# Calculating Capability of Delivery Performance

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#### MSPPSB

I am trying to determine the capability (Cpk) of the overall manufacturing process at our facility to deliver on time to our customers. The data will be skewed since the upper limit can be no more than 100%. I did a transformation and ended up with a Fitted Johnson SI. The Cpk ends up .295 using a LSL of 85% and a target of 95%. Does it make sense to use Cpk or look just look at PPM and Sigma level?

#### rickpaul01

##### Involved in HankyPanky
I think you could use CPK if you treated ontime delivery with process/spec limits in days. i.e. 1 day early, one day late...

#### Bev D

##### Heretical Statistician
Super Moderator
No it doesn't make sense to use Cpk for on time delivery. Think about it from the perspective of those who need to improve it. How does that index provide insight into the level of performance that they can't get from a simple statistic: the average on time delivery for any particular time...you know your audience is just going to transform it back to that statistic anyway because that is a direct understandable measure of performance. Cpk is an abstract indicator.

But the real issue is where do you really want to spend your time: agonizing over an abstract index that only obscures the situation or providing insightful and actionable information on the system. The first analysis I would perform is a simple run chart. Then I would focus my 5 whys, process mapping and lean tools on improving the process that generates the long and variable cycle times.

In improving numerous onetime delivery problems I have never used Cpk and I've never missed it.

#### Miner

##### Forum Moderator
Consider using SPAN as a metric. You can use a modified Box Plot to generate SPAN bars and use it both as a metric and a data exploration tool.

#### Bill McNeese

##### Involved In Discussions
Good advice from the others. For tracking on-time, I plot the % on-time over time as run chart and include a Pareto diagram for reasons for late deliveries. Your average is what your process is capable of generating, e.g., 95% average on-time.

Your customer base is not homogenous. The probability of a shipment being on-time is not the same for all customers. If you are like most companies, major customers will have priority. Cpk calculations are meaningless here.

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