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OTE/SPH
OTE/SPH
2:55
Char Count= 0
JWBK119-05
August 31, 2006
Case Study: Manpower Resource Planning 61
84
72
60
Total Waiting Times (mins)
48
36
24
12
0 11
8 10 View B
9 9
View A 10 8 No. of Dispensing Pharmacists
No. of Packers 11

89.0 90.0
79.0 80.0
Waiting Times 59.0 Waiting Times 60.0
69.0
70.0
49.0
50.0
39.0
29.0 40.0
30.0
19.0
20.0
9.0
8 9 10 11 10.0 8 9 10 11
Number of Packers Number of Dispensing Pharmacists
8 Dispensing Pharmacists 9 Dispensing Pharmacists
10 Dispensing Pharmacists 11 Dispensing Pharmacists 8 Packers 9 Packers 10 Packers 11 Packers
View A View B
Figure 5.3 Sensitivity of total waiting times to variations in the numbers of packers and
dispensing pharmacists.

pharmacists in a sensitivity analysis. Results for the lower arrival rate extracted from
the estimated arrival rate profile shown in Figure 5.1 are presented here. A correspond-
ing analysis for the higher arrival rate can be conducted. Subject to other practical con-
siderations, manpower deployment can then be adjusted dynamically throughout the
day.
With an arrival rate of 88 prescriptions an hour, at least 8 packers and 8 dispens-
ing pharmacists were needed for the packing and checking dispensing processes,
respectively, in order to ensure the finiteness of steady-state waiting times. Figure 5.3
shows the impact of varying the number of packers and dispensing pharmacists on
the mean total waiting times. It was observed that waiting times would be increased
significantly if the number of packers was reduced to 8. With more than 8 packers,
the waiting times were observed to be relatively stable over the different numbers
of dispensing pharmacists in the experiment. It was further observed that by having
one additional dispensing pharmacist, the targeted 15 minutes of mean total waiting
times could potentially be met.
In order to assess the robustness of each possible system configuration, arrival
rates of patients at the pharmacy were varied in the model. Figure 5.4 shows the