggested title.
You see,Saturday [May 7th] is the 300th birthday of David Hume, the most important philosopher ever to write in English according to the Stanford Encyclopedia of Philosophy.
