Wicked

It's been a few years since my wife and I went to the theater.  When we lived in Cincinnati, we had season tickets to Broadway in Cincinnati.  Our original plan was to continue our once-a-month tradition and purchase season tickets to the theater in our new city.  Well, then COVID-19 happened and most of the shows were canceled.  I suppose that we've been procrastinating.  It's probably time to start going back to the theater, as one of our favorite shows is coming to town soon.  We've se the show "Wicked" a few times, even once in New York City.

I'm reminded (sorry, my brain just works that way) of something that Keith Grint has called a "wicked problem" (as opposed to a "tame problem").  I've posted about "wicked problems" at least once before. Simply stated, "wicked problems" are both complicated and complex and probably have never occurred before.  The solutions to "Wicked" problems aren't readily apparent, and they may be as complicated and complex as the problem itself.  

"Wicked problems" are particularly prone to what Dietrich Dörner (see my last two posts) calls "the logic of failure".  He recommends the following sequence of steps (an algorithm, if you will) for attacking complex problems.  I would suggest that this sequence could help solve wicked problems too.

Dörner suggests that the first step is to set clear, unambiguous goals.  I like using SMART goals - goals should be specific, measurable, actionable, realistic and relevant, and time-bound.  While Dörner doesn't necessarily state that we should use SMART goals, he does caution against focusing on general goals.  If we do not state our goals clearly, we tend to fall into the trap of what he calls a "repair shop" mentality - we try to fix whatever problems that we can find.  

It's important to delineate all the goals, including what Dörner calls "implicit goals" (goals that are just as important, but perhaps not clearly stated).  For example, "Stop insects from eating crops" is an explicit goal (but of course, not a very SMART one), but by accomplishing that goal, we don't want to destroy the local ecosystem (the implicit goal).  We usually do not take into account these implicit goals, and we may not even know they are a goal.  Dörner uses another example.  For someone who is already healthy, "maintaining health" would be an implicit goal - not clearly stated, but perhaps just as important and relevant.

The second step in Dörner's approach is to gather information and analyze data.  Again, while he does not clearly state it in these terms, he does recommend that we should avoid oversimplifying the problem (the High Reliability Organization principle of "Reluctance to Simplify").  Collecting too much data is just as problematic as not collecting enough.  I like what Jeff Bezos calls the "70% rule" - make a decision when you have about 70% of the information that you need.

Next, Dörner says that we should make predictions and extrapolate from the data that we collected in step 2.  In other words, make a plan and then act on it.  Dörner cautions against something that Carl von Clausewitz called "methodism" (more on this in a future post), that tendency we all have to restrict our actions to the ones that have worked well for us in the past.  Dörner writes, "To be successful, a planner must know when to follow established practice and when to strike out in a new direction."

Finally, after we've executed our plan, Dörner says we should review the results that we achieved and make any necessary changes to our plan.  Several of you may noticed that Dörner's approach is very similar to the PDSA cycle (Plan-Do-Study-Act) used in quality improvement today.  That makes a lot of sense to me - PDSA cycles are often used to tackle complex or wicked problems.

Since I started with the Broadway musical "Wicked", I will end with a quote from the character Elphaba ("The Wicked Witch of the West").  She said, "Some things I cannot change.  But 'til I try, I'll never know."  Complex or wicked problems are like that too.  It would be very easy to say that they are just to hard to tackle, but until we try, we will never know for sure.

Sim City

Do you remember the computer game "SimCity"? There were several different versions of the game, but essentially the object of the game was to build and design your own city.  The player, acting as the mayor of the city, starts off with a blank geographic map (in later versions of the game, you could even change the geography).  He or she can then designate certain areas as industrial, commercial, or residential, after which they can build away!  Players frequently have to contend with natural disasters, such as tornadoes, fires, earthquakes, and floods (there was even a giant monster that could attack the city).  They can build amusement parks or industrial parks, marinas or golf courses, and apartment complexes or residential neighborhoods.  It's a really fun game - see the screen shot below of a newly constructed city:

Don't worry - this post is not just about the SimCity computer game.  During my last post, I mentioned that I recently finished the book The Logic of Failure by Dietrich Dörner.  While the main focus of the book is on why we make mistakes, at times with catastrophic consequences, Dörner primarily uses the results from two groups of experiments to support his theoretical concepts.  I was reminded of SimCity while reading the book, as the two groups of experiments involved a simulation where subjects became the leaders of a fictional country (in the first group, the results of which were also published in the journal Philosophical Transactions of the Royal Society) or town (in the second group), similar to the SimCity game.  

