DMAIC drops the mic!

I entertained myself more than I should have with that title.

So yesterday I wrote about how you might want to think more about which method to use to solve a problem before you get into solving it as I am a strong believer that each popular method has its strengths and weaknesses for different types of problems. I am of course assuming in this that you know more than one method or have access to experts across several methods. I realise this isn’t always the case.

So what about DMAIC? Well to start with I absolutely love DMAIC. It is my favorite method to use when problem solving myself and my favorite to coach. I love the elegant connectedness (not a real word) of all the different parts and how they weave together to form a free flow story line from event to causes to significant x’s and back to responses. Just talking about it gets me wanting to do some regression analysis!

For those of you who aren’t familiar with DMAIC WHERE HAVE YOU BEEN???? It is the backbone method for six sigma the hallowed continuous improvement movement based around statistical analysis of data. You can find more about six sigma here. There is a section on DMAIC there as well.

As you might have read in my previous post Do we have a problem, I am not a fan of too much data in problem solving. I find it confuses people and blurs the reality to the point where we can struggle to find the correct path. This would at first glance seem to contradict with six sigma. I mean its about statistics and everyone knows that when it comes to statistics more data is better. So why then say it is so great? The key here is that DMAIC gives you a framework and tools in which to continuously prioritise the different inputs you get, focus down on the important ones, decide how you want to measure them and take control of your incoming data for real good!

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It seems like magic! The first time I was walked through this path by my teacher and mentor Graham I was amazed and astounded in how clear you can make things and take control of information to assimilate it into an interpret-able result!

So going back to the beginning of the post. When would you maybe look to use DMAIC over KT PA (Kepner Tregoe Problem Analysis) for example? My thought is DMAIC:

  • Lends itself to big process problems. It analyzes systems and has the tools to create the understanding of these
  •  If you have easy sets of continuous data DMAIC is going to be your man
  • Problems where you are short on data and you know you need to get out there and gather more (again beware of thinking this all the time). DMAIC has the tools to help you gather the RIGHT data from the start

Anyway, that is it from me with regards to DMAIC. If you want a more detailed breakdown of anything in here please comment and I will do my best to help!

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