of the United Kingdom’s capitol city.
If you’re a regular listener of the podcast, you’ll know I’m sick and tired of the multiverse. It’s taken over everything. Everything Everywhere All At Once, the entire MCU, Star Trek, Devs, Nicolas Cage (ok I’m in on this), and so much more… gaaah. It’s annoyed me so much over the past few years that I found myself wondering…
Why is our culture so obsessed? I can’t believe I’m writing this… the multiverse is our exploration of “what-ifs”, which have scientific significance. The multiverse-obsessed are exploring counterfactual modality, which is a logical form of reasoning.
Cause and Effect
Since the Enlightenment we’ve been on the path of science and reason—that is cause and effect. The better we understood cause and effect, the more advanced we became as a society. Numbers… proofs… scientific laws… every action has an equal and opposite reaction… 1+1=2… everything can be uncovered by the scientific method. This accelerated in the early 20th century—electricity, automobiles, and modern infrastructure made the world feel as though it could be understood, even tamed. A shining, bright future.
We were able to uncover specific truths that gave us confidence about the future. Certainty was the target. While not achieved, this cause and effect mindset gave us hope that one day it might be possible to know what’s next.
However, the increased pace of change in the last 80 years has made this scientific approach more difficult. It’s impossible to repeat anything because context shifts so quickly. Technology, culture, scientific discovery—everything everywhere is changing all at once. Uncertainty abounds, because possibilities seem infinite. The nuclear possibilities of the 40s and 50s brought about global uncertainty for global power structures. The cultural possibilities of the 60s and 70s brought about uncertainty for identity. The technological advances of the 80s and 90s brought about uncertainty for technology. The connectivity possibilities of the 00s ushered us into an era of relational uncertainties.
The endless data of the last 10 years has left us utterly crippled under the uncertainty of what we can do with it.
The Uncertainty of Data Significance
That brings us to today: possibility overload. It seems as though if something gets mentioned as a possibility, even in jest, it might become a reality. The Simpsons joke that Donald Trump becomes president in an early episode and he becomes president nearly 20 years later. Descartes’ guiding principle of modernity was “I think, therefore I am,” but perhaps this needs to be updated for our postmodern age to “I think it, therefore it could exist.” We have a hard time determining if something is even real (see the recent confusion around whether the ads set in the movie Crazy People (1990) are actually real or not).
All of these uncertainties compound generation after generation. It’s not like the threat of nuclear obliteration is gone. It’s just been sitting there in the back of our minds (or maybe in recent months, the front of our minds), subconsciously reminding us that what’s next is utterly unknowable. We’re having a hard time even discerning how we got to where we are.
This unprecedented pace of change and massive influx of new data points is making it difficult to sort out what is significant along the cause-effect chain.
Determining the impact or significance of a specific event or person is murky. Yes, George Washington was our first president and the United States of America wouldn’t be what it is today without him. Or would it? What if someone else had taken the role? How different would our country be? Was my campaign successful because I hired that influencer? Would it have been more successful if I had hired several micro-influencers instead of one star? Could I have run the same campaign through my organic channels with a similar result?
The multiverse is an exploration of our confusion around how the past produces outcomes. This is especially important to us, because people—and especially businesses—want to be able to understand what’s next. We want to know how to achieve our goals, how to be successful. It’s hard to understand how we got to the present, let alone get to the future. If we can’t understand the mechanics of how we got to now, how can we ever know what to do?
The Multiverse is a Counterfactual Modality
The cultural obsession with the multiverse is our way of dealing with the rapid pace of change, because it’s a cultural touchstone; a shorthand for counterfactuals.
Counterfactuals are what could, might, or would have happened under different circumstances, i.e. “what-if” scenarios. The counterfactual modality was only recently widely accepted as a semantic framework in the 1970s (highly attributed to the work of David Lewis), and even that framework has had a fair share of refinement over the years.
Here’s an example of a counterfactual:
- A caused C.
- If A had not occurred, C would not have occurred.
Or conversely:
- C did not occur.
- If A had occurred, C would have occurred.
We’re at the point where what’s possible feels more relevant than present reality. It’s interesting to me that this happened only just after we accepted what-if scenarios as a logical way to address the world.
Causal claims almost always include some sort of counterfactual frame or dependence to make their case. Causal analysis has allowed us to create more things because we understand how things work better. However, this means there are more possible outcomes, which means the future is harder to predict, not easier. The creation of more things and the possibility for the creation of more things introduces more uncertainty, not less. Our post-enlightenment world of cause-effect thinking has widened our aperture to include more possible outcomes instead of fewer, more predictable next steps.
Additionally, the abundance of data has made our counterfactual models become overwhelming. Data relevance is a key component of good counterfactual analysis. If you can’t at minimum make some kind of measurable connection between the data and the situation, it’s hard to run any kind of plausible counterfactual scenario. The influx of new types of data, the structure and siloing of orgs, and the lack of cross-discipline expertise make ranking this data nigh impossible, even on a curve.
Every time a new piece of data is introduced (which happens all the time), we have to—or should—refactor our scenarios and we almost never take the time to go back and actually do.
It also takes guts to re-adjust data significance. Just this past week, progress-cataloger, Derek Thompson from the Atlantic recently started putting weight on different data:
“In a cover story for this magazine several years ago, several years ago, I insisted that America suffered primarily from an invention recession—a serious deficit of new ideas about hardware. Now I think that I, like others, probably got this wrong… Progress is a puzzle whose answer requires science and technology. But believing that material progress is only a question of science and technology is a profound mistake.”
Not everyone has the ability to admit their cover story was wrong. Not every business leader has the time, guts, or expertise to re-attribute their successes or reassign weights to failures.
All of this of course, with the increasing speed of change, which means the window of contextual relevance for reapplication of insight is shrinking all the time.
The cost of quality counterfactual analysis is high and the opportunity for it to even be useful is low.
Counterfactuals Are Prevalent
Regardless, counterfactual-led causal analysis is prevalent throughout our industry.
Customers use counterfactuals
Consumers often use counterfactuals when evaluating both what they should buy and their past purchases. Last year I hiked Mount Adams with some of my much more experienced relatives. As we started down the trail, I realized my backpack was much larger than theirs. We hit the “Lunch Counter” (the traditional spot to stay the night), and my cousin unloaded his bag upon which I noticed his sleeping bag was much smaller than mine. He was packing a down sleeping bag. I enviously pondered, “if I had just bought a down bag instead of synthetic, I wouldn’t have had to lug such a huge bag all this way up.” Upon getting home, I immediately started researching which down bag I wanted to buy and made the purchase. A simple example, but a common story. Nearly everyone who makes purchases uses counterfactual reasoning in their decision making process.
