UNIVERSITY OF BOHOL PROFESSIONAL STUDIES
GROUP 2 CASE STUDY ANALYSES 1. Southwestern University Case Study 2. State Automobile License Renewals May 15, 2013
Cases Analyses Submitted to
Engr. Liezl Gallardo, Ph D BM (cand) as partial fulfillment of the requirements in
BA 203- Production Management Summer, SY 2013
Beverly S. Baruis Pretty Edulan JP Patatag MSBA
1. SOUTHWESTERN UNIVERSITY CASE STUDY:
Brief Description:
Southwestern University is known in its city as a football powerhouse. SWU is usually in the top 20 in college football ranking. ranking. As we have known that the enrollees in this university close to 20,000 students only. When Bo Pitterno was hired as its head coach in 2003, the attendance at the five Saturday home games each year increased. The attendance generally averaged 25,000 to 29,000 per game. Season ticket sales bumped up by 10,000 just with the announcement of the new coach. The existing stadium has seating capacity of 54,000 fans.
Discussion Questions:
1. Develop a forecasting model, justifying its selection over other techniques, and project attendance through 2011. Group 2 selected three (3) models to develop a forecasting model in this case: (a) naïve approach, (b) moving average, and (c) trend projections projections with seasonality. A) Naïve Approach is to assume that demand in the next year/period will be equal to demand in the most recent period. Naïve Approach 2009 Attendance
2010 Attendance
2011 Attendance
1
46,900
46,900
46,900
2a
50,100
50,100
50,100
3
45,900
45,900
45,900
4b
36,300
36,300
36,300
5
49,900
49,900
49,900
Game
B) Moving Average forecast uses a number of historical actual data values to generate a forecast. It is useful if we can assume that market demand will stay fairly steady over time. Moving Average Games
2004
2005
2006
2007
2008
2009
2010
2011 201 1
1
34,200
36,100
35,900
41,900
42,500
46,900
39,583
40,480
2a
39,800
40,200
46,500
46,100
48,200
50,100
45,150
46,041
3
38,200
39,100
43,100
43,900
44,200
45,900
42,400
43,100
4b
26,900
25,300
27,900
30,100
33,900
36,300
30,067
30,594
5
35,100
36,200
39,200
40,500
47,800
49,900
41,450
42,508
C)Trend projections. According to the meaning of the trend projections that this technique fits a trend line to a series of historical data points and then projects the line into the future for medium to longrange forecasts. Table C.1 Trend Projections 2010
Time period
Demand per year
x²
xy
2004
1
174,200
1
174,200
2005
2
176,900
4
353,800
2006
3
192,600
9
577,800
2007
4
202,500
16
810,000
2008
5
216,600
25
1,083,000
2009
6
229,100
36
1,374,600
21
1,191,900
91
Year
xˉ = 21/6 = 3.5
y= 1,191,900/6 = 198,650
4,373,400
b = 4,373,400 – (6) (3.5) (198,650) = 201,750 = 11,528 91 – (6) (3.5²)
17.50
a = 198,650 – 1,1528 (3.5) = 158,302 Demand in 2010 = 158,302 + 1,1528 (7)
= 238,998 attendees The forecasted demand attendees in 2010 are 238,998. Table C.2 Trend Projections 2011
xˉ = 28/7 = 4
Year
Time period
2004
1
2005
Demand
x²
xy
174,200
1
174,200
2
176,900
4
353,800
2006
3
192,600
9
577,800
2007
4
202,500
16
810,000
2008
5
216,600
25
1,083,000
2009
6
229,100
36
1,374,600
2010
7
238,998
49
28
1,430,898
140
y = 1,430,898/7 =204,414
b = 6,046,386 – (7) (4) (204,414) = 322,822 = 11,529 140 – (7) (4²)
28
a = 204,414 – 11,529 (4) = 158,298 Demand in 2011 = 158,298 + 11,529 (8)
= 250,530 attendees The forecasted demand attendees in 2011 are 250,530.
