“The Causal Mindset” is a structured approach to understanding and applying causal analysis in an accessible and practical way to improve decision-making in business and beyond.

Why it matters?

Most of our decisions are based on causal relationships, whether assessing past decisions ("What was the effect of including ads on Netflix on revenue and subscription growth?") or making new ones ("What will happen if we remove Sam Altman as OpenAI CEO?"). Yet, causal inference remains niche, and relying on correlational analysis or intuition can lead to costly mistakes (see practical applications section for examples). Every time we hear "because", some causal assumptions are being made, and we could or should use causal inference to question those assumptions. While many people know that “correlation does not imply causation,” very few understand how to move beyond mere correlation.

What’s new?

The good news is that there is a scientific way to study cause and effect known as causal inference.

However, traditional methods of mastering causal inference can take years of study and precise experimentation. This timeline is not compatible outside academia where quick decisions are often necessary.

To address this issue, “The Causal Mindset” allows decision makers to apply causal inference principles to improve decision-making and critical thinking in real time, without needing a Ph.D. or complex mathematical equations.

This method teaches core concepts and then provides a framework to question causality from past events and evaluate the potential effect of future decisions. The Causal Mindset framework can be applied by asking five questions: 1. What is the counter factual? 2. Is there something else? 3. What is the direction of the bias? 4. Can we extrapolate?

This methodology enhances strategic thinking by incorporating a more nuanced understanding of causality, which, though crucial, is not the sole element in the decision-making process. Concepts of causal inference structure the way we tackle complex questions through systems thinking, thereby reducing the risk of blind spots or decisions backfiring. Whether you are in business, government, or a global institution, understanding causality is crucial for navigating uncertainty and achieving your goals.

Additionally, it includes a free companion app (thecausalmindset.com) that automates the application of the method, further enhancing its practicality and accessibility.

Practical Applications

Business Application: Marketing Strategy:

Imagine a company observing an increase in sales after their last marketing campaign. The company decides to double the budget and follow the same strategy. Surprisingly, no effect on sales is observed this time.  Maybe the increase in sales was not caused by the marketing campaign but rather by a simultaneous change in the competition's behavior. It was just correlational. Causal inference reduces the risk of misguided investments and refines marketing strategies to focus on true causal factors.

Institutional Application: Public Health Policy

At the beginning of the COVID-19 pandemic, a French “expert” argued that lockdowns were counterproductive, using a graph depicting a positive relationship between the number of deaths and the stringency of the lockdown measures. This correlation was mainly affected by a problem called “reverse causation”: when the situation was critical in a country, the government would impose stronger measures. The Causal Mindset helps not only to spot this issue quickly but also allows reflection on how to approach a causal measure.

Global Development: Economic Aid

While the GDP in Sub-Saharan Africa since 2000 increased by approximately a third, the development aid received per capita more than doubled. These figures are often used to claim that developmental aid is useless or counterproductive. However, to properly assess the effect of developmental aid, we need to evaluate what would have happened without it. The GDP could be much lower or higher. This is a central concept in causal inference and in The Causal Mindset called the “counterfactual.” The first step of the method focuses on the choice of an adequate counterfactual.

Environmental Policy: Renewable Energy Initiatives

Questions related to sustainability require systems thinking and should be carefully evaluated, as they can easily become counterproductive. To measure their positive impact, the company used life cycle analysis (evaluation of the environmental impact from raw material extraction to end of life and waste management), revealing that driving an e-scooter was less polluting than driving a car. But there is a catch. E-scooters have been shown to substitute mainly public transportation or even walking, which are more environmentally friendly than e-scooters. Again, this issue arises from a problem in the comparison being made, specifically the choice of counterfactual. 

Advisory and Trainings

I help you apply these methods to solve your challenges or train you and your team to acquire this causal mindset. Whether you need tailored advisory services to integrate causal analysis into your decision-making processes or comprehensive training programs to develop your team's skills, I am here to support your journey.

Explore my services [here]

Read the testimonials [here]

Start learning with my online resources [here]

Use my companion free App to apply my method on your own questions [here]