Marketers use counterfactuals
Given the mindset of customers, it follows that marketers have been chronic counterfactual employers since the advent of modern advertising. There are two types of counterfactual thinking: upward and downward. Downward thinking is when you consider what could have been worse. Upward thinking is when you focus on what could have been better.
Upward counterfactual thinking is the name of the advertising game. The slickest of advertisers don’t say “buy our product and you will have x outcome”, their message instead is “if you had used this product in the past, your outcome today would have been x”.
Business leaders use counterfactuals
Attribution of success or failure is an exercise in counterfactual thinking. “Had we not done this, this would not have happened” or in other words “had we done x, we would not have achieved y.” Monday morning quarterbacking, retrospectives, anything with what “could/should have been done better if only” or what “could/should have gone worse if x had happened”. Assignment of blame and success usually includes counterfactual thinking.
Changing our thinking
I said I was tired of the multiverse; I’ve come to understand that I’m tired of the sloppy overapplication of counterfactuals. Humans typically use counterfactuals when something negative happens as a way to process it, ie “what if I/we had only”. Analysis of success often comes with fast assumptions of what led to success with very little review of other possible outcomes. Also people are prone to upward counterfactual thinking - how a situation could have been better, not how it could have been worse, which means potential pitfalls are often missed and risks are miscalculated for future engagement.
There’s also the relevancy bias, i.e. the improper application or lack of information about the significance of the inputs. Christopher Hitchcock, another bastion of counterfactual thinking, said to eliminate variables “that one is not willing to take seriously”. However, the criticism of this view is that it can still lead to bias. And to pile on: context almost always changes significance.
We also tend to use counterfactuals to explain outliers, because they’re hard to understand and potential what/ifs tend to be easy to imagine - to “leap out” as it’s said.
Outliers seem to be popping up everywhere. Outliers have become the mundane. Possibilities seem endless and therefore counterfactuals are being applied to solve just about everything.
Three ideas to course-correct:
1. Intentional application of counterfactuals. Be conscious when you’re using them and be conscious of how you’re applying them. There’s a whole world of counterfactual analysis systems that has been scrutinized and applied carefully in different contexts. For instance, in the world of security, counterfactuals are extra useful for thinking through how someone might circumvent or hack a system, but they can get out of hand and cause over-investment or confusion.
Counterfactuals (or what-if scenarios) are often employed as security arguments, but the dos and don'ts of their use are poorly understood. They are useful to discuss vulnerability of systems under threats that haven't yet materialized, but they can also be used to justify investment in obscure controls… We conclude that counterfactuals are a necessary evil in security, which should be carefully controlled. - Cormac Herley, Microsoft Research, 2015
Cormac is saying you need to make sure you have a good handle on the significance of your data before applying a counterfactual scenario to gain insight. This is as true for marketers as it is for security professionals, as it is for your personal life. It’s easy to make sweeping statements about success or failure solely due to a biased, unfounded, or uneducated understanding of a specific factor. See: the Derek Thompson example above. Another way to put it - we spend a lot on acquiring, adding, and discovering data, but perhaps we should focus more on validating and ranking the importance of the data we already have.
2. Diversity of thought and investment. Rather than obsess over nailing what happened or what will happen, have your eggs in a lot of baskets. When things shift, you will have a headstart on those who didn’t take a first step.
The two counter arguments to this are, first, that you can’t do a good job if you don’t specialize and focus, and second, that if you apply yourself to too many things you’ll burn out. To this I say - lean in and invest more where you have momentum or zeal, but make sure to run a “minimum viable product” in the places where you don’t get it or don’t have the focus. It’ll be a little bit of a stretch, but it’s better cut your main investments a little bit to not miss out on a channel that might blow up.
You might be criticized for a lack of initial ROI (internal) or for the unsophistication of your effort (external), however there’s too much upside of having data and learning from these channels that have potential even if it’s quite not clear to you yet.
Same for people. If you have the ability, make sure you keep outliers in your org that you don’t understand. Yes, do your best to make sure they’re smart, even if you don’t see things their way. Keep healthy discourse open. You’ll learn new things and stay ahead of what’s happening.
3. Focus on character. We cannot control the future but we can control our reaction to the present: who we are, who we will become. Our character with how we interact with the present is how we survive the unknown future.
Maybe we need to look back in order to go forward. In modernity, we’ve looked toward a future, a bright utopia, for our personal selves, for our businesses, and for all humankind. Cause and effect can be known therefore this bright future is possible. The dissonance is that the more we march toward that future - building, improving, inventing, and discovering, the more convincing it is that our future is uncontrollable. Pre-enlightenment, western society didn’t necessarily think of their relation to the future in the straightline unfolding of history or the evolutionary development of what was to come next. They saw both history and their future as an expression of their relationship with God, i.e. individual progress toward the moral and religious. To translate to the modern ethos, they cared about their character and their relationships.
Maybe that’s exactly what we need now. In a world where possibilities are endless, maybe the way to future-proof is to focus more on the who, instead of the how and the what.
The tactics that are employed to try and tame the future will often result in an either unsustainable or undesirable future, or maybe both. The tactics that are developed from a high focus on character are the ones that will drive us toward the world we hope for the future to be.
Conclusion
I’m not suggesting we abandon reason, or cause-effect logic to address pinpoint solutions. But perhaps the best way to address “Ballung” concepts (and the multiverse has oft been used to attempt this) is by focusing on who we want to be to the people around us in the present. And in business, the greatest Ballung concept is future viability and profitability.
Look at our most admired companies - REI, Eileen Fisher, Costco, Patagonia, etc. They’ve secured their future through yes, smart business decisions, but also by sticking by principles and caring about people. It looks and feels squishy to the bean counters and straight-line thinkers, but probably less squishy than the future that scares the hell out of them because they have no idea what’s coming next.
Better counterfactual analysis, diversity of thought, and our present character give us the best chance at that shining, bright future that the age of reason promised. Also this just might give us a chance to stop making movies about the multiverse. I’m in.
