Representing and Reporting Data

Background Information

What is statistical process control? SPC consists of some techniques used to help individuals understand, analyze, and interpret numerical information. SPC is used to identify and track variation in processes. All processes will have some natural variation. Think about it this way: suppose you get into your car and drive to work every weekday. What can vary about that? Well, assuming that you do not change the route you take, the natural variation can be the number of stoplights you hit (that means the lights you must stop at not that you hit them with your car), the number of cars waiting at the stoplight, the number of cars that are making turns at the stoplight, etc. It can also include the number of accidents (if accidents are a normal part of your drive into work), the number of school buses you get behind, and, on a really good day when everything seems to irritate you, the number of trash trucks you follow that you just cannot seem to pass. All of these frustrations are those that you currently, normally encounter on your way to work. While the number of trash trucks may change, and the number of cars turning may change, the basic process of driving to work has not changed. Those variations are normal variations. The exceptional variation would be when you decide to drive into work on a weekday that just happens to have a holiday fall on that day. Suppose that, due to a crushing workload, you decide to drive into work on Labor Day (which for those of you not familiar with U.S. holidays, always falls on the first Monday in September). Hopefully, you do not always go to work on a holiday, so this is an exception. You follow the same route, but it does not take as long, you do not hit as many stoplights, and the number of cars in front of you is lessened.

Due to the normal variation in any process, the numbers (in this example, the number of cars waiting at the stoplight, the number of accidents that may occur) can change when the process really has not. So, we need to understand both the numbers relating to our processes and the changes that occur in our processes so that we may respond appropriately.

Other terms that you may see are common causes of variation and special causes of variation, as well as common cause systems and special cause systems. Common causes of variation result from such things as system design decisions and the use of one development tool over another. This variation will occur predictably across the entire process associated with it and is considered normal variation. Special causes of variation are those that arise from such things as inconsistent process execution and lack of resources. This variation is exceptional variation and is also known as assignable causes of variation. We will use both terms. Other terms you will hear are in control for predictable processes or steady-state ; and out of control for unpredictable processes that are "outside the natural limits."

When a process is predictable, it exhibits routine variation as a result of common causes. When a process is unpredictable, it exhibits exceptional variation as a result of assignable causes. It is our job to be able to tell the difference and to find the assignable cause. When a process is predictable , it is performing as consistently as it can (either for better or for worse ). It will not be performing perfectly ; there will always be some normal, routine variation. Looking for assignable causes for processes that are running predictably is a waste of time because you will not find any. Work instead on improving the process itself. When a process is unpredictable, that means it is not operating consistently. It is a waste of time to try to improve the process itself. In this case, you must find out why it is not operating predictably and detail the "whys" as specifically as possible. To do that, you must find and fix the assignable cause(s); that is, the activity that is causing the process to behave erratically.

An example of fixing an assignable or special cause of variation in the driving to work example would be if your car breaks down on the way to work. If this happens once, you might not take any action. However, if your car is old and breakdowns occur frequently, you might decide to remove this special cause by buying a newer car.

In contrast to the predictability of a process, we may want to consider if a process is capable of delivering what is needed by the customer. Capable processes perform within the specification limits set by the customer. So, a process may be predictable, but not capable.