Over the past 20 years, academia has increasingly been managed through metrics such as funding, staff numbers, publication counts, and citation scores, based on the assumption that more inputs automatically produce more outputs.

Using two decades of institutional data from the IBME, this presentation challenges that logic.

Through correlations, multiple regressions, and Granger causality analyses, we show that the relationships between resources and results are weak, non-linear, or entirely absent. Publications precede grants, not the other way around; impact emerges only after long delays; and financial inflow is decoupled from performance.

Academia behaves not like a factory but like an ecosystem: path-dependent, sensitive to early initiative, and shaped by slow, cumulative processes. The talk concludes by rethinking what academia should stand for in the next 20 years, and how institutions, funders, directors, researchers, and students can align incentives with meaningful, sustainable scholarly growth.