If you’re a regular listener of the podcast, you’ll know I’m sick and tired of the multiverse. It’s taken over everything. Everything Everywhere All At Once, the entire MCU, Star Trek, Devs, Nicolas Cage (ok I’m in on this), and so much more… gaaah. It’s annoyed me so much over the past few years that I found myself wondering…
Why is our culture so obsessed? I can’t believe I’m writing this… the multiverse is our exploration of “what-ifs”, which have scientific significance. The multiverse-obsessed are exploring counterfactual modality, which is a logical form of reasoning.
Cause and Effect
Since the Enlightenment we’ve been on the path of science and reason—that is cause and effect. The better we understood cause and effect, the more advanced we became as a society. Numbers… proofs… scientific laws… every action has an equal and opposite reaction… 1+1=2… everything can be uncovered by the scientific method. This accelerated in the early 20th century—electricity, automobiles, and modern infrastructure made the world feel as though it could be understood, even tamed. A shining, bright future.
We were able to uncover specific truths that gave us confidence about the future. Certainty was the target. While not achieved, this cause and effect mindset gave us hope that one day it might be possible to know what’s next.
However, the increased pace of change in the last 80 years has made this scientific approach more difficult. It’s impossible to repeat anything because context shifts so quickly. Technology, culture, scientific discovery—everything everywhere is changing all at once. Uncertainty abounds, because possibilities seem infinite. The nuclear possibilities of the 40s and 50s brought about global uncertainty for global power structures. The cultural possibilities of the 60s and 70s brought about uncertainty for identity. The technological advances of the 80s and 90s brought about uncertainty for technology. The connectivity possibilities of the 00s ushered us into an era of relational uncertainties.
The endless data of the last 10 years has left us utterly crippled under the uncertainty of what we can do with it.
The Uncertainty of Data Significance
That brings us to today: possibility overload. It seems as though if something gets mentioned as a possibility, even in jest, it might become a reality. The Simpsons joke that Donald Trump becomes president in an early episode and he becomes president nearly 20 years later. Descartes’ guiding principle of modernity was “I think, therefore I am,” but perhaps this needs to be updated for our postmodern age to “I think it, therefore it could exist.” We have a hard time determining if something is even real (see the recent confusion around whether the ads set in the movie Crazy People (1990) are actually real or not).
All of these uncertainties compound generation after generation. It’s not like the threat of nuclear obliteration is gone. It’s just been sitting there in the back of our minds (or maybe in recent months, the front of our minds), subconsciously reminding us that what’s next is utterly unknowable. We’re having a hard time even discerning how we got to where we are.
This unprecedented pace of change and massive influx of new data points is making it difficult to sort out what is significant along the cause-effect chain.
Determining the impact or significance of a specific event or person is murky. Yes, George Washington was our first president and the United States of America wouldn’t be what it is today without him. Or would it? What if someone else had taken the role? How different would our country be? Was my campaign successful because I hired that influencer? Would it have been more successful if I had hired several micro-influencers instead of one star? Could I have run the same campaign through my organic channels with a similar result?
The multiverse is an exploration of our confusion around how the past produces outcomes. This is especially important to us, because people—and especially businesses—want to be able to understand what’s next. We want to know how to achieve our goals, how to be successful. It’s hard to understand how we got to the present, let alone get to the future. If we can’t understand the mechanics of how we got to now, how can we ever know what to do?
The Multiverse is a Counterfactual Modality
The cultural obsession with the multiverse is our way of dealing with the rapid pace of change, because it’s a cultural touchstone; a shorthand for counterfactuals.
Counterfactuals are what could, might, or would have happened under different circumstances, i.e. “what-if” scenarios. The counterfactual modality was only recently widely accepted as a semantic framework in the 1970s (highly attributed to the work of David Lewis), and even that framework has had a fair share of refinement over the years.
Here’s an example of a counterfactual:
- A caused C.
- If A had not occurred, C would not have occurred.
Or conversely:
- C did not occur.
- If A had occurred, C would have occurred.
We’re at the point where what’s possible feels more relevant than present reality. It’s interesting to me that this happened only just after we accepted what-if scenarios as a logical way to address the world.
Causal claims almost always include some sort of counterfactual frame or dependence to make their case. Causal analysis has allowed us to create more things because we understand how things work better. However, this means there are more possible outcomes, which means the future is harder to predict, not easier. The creation of more things and the possibility for the creation of more things introduces more uncertainty, not less. Our post-enlightenment world of cause-effect thinking has widened our aperture to include more possible outcomes instead of fewer, more predictable next steps.
Additionally, the abundance of data has made our counterfactual models become overwhelming. Data relevance is a key component of good counterfactual analysis. If you can’t at minimum make some kind of measurable connection between the data and the situation, it’s hard to run any kind of plausible counterfactual scenario. The influx of new types of data, the structure and siloing of orgs, and the lack of cross-discipline expertise make ranking this data nigh impossible, even on a curve.
Every time a new piece of data is introduced (which happens all the time), we have to—or should—refactor our scenarios and we almost never take the time to go back and actually do.
It also takes guts to re-adjust data significance. Just this past week, progress-cataloger, Derek Thompson from the Atlantic recently started putting weight on different data:
“In a cover story for this magazine several years ago, several years ago, I insisted that America suffered primarily from an invention recession—a serious deficit of new ideas about hardware. Now I think that I, like others, probably got this wrong… Progress is a puzzle whose answer requires science and technology. But believing that material progress is only a question of science and technology is a profound mistake.”
Not everyone has the ability to admit their cover story was wrong. Not every business leader has the time, guts, or expertise to re-attribute their successes or reassign weights to failures.
All of this of course, with the increasing speed of change, which means the window of contextual relevance for reapplication of insight is shrinking all the time.
The cost of quality counterfactual analysis is high and the opportunity for it to even be useful is low.
Counterfactuals Are Prevalent
Regardless, counterfactual-led causal analysis is prevalent throughout our industry.
Customers use counterfactuals
Consumers often use counterfactuals when evaluating both what they should buy and their past purchases. Last year I hiked Mount Adams with some of my much more experienced relatives. As we started down the trail, I realized my backpack was much larger than theirs. We hit the “Lunch Counter” (the traditional spot to stay the night), and my cousin unloaded his bag upon which I noticed his sleeping bag was much smaller than mine. He was packing a down sleeping bag. I enviously pondered, “if I had just bought a down bag instead of synthetic, I wouldn’t have had to lug such a huge bag all this way up.” Upon getting home, I immediately started researching which down bag I wanted to buy and made the purchase. A simple example, but a common story. Nearly everyone who makes purchases uses counterfactual reasoning in their decision making process.
