Question description
The data in the table below is from a study conducted by an
insurance company to determine the effect of changing the process by which
insurance claims are approved. The goal was to improve policyholder
satisfaction by speeding up the process and eliminating some non-value-added
approval steps in the process. The response measured was the average time
required to approve and mail all claims initiated in a week. The new procedure
was tested for 12 weeks, and the results were compared to the process
performance for the 12 weeks prior to instituting the change.
Table: Insurance Claim Approval
Times (days)
Old Process
New Process
Week
Elapsed Time
Week
Elapsed Time
1
31.7
13
24
2
27
14
25.8
3
33.8
15
31
4
30
16
23.5
5
32.5
17
28.5
6
33.5
18
25.6
7
38.2
19
28.7
8
37.5
20
27.4
9
29
21
28.5
10
31.3
22
25.2
11
38.6
23
24.5
12
39.3
24
23.5
Use the date in table above and answer the following
questions in the space provided below:
1.
What
was the average effect of the process change? Did the process average increase
or decrease and by how much?
2.
Analyze
the data using the regression model y
= b0 + b1x, where y = time to approve and mail a claim
(weekly average), x = 0 for the old
process, and x = 1 for the new
process.
3.
How
does this model measure the effect of the process change?
4.
How
much did the process performance change on the average? (Hint: Compare the
values of b1 and the average of new
process performance minus the average of the performance of the old process.)
