Monday, March 5, 2012
How can we speed up our learning and make improvements that will help us reduce costs? Typically, people making improvements try to change one thing at a time. The problem with this approach is the complexity of the processes and the interdependent factors we are studying. To be more effective, we need to learn how to test more than one factor at a time. Let’s consider an example.
An improvement team in a hospital system that is supported with citizens’ taxes is attempting to help patients not miss appointments. When someone does not show up for an appointment, this is a loss to the society. The improvement team tried texting the patients one day in advance. This did not seem to make much impact. It was then decided to have a person call the patient personally one day in advance. An improvement advisor happened to overhear this discussion and suggested that the team test two factors at two levels or sometimes referred to as a design which will require 4 runs or tests. Rather than abandon the text idea, test it with the call idea, but add in a lead time factor with a call 1 day and 3 days in advance. The improvement advisor suggested calling three days in advance might allow the patients to plan better. Figure 1 describes the simple designed experiment matrix that was developed. Also included are the percent of no shows as the response variable.
Figure 1: Design Matrix for a Two Factor at Two Level Experiment
From Figure 1, you can see readily that the 4th test that combined the call with 3 days reduced the no show rate to 10%. The next best combination was a text messages at 3 days in advance of the appointment with a 12% no show rate. The team decided to avoid the cost of taking up a person’s time to actually call patients and use the 3 day advance text. One team member suggested setting the computer to also give a 7 day warning. The team agreed to use another test to follow this idea up. The response plots in Figure 2 describes the results from the 4 test runs.
Figure 2: Response Plots for the Factorial design
Before the improvement advisor suggested the designed experiment, the team was ready to run another one factor test: the more expensive idea of adding more people to make personal calls. This would have reduced the no show rate from 25% to 15%, a large improvement but at a significant cost increase. By experimenting with the text and call idea with different frequency levels the team was able to improve while lowering costs.
1. Quality Improvement through Planned Experimentation, Ronald Moen, Thomas Nolan, and Lloyd Provost, McGraw-Hill, NY, second edition, 1999
Thursday, February 23, 2012
This article begins with a quote from Deming in the New Economics: “Conformance to specifications, zero defects, Six Sigma Quality, and all other (specification-based) nostrums all miss the point.”
In addition a good history of the Crosby contributions to Zero Defects and quotes from Dr. Juran on Six Sigma are included. The paper finishes with the Taguchi Loss Function and Deming's System of Profound Knowledge.
Lost to history is the experience of Ford with the Batavia Plant where they were making exactly the same transmission as Mazda. This provides a real life example of the difference focusing on meeting specification versus manufacturing to target (Taguchi's idea). Both outputs from Mazda and Ford were within specification. However, the Ford transmissions had twice the customer problems as the Mazda transmissions. VP John Beti famously remarked, "While we were busy meeting specifications, they were busy making them all the same." If you have never seen this video produced by Ford, it is worth the time. It is less than 12 minutes long.
Ford at first elected to close the Batavia plant. This caused an outbreak of cooperation between the management and the union. It took the plant 8 months to match the quality of Mazda.
Harry Truman once remarked, "History does not repeat itself. We just keep making the same stupid mistakes."
Deming warned us in 1993 before he passed: : “Conformance to specifications, zero defects, Six Sigma Quality, and all other (specification-based) nostrums all miss the point.” Since his passing we now have a world wide movement that is back to focusing on specifications.