The first group of simulations took place in the fictional country of Tanaland, Africa.  Leaders (i.e. the study participants) were tasked with promoting the health and well-being of Tanaland's inhabitants and the surrounding region.  For example, they could improve the fertilization of the fields and orchards, install irrigation systems, or build dams.  They could introduce measures focused on improving access to medical care or build infrastructure such as power plants or roads.  Leaders were given free reign to introduce as many measures as they wanted to at six "planning sessions" over the course of a simulated ten-year period.  In this way, they could evaluate the success or failure of each introduced measure at regular intervals and cancel or modify earlier decisions.  

Several metrics were followed over the course of the simulation, including crop yield, population, birth rate, etc.   The individual results of these simulations are illustrative.  For example, one leader introduced measures to improve medical care and the supply of food to the region.  Initially, both the birth rate and life expectancy increased.  However, once the population of Tanaland hit a certain threshold, there was no longer enough food to support the growing population, and a famine occurred.  As Dörner himself explained, "Catastrophe was inevitable because a linear increase in the food supply was accompanied by an exponential increase in the population."

Similarly, the second group of simulations took place in the fictional town of Greenvale, England.  Once again (and unrealistically, but that's the nature of the simulation), leaders (study participants) could exercise near dictatorial powers for ten years.  The town's single biggest employer was a municipally-owned watch factory.  Leaders could adjust local tax rates or change the hiring practices at the watch factory, introduce measures to improve medical care, or build more houses.  Again, just like the Tanaland simulation, leaders frequently succumbed to the law of unintended consequences.  

The key lesson from these simulations is that systems are prone to human failure when they are complex (see again my last post), dynamic (i.e. evolving over time), and intransparent.  The word "intransparency" means "lack of transparency" which in this context refers to the fact that in complex systems (in particular), information is often incomplete or hidden from view.  Economists often refer to something called "information asymmetry" where two individuals, groups, or teams have unequal access to information.  Collectively, these characteristics of complex systems are really what contributes to what Dörner called "the logic of failure", which he defined as the tendencies and patterns of thought that humans make (as a natural result of our evolution), such as taking one thing at a time, cause and effect, and linear thinking, that were probably appropriate in an older, simpler world but can prove disastrous in our complex world today.  For example, the study participant who increased access to medical care and improved the irrigation in Tanaland didn't anticipate the effects of both of these initiatives on what is now called the Malthusian Trap (named after the 18th century economist Thomas Malthus, who first described it).  The population in Tanaland grew exponentially, while the food supply continued to grow linearly.  

Fortunately, there are some tricks and tools of the trade that leaders can use to help them effectively make decisions, even when the situation is complex.  Dr. Dörner had some suggestions as well.  And we will talk about some of his recommendations, as well as some of the recommendations from other experts, in my next post.

It's complicated...

I just read one of the classic books in safety science, The Logic of Failure by Dietrich Dörner.  There is more than one edition out I think, and the one I read (thank you to my local library) was the 1986 English translation of the original book that was published in German.  The premise of the book is perhaps best summarized by a statement in the blurb (yes, that's apparently the proper term, though I have also seen the term "flap copy" used) from the dust jacket:

"Dietrich Dörner, winner of Germany's highest science prize, here considers why - given all our intelligence, experience, and information - we make mistakes, sometimes with catastrophic consequences.  Surprisingly, he finds the answer not in negligence or carelessness, but in what he calls "the logic of failure": certain tendencies in our patterns of thought - such as taking one thing at a time, cause and effect, and linear thinking - that, while appropriate to an older, simper world, prove disastrous for the complex world we live in now."

Unfortunately, I'm not fluent enough in German to read some of the original studies that Dr. Dörner referenced in his book.  Regardless, there were several interesting points made in the book that I would like to discuss in greater detail.  The first is how he defines and explains the concept of complexity.  There's been a lot written on the difference between complex and complicated.  One of the best explanations I've found is an article by Alexandre Di Miceli ("Complex or Complicated?").  He says, "A complicated system has a direct cause and effect relationship.  Its elements interact in a predictable way."  Complicated systems are controllable, often by following specific rules or algorithms.  Conversely, he says that complex systems are composed of elements that interact with each other in unpredictable ways.  It is these interactions that differentiate complex systems from merely complicated ones.  Di Miceli goes on to say:

"A car engine is complicated.  Traffic is complex."

