Does It Get Easier As You Get Better? It Shouldn’t

Throughout my career I’ve had the pleasure of meeting colleagues from a very large variety of manufacturing cultures. Sometimes I talk to people that work in a “mass” environment with poor performance, and I hear about how good it must be to work in an efficient workplace, with relatively good performance. I always get the questions about how easy it is.

Let me tell you…it’s not easy, and by the way – it shouldn’t be.

You might ask me why… and here are some reasons.

The name of the game is continuous improvement. If your organization doesn’t get better, then you aren’t  going anywhere. You maintain your improvements be continuously revising your metrics to reflect your improvements. Your plant may start at 50% production efficiency, then move to 75%, then to 90%, then to 95%, 97%, 99%, 99.5%, etc…how hard do you think it is to go from 99% to 99.5% production efficiency? It’s very difficult – probably more difficult than going from 50 to 75%. No doubt, you’re doing much better at 99% than you were at 50%… but then again, the 50% number doesn’t matter anymore, since your system has grown to be much more capable than that.

Now, imagine what it’s like to have this approach with all of the organizational metrics.The unique part about all of this is that this type of culture grooms people into constantly thinking of how to get better every day.That’s a powerful element.

Any people out there living through this type of culture? What are your challenges and how do you get through them?

Comments 3

  1. greenbelt01


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  2. Kosta Chingas

    Hi Robin,

    Using discrete data surely can be cumbersome, especially when we’re dealing with very high percentage.

    The thing that saves me a lot of times is the volume of data available. If you produce 700 – 1000 widgets in a day, you can tell if you made your 99.5%.

    Now, if we actually want to be able to prove the difference between 99.2% and 99.5% using a hypothesis test, like you said, your sample size would be considerable…. So what do we do?

    Try to convert your discrete data into variable….somehow. If you are using "on time/late" criteria, then try to get a time instead, etc….

    hope this helps..


  3. Robin Barnwell

    Hello Kosta

    Please can I ask a question? I work in the Insurance business not in manufacturing so not sure how this will translate but…..

    When you get to efficency levels of 99.5% or better what methods do you use to detect defects?

    For me its mainly discrete sampling rather than continuous and the sample sizes go through the roof.

    Its as though sampling theory breaks-down at these levels?

    Be keen to understand how you guys do it in the manufacturing environment.


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