By: Taran March @ Quality Digest
06/23/2020
What is quality intelligence, exactly? It’s more than marketing spin. More, even, than the sum of its many control charts. It’s not collecting data simply to further go/no-go actions. And it doesn’t mean turning the cognitive wheel entirely over to artificial intelligence, either—far from it.
We might think of quality intelligence as a natural progression of quality control. It’s both granular, in that core quality tools underpin it, and forward-looking because quality data are used to improve not only products and processes but also operational performance. It’s very deliberate in that its goal is to wring the maximum value possible from reliable data.
To do this, quality intelligence employs four key tools: ensuring compliance, grading collected data, exploiting software, and implementing data strategically.
Ensuring compliance
People often assume that compliance applies solely to government or industry standards, but the term surfaces in many shop-floor conversations and processes. For instance, there is compliance to limits: Are data in specification? Are the appropriate statistical rules being met? There’s also compliance to procedures: Are people collecting data in the right way, and on time?