"Building a skyscraper is complicated.  The functioning of cities is complex."

"Coding software is complicated.  Launching a software start-up is complex."

Dietrich Dörner would whole-heartedly agree with Di Miceli's explanation.  He writes, "Complexity is the label we give to the existence of many interdependent variables in a given system.  The more variables and the greater their interdependence, the greater that system's complexity."  He goes on to define something that he calls the "complexity quotient" as the product of the number of features within a system times the number of interrelationships that they have.  For example, if there are ten variables and five links between them, the complexity quotient is fifty (10 x 5 = 50).  As another example, if there are one hundred variables that are completely unrelated (no interrelationships or links between them), the system's complexity quotient is zero (100 x 0 = 0).

Dörner next makes a profound statement, at least in my opinion.  He says that "complexity is not an objective factor but a subjective one."  Imagine, as an example, the everyday activity of driving a car to and from work.  For someone my age, who has been driving for the past few decades (I won't say how many decades!), driving a car in busy traffic might be frustrating at times, but it's fairly straightforward.  However, put a new driver behind the wheel in the middle of Chicago rush hour traffic, and you may find a completely different perspective on how hard it is to drive in traffic.  The key here is something that Dörner calls "supersignals."  For the experienced driver, rush hour traffic is not made up of hundreds of different elements that myst be interpreted individually, but rather he or she is processing information in aggregate and by "gestalt."

Supersignals reduce complexity by collapsing a number of features together into one.  Think about how we look at someone's face.  We don't see all the contours, surfaces, and color variations.  Instead, we see just one face in aggregate.  Because of these supersignals, complexity must be understood subjectively from an individual's perspective.  We learn these "supersignals" by experience and training.  Dr. Gary Klein suggests that experts base their decisions by looking at the aggregate, recognizing a pattern that they've experienced before, and making a decision (he calls it recognition primed decisionmaking).

It seems like a simple concept, but I found it to be much more profound.  Interestingly, some of the other topics in The Logic of Failure reminded me of the computer game SimCity.  More on that in my next post.

"One home run is much better than two doubles."

The late Steve Jobs once said, "Quality is more important than quantity.  One home run is much better than two doubles."  I don't know if I completely agree, but more on that in a second.  Let's look at this strictly in baseball terms.  A home run occurs when a player hits the ball out of the ballpark (or alternatively, runs around all the bases on a hit that never makes it out of the park) and scores a run for his team.  A double occurs when a player hits the ball and makes it all the way to second base.  Notably, two doubles, particularly if they occur in the same inning, frequently score a run too.  So if the end result is the same, which is preferable?  A home run or two doubles?  Certainly the home run is more exciting, but most baseball purists wouldn't care either way, as long as the team scores a run (this approach is often called "manufacturing runs" by these same baseball purists).  To this end, I have always heard that the really good baseball players have just as many doubles as they do home runs.

All of this reminds me of a scene from the 2011 movie "Moneyball" starring Brad Pitt and Jonah Hill.  The movie is based on the non-fiction book by Michael Lewis, which tells the story of how the Oakland Athletics' general manager Billy Beane (played by Brad Pitt) built a winning baseball team, in spite of a low budget, by selecting under-valued (i.e. cheap) players using a statistical technique known as sabermetrics.  Beane is meeting with several of his baseball scouts, who are trying to select free agents using their traditional approach.  Specifically, the scouts are trying to replace three key players who signed with other teams during the off-season (Jason Giambi, Johnny Damon, and pitcher Jason Isringhausen).  Beane tells the scouts that they keep trying to replace Giambi with a comparable free agent player.  He tells the scouts, "Guys we can't do it.  Now what we might be able to do is recreate him in the aggregate."  He proceeds to tell the scouts (who are very skeptical of his new approach) that they can find three players who would be a lot less expensive whose combined on-base percentage would equal Giambi's.  Using Beane's new approach, the 2002 Oakland Athletics won the American League West Division with an overall record of 103-59, despite having one of the smallest payrolls in baseball that year ($42 million - notably, the New York Yankees had a payroll of $125 million that same season and also won their Division).  

