Soap powder

August 22, 2016

By  via   Article

Sex and Soap Powder, Trial and Error

“There is a soap powder factory near Liverpool. … In that factory they mix a bunch of ingredients together: water softeners, enzymes, bleach, detergent, and water.  Then they pump the resulting slurry at high pressure and temperature through a spray nozzle.  When they do that the water evaporates and leaves a powder that looks a little like snow. Finally they take that powder and put it in a box and sell it for a chunk of change.

But the people who do this for a living had a problem. The nozzle kept blocking. The powder that came out was too big or too small, too dry or too wet. If you make soap powder the last thing you need is a nozzle full of lumpy, gunky, almost but not quite, soap powder. …

The solution to a problem like this is to find some experts.

The first set of experts were chemical engineers.  They had qualifications in heat exchange mechanisms and applied mathematics.  If fluid dynamics was top of your list, these were the men to have in the room. …

The second set of experts were evolutionary biologists.  For my sins I was once an evolutionary biologist.  People like me know all about sex, but only the theory, not the practice I’d hasten to add. …

The engineers … Investigated the problem, wrote equations and held meetings.  Then they designed and built a solution and implemented it.  It was a better nozzle.  I’d love to tell you how much better, but I can’t find a reference, so let’s go with not much better.  The problems prevailed.

The biologists … Took a different tack.  They weren’t experts in making soap powder, but they did know about evolution.

They took the nozzle and make 10 copies of it, but no copy was exactly the same. Some were fatter, some were thinner.  Some were taller or shorter.  Some had notches in them, others had grooves.  They were all slightly different. Then they pumped soap slurry through the different nozzles until they blocked and looked at the results. They measured the quality and volume and worked out which of the ten nozzles was the best.

They threw away the 9 failures, took the best nozzle and made ten copies of it…  Repeating the trial and error process for 45 generations. … After they had failed four hundred and forty nine times, the biologists stopped.  They had developed a nozzle that was (allegedly) hundreds of time better.

The lesson … Mistakes are inevitable.  We live in a complex world.  We can’t hope to understand everything.   So don’t worry about making mistakes.  Just make sure you have a way of capturing and learning from them.”

The 1 best question

August 22, 2016

By Jim Schleckser via   Article  

The 1 Best Question to Use in an Interview  

“If I was to hire you, how would I know if you were doing a good job?” This is a great question because it forces the candidate to put herself into the job and be thoughtful about how she might be measured by you, her boss. The answer you get will tell you a lot about the candidate’s maturity and comfort level with having her performance measured.

If you ask a C player this question, for instance, you might get some stammering followed by some noncritical metrics such as he will show up for work on time and not take extended lunch hours.

A players, on the other hand, will give you exactly what you’re looking for. Let’s say you are hiring a software engineer. When you ask an A player the magic question, he might respond by saying you will know whether he is doing a good job by using three metrics: the total volume of software code he produces on a weekly or monthly basis; the quality of the code based on a limited number of bugs; and his on-time delivery rate in which he hits the targets he said he would.

This would be a great answer because each of the metrics is measurable and quantifiable. You know if you had a group of engineers who were all willing to be measured on those metrics, you’d have a high-performing team.

Similarly, if you were hiring a salesperson, you might want to hear her answer the magic question by saying that you could tell she was doing a good job if she was exceeding her quota and selling profitable business, and her customer satisfaction rating was off the charts.

A key point here is that while you might know what you want to hear from a candidate, leave some wiggle room to be surprised and to learn something new about the position from an A player–someone who might think of a metric you’ve never considered.

The beauty of asking the magic question is also that, after the candidate gives you his answer, you pause for a second and say: ‘Let me write these down because, if I hire you, this is exactly how I will measure you after you start your new job.’

In other words, you can use the answer to the magic question as a great onboarding tool in which you have eliminated any chance that your new hire will be surprised about what is expected of him after he starts his new job.”

