In Part One we looked at the three most prevalent fatal thinking flaws, and I used a few different thought challenges as the backdrop. They were hard, but we are going to kick it up a notch in Part Two, where we look at the next two thinking flaws—Satisficing and Downgrading—in the context of thinking challenges in which elegant solutions are not as easily achieved, because the challenges themselves are more vexing.
For example, take a look at a more difficult insight problem involving an incorrect Roman numeral equation, like the one I showed you in Chapter 2 (Fixation). In this one, you cannot move or alter in any way either the plus sign or the equals sign. The challenge: Imagine that the numbers are moveable sticks. Leaving the plus and equals signs as they are, what is the least number of sticks you would have to move to correct the equation?*
XI + I = X
If you answered “one,” welcome to Satisficing. I bet you saw a solution right away, in less than a second. Almost everyone does. You probably saw immediately that X + I = XI or IX + I = X are good solutions, right? They are indeed good solutions, but only good enough, because there is a better answer to the original question, which asked about “the least number of sticks” to move. I’m sure you’ll agree that an answer of “zero” is the optimal answer, and certainly better than “one.” So by employing the Inversion fix, you can recast the problem as “how do I correct the equation without moving any sticks?”
There are three ways. You could simply look at the problem upside down—flipping this book is the easiest way. Or you could get creative and read it literally right to left, so that X (ten) = I (one) plus IX (nine). Or you might recognize the visual symmetry, and reflect it in a mirror. All three ways are different ways to achieve the elegant solution, and involve moving beyond the first obvious solution that looks good enough, which is, by the way, the definition of the fourth fatal flaw, Satisficing.
Satisficing is a real word, part satisfying and part sufficing, coined by the late economics Nobel laureate Herbert Simon his 1956 book Models of Man. He used it to describe our natural inclination to settle for “good enough” when faced with a decision. In general, we go with the first option that offers an acceptable payoff, choose the one that appears to get us “in the ballpark” quickest, but then stop looking for other ways, including the best way, to solve the problem. We rationalize that the optimal solution is too difficult, not worth the effort involved, or simply unnecessary. Simon called this “bounded rationality.”
Forty years after Simon introduced satisficing, MIT lecturer Peter Senge in his book The Fifth Discipline wrote, “Business and human endeavors are systems . . . we tend to focus on snapshots of isolated parts of the system. And wonder why our deepest problems never get solved.” Senge had it right. Remember the second line of our mantra: What appears to be the solution, isn’t.
Now, there is a time and place for satisficing, and like many things in life, the secret lies in balance and timing. Satisficing is wonderfully efficient and magically stress-reducing when operating under the appropriate context. In the vast majority of routine, everyday decisions, we’d be wise to satisfice. That’s when “good enough” is, well, just that. But when you’re trying to solve a difficult problem in which a suboptimal solution could put you at risk is not one of those times.
One of the most common “at risk” contexts is when we are working as part of a larger group—a team, an organization, even a family—for that is where the impact of individual Satisficing can wreak havoc on the interests of other group members. When I begin working with organizations, I often have the teams I’m working with play a game that I call “Win As Much As You Can.” It is a simple problem to solve: all you have to do is to decide, as a team, whether you should choose an X or a Y.
Take a look at the rules and scoring:
I’ve been using this game for nearly 25 years and have played it with hundreds of teams during that time. The results are almost always the same. What happens through the first five rounds is that each team tries to outguess the others, so while the specific mix of X’s and Y’s varies with each round, no team chooses the optimizing decision: every team chooses Y. I’ve rarely had a group in which all four teams chose Y during the first half of the game. Smaller teams do not view themselves as part of the larger group, aka The Everyday Organization, and thus do not try to achieve a larger group win. The teams do not communicate with one another, even though I have not expressly prohibited it.
After the fifth round, I have each team select a representative, then have the representatives confer with each other for one minute. The hope here is that by doing this, they will figure out how to make decisions that enable every team to win. I’m hoping that the simple logic of the game is revealed during the short conversation, namely that it is a zero-sum game. Meaning, unless every team chooses Y, someone loses. This is de facto suboptimization, and quite possibly the epitome of shortsightedness.
