It is human nature to want to improve and now, more than ever, we have tools to make this easier. We live in a day and age of data – think of all the information that we have at our fingertips each day, with a simple swipe of a finger on our smart phones, a powerful combination – we improve and optimize based upon that wealth of data.
But wait there is a snag… Data is not information; without understanding, it often times can lead us to bad decisions. We have discussed the need for context and timing before [please click the links if you need a refresher]. Today I am going to focus on Metrics and KPIs.
First let me state that Metrics (or Key Performance Indicators – KPIs) can be very good thing. They are the key sharing your manufacturing goals and vision. For this reason, they should be visible and aligned to your overall vision. By adding this visibility, it drives people to focus on the metric and improve. So why did I use the word “can”? Metrics in themselves are a tool, if they are not consistent or align to a vision that is a very bad thing!
Take for example Cycle Time, most people try improving Cycle Time – but is it the right metric for you? Is it a single cell or an entire line? I have the fortune of observing many different processes and plants and often see areas of local optimization. Local optimization is where a particular KPI is applied towards a machine and improved, however in the larger picture these are counter-productive. Back to the Cycle Time reference, it doesn't do any good to run at a faster pace, if the upstream or downstream processes can’t keep up, or worse yet if you are producing the wrong parts (no demand). If you haven’t done so, I would highly recommend that you read “The Goal” by Eliyahu Goldratt.
Also keep in mind that Metrics and KPIs do not need to be permanent – they are there simply as a tool to affect a change. Most companies have a continuous improvement initiative, the underlying metrics should change to support new initiatives and evolve over time.
My next post will focus on the methods for getting data and how based upon the maturity of a plant, how data collection and KPIs will evolve.
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