The Audi race team

August 22, 2016

By  via   Article

How Constraints Create Space for Innovation

“The Audi race team had the goal of winning the prestigious Le Mans race. Both their closest competitors, BMW and Mercedes, had won the race before which made the goal particularly worthy of pursuing.

The obvious way to win a race is by building a faster car. However, building a significantly faster car is non-trivial. The chief engineer at Audi instead posed a different question to his team: ‘How can we win Le Mans if our car cannot go faster than anyone else’s’? Audi won Le Mans that year. Can you guess how?

Constraints Create Space for Innovation

They won the race, not by building a faster car, but a more efficient car. The Le Mans is a grueling twenty four hours race. During that time, cars have to be refueled multiple times. By putting diesel technology into their race cars, Audi reduced the number of pitstops their car had to make which was the edge they needed to win.

Constraints Are Gifts

The word ‘constraint’ evokes a negative feeling in most people.

Constraint (noun): something that limits or restricts someone or something.

When people face a constraint, they either fall victim and revise their ambition downward, or confront the constraint head-on and look for ways to lift it.

From a systems perspective, however, constraints are neither good nor bad. Every system always has one and correctly identifying that single constraint holds the key to practicing ‘right action, right time’.”

Is a machine about to take your job?

August 22, 2016

By  and  via   Article

“Michael Chui and his colleagues at the McKinsey Global Institute … [look] at which occupations in the U.S. are most susceptible to automation, and which are least.

At the top of the list are physical activities performed ‘in a predictable setting’ – factories, fast food restaurants, etc. Also high are jobs that involve data processing or data collection – including some well-paying financial services jobs. The authors calculate that ‘one-third of the time spent in the workplace involves either collecting or processing data, and that both activities have a potential for automation exceeding 60%.’

Less susceptible to automation are jobs that involve physical activity but in ‘unpredictable environments’ – cutting trees, making beds, collecting trash – or jobs that require interaction with other people – retail sales, purchasing supplies, etc.

Which jobs are least susceptible to automation? Those that ‘involve managing or developing people,’ those where ‘expertise is applied to decision making and planning,’ and ‘creative work’ – which includes everything from writing software to creating menus to getting up at the crack of dawn to compose a newsletter. (Phew.)

The safest jobs are in education. ‘While digital technology is transforming the classroom,’ the authors say, ‘the essence of teaching is deep expertise and complex interactions with other people that machines so far are not good at.'”




White guy problem

August 15, 2016

By Kate Crawford via   Article

Artificial Intelligence’s White Guy Problem

“Accoring to some prominent voices in the tech world, artificial intelligence presents a looming existential threat to humanity: Warnings by luminaries like Elon Musk and Nick Bostrom about ‘the singularity’ — when machines become smarter than humans — have attracted millions of dollars and spawned a multitude of conferences.

But this hand-wringing is a distraction from the very real problems with artificial intelligence today, which may already be exacerbating inequality in the workplace, at home and in our legal and judicial systems. Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many ‘intelligent’ systems that shape how we are categorized and advertised to. …

We need to be vigilant about how we design and train these machine-learning systems, or we will see ingrained forms of bias built into the artificial intelligence of the future.

Like all technologies before it, artificial intelligence will reflect the values of its creators. So inclusivity matters — from who designs it to who sits on the company boards and which ethical perspectives are included. Otherwise, we risk constructing machine intelligence that mirrors a narrow and privileged vision of society, with its old, familiar biases and stereotypes.

If we look at how systems can be discriminatory now, we will be much better placed to design fairer artificial intelligence. But that requires far more accountability from the tech community. Governments and public institutions can do their part as well: As they invest in predictive technologies, they need to commit to fairness and due process.

While machine-learning technology can offer unexpected insights and new forms of convenience, we must address the current implications for communities that have less power, for those who aren’t dominant in elite Silicon Valley circles.

Currently the loudest voices debating the potential dangers of superintelligence are affluent white men, and, perhaps for them, the biggest threat is the rise of an artificially intelligent apex predator.”