Marketers use counterfactuals
Given the mindset of customers, it follows that marketers have been chronic counterfactual employers since the advent of modern advertising. There are two types of counterfactual thinking: upward and downward. Downward thinking is when you consider what could have been worse. Upward thinking is when you focus on what could have been better.
Upward counterfactual thinking is the name of the advertising game. The slickest of advertisers don’t say “buy our product and you will have x outcome”, their message instead is “if you had used this product in the past, your outcome today would have been x”.
Business leaders use counterfactuals
Attribution of success or failure is an exercise in counterfactual thinking. “Had we not done this, this would not have happened” or in other words “had we done x, we would not have achieved y.” Monday morning quarterbacking, retrospectives, anything with what “could/should have been done better if only” or what “could/should have gone worse if x had happened”. Assignment of blame and success usually includes counterfactual thinking.
Changing our thinking
I said I was tired of the multiverse; I’ve come to understand that I’m tired of the sloppy overapplication of counterfactuals. Humans typically use counterfactuals when something negative happens as a way to process it, ie “what if I/we had only”. Analysis of success often comes with fast assumptions of what led to success with very little review of other possible outcomes. Also people are prone to upward counterfactual thinking - how a situation could have been better, not how it could have been worse, which means potential pitfalls are often missed and risks are miscalculated for future engagement.
There’s also the relevancy bias, i.e. the improper application or lack of information about the significance of the inputs. Christopher Hitchcock, another bastion of counterfactual thinking, said to eliminate variables “that one is not willing to take seriously”. However, the criticism of this view is that it can still lead to bias. And to pile on: context almost always changes significance.
We also tend to use counterfactuals to explain outliers, because they’re hard to understand and potential what/ifs tend to be easy to imagine - to “leap out” as it’s said.
Outliers seem to be popping up everywhere. Outliers have become the mundane. Possibilities seem endless and therefore counterfactuals are being applied to solve just about everything.
Three ideas to course-correct:
1. Intentional application of counterfactuals. Be conscious when you’re using them and be conscious of how you’re applying them. There’s a whole world of counterfactual analysis systems that has been scrutinized and applied carefully in different contexts. For instance, in the world of security, counterfactuals are extra useful for thinking through how someone might circumvent or hack a system, but they can get out of hand and cause over-investment or confusion.
Counterfactuals (or what-if scenarios) are often employed as security arguments, but the dos and don'ts of their use are poorly understood. They are useful to discuss vulnerability of systems under threats that haven't yet materialized, but they can also be used to justify investment in obscure controls… We conclude that counterfactuals are a necessary evil in security, which should be carefully controlled. - Cormac Herley, Microsoft Research, 2015
Cormac is saying you need to make sure you have a good handle on the significance of your data before applying a counterfactual scenario to gain insight. This is as true for marketers as it is for security professionals, as it is for your personal life. It’s easy to make sweeping statements about success or failure solely due to a biased, unfounded, or uneducated understanding of a specific factor. See: the Derek Thompson example above. Another way to put it - we spend a lot on acquiring, adding, and discovering data, but perhaps we should focus more on validating and ranking the importance of the data we already have.
2. Diversity of thought and investment. Rather than obsess over nailing what happened or what will happen, have your eggs in a lot of baskets. When things shift, you will have a headstart on those who didn’t take a first step.
The two counter arguments to this are, first, that you can’t do a good job if you don’t specialize and focus, and second, that if you apply yourself to too many things you’ll burn out. To this I say - lean in and invest more where you have momentum or zeal, but make sure to run a “minimum viable product” in the places where you don’t get it or don’t have the focus. It’ll be a little bit of a stretch, but it’s better cut your main investments a little bit to not miss out on a channel that might blow up.
You might be criticized for a lack of initial ROI (internal) or for the unsophistication of your effort (external), however there’s too much upside of having data and learning from these channels that have potential even if it’s quite not clear to you yet.
Same for people. If you have the ability, make sure you keep outliers in your org that you don’t understand. Yes, do your best to make sure they’re smart, even if you don’t see things their way. Keep healthy discourse open. You’ll learn new things and stay ahead of what’s happening.
3. Focus on character. We cannot control the future but we can control our reaction to the present: who we are, who we will become. Our character with how we interact with the present is how we survive the unknown future.
Maybe we need to look back in order to go forward. In modernity, we’ve looked toward a future, a bright utopia, for our personal selves, for our businesses, and for all humankind. Cause and effect can be known therefore this bright future is possible. The dissonance is that the more we march toward that future - building, improving, inventing, and discovering, the more convincing it is that our future is uncontrollable. Pre-enlightenment, western society didn’t necessarily think of their relation to the future in the straightline unfolding of history or the evolutionary development of what was to come next. They saw both history and their future as an expression of their relationship with God, i.e. individual progress toward the moral and religious. To translate to the modern ethos, they cared about their character and their relationships.
Maybe that’s exactly what we need now. In a world where possibilities are endless, maybe the way to future-proof is to focus more on the who, instead of the how and the what.
The tactics that are employed to try and tame the future will often result in an either unsustainable or undesirable future, or maybe both. The tactics that are developed from a high focus on character are the ones that will drive us toward the world we hope for the future to be.
Conclusion
I’m not suggesting we abandon reason, or cause-effect logic to address pinpoint solutions. But perhaps the best way to address “Ballung” concepts (and the multiverse has oft been used to attempt this) is by focusing on who we want to be to the people around us in the present. And in business, the greatest Ballung concept is future viability and profitability.
Look at our most admired companies - REI, Eileen Fisher, Costco, Patagonia, etc. They’ve secured their future through yes, smart business decisions, but also by sticking by principles and caring about people. It looks and feels squishy to the bean counters and straight-line thinkers, but probably less squishy than the future that scares the hell out of them because they have no idea what’s coming next.
Better counterfactual analysis, diversity of thought, and our present character give us the best chance at that shining, bright future that the age of reason promised. Also this just might give us a chance to stop making movies about the multiverse. I’m in.
