Analyzing Continuous Data with a Maximum Possible Value

You can set a maximum or minimum for control limits within the Minitab generated SPC charts.

Please consider SPC is not always the best tool for all situations.

If that’s the case then the issue should be framed and analyzed in terms of what you mean by on-time delivery.

1. What do you mean by on-time delivery? – need an operational definition here
2. What does your customer consider to be on-time delivery? – need an operational definition here too.
3. What do you need to take into account to adjust the on-time delivery definition for different delivery scenarios?
a. If it is the physical delivery of a product to a company platform – how are you addressing things like, size of load, distance needed for travel, etc.
b. If it is a matter of delivering something electronically – how are you adjusting for things like task difficulty, resource allocation to address a problem, etc.

After you have your definitions and an understanding of how your system is set up for production you should be able to start looking for ways to assess your on-time delivery and also identify ways to improve it.

I agree with grazman — if you can track the actual times each shipment left your dock or arrived at your customer’s dock (depending on who is responsible for freight), you can get a lot more information with less data than %OTD. You would set each shipment’s target as zero, and record minutes before (-) or after (+) the target.

If you don’t have that data available, you can also use a P-chart for the inverse of %OTD — that is the proportion of late deliveries. (You could use a P-chart directly for proportion of on-time deliveries, but since most people associate P-chart with proportion defective, interpretation would be easier for proportion of late deliveries.)

• This reply was modified 1 year, 4 months ago by Chuck White.