Data Collection
As part of the Foresight research team, we owe quite a bit to our first group of participants. While today we use a powerful-but-simplified two-page data collection instrument we affectionately call “LabRAT” (Laboratory Reporting and Analysis Tool), in the beginning we asked our participating labs to provide pages upon pages of data for our initial evaluation. It was an onerous task, and we are forever grateful they were up to it. It helped us refine what we needed to collect, focusing on key metrics rather than the entire universe of information. It also exposed some unexpected areas for improvement, most notably in the area of language.

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The Language Barrier
When we first began collecting data for Foresight, we ran into a few unexpected problems. When we talked about the most basic elements, such as a “case” or “test,” we quickly realized that everyone in the room had a slightly different definition. As you can imagine, this posed some problems for accurate data collection. It was enlightening to learn that standard definitions didn’t exist. We spent more than a year-and-a-half working out exactly what every term meant to be sure we were all speaking the same language. Our group of 15 or so scientists and lab directors from all across the United States and Canada were infinitely patient and willing. Sitting together every few months to discuss our goals, we were able to create succinct and agreed-upon definitions that formed the basis of our research data collection.

Developing Best Practices
Once we had definitions in place, we dove into the issues at hand. These issues were no different than the challenges that persist today: Reducing backloads, making sure each lab group had enough but not too many professionals to do the job at hand, ensuring the best mix of scientists/analysts/ support staff, and dealing with generational and other interpersonal issues.