What happens next is nothing short of mind-blowing: I never get 4 Y’s. In fact, 80 percent of the time an act of outright sabotage occurs, and I field 3 Y’s and 1 X. 80 percent of the time! Then, in the next two rounds, with trust destroyed, teams revert to their original behavior, but the recognition that the higher aspiration is desired is omnipresent. In the eighth round, I have each team select a new representative to confer with the others. With a rare exception or two, rounds nine and ten see all teams choosing Y, thankfully.
But I had to bang them on the head a bit. The Satisficing flaw looms large!
As I watch people grappling with various thought challenges engage in Satisficing behavior, I see them ignore the very constraints that can paradoxically open up new and different ways of looking at things. I watch them mistakenly pose the question “What should we do?” before asking “What is possible?” They want a solution, but they don’t have the patience to pursue the optimal one, favoring implementation over incubation. They would much prefer to throw some resources at the problem and move on, or tweak a previous solution and fit it to the current situation. They fail to look more holistically at the challenge, to search, scan, and see the bigger picture. The result is that elegant solutions completely elude them.
The causes of Satisficing aren’t clear, don’t enjoy consensus, and run to the complex. Herbert Simon’s findings are a start, because they were contrary to what classic economics held at the time, which was that people seek to maximize utility, meaning to get the very best they can from every decision. The problem was that basic economics assumed that people are mostly rational, and armed with complete information regarding their choices. Simon, a behavioral economist, revealed the limitations of maximizing.
“Whereas economic man maximises, selects the best alternative from among all those available to him,” he wrote, “his cousin, administrative man, satisfices, looks for a course of action that is satisfactory or ‘good enough’.” He reasoned that getting all of the information necessary to make the best possible decision was simply too hard. Google wasn’t around back then. That didn’t deter him, though, because he went on to theorize that the human mind has cognitive limits, such that even if people could find all the relevant information easily, they would not be able to process it mentally in any helpful way that informed their pursuits. As he put it, somewhat harshly, “Because he treats the world as rather empty and ignores the interrelatedness of all things (so stupefying to thought and action), administrative man can make decisions with relatively simple rules of thumb that do not make impossible demands upon his capacity for thought.”
All of which is to say that lacking a solid algorithm for making decisions, our only choice is to use the most efficient means we have, which are rules of thumb, the fancy name for which is heuristics.
But we now live in a Google world, and information is massively abundant, so much so that too much information can exhaust our attention and loop us into an Overthinking mode, where too many choices not only stall our progress, but can actually make us unhappy. Swarthmore College professor and psychologist Barry Schwartz, author of The Paradox of Choice: Why Less Is More, in a follow-up study to his famous research16 on people facing 24 varieties of jam, followed over 500 job-seeking college seniors at several different colleges for the eight months leading up to their graduation. The results were confirming: the maximizers landed better jobs, with starting salaries on average 20 percent higher than those of the satisficers, but they felt worse about their jobs. And a recent study17 underscored the finding, by showing that not only were satisficers more satisfied after making an irreversible decision, but given the choice of irreversibility or reversibility in a future decision, they would prefer it to be irreversible, presumably to avoid needless worry or second-guessing. Maximizers, as you can imagine, were more satisfied after making a reversible decision, and would prefer reversibility if they had the option in a future decision, presumably to avoid what we now call FOMO: Fear of Missing Out.
At this point, you may see the similarities between Leaping and Satisficing when it comes to the deeper thinking required to address tougher challenges: both call up the wrong thinking at the wrong time. In other words, Satisficing is a perfectly sound strategy for picking jams and even jobs, but when faced with higher-order decisions or seeking farther-reaching solutions in which the potential impact can result in significant downstream effects that prevent us from achieving the kind of success we seek, we need to give the pursuit of an optimal solution more consideration. We need to wear the hat of the maximizer if we want to win.
First century philosopher Epictetus gives us a clue to the fix for Satisficing (in those situations in which we would be better off maximizing) saying: “In every affair consider what precedes and follows, and then undertake it. Otherwise you will begin with spirit; but not having thought of the consequences, when some of them appear you will shamefully desist.”
Meaning, action isn’t bad, as long as you’ve given careful thought to what it is you really want.
