But his biggest challenge was in scaling up his organization to deal with the ton of chances he desired to address. Together with its massive investments in gene sequencing machines and computing resources for data analysis, BGI had built a large cadre of data scientists who could develop and run applications to sift through the mountains of genetic data that were being created daily.
But other questions were raised by the approach. Could folks trained in conventional disciplines of animal husbandry, and botany, biochemistry only make use of the BGI sequencing platform as a black box, much as men and women in other sectors relied on a modular division of labor as well as specialty? Or did it take the type of cross-training and cross-boundary work in? Could the data scientists in BGI's "factory" grow sufficiently to get the science, and was that now even necessary?
PUBLICATION DATE: February 28, 2014 PRODUCT #: 614056-PDF-ENG
This is just an excerpt. This case is about TECHNOLOGY & OPERATIONS
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