Mastitis is assessed by SCC level and counting the number and severity of clinical mastitis cases. However, since both are measured after the mammary gland infection has already occurred, they are also "lagging indicators". Some potential "leading indicators" are not always high-tech. Cow hygiene score and bulk tank milk culture results are certainly "leading indicators" of environmental mastitis and are already being used. Teat end condition as well the completeness and consistency of teat dip application are also important leading indicators of mammary gland health. Unfortunately, these data are sporadically collected and not stored in a form for easy and effective analysis. Here again, emerging technology is coming to our rescue. Smartphone and tablet on-farm electronic data collection and "cloud based" analysis software are now making possible sophisticated use of these valuable on-farm observations.
Moving closer to the causes of problems, the leading indicators of evolving problems are often more general in nature and not specific to any specific disease or condition. Change in milk production, for example, is the most sensitive signal of biological status. Research here at the University of Minnesota has shown that statistical process control analysis of daily milk yield alone detected the onset of disease up to 8 to 10 days prior to the clinical disease. The difficulty is that without specific symptoms of a disease or condition, what do you treat? Treatment is not the goal nor is it a victory. It is a failure. My suggestion is to shift the focus to "treating" the production system, alleviating pre-disposing causes preventing sub-par health and productivity altogether.
I am not advocating that we abandon many of our traditional measures of cow/herd performance. A balanced approach seems best. However, the scientific literature is full of examples of potential leading indicators of sub-par health and performance that are yet untapped and not routinely tracked at most farms. But as technology improves and more sensitive "leading indicators" of both cow and herd performance evolve, we need to utilize them. In the meantime, a good starting point is to review the reports and metrics you use today. Justify why you're measuring what you're measuring. If you think you're already using leading indicators, challenge them. Do the metrics provide insight into the causes of potential future problems or just a confirmation of past performance? Stay tuned ― help is on the way.