Herbert Simon also introduced the world to the concept of design thinking in his 1969 book The Sciences of the Artificial, making a strong case for the importance of designers to pursue alternative solutions, writing: “. . . problem-solving systems and design procedures in the real world do not merely assemble problem solutions from components but must search for appropriate assemblies. In carrying out such a search, it is often efficient to divide one’s eggs among a number of baskets—that is, not to follow out one line until it succeeds completely or fails definitely but to begin to explore several tentative paths, continuing to pursue a few that look most promising at a given moment. If one of the active paths begins to look less promising, it may be replaced by another that had previously been assigned a lower priority.”18
Simon is talking about the fix for Satisficing in the context of problem-solving: Synthesis. An easy way to think about Synthesis is “both-and” thinking, versus the kind of thinking both Simon and Barry Schwartz were studying, which was “either-or.” Synthesis lies at the core of Roger Martin’s integrative thinking, which is the basis for both his 2009 book The Opposable Mind as well as the foundation for University of Toronto’s graduate business program at the progressive Rotman School of Management, which is focused on developing successful leaders who “rather than accepting the unattractive trade-offs the world presents them, see it as their job to overcome the trade-off and build a new and better model that resolves it and creates new value for world.”19
Consider the challenge facing Piers Handling, who in 1994 became director of the Toronto International Film Festival.20 Before coming under Handling’s management, the festival did not enjoy the level of prestige it does today, and certainly nowhere near that of the famous Cannes Film Festival. At the time, it was called Festival of Festivals, open to the public, and focused on Toronto’s local film industry and movie-lovers. This approach lacked the status and appeal that invitation-only Cannes had to the broader industry, including film producers and celebrities, who were attracted to the exclusivity absent in the Toronto model. As Handling saw it, switching to the Cannes approach would entail an unacceptable trade-off: alienating the robust Toronto industry and audience. He saw that the tension between inclusivity and exclusivity could not be easily resolved with a simple mashing together of the two opposing models.
Handling looked to synthesize a solution that appealed to every interested party. He thought about what mattered most to the various players: celebrities seeking publicity for their movies, moviegoers rubbing elbows with movie stars, news media seeking stories; production studios seeking box office success; event marketers wanting broad audience exposure. What Toronto had going for it was the massive movie audience, which was a good proxy for the larger North American market.
He examined the ingredients of the Cannes formula and found that the real draw for industry insiders was the enormous media buzz around the prestigious grand prize—the Palme d’Or. He realized that winning the award, though, was not an indicator of eventual box office success. Box office success is a matter of audience preference, not industry preference. That was Handling’s Aha! moment.
Enter the People’s Choice Award, which at the time was a small award buried in the Toronto Film Festival agenda. The People’s Choice is decided not by a select jury like the Palme d’Or, but by moviegoers . . . the people who spend money and actually determine a film’s financial success. Handling recast the People’s Choice Award as the highlight of the festival. It was a brilliant synthesis, blending the best of what Cannes had to offer in terms of industry appeal and buzz with Toronto’s best feature: its audience.
Today, the Toronto International Film Festival is one of the most prestigious events of its kind in the world, and, according to Variety, “second only to Cannes in terms of high-profile pics, stars and market activity.”21
Roger Martin and Jennifer Riel suggest that “by following the example of integrative thinkers like Piers Handling,” we can learn to take a more sophisticated and rigorous approach to thinking, and offer two Synthesis techniques.22
This is what Piers Handling did in rethinking the Toronto International Film Festival. You have two solutions, one of which has many benefits with one huge drawback and the other of which has one huge benefit but many drawbacks. Taking a cue from Blackjack players who double down on a hot hand may be a way to synthesize a third option. Martin and Riel state that, “The trick is to find the conditions under which the first model can produce the benefits of the second.” They give the example of Walmart, facing a huge drawback in the form of a massive erosion of their global reputation if they did not change both their stance on environmental sustainability as well as carbon footprint. Doing so would be expensive, which for a low-cost provider strategy is a big drawback, but would do wonders for the company’s reputation. Walmart effectively doubled down by extending their general strategy of placing pressure on suppliers to reduce costs. In this case they placed pressure on their suppliers to adopt more environmentally friendly strategies, refusing to purchase goods from suppliers who did not meet certain standards for water, waste, and carbon. As Martin and Riel write, “In short, Walmart extended its business-as-usual model in order to produce a reputation for environmental leadership. The essential question to ask in this scenario: Under what conditions could model A actually generate the benefits of model B?”
