Were you ever in an uncertain situation where suddenly you realized things were failing and did not know in which point they started to? Or did you suspect it and wanted to verify it? Or, perhaps, is this precisely what you want to avoid, and the way forward is to have a maximum control throughout the whole process?
Imagine yourself looking historical data from a very recent or unknown experiment. Let’s say, for example, that you want to analyze the impact of a nutrient you have incorporated into the diet of animals and you do it through stool and urine samples. Thus, you know it may be a good time to corroborate whether the hypotheses you had were true because, as time progresses, you have suspicions of some patterns. And you do it: you test it and find out does it work, its effects, and anything you want to know.
But it is not enough to observe, analyze and make conclusions from the data. That information must have been collected according to an objective and after a personalized preparation. Only then, we can contrast hypotheses, test ideas and cause-effects relations, compare with previous periods, detect errors, …
That is why Siagro was created. Long ago we detected a lack of standardized and automatized processes within the agri-food sector, which is why we decided to create a tool that facilitates the implementation of uniform working protocols and efficiency improvement methodologies. This is the only way we can deal with the variability generated by assignable causes that are within our reach to reduce, and thus increase the quality of our results.