Continuous process improvement does not always seem like a realistic task during what already feels like overly busy days. Work days (and nights) are spent conforming to customer compliance standards, investigating customer complaints, or struggling with data collection hardware and software.

Tasks pile up, demands increase, and products become more diverse. It might seem like the demands on your time will always outpace your ability to fulfill them. How do you find ways to create real value?

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The first step is to look closely at how you are collecting data. Typically, quality data is sampled during the process to determine whether the product or part is in compliance. This data is often appended to traceability information, such as a lot, purchase order number, or work order number. This is the bare minimum for satisfying customer needs and to be able to respond to a recall.

Let’s look at what you can learn by adding machine, part, and shift to increase your data’s resolution and make it more valuable.


One or more machines are ultimately responsible for certain quality criteria measured on a given part. Capturing the machine as an identifier (e.g., giving it a designation such as an asset number rather than simply "Line 1") gives you increased resolution of the process.

If machines are switched out, upgraded, or replaced, you can focus on the process performance of each one individually. This enables you to provide a more accurate benchmark of your process.

Remember, the process can be defined as you see fit. Adding resolution to your data collection gives you more options.


You are probably collecting a "part" with your quality data. However, you may want to consider adding more detail.

For example, assign a work in progress (WIP) part number at different stages of production. This will enable comparative analysis at multiple levels, giving you greater resolution for recalls. It will also allow you to pinpoint not just under-performing products but also specific problem areas in your process with more certainty.


There is always a human component to your process performance. Appending shift to quality data is not the same as simply noting the time that a check was performed.

Adding a shift indicator to your data will allow you to aggregate data by shift, regardless of the specific date and time the data was collected. Try looking at the Cpk of a given process/part/test combination. Now look at the same data by individual shift.

What if Third Shift performance yields a Cpk of 0.87 while First Shift yields 1.34? The answer could help you quickly identify issues such as understaffing or inadequate training.

Get More Value from the Data You Collect

Process improvement is all about collecting the right data so that you can see your process not just at a high level but also with high resolution. Comparative analysis of quality data by machine, part, and shift can help you quickly identify areas to improve, rather than tackling too many variables at once.

It’s time to start making your quality data truly valuable.

InfinityQS solutions are purpose-built to enable even greater visibility—across products, processes, and plants. Learn how our patent-pending Data Stream Grading feature is radically changing the way organizations make transformative, data-driven decisions.