The problem: odd results with no obvious cause
When a run behaves differently, the cause is often in a lot number. If lots aren't recorded on the experiment, there's nothing to compare.
The run came out thicker than its control, and the formulation looks identical. Without lot numbers on the experiment, the team has to dig through inventory logs or memory to find what was different.
What this demo shows
- Read one experiment's formulation and results, with every ingredient, amount and lot on one record.
- Compare past runs.
- Trace the difference to the resin lot.
Why it matters
Lot-level detail on every experiment turns a puzzling result into a comparison. When ingredients, amounts and lots sit on one record, the difference shows up quickly.
Finding the cause in the records, without a spreadsheet export, means the team can act on it the same day and flag the lot for future work.
See it with your own data
This video is part of LIMS for R&D. To see how it would work with your own formulations and records, request a demo. Our team replies within 30 minutes during business hours.
Read the transcript
A useful result keeps its context. Here is one experiment. Uncountable stores each experiment as structured data. Every ingredient, its amount, and the resin lot. The results sit on the same record. Viscosity, gloss, haze, and yellow index. Why does this run read thicker than the control? Compare puts past runs with the same inputs beside it.
Same inputs, different resin lot. Lot 3018 runs thicker and yellower than lot 2291. Connected records answered the question with no spreadsheet export. Ask every vendor to show you this path on your own data.
