Challenging Assumptions Archive

This entry is part 3 of 3 in the series Practicing Safe Science

Irrationality of Science

The origin and development of the idea of modern science have many problem-solving lessons for us.

Understanding the birth and development of modern science helps us become better problem solvers. It was just an idea over 355 years ago. Today, it’s an industry.

Ideas that old often take on the status of immutable truths. Dissecting the idea of modern science discloses the arbitrary assumptions and processes that make up all ideas, not just science. Identifying these are critical to “thinking outside the box.”

According to “The Establishment of Science”(The Economist, January 9, 2010 edition), a dozen men birthed modern science in 1660. They called their group the Royal Society. Other scientific societies propagated but none challenged it. Their standards became science’s standards. Today, programs accredit those desiring to practice research in accordance with the scientific method.

Science’s subjective origins help us answer two questions. First, who or what creates experts? Science shows experts beget experts. Second, how were first experts conceived? Science shows they were conceived by virgin birth. No programs, processes or organizations seeded them. Only the divine declarations and pledges of a dozen men did.

Science also symbolizes the growth, development and maturation of ideas. Science shows that complex webs of programs and processes form to promote ideas as immutable truths. Declarations that science or experts proved something often deter us from gazing outside the box.

Emotionally, immutable truths satisfy our security needs. Thus, we are motivated to overlook that behind processes supporting ideas are people. These people are no less influenced by fame, money, respect and fun than the rest of us are, consciously or unconsciously. That’s why emotional intelligence is more important to success than intelligence quotient even with ideas. Relational politics matter. Science demonstrates that.

In short, science’s birth shows that at the root of virtually every concrete idea is arbitrariness. Science also shows that complex processes develop around the ideas we want to promote as immutable truths. Finally, science shows that despite the myth around such processes, humans still run them.

Science’s origins and development remind us that truths don’t create ideas but rather ideas create truths. Finding the subjective, variable nature inherent in ideas, opens tremendous problem-solving opportunities to create newer and better truths.

 

 

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Dice (Twelve & Two)  [0691]

Who forecasts the future better, the confident or the prudent?

Who’s better at forecasting, the confident or prudent? So far, the prudent seem to be winning confidently. More decisively, those most confident tend to be most wrong.

We have endured the wrong forecasts of pundits and experts without them experiencing any costs for their errors. Yet, Philip Tetlock ( University of Pennsylvania) highlighted this in 2005, when he released his 20-year study of 284 experts (professors, journalists, civil servants, etc.). According to “Intelligent Intelligence” (The Economist, July 19, 2014 edition) “their performance was abysmal.”

These results automatically created questions about intelligence agencies, causing David Mandel, of Defence Research and Development Canada, and Alan Barnes, a former intelligence analyst to publish, Accuracy of Forecasts in Strategic Intelligence. In this examination of intelligence analysts’ forecasts, they found significantly better forecasters than Tetlock did with pundits and experts.

When they dug deeper into analysts’ personalities, they found caution – even about their own abilities – pronounced especially among those classified as “superforecasters.” If they erred, it was on the side of uncertainty, meaning they were more likely to say, “I don’t know.”

More significantly, experienced analysts forecasted better than junior ones, meaning good forecasting is learnable as long as three protocols exist:

  1. Accountability for forecasts
  2. Skepticism by analysts’ managers
  3. Absence of self-serving biases

As James Surowiecki writes in “Punditonomics” (The New Yorker, April 7, 2014 edition), pundits and experts don’t forecast within these protocols. Their confidence is rewarded and errors unpunished. People can suffer from erroneous intelligence forecasts.

Businesses aren’t immune. Confidence and glowing forecasts easily seduce us. Style often trumps content and competence. Skepticism is difficult when hearing what we want to hear, and more so when seeing it as dissent or pessimism. That doesn’t even address interpreting prudence as underconfidence.

All of which I’m prudently confident will change . . . some day.

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Sand and Water in GlassIf you don’t like the rules, change them. The article, “Boundary Problems” [The Economist, August 3, 2013 edition], reports that the United States “has changed the way it measures GDP.” More importantly, the article summarizes the history and depth of this statistic’s arbitrary nature. The questions it poses serve as a problem-solving primer on attacking any business statistics to uncover hidden problems and solutions.

When we write down a problem to solve, attacking definitions is a great idea. Attacking the origins of statistics is essentially the same thing when we attack the assumptions defining them such as what, how, when and where to count. Their arbitrary birth comes from the fact that someone has to make these assumptions. Once we shake the foundations of these assumptions, we take on a different perspective, thus creating problem-solving opportunities.

This happens because just as no set of sporting statistics can capture the reality of a sporting event, no set of business statistics can do the same for a business. Statistics perform their quantifying job by ignoring parts of reality. Within these statistical voids defining our problem are solutions. If you fill a 12-ounce glass with fine, playground sand, even though it looks full, you can add about 4-5 ounces of water. This serves as a metaphor for the illusionary fullness statistics often present us and for the hidden solutions in their gaps.

