Blecher didn’t actually have sufficient data either to make that vision his purpose in life or to see CIDA as the means of achieving it. He couldn’t prove it in advance or deduce or induce it from the existing theories or data. It required him to make leaps in his mind to reason about what might be. Let’s examine what that reasoning looks like in practice.
The Art and Science of Generative Reasoning
My colleagues and I at Rotman try to teach MBA students and executives to reason generatively. We teach them how to seek insights that don’t fit neatly into the existing models. Then we ask them to proceed from those insights to visualize new models. We also teach them to how to prototype and refine their mental models, gathering additional data with each iteration. Many students find it scary, and somewhat transgressive, to flex their abductive logic muscles, having been taught to see deductive and inductive logic as the only legitimate forms of reasoning. It’s always a pleasure to see the light come on as they realize that generative reasoning does not destroy life as we know it. To the contrary—it opens the door to new possibilities.
When we teach executive groups, we use the dilemmas they face in their current businesses as the modeling challenge. One group of executives that came through recently was from a hair-care business that wanted to increase its share of the styling-products market. One evening, we arranged for them to visit a hair salon and watch a group of women get their hair styled. The next morning, the executives interviewed the women in detail.
The aim of the exercise was to give the executives a deeper understanding of how users felt about the styling experience. We emphasized to the executives that we didn’t want them to gather a statistically significant sample but to seek a deeper understanding of the end users of their products. Then we asked them to use that understanding to imagine new ways to meet the needs of the women in the salon. In other words, we asked them to infer backward from their understanding to the “best explanation”—in this case, a product that would meet their customers’ needs better than anything yet on the market. We worked with them to prototype and refine their new offerings until they were ready to be tested on the target customers—the ladies in the salon.
MBA students at Rotman hone their abductive reasoning skills on challenges proposed by corporations or nonprofits. Just as the hair-care executives did, the MBA students work through a series of exercises aimed initially at gaining a deeper understanding of the users of a particular product or service. Then we ask them to visualize new ways of serving those users and mentally work their way through a series of prototypes of the new product or service.
Both MBA students and seasoned executives often find these exercises unsettling. They share certainties about the world and about the deductive and inductive logics that confirm their certainties. It makes them uneasy to deliberately seek out data that unsettles their certainties. As they gain practice with the mental exercises, though, they grow less defensive when faced with disconfirming data and more eager to make something new of the novel and different data they’ve uncovered. What had been a threat becomes an exhilarating form of play.
Causal Modeling
The second tool of integrative thinkers, also illustrated by Blecher, is causal modeling. Sophisticated causal modeling is a crucial underpinning for causality and architecture, the middle two steps of the integrative thinking process. Recall that in the causality step, the thinker must consider nonlinear and multidirectional causal links between salient variables. In the architecture step, the thinker must keep the whole interlocking structure of causal relationships in mind while working on the individual parts of a solution.
To build sophisticated models, we need to consciously acquire tools. We don’t have to do that to build basic models. After all, we’re natural model builders, with a factory setting biased in favor of shaping the fabric of our experiences into mental models. “You never have the choice of ‘let’s model or not,’” says John Sterman, a professor at MIT Sloan School of Management and a leading thinker in system dynamics. “It’s only a question of which model. And most of the time, the models that you’re operating from are ones that you’re not even aware that you’re using.” 6 Integrative thinkers differ from the rest of us in being more conscious about the tools they choose to use to model.
Two forms of causation are important to causal modeling. The first is material causation, which says that under a certain set of conditions, x causes y to happen: If we price our product 10 percent below our competitors’ price (x), our market share (y) will rise.
The second form of causation we need to know about is teleological causation, which asks, what is the purpose of y, or why do we want y to happen? Let’s say you’re a CEO who wants to increase market share so your company can increase scale and reap the resulting economies. For the causal modeler, material causation and teleological causation connect the way things are to their desired end-state. Material causation is how we know that if we press this button, we shut down the nuclear reactor. Teleological causation is the process by which we understand that if we want to shut down the reactor, we press the button. When the desire to shut down the reactor causes us to press the button, we’re enlisting the material to achieve the teleological. We aim to change the present state (a hot reactor) into a desired end-state (a cool one), and we do so by following a known chain of material causation.
For Blecher, the existing state was of disadvantaged, disempowered black youth who had neither hope nor opportunity. His desired end-state was that they would have self-esteem and capability. His task as an integrative thinker was to build a causal model to get from the current state to the desired end-state.
The material causation that he envisioned was to give the students the tools they needed to understand their world better and contribute to it. “This process really builds a tremendous sense of ownership in the students and a sense of self-belief,” Blecher explains. But this material causation requires a narrow and specific set of conditions to be operative. “It requires,” he says, “a very special kind of education that is enormously loving, enormously holistic, and really does give the students the opportunity to completely change the way they feel about themselves.”
