I’ve got a confession to make to my fellow synthetic chemists: I’ve never really been all that obsessed with yields. You know that old saying about yields - there are only two kinds, enough and not enough - it’s been said so many times that it’s practically become a cliché. But, clichés are clichés because they are true. Sometimes.

Now, don’t get me wrong, I understand that a higher yield is generally better for all sorts of reasons - like economics and the environment. But here’s the thing: the yield we attach to a reaction is influenced by a whole bunch of factors, most of which we don’t really control. Take extraction volume, for example. It can have a big impact on yield, but how often do you see it reported as an experimental variable? Almost never. And it’s even rarer to see it explored as a parameter that affects yield.

This obsession with yield often leads to another problem in synthetic papers: the relentless pursuit of reaction optimization. In theory, this means tweaking various reaction parameters to maximize the yield of a product. Recent chemical methods comprise a large number of reaction variables, however, and the field of design of experiments tells us that proper reaction parametrization would require n! conditions for n reaction variables. This blows up quickly. So, instead of doing the right thing, we often take the easy way out - changing the solvent a few times, adding an additive, or adjusting the reaction conditions in minor ways. The result? A table of numbers, but no real insights. Does the solvent’s dielectric constant actually correlate with yield? Is the water or oxygen content in solvents affecting yield, sometimes negatively, sometimes positively? We’re left with more questions than answers.

What’s even worse is that we often stumble upon reaction conditions by accident and then explore a narrow range of parameters around those accidental conditions, like Mickey Mouse drawing a bullseye around his randomly released arrow. It’s not exactly a scientific approach.

Instead of fixating on yield, I propose that we shift our focus to understanding the factors that truly drive yield in a reaction. Are there any unwanted by-products? If so, what are they, and can we adjust reaction rates to minimize them? Is reagent or catalyst inactivation leading to low conversion rates? Is the final product unstable under isolation conditions? What is the stereochemical model that can help us make sense of the selectivity numbers? These are all specific and unique questions for each reaction, and by lumping them all into a single yield number, we risk losing sight of the essential features of the reactions we’re studying. Let’s look beyond the numbers and dig deeper into the chemistry.