Data can be either qualitative or quantitative. Qualitative data characterize things that are sorted by type, such as fruit (oranges, pears, apples, …), defects (scratches, burrs, dents, …), or operators (Jim, Harry, Martha, …). Qualitative data are usually summarized by counting the number of occurrences of each type of event. Quantitative data, on the other hand, characterizes things by size which requires a system of measurement. Examples of quantitative data are length, time, and weight.
There are 5 steps in the data collection process:
1. Clarify your data-collection goals. Make sure the data you collect will give you the answers you need. You can use these questions to help you identify your data-collection goals:
- Why are you collecting data?
- What questions do you want to answer?
- What will you do with the data?
- How will the data help you?
- What patterns or relationships might you want to explore?
Consider how you can possibly stratify the data. Think of the following categories:
- Who – which people, groups, departments, etc. are involved
- What – relevant machines, equipment, products, services, etc.
- Where – the physical location of the defect or problem
- When – time of day, day of week, or step of the process involved