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.

Quentin Gallea, Ph.D

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.