Blecher built a concrete causal model that informed his actions in designing CIDA. His challenge as an integrative thinker imagining what might be was to visualize the causal relationships in enough depth and detail that his vision would hold up in the real world. When facing this challenge, certain tools, known as system dynamics, can improve the causal modeling.
System dynamics is a theory of mapping the activity of complex systems that Jay Forrester of MIT developed in the early 1960s. He brought the tool set from the engineering domain and applied it to the business world. 7 System dynamics holds that the results of our decisions are so often disappointing because we overlook important causal relationships, or because we misread causal relationships, usually by assuming them to be linear and unidirectional when they are in fact nonlinear and multidirectional.
A primary focus of system dynamics is one sort of causal relationship: multidirectional feedback loops that accelerate relationships between variables. Here’s an example: hotel developers are often dismayed to discover that when they open a hotel in a market that supports high room rates, those rates often fall because the new hotel increases local capacity. The usual managerial response is to cut costs and prices, but that step often hurts the hotel’s premium image, and thus its occupancy and profitability. Another round of cost- and price-cutting ensues, doing further damage to occupancy and profitability. Repeat, with accelerating frequency, until bankruptcy.
System dynamics experts call that an accelerating feedback loop. A person could not model the dynamic accurately or intelligently without an ability to imagine nonlinear, multidirectional causal relationships.
System dynamics tools help integrative thinkers consider complex causal loops in creating their models and help them build models in which the whole is viewed togeth
er rather than split into discrete components. In fact, in system dynamics, the whole must be held in mind to capture and understand all the relevant causal feedback loops.
Such feedback loops are built into Blecher’s model for CIDA. His view of a self-sustaining, self-generating university community, surrounded and nourished by student-led businesses, assumes feedback loops between education and commerce. Another feedback loop forms when students adopt thirty high school students from their home communities. And Blecher’s preferred practice of creating something out of nothing is a third accelerating feedback loop, in which a handful of resources begets greater resources, which in turn beget ever-greater resources. The man makes a mean pot of stone soup.
Causal model building and generative reasoning combine to form one of the most potent tools in the integrative thinker’s kit. Generative reasoning seeks to build new models that take into account data that doesn’t comport with the current models available. A tool for forming such models is what George Lakoff and Mark Johnson call “radial metaphors,” by which one devises a metaphor and builds a model around that metaphor. 8 For example, people commonly use a few different metaphors to describe a business organization. The metaphor might be that of a sports team, in which the employees are the players, business competition is a game, business etiquette and business ethics are the rules of the game, and customers are the fans. Another common metaphor is that of the family. Senior executives are parents, employees are children, the task of the organization is to nurture, the resources of the organization are love and affection, and resource allocation is based on suitability of behavior. Other metaphors around which a structure takes shape are the organization as army, the organization as market, and the organization as ecosystem.
The radial metaphor tool helps integrative thinkers in two ways. First, it helps thinkers conceive of the situation at hand in a way that’s conducive to creating a new model. In that sense, the radial metaphor is one of those tools of efficiency discussed in the first half of the book.
The radial metaphor also helps with the cognitive heavy lifting of keeping a coherent whole in mind while honing the individual parts. That skill is critical to integrative thinking, and the radial metaphor can be an invaluable help.
Blecher’s radial metaphor when building the CIDA model was the organization as family. CIDA is the nurturing and loving parent and the students are the children who thrive on the parent’s love. Blecher is quite explicit about the role love and affection play in his vision of education. But love and discipline go hand in hand. Students must obey CIDA’s many rules if they want to continue to receive the school’s love and nurturing.
Blecher’s causal modeling of CIDA can be seen at three levels. At the basic level, there’s the combination of teleological and material modeling (young people can gain the desired hope and self-worth through education). At the next level, Blecher modeled a dynamic system that takes advantage of the feedback effects between happy, motivated, and successful students and the communities in which they live, work, and socialize. At the third level is that radial metaphor of the CIDA organization as a family.
Working on these three causal levels, Blecher used insights that had eluded other observers to build an entirely new model to resolve the trade-offs he faced. The three levels of modeling enabled him to see the basic causal relationships between relevant variables, the more sophisticated relationships, and finally, to hold the whole picture in his mind while working on the individual pieces.
At Rotman, we give students practice at all three levels of causal modeling. The simplest practice is to ask students to reverse engineer their own models. We ask them to pick a belief (better grades help get a better job) or practice (calling team meetings every Friday morning) and break down the causal reasoning that underlies the belief or practice. This helps them recognize how they’re already using causal modeling without realizing it, and shows how the modeling might improved by being more explicit about it.