To uncover these gaps, we ask others and ourselves questions such as, why are we counting:

  • This?
  • In this way?
  • At that time?
  • At that place?

Then, we ask, What tangibles and intangibles are missing?

Since numbers naturally attract us, we tend to focus here. So, let’s ask, What’s the most vital immeasurable of our businesses? We just found a statistical gap filled with solutions.

 

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Definitions = Castle

Stories form boxes outside of which we try to think.

Stories galvanize people, helping them to learn, to coalesce around ideas. If we look at this galvanization as solidification, we can also see how stories could thwart change and innovation.

In a book review titled “Dead Certain” [The New Yorker, November 29, 2010 edition], I came across this passage by George Packer quoting Dan McAdams, a psychology professor at Northwestern University:

Psychological research shows that powerful narratives in people’s lives make it nearly impossible, in many cases, to consider ideas, opinions, possibilities, and facts that run counter to the story

Now, let’s expand this thought. Stories have many aspects and many forms: allegories, rationales, themes, descriptions, characterizations, histories, records, chronicles, accounts, testimonies, anecdotes, biographies, depictions, portraits, assumptions and statements. All can create vivid pictures of events, ideas, plans and strategies.

These pictures define facts, accepted truths, and work the same as definitions. Stories become the box outside of which we are trying to think. They come to define the culture, traditions, practices and expectations of our businesses.

For instance, a business whose history, pride and success come from a particular market will find difficulty deemphasizing it as it diminishes. It will also find it hard to seize opportunities that it has traditionally scoffed.

Business plans are other examples of stories’ influence. Plans are not only stories themselves, but they contain smaller stories such as rationales, accounts, descriptions and assumptions. For instance, the main assumption driving plans and strategies is that last year is a great baseline for projecting this year, that this year won’t be vastly different from last year.

Therefore, when we seek to change, to innovate, we will likely need to question the validity of existing stories no matter how factual and truthful they seem. They are likely prisons inhibiting us from considering what is outside their walls.

 

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Hell Image Text [IMG-0124]Businesses strive for predictability. Standardization helps them achieve that. Still, many employees like their jobs for their variability, “It’s something different every day.” Herein is a paradox.

On one hand, we have predictability containing expenses by minimizing surprises. On the other hand, work’s variability gives us pleasure. Could predictability make us wealthy but miserable too? Walter Kirn touches on this paradox in his article “Knowledge of the Future Is Messing With the Present” (The Atlantic, July/August edition) by asking:

Has making life more explicable actually made it any more pleasurable?

Perhaps by understanding predictability better, we could appreciate change better and strip its fearsomeness. The The Twilight Zone episode, “A Nice Place to Visit,” can help.

The main character, Rocky, is a petty thief who dies. A divine guide finds him to deliver the news and show him to his new “home.” At first, Rocky can’t believe his luck for in this place he gets whatever he wants. In poker, all the cards go his way. With women, none deny him. Despite his long list of sins, Rocky figures God granted him heaven.

However, after a while, he becomes bored with the predictability of succeeding at whatever he attempts, poker, slots, women, robberies, billiards etc. Finally, he approaches his divine host and says, “If I gotta stay here another day, I’m gonna go nuts! Look, look, I don’t belong in Heaven, see? I want to go to the other place.”

The divinity rebuts, “Heaven? Whatever gave you the idea that you were in heaven, Mr. Valentine? This IS the other place!”

By imagining extremes, we alter our perspectives, permitting a more realistic assessment of our conditions. Not only do these perspectives influence our emotions (i.e. reducing fear of change) but also they improve our problem-solving skills.

 

 

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Often we assume fast service is good service; however, we need to challenge constantly this assumption. As I wrote previously, customer service borders on entertainment. To help people feel this, I use my Red Ferrari Analogy. I introduce it by asking, “When you go home from work, which way do you take?” Eventually, people agree: the quickest.

From here, I continue with the following:

All right then, let’s say that instead of going home in your present car at the end of today I give you the keys to a red Ferrari to drive home. How would you like that?

People agree that they would like this very much; however, I then present a caveat:

Great, however, there is only one condition: once you reach home, you give the keys and the car back to me. Now, let me ask you this: Knowing this would you still take the quickest way home?

At this point, people are usually laughing but say, “No.” I’ve even had a few who said, “I would never go home.” Nevertheless, I finish with this point:

So, the question is this: Are you providing people with a quick experience or a Ferrari experience?

 

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This entry is part 2 of 15 in the series Creative Innovation

We often forget that innovation is born from people. Thus, since children are often like their parents and most innovations cause disruptions, innovation is likely to be born of disruptive people. Even though research supports the role of dissenters in improving businesses, integrating disruptors with other talent requires a higher quality manager.

For example, consider what Steve Wozniak, the co-founder of Apple, told David Kushner for his article, “Machine Politics,” (The New Yorker, May 7, 2012 edition) about the notorious hacker, George Holtz, arguably the best of our time:

I understand the mind-set of a person who wants to [hack], and I don’t think of people like that as criminals. In fact, I think that misbehavior is very strongly correlated with and responsible for creative thought.

