Delivering the highest quality product at the least cost is among the top priorities for manufacturers. When it comes to addressing problems in the actual production process, manufacturers have two options: being reactive or proactive. Most companies want to be proactive but find it difficult for numerous reasons. Manufacturers strive to turn prevention into a strategy that manages risk via established, measurable goals. Measuring the cost of quality (COQ) has been an elusive quest for many organizations. This paper describes four principles to apply to in-process operational data to overcome perceived obstacles to measure and manage the cost of quality. A misconception about both of these is that they are burdensome and administrative-intensive. They are not. The trick is in smart, proactive design rather than reactive action based on a disparate collection of data.
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