But for those who already face marginalization or bias, the threats are here.”

The moral bucket list

August 15, 2016

By  via   Article

“… there were two sets of virtues, the résumé virtues and the eulogy virtues. The résumé virtues are the skills you bring to the marketplace. The eulogy virtues are the ones that are talked about at your funeral — whether you were kind, brave, honest or faithful. Were you capable of deep love?

We all know that the eulogy virtues are more important than the résumé ones. But our culture and our educational systems spend more time teaching the skills and strategies you need for career success than the qualities you need to radiate that sort of inner light. Many of us are clearer on how to build an external career than on how to build inner character.

But if you live for external achievement, years pass and the deepest parts of you go unexplored and unstructured. You lack a moral vocabulary. It is easy to slip into a self-satisfied moral mediocrity. You grade yourself on a forgiving curve. You figure as long as you are not obviously hurting anybody and people seem to like you, you must be O.K. But you live with an unconscious boredom, separated from the deepest meaning of life and the highest moral joys. Gradually, a humiliating gap opens between your actual self and your desired self, between you and those incandescent souls you sometimes meet.

So a few years ago I set out to discover how those deeply good people got that way. I didn’t know if I could follow their road to character (I’m a pundit, more or less paid to appear smarter and better than I really am). But I at least wanted to know what the road looked like.

I came to the conclusion that wonderful people are made, not born — that the people I admired had achieved an unfakeable inner virtue, built slowly from specific moral and spiritual accomplishments.

If we wanted to be gimmicky, we could say these accomplishments amounted to a moral bucket list, the experiences one should have on the way toward the richest possible inner life. Here, quickly, are some of them: …”

The idea of shareholder value

August 15, 2016

By Michael J. Mauboussin and Alfred Rappaport via   Article

Reclaiming the Idea of Shareholder Value

“Today there are two camps that aim to define the idea of governing objective, but neither is effective. The first believes the company’s goal is to maximize shareholder value. Countries that operate under common law, including the United States and the United Kingdom, lean in this direction.

The second advocates that the company balance the interests of all stakeholders. Countries that operate under civil law, including France, Germany, and Japan, tend to be in this camp.

The problem with the term ‘maximize shareholder value’ is that it has been hijacked by those who incorrectly believe that the goal is to maximize short-term earnings to boost today’s stock price. Properly understood, maximizing shareholder value means allocating resources so as to maximize long-term cash flow. Because an organization’s success depends on long-term relationships with each of its stakeholders, lengthening the investment time horizon benefits not only shareholders but customers, employees, suppliers, creditors, and communities as well.

Balancing stakeholder interests sounds like an entirely reasonable idea. But it cannot serve as a company’s singular governing objective because it is impossible to simultaneously satisfy the interests of all stakeholders. In the absence of a singular governing objective, executives are free to decide as they see fit and to balance those interests however they think is right. And without knowing how managers decide, it is almost impossible to hold them accountable for what they decide. …

… corporate boards must select a clear governing objective. That may mean choosing shareholder or stakeholder value, but that is not enough. Those that do embrace maximizing shareholder value as their governing objective also need to specify the time horizons they will use in their planning and decision-making processes.

Companies that choose to balance the interests of stakeholders as their governing objective must explain how they intend to manage the diverse and often conflicting interests of their stakeholders. In particular, they need to disclose the acceptable limits for tradeoffs they are willing to make at the expense of their shareholders.

Time horizon is a particularly important part of the governing objective’s definition. Some observers contend that focusing on an uncertain long term distracts the organization from what it needs to accomplish in the short term. But the short term and the long term are not adversaries in a zero-sum game. The overriding goal should be to focus continuously on what the organization needs to accomplish in the short and intermediate term in order to achieve its long-term goals. Peter Drucker, the great management thinker, had it right when he said, ‘keep [your] noses to the grindstone while lifting [your] eyes to the hills.'”



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