Extraordinary claims require extraordinary evidence - Carl Sagan
We need to have a brief chat about the big elephant in the room. It is everywhere around us - on social media, TV, work, government, business. And it's becoming more pervasive and growing every day.
Yup, let's call it what it is. Bullshit.
Bullshit is everywhere, and especially where decisions are being made. My experience is that the higher up in management you are, the bigger the bullshit, and this is especially true for the topic of strategy. In this post, I'm going to tell you about bullshit and why it's even worse than lying, why there's so much bullshit in business and the boardroom, what tools bullshitters use, and how you can detect and uncover bullshit and bullshitters in three easy steps.
What is Bullshit and Who Are Bullshitters?
Philosopher Harry Frankfurt made a fascinating distinction in his influential essay "On Bullshit": bullshit is actually different from lying, and in many ways, it's worse. Here's why: while liars at least acknowledge the truth exists (they're actively choosing to deviate from it), bullshitters are completely indifferent to whether what they're saying is true or false. They simply don't care.
As organizational theorist André Spicer explains in his book "Business Bullshit," bullshitters are more concerned with impressing or persuading their audience than with truth or accuracy. Their goal isn't to deceive per se - it's to win the argument or advance their agenda, regardless of truth.
Consider the classic corporate strategy presentation: "Our synergistic approach leverages cross-functional dynamics to drive paradigm-shifting innovation across vertical markets." It sounds impressive, but what does it actually mean? Nothing concrete. That's bullshit in its natural habitat.
Why Is There So Much Bullshit?
Several factors contribute to the proliferation of bullshit in modern society:
Information Overload: We're drowning in data and expected to have opinions on everything
Complexity: Modern organizations and problems are increasingly complex
Pressure to Communicate: There's constant pressure to produce content and demonstrate expertise
Legitimacy Needs: Organizations and individuals feel compelled to appear knowledgeable and authoritative
Uncertainty: In rapidly changing environments, people often resort to bullshit when they lack real understanding
Take the rise of AI strategy consultants as an example. Many have limited deep understanding of AI technology but feel compelled to position themselves as experts, leading to an explosion of impressive-sounding but substanceless recommendations.
The Bullshitter's Toolbox
According to researchers Carl T. Bergstrom and Jevin D. West, authors of "Calling Bullshit," modern bullshitters rely on three main tools:
Language: Using complex jargon and buzzwords to obscure simple (or empty) ideas
Statistics: Manipulating numbers to support predetermined conclusions
Graphics: Creating impressive-looking visualizations that may misrepresent data
Common Bullshit Techniques
1. The Percentage Game
Let's break down a classic example of statistical manipulation. A Starbucks coffee contains 415 mg of caffeine per 20 ounces, making it approximately 0.07% caffeine by volume. This means that coffee itself is 99.9% caffeine-free. So when you see hot chocolate proudly advertised as "99.9% caffeine-free," you're looking at a masterclass in misleading marketing. The claim is technically true but completely meaningless - you could say the same about regular coffee!
In strategy work, we often see this with market share claims. A company might boast about "500% growth in the enterprise segment" without mentioning they went from 2 to 12 customers in a market of thousands.
2. Correlation vs. Causation
One of the most dangerous forms of bullshit involves confusing correlation with causation. Consider a real strategic blunder: A retail chain noticed their stores with better customer satisfaction scores also had higher sales. They invested millions in customer service training, only to discover later that both metrics were actually driven by store location - wealthy areas naturally had both higher sales and more satisfied customers.
3. Selection Bias
Selection bias is particularly evident in both scientific research and machine learning. In machine learning, your model is only as good as your training data. If your training data isn't representative of the real world, your model will inherit and potentially amplify these biases.
For example, an AI recruitment tool developed by a major tech company had to be abandoned because it showed bias against women. Why? Because it was trained on historical hiring data from an industry that had historically favored male candidates. The system didn't create the bias - it amplified existing selection bias in the training data.
4. The P-Value Problem and Goodhart's Law
In scientific research, p-values (statistical significance measures) are often manipulated through "p-hacking" - selectively choosing data points to achieve desired results. This relates directly to Goodhart's Law, which states: "When a measure becomes a target, it ceases to be a good measure."
This is particularly relevant in business and strategy. When organizations focus too intensely on meeting specific metrics or KPIs, people often find ways to game the system rather than achieve the underlying objectives. A classic example is Wells Fargo's account scandal, where pressure to meet new account targets led employees to create millions of unauthorized accounts. The metric became the target, and the true objective - serving customers - was lost.
How to Spot Bullshit: The Three-Question Test
When evaluating any claim or information, ask these three essential questions:
1. Who is behind this information?
2. How did they obtain their data?
3. What are they trying to sell or prove?
Additional Red Flags indicating bullshit
Overwhelming complexity in simple explanations
Perfect correlations or too-good-to-be-true results
Cherry-picked data points
Impressive-looking graphics that don't actually convey meaningful information
Appeals to authority without substantive evidence
People fail to simply answer a question or provide a definition of what a metric measures
The Path Forward
While we can't eliminate bullshit entirely, we can get better at recognizing and calling it out. This is particularly crucial in strategy work, where bullshit can have devastating consequences. Strategy is foundational work - it sets the direction and framework for everything an organization does. If your strategy is built on bullshit - whether it's misleading market data, false assumptions about customer needs, or misinterpreted competitive analysis - everything that follows will be fundamentally flawed.
Think of strategy like the foundation of a building. If you build on soft ground (bullshit), the entire structure becomes unstable and might eventually collapse. We've seen this play out countless times in business history, where companies made strategic decisions based on wishful thinking or manipulated data rather than hard truths, leading to spectacular failures.
Consider Kodak's strategic response to digital photography. Despite inventing the first digital camera, their strategy was built on the bullshit assumption that people would always want physical photos because that's what they were used to. This fundamental misunderstanding, dressed up in impressive-sounding market research and customer insight reports, led to one of the most famous strategic failures in business history.
Remember: in strategy, uncomfortable truths are far more valuable than comfortable bullshit. Your strategy needs to be built on solid, verifiable facts and clear-eyed analysis, not on impressive-sounding but empty assertions or manipulated data.
As Carl Sagan famously said, "Extraordinary claims require extraordinary evidence." In a world increasingly dominated by bullshit, critical thinking and skepticism are more important than ever. The goal isn't to become cynical, but to become more discerning. By understanding how bullshit works and the tools used to create it, we can better navigate our information-rich world and make more informed strategic decisions.