1,672,986 6,046,386
Now the group wants to develop at the five Saturday home games indices for attendance from 2010 to 2011. Seasonal variations that in data are regular up-and-down movements movements in a time series that relate to recurring events such as weather or holidays. Seasonality may be applied to hourly, daily, weekly, monthly, or other recurring patterns. Similarly, understanding seasonal variations is important for capacity planning in organizations that handle peak loads. The presence of seasonality makes adjustments in trend-line forecasts necessary. Table C.3 Seasonal Variations
Project Attendance 2010
Games
2004
2005
2006
2007
2008
2009
Average Demand
Average per game
Seasonal Index
1
34,200
36,100
35,900
41,900
42,500
46,900
39,583
39,730
0.9963
2a
39,800
40,200
46,500
46,100
48,200
50,100
45,150
39,730
1.1364208
3
38,200
39,100
43,100
43,900
44,200
45,900
42,400
39,730
1.0672036
4b
26,900
25,300
27,900
30,100
33,900
36,300
30,066
39,730
0.756745
5
35,100
36,200
39,200
40,500
47,800
49,900
41,450
39,730
1.0432922
198,649 Average per game demand = 198,649/5 = 39,730 As per forecasted demand attendees in 2010 are 238,998. We will be using the seasonal indices above to forecast at the five Saturday home games in 2010. Game 1 2a 3 4b 5
Attendance Demand per game 238,998/5 x .9963 = 47,622 238,998/5 x 1.1364208 = 54,320 238,998/5 x 1.0672036 = 51,011 238,998/5 x .7567581 = 36,173 238,998/5 x 1.0432922 = 49,868
Table C.4
Project Attendance 2011 Average per game
Games
2004
2005 2 005
2006
2007
2008
2009
2010
Average Demand
1
34,200
36,100
35,900
41,900
42,500
46,900
47,623
40,731
40,882
0.9963064
2a
39,800
40,200
46,500
46,100
48,200
50,100
54,321
46,460
40,882
1.1364415
3
38,200
39,100
43,100
43,900
44,200
45,900
51,012
43,630
40,882
1.0672178
4b
26,900
25,300
27,900
30,100
33,900
36,300
36,173
30,939
40,882
0.7567878
5
35,100
36,200
39,200
40,500
47,800
49,900
49,869
42,652
40,882
1.0432953
204,412
Average per game = 204,412/5 = 40,882 As per forecasted demand in 2011 are 250,530 We will be using those seasonal indices above to forecast the attendance at the five Saturday home games in 2011. Game 1 2a 3 4b 5
Attendance Demand per game 250,530/5 x .9963064 = 49,920 250,530/5 x 1.1364415 = 56,942 250,530/5 x 1.0672178 = 53,474 250,530/5 x .7567878 = 37,919 250.530/5 x 1.0432953 = 52,275
Seasonal Index
Table C.5 Projected attendees per game from 2010 to 2011
Games
2004
2005
2006
2007
2008
2009
2010
2011
1
34,200
36,100
35,900
41,900
42,500
46,900
47,623
49,920
2a
39,800
40,200
46,500
46,100
48,200
50,100
54,321
56,942
3
38,200
39,100
43,100
43,900
44,200
45,900
51,012
53,474
4b
26,900
25,300
27,900
30,100
33,900
36,300
36,173
37,919
5
35,100
36,200
39,200
40,500
47,800
49,900
49,869
52,275
Based on the computation computation above only the trend projections showed that the attendance from the past years games through 2011 has gone up. The naïve approach keeps the projection the same as the previous year’s attendance. The moving average made the forecast far less than the last years’ attendance.
On these factors Group 2 believes that the trend projection forecasting method is the best fit for projecting in this case where attendance for Southwestern University will actually increasing in 2010 and 2011. This method also gives leverage to the new coach to get him new stadium that he requested.
2. What revenue forecasted are to be expected in 2010 and 2011? An assumed average ticket price of $50 in 2010 and a 5% increase each year in future prices. Based upon the trend projection with seasonality forecasts, the revenue for both 2010 and 2011 were computed. By computing the sum of the attendees for all the five games each year and multiply by the respective ticket price for that year we can forecast the revenue to be expected in 2010 and 2011.
Revenue:
Game
2010
2011
1
47,623
49,920
2a
54,321
56,942
3
51,012
53,474
4b
36,173
37,919
5
49,869
52,275
Total Price Revenue
238,998 $50.00
250,530 $52.50
$11,949,900.00
$13,152,825.00
The computation above shows the forecasted revenue in 2010 and 2011. The revenue in 2010 is expected to $11,949,900.00 and $13,152,825.00 in 2011 respectively.
3. Discuss the school’s opinions. The option that this group will be taking is to build a new stadium as the forecasts show that the stadium will be sold out somewhere in 2010 game days. It will continue to rise and this should definitely be dealt with now to ensure there is no loss in revenue due to sold out games. As the population increasing and generation getting modernize it is more likely to build a new stadium to replace the aging stadium and that fits to the new generation and can accommodate with the forecasted attendance in 2010 and 2011 and for the future to come. Since technology is progressing in this modern world it is reasonable to think that s stadium could be built in less than a year.
2. STATE AUTOMOBILE LICENSE RENEWALS
The following table is the steps of the driver’s license-renewal operations associated with times required:
Table 2.1
State Automobile License – Renewal Process Times Step 1. Review renewal application for correctness. 2. Process and record payments 3. Check file for violations and restrictions 4. Conduct eye test 5. Photograph applicant 6. Issue temporary license
Average time to perform (seconds) 15” 30” 60” 40” 20” 30”
Questions:
1. What is the maximum number of applications per hour that can be handled by the present configuration of the process? Figure 2.1
Step 1
Step 2
Step 3
15”
30”
60”
Step 4 40”
Step 5
Step 6
20”
30”
Solution: The bottleneck in this system is in step 3 at 60-seconds per application, resulting in an hourly
system capacity of 1 hour x 60 minutes x 60 seconds/ 60-seonds per application = 60 applications/ hour. Answer: The maximum numbers of applications per hour that can be handled by the present
configuration of the process are 60 applications/hour.
