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remittance (OTR) time for hardware / software installations for the last 76 installations (from first to last)

Posted on Posted in MAT510 Business Statistics, Mathematics, Statistics

The data in below table lists country code and the order to remittance (OTR) time for hardware / software installations for the last 76 installations (from first to last). OTR is the time it takes from an order being placed until the system is installed and we receive payment (remittance). Because this company does business internationally, it also notes the country of installation using a country code. This code is listed in the first column.

 

Table: Country Code and OTR Cycle Time for Software Systems Installation

Country Code Cycle Time Country Code Cycle Time
1 20 5 29
1 24 6 40
1 46 7 157
1 26 8 19
14 38 5 24
1 15 1 81
1 15 7 53
17 23 7 26
1 31 1 28
1 31 1 34
6 64 1 34
5 29 7 50
5 44 1 52
1 32 1 19
1 15 1 44
7 11 14 150
7 14 7 29
1 89 17 23
17 41 6 79
7 41 17 13
1 36 6 32
8 43 7 61
17 21 8 42
8 28 8 46
7 18 7 88
8 47 14 24
6 26 7 7
6 47 1 33
5 9 5 129
7 42 17 41
5 5 17 43
6 27 14 42
6 27 14 42
1 33 7 53
7 44 7 53
1 21 7 48
1 22 5 21
1 50 1 19

 

 

Use the date in table above and answer the following questions in the space provided below:

  1. Does the OTR time appear to be stable? Why or why not?

Looking closely at the data presented in the chart, it appears that the OTR time is not stable. We can easily assess it by looking at the code of the country and the time interval of the cycle times. For example, for country code 4, the cycle time is between 24 and 150 which is a clear reflection of unstable OTR in the chart under discussion.

  1. If you were to use a control chart to evaluate stability, which chart would you use? Why?

To evaluate the stability, I would use a Run Chart. A run chart would enable me to observe the data in a time sequence with different variable on x and y axis. The information in the chart can be better observed with a run chart. This would allow me to observe the flow of data on different times rather than jumping in to conclusions.

  1. What can you learn about the distribution of the installation process?

We can observe from the above chart that the distribution pattern of the installation process is not even and there are instabilities. As earlier mentioned, the country codes when observed vs the cycle time, it did not show a stable pattern.

  1. Does it appear that the country has an impact on installation time? Why or why not?

From the above chart, it is evident that there are many special causes related to different countries. We do have enough data for country code 1 but not other countries. In the case of special causes, it is hard to comment on whether a country has an impact on installation time.

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