We then graduate to interviewing another person to understand the causal modeling that underlies a particular belief or practice. This exercise entails speculating on the logic another person follows to arrive at a particular conclusion, and many students find it challenging. One student interviewed her female counterpart about her decision to break off an engagement with only weeks to go until the wedding. The interviewer’s first attempt at imagining her counterpart’s causal model focused on the aspects that were easy to describe in practical, utilitarian terms. One such aspect was that their careers weren’t suited for one another. Another was that they wanted to work in different cities.
But in discussing this model with her interview subject, our interviewer soon understood that it didn’t offer a complete or convincing account of the problem. It failed to take into account powerful emotional forces that played at least as large a role in the decision to break off the engagement as any practical concerns.
The most important takeaway from these interview sessions is that it’s extremely difficult to build a causal model that adequately takes account of human beings and their wishes and dreams. It taxes students’ abilities to take a wide view of what’s salient, to perceive complex causal relationships, and to hold the whole in mind while drilling down on a particular part.
The faculty’s goals in these exercises are threefold. First, we want students to see themselves as thinkers capable of conscious causal modeling. We want them to understand that their modeling gains power and effectiveness when they’re conscious and explicit about it. And we want them to practice using techniques such as system dynamics and radial metaphors to build sophisticated causal models.
Assertive Inquiry
The third important tool for the integrative thinker is assertive inquiry. Integrative thinkers use it to explore opposing models, and in particular, models that oppose their own.
When we interact with other people on the basis of a particular mental model, we usually try to defend that model against any challenges. Our energy goes into explaining our model to others and defending it from criticism. Parrying critiques of our model gives us a deeper understanding of it, but it teaches us nothing about the models other people hold in their heads. In fact, the defensive stance helps ensure that we never learn anything about models that might oppose our own. And that keeps us from finding clues that might lead to a creative resolution should our mental model come into conflict with someone else’s mental model.
The antidote to advocacy is inquiry, which produces meaningful dialogue. When you use assertive inquiry to investigate someone else’s mental model, you find saliencies that wouldn’t have occurred to you and causal relationships you didn’t perceive. You may not want to adopt the mental model as your own, but even the least compelling model can provide clues to saliencies or causal relationships that will generate a creative resolution.
Assertive inquiry’s intent isn’t argumentative, and its method isn’t to ask leading questions (“don’t you think that . . . ?”) or discourage challenge (“wouldn’t you agree that that . . . ?”). Assertive inquiry involves a sincere search for another’s views (“could you please help me understand how you came to believe that?”) and tries to fill in gaps of understanding (“could you clarify that point for me with an illustration or example?”). It seeks common ground between conflicting models (“how does what you are saying overlap, if at all, with what I suggested?”).
Assertive inquiry isn’t a form of challenge, but it is pointed. It explicitly seeks to explore the underpinnings of your own model and that of another person. Its aim is to learn about the salient data and causal maps baked into another person’s model, then use the insight gained to fashion a creative resolution of the conflict between that person’s model and your own.
Assertive inquiry promotes generative reasoning and causal modeling. It enables generative reasoning by breaking down conflicting models into pieces that can be recombined into something better than either of the two models that are in conflict.
And assertive inquiry produces more robust causal modeling by enlisting more minds to explore and map the material and teleological links that undergird the conflicting models.
My colleagues and I try to imbue our students with a similar curiosity about other people’s mental models. Many aren’t eager to learn. To them, clashing models have always meant only conflict, hurt feelings, and misunderstanding. Our task is to help them come away from an episode of clashing models feeling that they have made something positive of the clash and contributed to a valuable resolution.
We try to teach students how to engage in productive dialogue in the face of clashing models, and the vehicle we use for teaching it is the “personal case.” I have adopted the technique from the methods and theories of Chris Argyris, a professor emeritus at Harvard Business School and a leading theorist of organizational learning. 9 We ask each class participant to recall an encounter with another person that involved a clash of views or positions. This encounter, moreover, had to end badly, in egocentric terms. That is, the outcome had to be less favorable than the one the student sought at the outset of the interaction. If it is only a failure in the minds of others, the student can distance himself or herself from the failure (i.e., I succeeded but they thought it was a failure), and in doing so, lessen the learning.
We ask participants to explain in a paragraph or two the purpose of the failed encounter, and then in another paragraph or two explain what they hoped the interaction would accomplish, and how. Then we ask them to record, as best they can recall, the actual conversation during the interaction, and present it as dialogue in a play.
We ask that they display the dialogue on the right half of the page. On the left half, we ask them to provide a sort of running commentary on the dialogue, made up of what they thought and felt but did not say. Finally, we ask them to write a paragraph or two of reflection on the outcome of the interaction.
The Opposable Mind Page 14