¶ … Cause-And-Effect Relationships
Required: Use the data presented in Table 1 below to conduct a design of experiment (DOE) in order to test cause-and-effect relationships in business process for the company
Improving Email Response Rate
Run
Heading
Email Open
Replicate
Response Rate
Generic
Detailed
Generic
Detailed
Generic
HTML
Detailed
HTML
Generic
HTML
Detailed
HTML
Generic
Detailed
Generic
Detailed
Generic
HTML
Detailed
HTML
Generic
HTML
Detailed
HTML
Taking averages of the response rate in the repeat experiments, we end up with table 1.1 as shown below:
Run
Email Heading
Email Open
Email Body
Response Rate
Generic
No
Text
(46+38)/2
Detailed
No
Text
(34+38)/2
Generic
Yes
Text
(56+59)/2
Detailed
Yes
Text
74(68+80)/2
Generic
No
HTML
26(25+27)/2
Detailed
No
HTML
27(22+32)/2
Generic
Yes
HTML
22(21+23)/2
Detailed
Yes
HTML
26(19+33)/2
Coding the data in table 1.1 in the form of 1 and -1 for all the three key factors, where i) for the Email Heading factor (abbreviated as EH) 1 represents 'Generic' and -1 represents 'Detailed'; ii) for the Email Opening factor (abbreviated as EO) 1 represents 'No' and -1 represents 'Yes'; and iii) for the Email Body factor (abbreviated as EB) 1 represents 'Text' and -1 represents 'HTML', we end up with table 1.2:
Run
EH
EO
EB
Response Rate
1
1
1
1
42
2
-1
1
1
36
3
1
-1
1
57.5
4
-1
-1
1
74
5
1
1
-1
26
6
-1
1
-1
27
This implies that we could use the main effects scatter plot to determine the pareto levels of operation for the three factors (Morris, 2010). However, the interaction results show that there is some significant interaction among factors. Towards this end, rather than use the main effects plot, we could use the interactions effect…
