It’s normal. You are crafting a well-designed experimental process just as a product designer might craft a new product concept. Experimental design is the heart of the scientific method. Getting it right means you'll get your results data faster with less errors, and have more reusable processes and data that you or others can build on.
Riffyn makes what you do in the lab completely transparent and explicit. It’s possible that you’ve never had to consider your processes in such explicit detail before. That transparency also causes you to consider questions you may never have considered before. Like “why do we do step X?” and “what is the allowable range of concentrations for that reagent?”
But that consideration is good. It’s causing you to think about how to improve, and even lean-out your process before you even collect data.
Also realize that when your are designing an experimental process, you are probably solving a multi-dimensional problem without realizing it. I.e., you are solving for:
- the best / leanest process design that is easy to follow in the lab
- the best experimental design (sample and replication structure)
- a design that effectively communicates your process to others and is reusable
- a design that facilitates good data analysis
That’s a lot to think about, but we encourage you not to solve all those problems at once. All design, in any field of human endeavor, is iterative. Riffyn lets you iterate without breaking the integrity of your historical data.
So don’t be afraid to make a mistake, you can fix it and make it better later. And you can reach out to firstname.lastname@example.org for help.