We've all been there - suddenly you have a brilliant idea for a new experiment and the excitement is high. You program the experiment, start collecting data, and, if you're lucky, the idea pans out and you start getting great results that are super interesting. You then realize you need to run a few follow-up studies to avoid some potential confounds or test alternative hypotheses, so you start collecting data for those as well. The problem? Chances are you had old data sitting around just waiting to be written up that is being ignored while you pursue this new exciting project. And in the end, it doesn't matter how many incredible projects you come up with if none of them ever get disseminated to the academic community. There will almost always be a new project that is more exciting than your old data.
I've seen this happen to people at every level (I'm guilty of it) but it seems to be particularly common amongst graduate students, who get excited about new data and ideas but find writing (and re-writing, and re-writing) not very appealing. The first time you get feedback on a manuscript draft from your supervisor asking you to almost completely revise it SUCKS. Getting negative reviews back from reviewers SUCKS. Being outright rejected from journals SUCKS. Lets not deny it, there's a lot about the publishing process that can be really disheartening. So a lot of the time it's easier and more pleasant to focus on these new, exciting ideas than to deal with a manuscript for data collected a year ago (or more, in my case - I'm trying to get papers done for 5+ year old projects).
Oftentimes these projects are presented at conferences as posters or talks while still in their exciting phase, but then new things come up and the manuscript writing gets put on the backburner. This is particularly problematic if someone at the conference gets excited by the work, starts following up on it, and publishes their own paper that essentially scoops you. The longer your data sit unpublished, the more likely that someone else will either do the same thing or do some related study that makes your data entirely unpublishable.
The moral of the story - balance time between new projects and finishing up old ones. It's great to be excited by research, but if you don't finish anything you won't get the credit for all your great ideas. Having run 30 experiments doesn't make you employable - but publishing 15 papers from those experiments will. I once heard some great advice, which was to always have one project at each stage in the pipeline (e.g. on project you're collecting data for, one that you're analyzing, one that is being written, one that is submitted) and not to start a new project until the old projects have moved up in the chain. That way you always have one manuscript that is in progress and you don't get backlogged in data collection. I'm sure there are lots of other ways you could organize your time, like doing all data collection in the first half of the semester and dedicating the end of the semester (when participants are notoriously crappy) to writing. No matter how you balance it, the key is to make sure that things get published, because in the academic world your projects mean nothing until they're in a peer-reviewed article.
Now I'm going to try and take my own advice and get some writing done.