If you’re a regular listener of the podcast, you’ll know I’m sick and tired of the multiverse. It’s taken over everything. Everything Everywhere All At Once, the entire MCU, Star Trek, Devs, Nicolas Cage (ok I’m in on this), and so much more… gaaah. It’s annoyed me so much over the past few years that I found myself wondering…
Why is our culture so obsessed? I can’t believe I’m writing this… the multiverse is our exploration of “what-ifs”, which have scientific significance. The multiverse-obsessed are exploring counterfactual modality, which is a logical form of reasoning.
Cause and Effect
Since the Enlightenment we’ve been on the path of science and reason—that is cause and effect. The better we understood cause and effect, the more advanced we became as a society. Numbers… proofs… scientific laws… every action has an equal and opposite reaction… 1+1=2… everything can be uncovered by the scientific method. This accelerated in the early 20th century—electricity, automobiles, and modern infrastructure made the world feel as though it could be understood, even tamed. A shining, bright future.
We were able to uncover specific truths that gave us confidence about the future. Certainty was the target. While not achieved, this cause and effect mindset gave us hope that one day it might be possible to know what’s next.
However, the increased pace of change in the last 80 years has made this scientific approach more difficult. It’s impossible to repeat anything because context shifts so quickly. Technology, culture, scientific discovery—everything everywhere is changing all at once. Uncertainty abounds, because possibilities seem infinite. The nuclear possibilities of the 40s and 50s brought about global uncertainty for global power structures. The cultural possibilities of the 60s and 70s brought about uncertainty for identity. The technological advances of the 80s and 90s brought about uncertainty for technology. The connectivity possibilities of the 00s ushered us into an era of relational uncertainties.
The endless data of the last 10 years has left us utterly crippled under the uncertainty of what we can do with it.
The Uncertainty of Data Significance
That brings us to today: possibility overload. It seems as though if something gets mentioned as a possibility, even in jest, it might become a reality. The Simpsons joke that Donald Trump becomes president in an early episode and he becomes president nearly 20 years later. Descartes’ guiding principle of modernity was “I think, therefore I am,” but perhaps this needs to be updated for our postmodern age to “I think it, therefore it could exist.” We have a hard time determining if something is even real (see the recent confusion around whether the ads set in the movie Crazy People (1990) are actually real or not).
All of these uncertainties compound generation after generation. It’s not like the threat of nuclear obliteration is gone. It’s just been sitting there in the back of our minds (or maybe in recent months, the front of our minds), subconsciously reminding us that what’s next is utterly unknowable. We’re having a hard time even discerning how we got to where we are.
This unprecedented pace of change and massive influx of new data points is making it difficult to sort out what is significant along the cause-effect chain.
Determining the impact or significance of a specific event or person is murky. Yes, George Washington was our first president and the United States of America wouldn’t be what it is today without him. Or would it? What if someone else had taken the role? How different would our country be? Was my campaign successful because I hired that influencer? Would it have been more successful if I had hired several micro-influencers instead of one star? Could I have run the same campaign through my organic channels with a similar result?
The multiverse is an exploration of our confusion around how the past produces outcomes. This is especially important to us, because people—and especially businesses—want to be able to understand what’s next. We want to know how to achieve our goals, how to be successful. It’s hard to understand how we got to the present, let alone get to the future. If we can’t understand the mechanics of how we got to now, how can we ever know what to do?
The Multiverse is a Counterfactual Modality
The cultural obsession with the multiverse is our way of dealing with the rapid pace of change, because it’s a cultural touchstone; a shorthand for counterfactuals.
Counterfactuals are what could, might, or would have happened under different circumstances, i.e. “what-if” scenarios. The counterfactual modality was only recently widely accepted as a semantic framework in the 1970s (highly attributed to the work of David Lewis), and even that framework has had a fair share of refinement over the years.
Here’s an example of a counterfactual:
- A caused C.
- If A had not occurred, C would not have occurred.
Or conversely:
- C did not occur.
- If A had occurred, C would have occurred.
We’re at the point where what’s possible feels more relevant than present reality. It’s interesting to me that this happened only just after we accepted what-if scenarios as a logical way to address the world.
Causal claims almost always include some sort of counterfactual frame or dependence to make their case. Causal analysis has allowed us to create more things because we understand how things work better. However, this means there are more possible outcomes, which means the future is harder to predict, not easier. The creation of more things and the possibility for the creation of more things introduces more uncertainty, not less. Our post-enlightenment world of cause-effect thinking has widened our aperture to include more possible outcomes instead of fewer, more predictable next steps.
Additionally, the abundance of data has made our counterfactual models become overwhelming. Data relevance is a key component of good counterfactual analysis. If you can’t at minimum make some kind of measurable connection between the data and the situation, it’s hard to run any kind of plausible counterfactual scenario. The influx of new types of data, the structure and siloing of orgs, and the lack of cross-discipline expertise make ranking this data nigh impossible, even on a curve.
Every time a new piece of data is introduced (which happens all the time), we have to—or should—refactor our scenarios and we almost never take the time to go back and actually do.
It also takes guts to re-adjust data significance. Just this past week, progress-cataloger, Derek Thompson from the Atlantic recently started putting weight on different data:
“In a cover story for this magazine several years ago, several years ago, I insisted that America suffered primarily from an invention recession—a serious deficit of new ideas about hardware. Now I think that I, like others, probably got this wrong… Progress is a puzzle whose answer requires science and technology. But believing that material progress is only a question of science and technology is a profound mistake.”
Not everyone has the ability to admit their cover story was wrong. Not every business leader has the time, guts, or expertise to re-attribute their successes or reassign weights to failures.
All of this of course, with the increasing speed of change, which means the window of contextual relevance for reapplication of insight is shrinking all the time.
The cost of quality counterfactual analysis is high and the opportunity for it to even be useful is low.
Counterfactuals Are Prevalent
Regardless, counterfactual-led causal analysis is prevalent throughout our industry.
Customers use counterfactuals
Consumers often use counterfactuals when evaluating both what they should buy and their past purchases. Last year I hiked Mount Adams with some of my much more experienced relatives. As we started down the trail, I realized my backpack was much larger than theirs. We hit the “Lunch Counter” (the traditional spot to stay the night), and my cousin unloaded his bag upon which I noticed his sleeping bag was much smaller than mine. He was packing a down sleeping bag. I enviously pondered, “if I had just bought a down bag instead of synthetic, I wouldn’t have had to lug such a huge bag all this way up.” Upon getting home, I immediately started researching which down bag I wanted to buy and made the purchase. A simple example, but a common story. Nearly everyone who makes purchases uses counterfactual reasoning in their decision making process.