Now, back to the quote by Steve Jobs.  Is quality better than quantity?  I would argue that the answer depends on the context.  In most cases, I would agree that quality is better than quantity, and at least in this specific example, Jobs was referring (I think) to the product release of the iPhone.  I suppose then, that if you are talking sales, leading the market with one "home run" kind of product like the iPhone is a lot better than having two good products that aren't necessarily leading the market.  But is that true in other contexts?

Let's go back to baseball.  If you were putting a team together, would you rather have a team of mediocre players and one superstar who hits a lot of home runs or a team of really good players who aren't necessarily flashy but get on base a lot and can "manufacture" a lot of runs?  I would choose the latter.  And I think the same is true for organizations in general.  Which would you have on your team (and I mean any team, not just in the sports context)?  Several above average performers or one superstar employee?  I talked a little about this in an earlier post, "I play not my eleven best, but my best eleven..."

When you are leading a group or putting together a team, resist the temptation to look at everyone's individual strengths and weaknesses.  Instead, try to look at the aggregate strength of the entire team.  Also look at the superstar employees.  Is that individual going to make us better or worse?  If you can answer that question honestly, it's an easy decision.

"Culture eats strategy"

If you have been paying any attention whatsoever to the management literature over the past 20 plus years, you will have heard the axiom, "Culture eats strategy for lunch" (or a different version, "Culture eats strategy for breakfast").  The phrase is often attributed to the management guru Peter Drucker, though in actual truth he probably never said it.  Regardless of who said it first, the point is that organizational culture is very important.  The important caveat is that strategy is important too, and that's what often gets lost when this axiom is loosely thrown around.  Organizations who ignore strategy do so at their own peril.

What is absolutely clear is that a bad culture will subsume a good strategy.  Whether or not one is more important than the other is probably irrelevant.  They are both necessary and critical aspects to the overall success of any group, team, or organization.

Mark Fields, the CEO of Ford Motor Company from 2014 to 2017 perhaps summarized it all best, when he said "You can have the best plan in the world, and if the culture isn't going to let it happen, it's going to die on the vine."  Adam Bryant, writing in Strategy + Business, suggests that it is often the "frozen middle" (a euphemism for middle managers who are reluctant to give up the status quo) who end up blocking or delaying strategic initiatives.  

The organizational culture, then, largely determines whether a new strategic initiative will be successful or end up failing.  If the culture is such that the organization is resistant to change or tied to strongly to the past, the initiative will undoubtedly fail.  However, if the culture is more entrepreneurial or innovative in nature, new initiatives will be embraced and ultimately successful.  Adam Bryant writes further, "Constructed properly, a healthy culture will reinforce the articulated values and the specific behaviors that leaders expect from all employees."

Christy Lake, Chief People Officer at Twilio, referred to culture as the operating system that keeps the organization on track to execute on strategy.  "It's like your phone's operating system - it works invisibly in the background to connect your apps and help you get things done.  You also expect it to be regularly updated with enhancements, performance improvements, and new features.  The same is true for compan culture.  The operating system needs to be updated to ensure that it's staying current with where the company is and where it is going."

Jacob Engel, writing for Forbes, offered three key points leaders need to bear in mind in order to make sure that the organizational culture is aligned with its strategy:

1. Culture is created by the behaviors you tolerate.  I've talked about this before in the past (see "What you permit, you promote...").  At that time, I was referring more to disruptive behaviors and incivility in the workplace, but the same is also true for a creating a culture that embraces change versus one that not just resists change, but fights it.  As I have also said before, "The need for change is not an indictment of the past".  Leaders that fight change in order to preserve the status quo are not leaders.  As Jim Collins recommends in his book Good to Great, "First Who, Then What", it's all about getting the right people on the bus.

2. Change starts at the top.  I would agree that change has to start at the top.  However, not everyone is a CEO in the organization.  The middle managers need to embrace change as well (see key point #1 above), so that they do not become part of the "frozen middle".  As Jacob Engel suggests, "You can't expect your people to change if you're not willing to change first."  Get on the bus or go home.

