BUS4101-3

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Week3Notes3.pdf

Statistical Process Control

Statistical process control (SPC) is a statistical method of separating special-cause variation from natural variation to eliminate the

special causes and to establish and maintain consistency in a process. This consistency enables process improvement.  Special-cause

variation is a departure from the output that a process would normally produce due to some unusual circumstances like a broken

machine or a power outage (in the case of the provision of a service like a car wash). 

There is a normal degree of variation in every process.  For example, when you to go the bank and stand in line to see a teller, some

days you wait for a very short time (or none at all), while on other days the wait seems very long.  Depending on how customers arrive

at the bank, this variation is normal and is to be expected.  However, if the bank begins to experience computer problems which cause

the tellers to be unable to complete the customers’ transactions at their normal pace, then the wait time may become much longer

than usual, and will likely not return to normal until the computer issues are �xed and the tellers have been able to catch up on the

job of completing the transactions of the customers.  

The key contribution of SPC to the collection of quality tools is the ability to distinguish the results of a special cause (an extremely

long wait time due to the computer problems) from the normal, day-to-day variation that is inherent in any process (short wait time

one day, longer wait time the next day). 

In order to understand how SPC works in improving processes, it is helpful to look at an example that demonstrates the importance

of the �ve key rationales of SPC. Please review the Supplemental Media entitled “Five Key Rationales of SPC” in order to see such an

example. 

Additional Materials 

View a PDF transcript of Five Key Rationales Of SPC 

(media/week5/SUO_BUS4101%20W5%20L1%20Five%20Key%20Rationales%20Of%20SPC.pdf?

_&d2lSessionVal=G8yTd5fDEtOWhKGrLSjs64OmW&ou=90832)