Specific Values of Quality Objectives

[Mike S.]

Maybe it exists here and I just didn't see it, but I saw several threads about quality objectives but very little of anyone posting what specific quality objectives they use in their company/industry. Surely it varies based on many factors, but it would be interesting to see some others' numbers.

For example, AS9100 tells us we must measure on-time delivery performance. Many companies also set this as an objective (goal, target). In the last 2 companies I worked for, the objective for OTD was > 98% for an OEM and > 97% for a manufacturer of electronic sub-assemblies. Both companies were in the crossover high-end commercial/aerospace and defense world.

Anyone else care to share their company's objectives?

 

[Jen]

Mine is 90%, medical device industry.

 

[qualprod]

Maybe it exists here and I just didn't see it, but I saw several threads about quality objectives but very little of anyone posting what specific quality objectives they use in their company/industry. Surely it varies based on many factors, but it would be interesting to see some others' numbers.

For example, AS9100 tells us we must measure on-time delivery performance. Many companies also set this as an objective (goal, target). In the last 2 companies I worked for, the objective for OTD was > 98% for an OEM and > 97% for a manufacturer of electronic sub-assemblies. Both companies were in the crossover high-end commercial/aerospace and defense world.

Anyone else care to share their company's objectives?

In 9001, otd > 90% and have not moved up in 1 years

 

[Cari Spears]

For our on-time delivery, we have two major customers that provide monthly performance reports; we track them individually, and our goal is what their requirements are for their highest rating - Boeing uses Gold, Silver, Bronze, etc., and Lockheed uses Blue, Green, etc.

For customers that do not give us on-time delivery requirements, we use 98% for our internal measure.

 

[Steve Prevette]

I'll invoke Dr. Deming - and elimination of numerical targets. We do have a large suite of quality (actually contractor assurance) metrics at several sites that I support, but do use Statistical Process Control to analyze the metrics. Now, if the data are stable and predictable, we do make a value judgement of does the process need improving or not, but (thankfully) I don't have to compare the month's results to some arbitrary target.

 

[Pflanz]

I'll invoke Dr. Deming - and elimination of numerical targets. We do have a large suite of quality (actually contractor assurance) metrics at several sites that I support, but do use Statistical Process Control to analyze the metrics. Now, if the data are stable and predictable, we do make a value judgement of does the process need improving or not, but (thankfully) I don't have to compare the month's results to some arbitrary target.

I have been absent for some time from the Cove but see that you are still going strong. Totally agree with you invoking Dr. Deming and the elimination of numerical targets.

 

[Mike S.]

I "get" Deming's point, and the point about arbitrary targets. But telling the AS9100 auditor that "Dr. Deming says...." might not cut it when "AS9100 says...." you must monitor and measure things and evaluate these results (5.1.2.d; 9.1). So most organizations (at least in my experience) have targets established, either by their customers or internally, for things like OTD, yields, quality escapes, etc.

IMO the mistake way too many organizations make is focusing on the wrong measures (i.e. monthly shipment dollars) and/or reacting inappropriately to noise (common cause variation).

Anyway, it is interesting to see what various fields and companies set for their goals....if they do such things.

 

[Steve Prevette]

I can still have goals and objectives, but they can be expressed relative to common cause variation and special cause variation. I do make the point to many - if you don't do good analysis of your data, you will never figure out which metrics are "right" or "wrong". If you do good analysis, it will become quickly obvious which metrics are "right" or "wrong". For more - see this webinar I did a while back on how I apply objectives at the projects I support with Fluor, which includes two national laboratories (in two different countries).