2. How many applications can be processed per hour if a second clerk is added to check for violation (step 3)? Figure 2.2
Step 1
Step 2
Step 3
Step 4
Step 5
Step 6
1 Clerk
1 Clerk
2 Clerks
1 Clerk
1 Clerk
1 Clerk
15”
30”
60”
40”
20”
30”
30”
Solution: In this case, second clerk added to step 3. The 60-seconds checking time of file for violations
and restrictions in step 3 represents the process time each station. Next, the process time of the combined or additional clerk in step 3 is 60-seconds per two applications, or 30 seconds per application. Therefore, step 4 becomes the bottleneck for the entire license-renewal process and the system process time is 40-seconds. The capacity per hour equals 3,600-seconds 3,600-seconds per hour/40-seconds per application = 90 applications per hour. Answer: The maximum number of application per hour if the second clerk is added to check for
violations and restrictions are 90 applications per hour. 3. If the second clerk could be added anywhere you choose (and not necessarily to check for violations, as in question 2), what is the maximum number of applications the process can handle? What is the new configuration? Figure 2.3
Step 1
Step 2
Step 3
Step 4
Step 5
Step 6
1 Clerk
2 Clerks
1 Clerk
1 Clerk
1 Clerk
1 Clerk
15’’
30’’
60’’
40’’
20’’
30’’
15’’
Solution: If the second clerk will be added in step 2, process and record payments. The 30-seconds
processing and recording time of payments in step 2 represents the process time each station. Since we added the second clerk in step 2 the process time with an additional clerk is 30-seconds per two applications, or 15-seconds per application. Therefore, step 3 becomes the bottleneck for the entire license-renewal process and the system process time is 60-seconds. So, the capacity per hour equals 3,600-seconds per hour/60-seconds per application = 60 applications/hour. Answer: a. The maximum number of application per hour if the second clerk is added to step 2, process
and record payments are 60 applications per hour. b. The table below is the new configuration. Table 2.2
State Automobile License – Renewal Process Times Step
1. Review renewal application for correctness. 2. Process and record payments 3. Check file for violations and restrictions 4. Conduct eye test
Processing time (seconds) 15” 30” 60” 40”
Number of clerks 1 2 1 1
Average time to perform (seconds) 15’’ 15’’ 60’’ 40’’
5. Photograph applicant 6. Issue temporary license
1 1
20” 30’’
20’’ 30’’
4. How would you suggest modifying the process to accommodate 120 applications per hour? What is the cost per application of this new configuration? Considering a review of the jobs indicated that step 1, reviewing applications for correctness, had to be performed before any other step could be taken. Similarly, step 6, issuing temporary licenses, could not be performed until all the other steps were completed. Table 2.3
State Automobile License – Renewal Process Times Step 1. Review renewal application for correctness. 2. Process and record payments 3. Check file for violations and restrictions 4. Conduct eye test 5. Photograph applicant 6. Issue temporary license
Average time to perform (seconds) 15” 30” 60” 40” 20” 30”
Solution: We need to determine line balancing to minimize the imbalance between clerks while
meeting the required output/demand. Cycle time (in seconds) = (1 hour x 60 minutes x 60 seconds)/ 120 applications = 3,600/120 applications = 30 seconds/application seconds/application Therefore, the bottleneck process time system requirement is 30-seconds. The license-renewal process time in Table 2.3 shows that 6 operations are necessary for a total operation o peration time of 195 seconds. Workers required = 195/30-seconds = 6.5 or 7 workers Based on the computation above that there are 30-seconds process time system requirement and there is a total of 7 workers in this license-renewal process time. So, we need to combined some activities and add workers on it.
The Table 2.4 below will be the suggested modifying process to accommodate 120 applications per hour. Table 2.4
The new step 1
2 3 4
Activities
Processing time (seconds)
Number of clerks
Average time to perform (seconds)
Review renewal application for correctness, Process and record payments, and Conduct eye test. Check file for violations and restrictions Photograph applicant Issue temporary license
85
3
28.33
60 20 30
2 1 1
30 20 30
As per average time to perform on Table 2.4 the bottleneck time is 30-seconds. We combined/added the three (3) clerks on step 1, review renewal application for correctness, process and record payments, and conduct eye test, and 2 clerks on step 2, check file for violations and restrictions. On this the capacity per hour equals 3,600 seconds per hour/ 30-seconds per application = 120 applications/ hour. Table 2.5
The new step 1
2 3 4
Activities
Review renewal application for correctness, Process and record payments, and Conduct eye test. Check file for violations and restrictions Photograph applicant Issue temporary license Total Labor cost per hour Cost of camera Total processing processin g cost per hour
The cost per application = 100/120 =$0.83
Number of clerks
Cost per hour
Total cost per hour
3
12
36
2
12
24
1 1
12 18
12 18 90 10 100
