It is fine, indeed should be encouraged, to put some papers in the system that don't have formal data but do record common-sense observations. If people don't like them, then they can trump opinion with data in the scientific process.
That's how some steps of the science work, specifically the empirical studies. Empirical validation, falsifiability, and repeatability is all in that ball-park. But it's a part of the process and not all of it.
If that's the only thing you want to consider, sure. As a layman it's probably a good principle, and more so in engineering. But you'll have to shave off some significant works of science from history if you do that.
Next, the acceptability of journal papers without conclusive experiments varies across fields. In some fields, such as observational sciences (e.g., astronomy, ecology, sociology), observational studies are common and valuable contributions to the literature. These studies often involve collecting and analyzing data from real-world observations, surveys, or existing datasets without the need for controlled experiments. In such cases, it is perfectly acceptable to publish papers based solely on observational data.
When you say, "is not enough," the question I respond with is "enough for what?" It's fully acceptable to publish a paper with observations in order to stimulate interest and encourage further research in the area. It's not necessary for a journal to require final results.
Finally, consider some of these famous and important papers which were published as observations without conclusive results. Should they have held back and waited until conclusive results were available?
1. Edwin Hubble's "A Relation between Distance and Radial Velocity among Extra-Galactic Nebulae"
2. Albert Einstein's "The Foundation of the General Theory of Relativity"
It is fine, indeed should be encouraged, to put some papers in the system that don't have formal data but do record common-sense observations. If people don't like them, then they can trump opinion with data in the scientific process.