The Causal Mindset

Master causality to make better decisions

Why did Your last initiative succeed—or fail?

Everyone knows that correlation does not imply causation, yet most business decisions still rely on correlations, leading to costly mistakes and missed opportunities. Change the status quo and gain the tools to uncover causal effects, just like top tech companies such as Meta, Netflix, and Amazon.

Practical Tools  |  Immediate Application  |   No Jargon

Part I : Why Causality?


Understand why causality is so central for decision making and why traditional AI is not the solution.

Part II : Correlation and Causation

Finally understand why correlation does not imply causation, when and how we can measure causal effects.

Part III : The Causal

Mindset

Acquire a framework, the causal mindset, to question causality in real time  for real-life applications

Start the revolution today

Seminar [Essential]

🕒 Duration: 2 hours

📣 Format (online or on-site): 1h30 Talk + 30 min Q&A 

💬 Language: FR or EN 

🏷️  Price: 3000 USD on-site (Flexible online pricing, contact me)

🤝Group Size: No limit

Overview: The ideal format for a focused course, enabling your team to initiate change and start applying the tools the same day. Participants will leave with actionable insights and a vision for future possibilities.


Workshop [Hands-on]

🕒 Duration: 4 hours

📣 Format (online or on-site):  1h30 Talk + 30 min Q&A

                   1h practice + 1h debrief

💬 Language: FR or EN

💰 Price: 6000 USD on-site (Flexible online pricing, contact me)

🤝 Group Size: Ideally less than 20

Overview: A hands-on experience where participants actively practice techniques, work on their own questions, and receive personalized feedback.



Quentin Gallea, Ph.D

With over a decade of expertise in causal analysis, data science, and decision-making, Dr. Quentin Gallea turns complex insights into practical solutions.

KEY NUMBERS

Current Roles

2019 - present | Founder, Advisor and Keynote speaker

Strategic advice, technical consulting and educational content.

The Causal Mindset


2024 - present | Senior Advisor (On-Call)

Supporting strategic decision with my expertise in data science.

Enlighten Advisory


2018 - present | Lecturer (part-time)

Teaching data science in academia and beyond.

EPFL | University of Lausanne | University of Zurich | Graduate Institute | ISM University of Management and Economics

Resources

Daily posts on LinkedIn

Articles on Towards Data Science

GenAI-based App The Causal Mindset


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.