3. The leader needs to recognize that they are a "voice" around the table, not "the voice".  Again, Engels writes "Culture is one of those intangibles that is very hard to define but needs to be designed and implemented - and never by default."  Leaders need to listen honestly, even to those who provide a dissenting opinion.  Ultimately, the leaders have to make the right decision for the organization, but they need to make sure that people feel like they've had a chance to provide input (which is one important aspect of the High Reliability Organization principle of Deference to Expertise).  While I 100% agree, leaders in the organization also have to pay attention to the first two points above.  

Again, Jim Collins explains how leaders in "Good to Great" organizations focus on the "First Who, Then What" principle.  He writes, "Those who build great organizations make sure they have the right people on the bus and the right people in the key seats before they figure out where to drive the bus. They always think first about who and then about what. When facing chaos and uncertainty, and you cannot possibly predict what's coming around the corner, your best "strategy" is to have a busload of people who can adapt to and perform brilliantly no matter what comes next. Great vision without great people is irrelevant."

"Unknown unknowns"

When asked about the lack of evidence linking Iraq and so-called "weapons of mass destruction" during a press briefing on February 12, 2002, former U.S. Secretary of Defense Donald Rumsfeld famously said, "Reports that say something hasn't always happened are always interesting to me, because as we know, there are known knowns; there are things we know we know.  We also know there are known unknowns; that is to say we know there are things we do not know.  But there are also unknown unknowns - the ones we don't know we don't know.  And if one looks throughout the history of our country and other free countries, it is the latter category that tends to be the difficult ones."

While Rumsfeld certainly did not invent the concept (his quote actually reminds me of the famous Johari Window, created by the psychologists Joseph Luft and Harrington Ingham to help leaders better understand their blind spots - note that "Johari" is an amalgamation of their two names), it became his most famous line, which he used in the title of his memoir Known and Unknown.  The director Errol Morris used the quotation for the title of his documentary on Donald Rumsfeld, "Unknown Known".  Mikael Krogerus adapted this quotation and subsequently referred to something he called the "Rumsfeld Matrix" in The Decision Book:

While I was familiar with the quote and knew of the matrix, I was surprised to find a tangential reference to both in a publication while searching for something called a "fundamental surprise".  Here, rather than depicting the concept as a matrix, they used a Venn diagram and slightly changed the classification by completely eliminating the category of "unknown knowns" and including "fundamental surprises" as a special subset of "Unknown unknowns".  The investigators were studying the impact of "fundamental surprises" on errors made during the Fukushima Daiichi nuclear power plant accident in 2011.  

The term "fundamental surprise" was first used by Zvi Lanir at the Center for Strategic Studies in Tel Aviv, Israel in 1983 in reference to the Yom Kippur War.  Lanir defined “fundamental surprise” as a surprising (unexpected) event which reveals an often profound discrepancy between one's perception of the world and the reality.  In regards to the Fukushima Daiichi disaster, the operators at the nuclear power plant never envisioned the chain of events that would lead to a partial nuclear meltdown and radiation leak.  The region experienced a magnitude 9.0 earthquake, which caused a tsunami.  The tsunami caused a flood, and the flood damaged the emergency generators that were critical to the reactor's cooling systems.  The loss of power to the cooling systems led to the meltdown.  The plant's operators never envisioned this kind of event.  In fact, the plant's safety design was never designed to deal with this kind of crisis.  When they were faced with the crisis, they were paralyzed by the reality of the situation.

Interestingly enough, there was a second, perhaps less well known, nuclear power plant impacted by the 2011 earthquake in the Fukushima region of Japan.  Ranjay Gulati, Charles Casto, and Charlotte Krontiris published an excellent article in the Harvard Business Review that compares and contrasts the experience at the Fukushima Daiichi plant and its sister plant, the Fukushima Daini plant.  While the aftermath of the earthquake led to a partial nuclear meltdown at the Fukushima Daiichi plant, the Fukushima Daini plant was back under control within 2 days of the earthquake, and the reactors were safely shut down. 

Gulati, Casto, and Krontiris (and others) suggest that the key difference between the two plants was leadership.  As they write, "A crisis disrupts the familiar.  When past experience doesn't explain the current condition, we must revise our interpretation of events and our response to them."  While there is no question that the damage sustained at the Daiichi plant were more severe, the leaders at the Daini plant simply responded better by acting decisively, stepping back when necessary to make sense of the rapidly evolving situation, and responding to shifting realities.  "In the heat of the crisis, problem by problem, they acted their way toward sense, purpose, and resolution."