Marketers use counterfactuals
Given the mindset of customers, it follows that marketers have been chronic counterfactual employers since the advent of modern advertising. There are two types of counterfactual thinking: upward and downward. Downward thinking is when you consider what could have been worse. Upward thinking is when you focus on what could have been better.
Upward counterfactual thinking is the name of the advertising game. The slickest of advertisers don’t say “buy our product and you will have x outcome”, their message instead is “if you had used this product in the past, your outcome today would have been x”.
Business leaders use counterfactuals
Attribution of success or failure is an exercise in counterfactual thinking. “Had we not done this, this would not have happened” or in other words “had we done x, we would not have achieved y.” Monday morning quarterbacking, retrospectives, anything with what “could/should have been done better if only” or what “could/should have gone worse if x had happened”. Assignment of blame and success usually includes counterfactual thinking.
Changing our thinking
I said I was tired of the multiverse; I’ve come to understand that I’m tired of the sloppy overapplication of counterfactuals. Humans typically use counterfactuals when something negative happens as a way to process it, ie “what if I/we had only”. Analysis of success often comes with fast assumptions of what led to success with very little review of other possible outcomes. Also people are prone to upward counterfactual thinking - how a situation could have been better, not how it could have been worse, which means potential pitfalls are often missed and risks are miscalculated for future engagement.
There’s also the relevancy bias, i.e. the improper application or lack of information about the significance of the inputs. Christopher Hitchcock, another bastion of counterfactual thinking, said to eliminate variables “that one is not willing to take seriously”. However, the criticism of this view is that it can still lead to bias. And to pile on: context almost always changes significance.
We also tend to use counterfactuals to explain outliers, because they’re hard to understand and potential what/ifs tend to be easy to imagine - to “leap out” as it’s said.
Outliers seem to be popping up everywhere. Outliers have become the mundane. Possibilities seem endless and therefore counterfactuals are being applied to solve just about everything.
Three ideas to course-correct:
1. Intentional application of counterfactuals. Be conscious when you’re using them and be conscious of how you’re applying them. There’s a whole world of counterfactual analysis systems that has been scrutinized and applied carefully in different contexts. For instance, in the world of security, counterfactuals are extra useful for thinking through how someone might circumvent or hack a system, but they can get out of hand and cause over-investment or confusion.
Counterfactuals (or what-if scenarios) are often employed as security arguments, but the dos and don'ts of their use are poorly understood. They are useful to discuss vulnerability of systems under threats that haven't yet materialized, but they can also be used to justify investment in obscure controls… We conclude that counterfactuals are a necessary evil in security, which should be carefully controlled. - Cormac Herley, Microsoft Research, 2015
Cormac is saying you need to make sure you have a good handle on the significance of your data before applying a counterfactual scenario to gain insight. This is as true for marketers as it is for security professionals, as it is for your personal life. It’s easy to make sweeping statements about success or failure solely due to a biased, unfounded, or uneducated understanding of a specific factor. See: the Derek Thompson example above. Another way to put it - we spend a lot on acquiring, adding, and discovering data, but perhaps we should focus more on validating and ranking the importance of the data we already have.
2. Diversity of thought and investment. Rather than obsess over nailing what happened or what will happen, have your eggs in a lot of baskets. When things shift, you will have a headstart on those who didn’t take a first step.
The two counter arguments to this are, first, that you can’t do a good job if you don’t specialize and focus, and second, that if you apply yourself to too many things you’ll burn out. To this I say - lean in and invest more where you have momentum or zeal, but make sure to run a “minimum viable product” in the places where you don’t get it or don’t have the focus. It’ll be a little bit of a stretch, but it’s better cut your main investments a little bit to not miss out on a channel that might blow up.
You might be criticized for a lack of initial ROI (internal) or for the unsophistication of your effort (external), however there’s too much upside of having data and learning from these channels that have potential even if it’s quite not clear to you yet.
Same for people. If you have the ability, make sure you keep outliers in your org that you don’t understand. Yes, do your best to make sure they’re smart, even if you don’t see things their way. Keep healthy discourse open. You’ll learn new things and stay ahead of what’s happening.
3. Focus on character. We cannot control the future but we can control our reaction to the present: who we are, who we will become. Our character with how we interact with the present is how we survive the unknown future.
Maybe we need to look back in order to go forward. In modernity, we’ve looked toward a future, a bright utopia, for our personal selves, for our businesses, and for all humankind. Cause and effect can be known therefore this bright future is possible. The dissonance is that the more we march toward that future - building, improving, inventing, and discovering, the more convincing it is that our future is uncontrollable. Pre-enlightenment, western society didn’t necessarily think of their relation to the future in the straightline unfolding of history or the evolutionary development of what was to come next. They saw both history and their future as an expression of their relationship with God, i.e. individual progress toward the moral and religious. To translate to the modern ethos, they cared about their character and their relationships.
Maybe that’s exactly what we need now. In a world where possibilities are endless, maybe the way to future-proof is to focus more on the who, instead of the how and the what.
The tactics that are employed to try and tame the future will often result in an either unsustainable or undesirable future, or maybe both. The tactics that are developed from a high focus on character are the ones that will drive us toward the world we hope for the future to be.
Conclusion
I’m not suggesting we abandon reason, or cause-effect logic to address pinpoint solutions. But perhaps the best way to address “Ballung” concepts (and the multiverse has oft been used to attempt this) is by focusing on who we want to be to the people around us in the present. And in business, the greatest Ballung concept is future viability and profitability.
Look at our most admired companies - REI, Eileen Fisher, Costco, Patagonia, etc. They’ve secured their future through yes, smart business decisions, but also by sticking by principles and caring about people. It looks and feels squishy to the bean counters and straight-line thinkers, but probably less squishy than the future that scares the hell out of them because they have no idea what’s coming next.
Better counterfactual analysis, diversity of thought, and our present character give us the best chance at that shining, bright future that the age of reason promised. Also this just might give us a chance to stop making movies about the multiverse. I’m in.
If you’re a regular listener of the podcast, you’ll know I’m sick and tired of the multiverse. It’s taken over everything. Everything Everywhere All At Once, the entire MCU, Star Trek, Devs, Nicolas Cage (ok I’m in on this), and so much more… gaaah. It’s annoyed me so much over the past few years that I found myself wondering…
Why is our culture so obsessed? I can’t believe I’m writing this… the multiverse is our exploration of “what-ifs”, which have scientific significance. The multiverse-obsessed are exploring counterfactual modality, which is a logical form of reasoning.