When you have two equally attractive solutions that you wish you could fully implement simultaneously but can’t because they are in direct conflict and require significant trade-offs, break the larger context down into component parts, so that you can apply each solution in whole to those components. For example, when Target was in its early years, its senior executives realized they faced a dilemma: it had to contend on one hand with Walmart, far and away the low-cost retail leader. Seeing Kmart relegated to also-ran status, Target knew it couldn’t win the game of everyday items offered at rock-bottom prices. On the other hand, it faced successful, highly differentiated department store retailers, such as Nordstrom and Macy’s, strong brands that would be nearly impossible to steal significant share from, much less unseat. In order to compete effectively, Target adopted a strategy of decomposition. It decided that groceries and everyday commodities—a box of Tide, a package of Bounty—would be sold at prices equivalent to Walmart’s. However, when it came to apparel and other higher-margin items, Target chose to partner with well-known designers and celebrity homemakers looking for broader audiences. These offers had no direct substitutes at either Walmart or higher end retailers, and Target was able to create the illusion of being a discounter in one part of the store, and a unique retailer in another. It broke the problem down and essentially created two stores under one roof, becoming a discounter-plus-retailer, convincing people that they could get fashionable things along with the halo of everyday low prices from the store within a store. It worked. Target grew exponentially, carving out a unique playing field on which it could win.*
As with all Synthesizing, the goal of decomposition is to avoid satisficing compromises and “either-or” trade-offs in order to create more value through “both-and” thinking. As Martin and Riel write, “Rather than choosing Option A or Option B to apply to the entire situation, or at all times, the integrative thinker applies the different models together by carefully distinguishing when and how each model can be applied to which elements of the problem space. Each model is then applied selectively. The essential question to ask in this scenario: Can I parse the problem in a new way, such that I can apply each model to a different part of the problem space?”
Now, one of the practical challenges in becoming a more integrative thinker is that problems requiring a more sophisticated, Synthesis approach don’t come along quite as often as much as other, less difficult problems, so we don’t have as many opportunities to practice and develop our Synthesis skills. I have a rather outside-the-box remedy: enter cartoon caption contests, like the most famous one offered weekly by the New Yorker, or the one offered monthly (with a distinctly business orientation) by Harvard Business Review.23
I will leave this chapter with the wisdom of Roger Martin:
Most of us, most of the time, do whatever we can to simplify this [problem-solving] process: we cut down the number of variables we will consider to a minimum; we think about the simplest and most straightforward kinds of causal relationships; we break the problem apart into manageable chunks and then accept the trade-offs that emerge from our thinking as “inevitable.” Or, we imagine the trade-offs away . . . taking the shortest possible route to remedying the tension between the two models. We do all of this in a highly implicit way, failing to look deeply into our thinking at each stage, and thus when we fall victim to a logical misstep, we are entirely unaware of it and only become cognizant of a problem when the outcome is not what we would wish for ourselves.
Integrative thinkers show us what is possible: they consider more features of the problem as salient to its resolution; they consider more complex kinds of causal relationship between the features; they are able to keep the whole problem in mind while they work on the individual parts; and they end up with creative resolutions. Importantly, they do all of this explicitly, pushing to understand “the thinking behind their thinking.”24
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* In case you forget your Roman numerals, the equation reads, “11 plus 1 equals 10,” which is obviously incorrect.
* In September 1991 a reader of Marilyn vos Savant’s column in the New York Times magazine Parade posed this very question, now known as the Monty Hall Problem, with its own Wikipedia entry. She answered correctly that the contestant should switch doors. Her answer provoked nearly 10,000 responses from readers, most of them disagreeing with her. Several were from mathematicians and scientists whose responses lamented the nation’s lack of math skills, and who later had to retract their statements. I first wrote about the Monty Hall Problem a decade ago in The Elegant Solution.
* Roger Martin told this story of Target to me and a team of executives in a joint client strategy session held in Santa Monica, California, December 1, 2015.
* My winning caption appeared in the March 24, 2008, print edition of the New Yorker.