I am reminded of a similar situation where the differences in how leaders responded to two very similar crises significantly altered the outcome.  As told in the book Island of the Lost by Joan Druett and my blog post "A tale of two leaders", two ships wrecked off the coast of the Auckland Islands in 1864.  The crew of the Grafton fared much better than the crew of the Invercauld, and again, the key difference was leadership.  As Florence Williams writes in her New York Times book review of the book, "Their divergent experiences provide a riveting study of the extremes of human nature and the effects of good (and bad) leadership."

Leadership matters, particularly during a crisis.  The best leaders are not paralyzed by the "unknown unknowns" and the "fundamental surprises".  As the Canadian writer Robin Sharma said, "Anyone can lead when the plan is working.  The best lead when the plan falls apart."

"A preacher, prosecutor, and politician walked into a bar..."

I realized that I haven't written about Adam Grant in a while, so I think now might be a great time to revisit one of the concepts he discussed in his book, Think Again.  I came across an article that he wrote a few weeks ago for The Guardian ("You can't say that!: How to argue, better").  At the beginning of the article, he told a story of how he once had an argument with a close friend who had decided not to vaccinate his children.  At the time, Grant and his friend decided to "agree to disagree" and avoid discussing the topic in the future.  However, they eventually found themselves discussing the topic of COVID-19 vaccination.  As Grant recalls, "We duked it out in email threads so long that we ran out of new colors for our replies."  His friend admitted to him at the end of one of those threads that they had argued more in the past year than they had spoken in almost a decade, saying "I don't know about you, but I love it!"

Unfortunately, we live in a very polarized world.  I am currently reading the book Why We're Polarized by Ezra Klein, which I hope to discuss more about in the future.  One of the main issues with society today is that we've become so polarized that people who disagree can't even have a productive conversation.  Grant cites one study that shows that the average person would rather talk to a stranger who shares their views than a friend who doesn't.  Grant suggests that the reason we can't have a productive conversation on a topic on which we disagree is that too many of us think like preachers, prosecutors, and politicians (these labels come from an article by Philp Tetlock) when we are having a disagreement. 

When someone is in preacher mode, they're trying to proselytize their views on someone else.  When they are in a prosecutor mode, they are attacking someone else's viewpoint.  Finally, when they are in politician mode, they don't even listen to someone else unless they share the same view.  

Grant offers a number of suggestions to avoid falling into the "preacher, prosecutor, or politician" trap:

1. Learn to recognize your own lazy thinking.  When it comes to logic and reason, we are really lazy.  Don't believe me?  A group of investigators conducted a really clever and interesting set of experiments.  They asked people to produce a series of arguments in response to a couple of specific problems.  Next, the study participants were asked to evaluate someone else's argument.  Unbeknownst to the participants, in some of the experiments they were asked to evaluate their own argument (i.e. they weren't told that it was their own argument).  Surprisingly, when they thought the argument was made by someone else, 57% of them rejected it!  Grant writes, "Our reasoning is selectively lazy.  We hold our own opinions to lower standards than other people's.  When someone else doesn't buy the case you're making, it's worth remembering that you might not either."

2. Stay critical, even when you're emotional.  The more politically charged the issue, the harder it is to stay in control and focus on the facts relevant to the argument.  When we allow our emotions to take over, we lose the ability to think critically.  When we get emotional, we tend to be more prone to confirmation bias.  We will seize upon facts and ideas that confirm or support our own line of reasoning, all while ignoring or discounting those that challenge them.  Remember, a difference of opinion can be just fine.  It doesn't have to damage a new or established relationship.

3. Embrace the shades of grey.  We are also subject to something that cognitive psychologists call binary bias.  Simply stated, we take a complex argument and narrow the range of possibilities into just two categories.  Going back to Grant's story above, he told his friend that the COVID-19 vaccine was effective.  Well, how effective exactly?  The world is not always black and white - sometimes we have to focus on the grey in the middle.  

4. Build up to the really toxic topics.  Grant writes, "The highest compliment from someone who disagrees with you is not, 'You were right.'  It's 'You made me think.'"  We don't always have to reach consensus.  Sometimes the whole point of debate is to help promote critical thinking.

5. Keep agreeing to disagree.  Remember, there are no winners and losers when it comes to most arguments and debates.  "Great minds don't think alike - they challenge each other to think again."