Cause and Effect
Since the Enlightenment we’ve been on the path of science and reason—that is cause and effect. The better we understood cause and effect, the more advanced we became as a society. Numbers… proofs… scientific laws… every action has an equal and opposite reaction… 1+1=2… everything can be uncovered by the scientific method. This accelerated in the early 20th century—electricity, automobiles, and modern infrastructure made the world feel as though it could be understood, even tamed. A shining, bright future.
We were able to uncover specific truths that gave us confidence about the future. Certainty was the target. While not achieved, this cause and effect mindset gave us hope that one day it might be possible to know what’s next.
However, the increased pace of change in the last 80 years has made this scientific approach more difficult. It’s impossible to repeat anything because context shifts so quickly. Technology, culture, scientific discovery—everything everywhere is changing all at once. Uncertainty abounds, because possibilities seem infinite. The nuclear possibilities of the 40s and 50s brought about global uncertainty for global power structures. The cultural possibilities of the 60s and 70s brought about uncertainty for identity. The technological advances of the 80s and 90s brought about uncertainty for technology. The connectivity possibilities of the 00s ushered us into an era of relational uncertainties.
The endless data of the last 10 years has left us utterly crippled under the uncertainty of what we can do with it.
The Uncertainty of Data Significance
That brings us to today: possibility overload. It seems as though if something gets mentioned as a possibility, even in jest, it might become a reality. The Simpsons joke that Donald Trump becomes president in an early episode and he becomes president nearly 20 years later. Descartes’ guiding principle of modernity was “I think, therefore I am,” but perhaps this needs to be updated for our postmodern age to “I think it, therefore it could exist.” We have a hard time determining if something is even real (see the recent confusion around whether the ads set in the movie Crazy People (1990) are actually real or not).
All of these uncertainties compound generation after generation. It’s not like the threat of nuclear obliteration is gone. It’s just been sitting there in the back of our minds (or maybe in recent months, the front of our minds), subconsciously reminding us that what’s next is utterly unknowable. We’re having a hard time even discerning how we got to where we are.
This unprecedented pace of change and massive influx of new data points is making it difficult to sort out what is significant along the cause-effect chain.
Determining the impact or significance of a specific event or person is murky. Yes, George Washington was our first president and the United States of America wouldn’t be what it is today without him. Or would it? What if someone else had taken the role? How different would our country be? Was my campaign successful because I hired that influencer? Would it have been more successful if I had hired several micro-influencers instead of one star? Could I have run the same campaign through my organic channels with a similar result?
The multiverse is an exploration of our confusion around how the past produces outcomes. This is especially important to us, because people—and especially businesses—want to be able to understand what’s next. We want to know how to achieve our goals, how to be successful. It’s hard to understand how we got to the present, let alone get to the future. If we can’t understand the mechanics of how we got to now, how can we ever know what to do?
The Multiverse is a Counterfactual Modality
The cultural obsession with the multiverse is our way of dealing with the rapid pace of change, because it’s a cultural touchstone; a shorthand for counterfactuals.
Counterfactuals are what could, might, or would have happened under different circumstances, i.e. “what-if” scenarios. The counterfactual modality was only recently widely accepted as a semantic framework in the 1970s (highly attributed to the work of David Lewis), and even that framework has had a fair share of refinement over the years.
Here’s an example of a counterfactual:
- A caused C.
- If A had not occurred, C would not have occurred.
Or conversely:
- C did not occur.
- If A had occurred, C would have occurred.
We’re at the point where what’s possible feels more relevant than present reality. It’s interesting to me that this happened only just after we accepted what-if scenarios as a logical way to address the world.
Causal claims almost always include some sort of counterfactual frame or dependence to make their case. Causal analysis has allowed us to create more things because we understand how things work better. However, this means there are more possible outcomes, which means the future is harder to predict, not easier. The creation of more things and the possibility for the creation of more things introduces more uncertainty, not less. Our post-enlightenment world of cause-effect thinking has widened our aperture to include more possible outcomes instead of fewer, more predictable next steps.
Additionally, the abundance of data has made our counterfactual models become overwhelming. Data relevance is a key component of good counterfactual analysis. If you can’t at minimum make some kind of measurable connection between the data and the situation, it’s hard to run any kind of plausible counterfactual scenario. The influx of new types of data, the structure and siloing of orgs, and the lack of cross-discipline expertise make ranking this data nigh impossible, even on a curve.
Every time a new piece of data is introduced (which happens all the time), we have to—or should—refactor our scenarios and we almost never take the time to go back and actually do.
It also takes guts to re-adjust data significance. Just this past week, progress-cataloger, Derek Thompson from the Atlantic recently started putting weight on different data:
“In a cover story for this magazine several years ago, several years ago, I insisted that America suffered primarily from an invention recession—a serious deficit of new ideas about hardware. Now I think that I, like others, probably got this wrong… Progress is a puzzle whose answer requires science and technology. But believing that material progress is only a question of science and technology is a profound mistake.”
Not everyone has the ability to admit their cover story was wrong. Not every business leader has the time, guts, or expertise to re-attribute their successes or reassign weights to failures.
All of this of course, with the increasing speed of change, which means the window of contextual relevance for reapplication of insight is shrinking all the time.
The cost of quality counterfactual analysis is high and the opportunity for it to even be useful is low.
Counterfactuals Are Prevalent
Regardless, counterfactual-led causal analysis is prevalent throughout our industry.
Customers use counterfactuals
Consumers often use counterfactuals when evaluating both what they should buy and their past purchases. Last year I hiked Mount Adams with some of my much more experienced relatives. As we started down the trail, I realized my backpack was much larger than theirs. We hit the “Lunch Counter” (the traditional spot to stay the night), and my cousin unloaded his bag upon which I noticed his sleeping bag was much smaller than mine. He was packing a down sleeping bag. I enviously pondered, “if I had just bought a down bag instead of synthetic, I wouldn’t have had to lug such a huge bag all this way up.” Upon getting home, I immediately started researching which down bag I wanted to buy and made the purchase. A simple example, but a common story. Nearly everyone who makes purchases uses counterfactual reasoning in their decision making process.
