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332    C o n t i n u o u s   I m p r o v e m e n t                                                                                                                              A n a l y z e   S t a g e    333


                                         Trial   Cycle Time     Type       Method     Score
                                         1       Low            Generic    Email      35
                                         2       High           Generic    Email      21
                                         3       Low            Personal   Email      28
                                         4       Low            Generic    Phone      27

                                       Table 15.2  One Factor at a Time Data Collection Scheme



                                varied at a time to estimate its effect. Table 15.2 lists three factors, with two
                                possible settings for each:

                                    •  Response cycle time [low, high]
                                    •  Personalized response type [generic or personal]
                                    •  Response method [email or phone]
                                    •  An initial baseline condition is taken by measuring the response
                                      [customer satisfaction score] when each of the factors is set at its
                                      low level. A second trial is then run to estimate the effect of the
                                      first factor: response cycle time. The difference between the Trial 2
                                      response and the baseline (Trial 1) is assumed to be the effect of
                                      the factor varied. In this case, it appears that raising the response
                                      cycle time from low to high results in a decrease in customer sat-
                                      isfaction of 14 units.

                                   Likewise, the effect of a personalized response type may be estimated
                                by comparing Trial 3 with Trial 1; the effect of response method is esti-
                                mated by comparing Trial 4 with Trial 1. In this way, the effect of the per-
                                sonalized response is estimated as a decrease in customer satisfaction of
                                7 units, and the effect of phone versus email as a decrease of 8 units in
                                customer satisfaction score.
                                   Based on these observations, customer satisfaction may be maximized
                                by setting the factors as follows: cycle time: low; personalized response:
                                generic; response type: email.
                                   The problem with this traditional one-factor-at-a-time experiment is
                                that it ignores the effect of interactions. Figure 15.11 displays the results
                                from a designed experiment of the same process. You can see that at the
                                high cycle time setting (shown by the line labeled 330.000), the satisfaction
                                score of 21.0 was observed when the response type is set at the generic (no
                                personal response) condition. This is Trial 2 from above, and is circled on
                                the graph. Trial 3 is shown on the line labeled 210.000 at the yes personal
                                response condition.
                                   On the 210.000 response cycle time line, moving from no personalized
                                response to yes personalized response (left to right along the line), there is
                                very little change in customer satisfaction score. In other words, there was








          15_Pyzdek_Ch15_p305-334.indd   332                                                          11/20/12   10:33 PM
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