Why scientific progress needs ideas, not just new methods (and definitely not an obsession with methodological advancement)

The obsession with methodological advancement in academic research is worth reflecting on. Is it justified? Are we progressing our fields by continually chasing new methods, or are we losing sight of what truly matters: advancing knowledge and making a tangible impact?

Fields like medicine and social psychology have made some of their most significant advancements using conventional methodologies. Clinical trials, statistical inference, and observational studies—none of these are cutting-edge anymore. Yet, they continue to underpin groundbreaking discoveries, from new treatments to understanding human behaviour. This suggests that intellectual progress doesn’t necessarily require reinventing the methodological wheel.

Take econometrics, for example. Early discrete choice models had notable methodological limitations, and their refinement over the decades was crucial. However, many of those methodological gaps have since been resolved. As the models improved, the need for entirely new methods naturally diminished. Today, we’re reaching a point of methodological saturation—where the marginal value of further innovations is shrinking. It’s harder to justify striving for methodological breakthroughs at the same rate as before. This isn’t to say methodologies shouldn’t evolve, but the pace of innovation doesn’t always need to match the pace of knowledge generation.

That brings us to the fundamental question: why do we develop new methodologies in the first place? The purpose of methodology is to enable scientific inquiry and advance knowledge. Once a robust method exists—whether it’s econometric models, machine learning algorithms, or statistical tests—the logical next step is to use it effectively, not to immediately move on to the next novelty. In social sciences, for example, simple statistical inference tests have been foundational for decades. Are they perfect? No. But then, no method is. Instead of discarding these tools in the endless pursuit of the “next big thing,” the focus should be on applying them meaningfully to generate new insights.

What’s troubling is the current pattern in academia: a researcher develops a new method, publishes it, and then… nothing. Few others adopt it, and even the original researcher moves on to the next methodological frontier in search of novelty and publications. This raises a critical question: who is the methodology for? If no one adopts it, if it doesn’t contribute to advancing knowledge or improving practice, what was its purpose?

There’s also the issue of diminishing returns. Just as in economics, where the benefits of investment decrease as more resources are poured in, the same applies to methodological innovation. Early advancements often bring significant improvements. But as we refine our tools, each new iteration delivers smaller gains. Take discrete choice models in econometrics. Early improvements addressed major flaws, but today, the most sophisticated versions often offer only marginal accuracy gains compared to basic models. These diminishing returns should prompt us to rethink our priorities. Are we chasing complexity for its own sake, or are we genuinely advancing our fields?

To be clear, methodological innovation is essential. Fundamental breakthroughs can revolutionise a field. But the attention of scientific communities and resources are finite. Shouldn’t we allocate them proportionally? Shouldn’t we ensure that the focus remains on generating meaningful knowledge, practical impact, and policy relevance, rather than inflating equations with unnecessary Greek symbols? Sometimes, the most impactful discoveries come not from flashy methods, but from ingenious problem identification, creative research design, and insightful interpretation of data.

The rich menu of existing methodologies often suffices to answer our questions. We don’t always need to overcomplicate. Science should not be about creating tools for the sake of it. It should be about using tools, old or new, to advance understanding and improve the world. To progress, we need to step out of our methodological bubble and recognise that true innovation lies in the pursuit of knowledge, not just the creation of another method.