Perfect Storm

Wednesday, July 23, 2014

lightning_strike_150_wht_5809[Drrrrring Drrrrring]

<Bob> Hi Lesley! How are you today?

<Leslie> Hi Bob.  Really good.  I have just got back from a well earned holiday so I am feeling refreshed and re-energised.

<Bob> That is good to hear.  It has been a bit stormy here over the past few weeks.  Apparently lots of  hot air hitting cold reality and forming a fog of disillusionment and storms of protest.

<Leslie> Is that a metaphor?

<Bob> Yes!  A good one do you think? And it leads us into our topic for this week. Perfect storms.

<Leslie> I am looking forward to it.  Can you be a bit more specific?

<Bob> Sure.  Remember the ISP exercise where I asked you to build a ‘chaos generator’?

<Leslie> I sure do. That was an eye-opener!  I had no idea how easy it is to create chaotic performance in a system – just by making the Flaw of Averages error and adding a pinch of variation. Booom!

<Bob> Good. We are going to use that model to demonstrate another facet of system design.  How to steer out of chaos.

<Leslie> OK – what do I need to do.

<Bob> Start up that model and set the cycle time to 10 minutes with a sigma of 1.5 minutes.

<Leslie> OK.

<Bob> Now set the demand interval to 10 minutes and the sigma of that to 2.0 minutes.

<Leslie> OK. That is what I had before.

<Bob> Set the lead time upper specification limit to 30 minutes. Run that 12 times and record the failure rate.

<Leslie> OK.  That gives a chaotic picture!  All over the place.

<Bob> OK now change just the average of the demand interval.  Start with a value of 8 minutes, run 12 times, and then increase to 8.5 minutes and repeat that up to 12 minutes.

<Leslie> OK. That will repeat the run for 10 minutes. Is that OK.

<Bob> Yes.

<Leslie> OK … it will take me a few minutes to run all these.  Do you want to get a cup of tea while I do that?

<Bob> Good idea.

[5 minutes later]

<Leslie> OK I have done all that – 108 data points. Do I plot that as a run chart?

<Bob> You could.  I suggest plotting as a scattergram.

<Leslie> With the average demand interval on the X axis and the Failure % on the  Y axis?

<Bob> Yes. Exactly so. And just the dots, no lines.

<Leslie> OK. Wow! That is amazing!  Now I see why you get so worked up about the Flaw of Averages!

<Bob> What you are looking at is called a performance curve.  Notice how steep and fuzzy it is. That is called a chaotic transition. The perfect storm.  And when fall into the Flaw of Averages trap we design our systems to be smack in the middle of it.

<Leslie> Yes I see what you are getting at.  And that implies that to calm the chaos we do not need very much resilient flow capacity … and we could probably release that just from a few minor design tweaks.

<Bob> Yup.

<Leslie> That is so cool. I cannot wait to share this with the team. Thanks again Bob.