The science of navigating business uncertainty

If they want to approach decision-making scientifically, entrepreneurs who have identified a problem that they believe is worth investigating should develop a theory of the problem and articulate hypotheses that logically flow from that theory. These hypotheses should, in turn, be tested through experiments and, if proved wrong, be reformulated.

In a seminal paper based on a small-scale randomized control trial (116 startups), back in 2020, we highlighted that entrepreneurs behaving like scientists are more “precise,” meaning that they are less likely to continue projects that seem good but aren't and more likely to terminate bad projects and pivot radically (i.e. to make major changes in the direction of their businesses).

The conclusion was drawn by comparing the results of entrepreneurs who were taught a standard entrepreneurship program and entrepreneurs who were taught the same program and were additionally encouraged to adopt the scientific method.

Cosimo Cecchini, a cofounder of Osense, a start-up focused on technology for sustainability, and a participant in the scientific entrepreneurship program, said to the Harvard Business Review that participation saved them from developing a non-viable idea.

“Our first start-up idea was for a peer-to-peer product-rental service,” he explained. “We used the scientific method to try to validate our idea that people would rather rent than buy products and that the owners of the products would make money from the rentals. To do that, we conducted field interviews asking whether people would be inclined to reuse other people’s goods and whether people had goods they wanted to rent out. We conducted approximately 25 interviews, but after only five, we realized this wasn’t going to work.”

Osense is currently supporting companies to optimize their sustainability strategies and operations.

Thanks to funding from the European Research Council, we’ve been able to replicate the 2020 experiment on a larger scale. We altered the original design and context incrementally to understand how these changes affect the original detected impact.

The second randomized control trial was conducted in the same context as the original study (Milan, Italy) but in a different year (2017). The third was conducted in Turin, Italy (2018), to reach a potentially different population of “tech” entrepreneurs (Turin is a technological hub). The fourth was conducted in London, United Kingdom (2019), and extended to a broader population that did not include only early-stage start-ups.

Overall, we analyzed data for 759 firms over time.

Our results align with the original study, demonstrating the robustness of the scientific approach across contexts. The larger sample size allows us to identify new effects, including:

• Idea Termination: We find a positive effect of the intervention on idea termination across all the experiments.
• Radical Pivots: Firms that adopted a scientific approach made a few strategic shifts, as opposed to either not changing or constantly changing their strategy. We suggest that this is due to the scientific approach helping entrepreneurs be more efficient when searching for valuable ideas, as well as being more careful in selecting those ideas.
• Performance: Our larger sample improves the precision of performance effect estimates. Restricting the analysis to the top 25% of revenue generators, we found that startups adopting a scientific approach generated €28,000 more than the control companies did over the course of the experiment.
• Strength of the effect: We show that the actual adoption of the scientific approach, measured by an index of scientific intensity, is crucial to the detected effects.
• Consistency: Similar effect estimates across randomized control trials underscore the approach's consistent benefits.

Our study makes two significant contributions. Firstly, it reinforces the credibility of preliminary findings through large-scale replication, addressing sensitivity to scale and contextual variations. Secondly, it supports the emerging research on the scientific approach to entrepreneurial decision-making, providing robust evidence of its teachability and associated performance benefits.

Arnaldo Camuffo, Alfonso Gambardella, Danilo Messinese, Elena Novelli, Emilio Paolucci, Chiara Spina, “A scientific approach to entrepreneurial decision-making: Large-scale replication and extension”. Strategic Management Journal, Volume 45, Issue 6, June 2024, Pages 1209-1237. DOI: https://doi.org/10.1002/smj.3580.

“Why entrepreneurs should think like scientists,” Harvard Business Review, July-August 2024 issue.