{"id":6374,"date":"2024-10-03T09:00:00","date_gmt":"2024-10-03T07:00:00","guid":{"rendered":"https:\/\/getnave.com\/blog\/?p=6374"},"modified":"2025-11-11T12:57:11","modified_gmt":"2025-11-11T11:57:11","slug":"set-accurate-process-limits","status":"publish","type":"post","link":"https:\/\/getnave.com\/blog\/set-accurate-process-limits\/","title":{"rendered":"How Much Data Do You Really Need to Set Accurate Process Limits?"},"content":{"rendered":"
<\/div>\n

Hello, hello there!<\/p>\n

If you caught my last post, we dove into how to set boundaries around your flow metrics using natural process limits<\/a>. We explored how these limits help you distinguish between normal variation and signals that something might be going wrong with your process.<\/p>\n

Today, we\u2019re taking it a step further by answering a critical question: How much data do you actually need to calculate a solid baseline for those limits? After all, detecting a true signal depends on having accurate limits, and that accuracy starts with a well-chosen baseline.<\/p>\n

How Much Data Is Enough?<\/h2>\n

When calculating natural process limits, the size of your baseline dataset matters\u2014a lot. You need enough data to capture the typical variation in your process without including outdated or irrelevant samples. So, what\u2019s the magic number?<\/p>\n

Here\u2019s the rule of thumb: In most cases, you should use a baseline dataset of at least 10 but not much more than 20 points. Why this range, you ask?<\/p>\n

Well, it\u2019s all about avoiding two key mistakes:<\/p>\n