A pharmaceutical company with global operations recently received a warning letter for failing to properly investigate a batch failure. Among the potential consequences: any pending drug applications listing the affected facility may be stalled. Of the worries that keep pharmaceutical executives up at night, receiving such a letter is high on the list. With the clock ticking, company personnel took stock of what they faced. Their blockbuster medication was manufactured in an ecosystem involving three countries. Was the problem really at that facility, or upstream at one of the others? The answer, of course, was in the data, which was disparate and came from different parts of the world. Moreover, this company’s data was mostly in paper form, and the few electronic files on hand were not contextualized. The organization faced a daunting task, with its billion-dollar-a-year product — and other products and business — at risk. But the story did not have to play out this way. This company could have identified the source of variation in real-time with the right data infrastructure.