Conquering the Data Black Hole

Before QIS came along, we witnessed company after company suffering from what we referred to as the “data black hole.” Processes would move along at a rapid pace, generating huge volumes of data with no effective way to store, process, analyze or archive it. We realized that a typical scenario was for product test data to be kept on paper, rarely investigated or reported to operators, and certainly not presented in a graphical, easy-to-understand format.

Day to day, this black hole would go largely unnoticed – until a problem would arise. The only alarm to identify an issue was a button in the lab that would illuminate a red light – really; we can’t make this stuff up. And then everyone from shop-floor operators to top-floor management would be scrambling to figure out what went wrong.

To make matters worse, it was baffling to realize the incredible number man-hours required to ineffectively chase a paper trail. As laboratory technicians and operators poured over page after page of inconclusive data, trying to organize it into some sort of spreadsheet, frustration rose to an all-time high while profits, understandably, dropped to new lows.

With QIS, we changed all of that. First and foremost, we wanted to be sure QIS was easy to use, and it is. Though the technology behind it is highly advanced, providing in-built analytical routines that are statistically sound, it’s designed for non-statisticians to readily use and get the most out of. It is, simply put, the basis for statistical process control. Beyond that, it also removes the blinders from previous methods and provides for enterprise-wide visibility so that everyone is in the know at all times. Top-to-bottom, front-of-the-line to the end, now, instead of breeding panic and placing blame, with QIS you have the technology that fosters team work and eliminates errors. Black hole? What black hole?

Kevin Luxton
Founder and CEO 24+ years