Buttressing the analogy we have the popular idea of disruptive innovation (aka disruptive technologies) originally asserted by Clayton Christensen of Harvard University (see Larissa MacFarquhar’s article “When Giants Fail” [The New Yorker, May 14, 2012 edition]). Yet, I’m sure disruptive innovation is far more popular in business than disruptive personalities are.

In business we tend to favor those who view their glass half-full rather than half-empty even though the latter is more likely to go and get more water. Consider that it often takes crises to trigger change: Who’s more likely to see a crisis – the “half-full” or “half-empty” person? Also, we often grow weary of the person who bucks rules and questions conventions; yet, attacking such things is important in innovation.

Of course, it’s important to distinguish disruptive from destructive. The line isn’t always clear, and only reinforces the need for better management. This could likely be a more sensitive manager, a manager adaptive to a broader array of personalities and aware that disruptive employees might be the most creative.

 

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When I was on the debate and student congress team in high school, practice would often entail arguing an opposing view. Often I would find arguments I had not considered and holes in my own that I hadn’t discovered. The main “AhHa!” point was just how much I missed by being comfortable in my own perspective.

Clay Johnson in a PBS NewsHour interview about his book, Information Diet, rhetorically asks, “Who wants to hear the truth when they can hear that they are right?” This applies to experts too. For instance, Daniel Klein wrote “I Was Wrong, and So Are You” in the December 2011 edition of The Atlantic about problems he incurred in his polling by altering the questions’ perspectives: it turned his original conclusions on their head.

Of course, this question assumes there is a best way, which isn’t necessary true, or at minimum, isn’t easily discerned. Still, even though Johnson and Klein speak and write with more of a political focus, their points apply to business: people tend to prefer information that reinforces their views over that which erodes it.

This can translate into an array of poor business decisions such as choosing a lesser option that we know fits our:

  • Skills over a better one that will require learning new ones
  • Managerial style over a better one that doesn’t
  • Expertise over a better one that has us relying upon others’ expertise

By arguing an opposing view, we vest in it, providing us with the motivation to dig where we had not. It might not change our minds, but we will discover problems, giving us a preemptive advantage; and, a different perspective that might allow us to find solutions to them where we could not see previously.

 

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How we position things greatly influences the outcome. In the April 7, 2012 edition of The Economist the article, “Dressing Up,” uncovers that women’s sizes have inflated by four sizes since the 1970’s. Unlike men’s sizing which is based on inches, women’s sizing is purely arbitrary and often varies by brand. Thus, depending on the size, a pair of women’s pants might have increased as much as four inches at the waist and three inches at the hips since then.

The generally accepted assumption for allowing this size inflation is that if consumers feel good about themselves they are likely to buy, thus why the fashion industry calls it “vanity sizing.” However, even though it seems like a topic to take lightly or with which to have fun, vanity sizing plays in all aspects of statistics. That is why it’s important to challenge definitions and assumptions in order to understand and solve problems.

For instance, the article “Botox and Beancounting” of the The Economist’s April 27, 2011 edition, discusses how official U.S. economic statistics might be overinflating its performance relative to Western European economies. Ironically, the article’s title makes an appropriate analogy to vanity sizing.

U.S. unemployment figures present another excellent example. They not only conflict with one another on occasions but they are difficult to figure. Additionally, their accounting changed in the 1980’s, making them appear lower than before.

Thus, while it’s commonly said that “numbers don’t lie,” that’s true; however, an ignoramus isn’t lying either if he believes his own ignorance. If we’re ignorant to numbers’ origination, we are more likely to accept them if they tell us our glass is half full rather than half empty, thus reinforcing our own perceptions . . . also known as “vanity believing.”

 

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House of Arbitrariness & Conditionality

 

We often view measurements as unchangeable. A meter is a meter, a pound a pound. We often forget that at some time someone somewhere declared what those were and that they would be a standard. The point is this: arbitrariness underlies almost all objective standards by which we live.

For example, in the January 29, 2011 edition of The Economist, the article, “The Constant Gardeners”, explores the kilogram. The official standard is a platinum-iridium alloy cast in 1879. However, today, its weight seems to vary from its copies by up to 69 micrograms, about half a grain of sand, an important variance when weighing small things. So, the question is this: How heavy is a kilogram . . . really?

The relevancy to problem solving is similar to that which I wrote in my post, “Arbitrariness: The Cornerstone of Conditions”:

By searching for the underlying arbitrary aspect of any apparently objective situation, we can often find the perspective – when altered – that can cause us to see that situation in a different light.

For example, when someone asks us, “What’s the best way to get from A to B?” we often give the fastest route. The assumption being that the “best way” is “fastest” when “best” could have many different attributes. Over time, the best-fastest link becomes the arbitrary point – when altered – that sheds a different light on what route might be best such as the most scenic one or the most fuel-efficient.

As a more sophisticated example, consider our reliance upon “proven outcomes.” What does that mean especially when you cannot scientifically prove that good leadership begets good results? Thus, when we look at what it took to be proven, we often find that it’s subjective based upon who is determining what “good leadership” and “good results” are.

 

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