Marketers use counterfactuals
Given the mindset of customers, it follows that marketers have been chronic counterfactual employers since the advent of modern advertising. There are two types of counterfactual thinking: upward and downward. Downward thinking is when you consider what could have been worse. Upward thinking is when you focus on what could have been better.
Upward counterfactual thinking is the name of the advertising game. The slickest of advertisers don’t say “buy our product and you will have x outcome”, their message instead is “if you had used this product in the past, your outcome today would have been x”.
Business leaders use counterfactuals
Attribution of success or failure is an exercise in counterfactual thinking. “Had we not done this, this would not have happened” or in other words “had we done x, we would not have achieved y.” Monday morning quarterbacking, retrospectives, anything with what “could/should have been done better if only” or what “could/should have gone worse if x had happened”. Assignment of blame and success usually includes counterfactual thinking.
Changing our thinking
I said I was tired of the multiverse; I’ve come to understand that I’m tired of the sloppy overapplication of counterfactuals. Humans typically use counterfactuals when something negative happens as a way to process it, ie “what if I/we had only”. Analysis of success often comes with fast assumptions of what led to success with very little review of other possible outcomes. Also people are prone to upward counterfactual thinking - how a situation could have been better, not how it could have been worse, which means potential pitfalls are often missed and risks are miscalculated for future engagement.
There’s also the relevancy bias, i.e. the improper application or lack of information about the significance of the inputs. Christopher Hitchcock, another bastion of counterfactual thinking, said to eliminate variables “that one is not willing to take seriously”. However, the criticism of this view is that it can still lead to bias. And to pile on: context almost always changes significance.
We also tend to use counterfactuals to explain outliers, because they’re hard to understand and potential what/ifs tend to be easy to imagine - to “leap out” as it’s said.
Outliers seem to be popping up everywhere. Outliers have become the mundane. Possibilities seem endless and therefore counterfactuals are being applied to solve just about everything.
Three ideas to course-correct:
1. Intentional application of counterfactuals. Be conscious when you’re using them and be conscious of how you’re applying them. There’s a whole world of counterfactual analysis systems that has been scrutinized and applied carefully in different contexts. For instance, in the world of security, counterfactuals are extra useful for thinking through how someone might circumvent or hack a system, but they can get out of hand and cause over-investment or confusion.
Counterfactuals (or what-if scenarios) are often employed as security arguments, but the dos and don'ts of their use are poorly understood. They are useful to discuss vulnerability of systems under threats that haven't yet materialized, but they can also be used to justify investment in obscure controls… We conclude that counterfactuals are a necessary evil in security, which should be carefully controlled. - Cormac Herley, Microsoft Research, 2015
Cormac is saying you need to make sure you have a good handle on the significance of your data before applying a counterfactual scenario to gain insight. This is as true for marketers as it is for security professionals, as it is for your personal life. It’s easy to make sweeping statements about success or failure solely due to a biased, unfounded, or uneducated understanding of a specific factor. See: the Derek Thompson example above. Another way to put it - we spend a lot on acquiring, adding, and discovering data, but perhaps we should focus more on validating and ranking the importance of the data we already have.
2. Diversity of thought and investment. Rather than obsess over nailing what happened or what will happen, have your eggs in a lot of baskets. When things shift, you will have a headstart on those who didn’t take a first step.
The two counter arguments to this are, first, that you can’t do a good job if you don’t specialize and focus, and second, that if you apply yourself to too many things you’ll burn out. To this I say - lean in and invest more where you have momentum or zeal, but make sure to run a “minimum viable product” in the places where you don’t get it or don’t have the focus. It’ll be a little bit of a stretch, but it’s better cut your main investments a little bit to not miss out on a channel that might blow up.
You might be criticized for a lack of initial ROI (internal) or for the unsophistication of your effort (external), however there’s too much upside of having data and learning from these channels that have potential even if it’s quite not clear to you yet.
Same for people. If you have the ability, make sure you keep outliers in your org that you don’t understand. Yes, do your best to make sure they’re smart, even if you don’t see things their way. Keep healthy discourse open. You’ll learn new things and stay ahead of what’s happening.
3. Focus on character. We cannot control the future but we can control our reaction to the present: who we are, who we will become. Our character with how we interact with the present is how we survive the unknown future.
Maybe we need to look back in order to go forward. In modernity, we’ve looked toward a future, a bright utopia, for our personal selves, for our businesses, and for all humankind. Cause and effect can be known therefore this bright future is possible. The dissonance is that the more we march toward that future - building, improving, inventing, and discovering, the more convincing it is that our future is uncontrollable. Pre-enlightenment, western society didn’t necessarily think of their relation to the future in the straightline unfolding of history or the evolutionary development of what was to come next. They saw both history and their future as an expression of their relationship with God, i.e. individual progress toward the moral and religious. To translate to the modern ethos, they cared about their character and their relationships.
Maybe that’s exactly what we need now. In a world where possibilities are endless, maybe the way to future-proof is to focus more on the who, instead of the how and the what.
The tactics that are employed to try and tame the future will often result in an either unsustainable or undesirable future, or maybe both. The tactics that are developed from a high focus on character are the ones that will drive us toward the world we hope for the future to be.
Conclusion
I’m not suggesting we abandon reason, or cause-effect logic to address pinpoint solutions. But perhaps the best way to address “Ballung” concepts (and the multiverse has oft been used to attempt this) is by focusing on who we want to be to the people around us in the present. And in business, the greatest Ballung concept is future viability and profitability.
Look at our most admired companies - REI, Eileen Fisher, Costco, Patagonia, etc. They’ve secured their future through yes, smart business decisions, but also by sticking by principles and caring about people. It looks and feels squishy to the bean counters and straight-line thinkers, but probably less squishy than the future that scares the hell out of them because they have no idea what’s coming next.
Better counterfactual analysis, diversity of thought, and our present character give us the best chance at that shining, bright future that the age of reason promised. Also this just might give us a chance to stop making movies about the multiverse. I’m in.
THIS ARTICLE IS FOR MEMBERS ONLY
Those things we shouldn’t say out loud? We say them on the private feed. Bi-weekly “after dark” podcasts and a members-only newsletter, just for subscribers.
Our research reports combine visionary thinking with data-backed findings from our own advisory panel, made up of leaders at brands you know and trust.
Query and prompt our vast archive of research, podcasts, and newsletters with a ChatGPT-like interface. Get exclusive access to Alani™, the AI-powered engine for Future Commerce, powered by BundleIQ.