This order contains the solution to two questions and a case study from the book, 'Managing Operations Across the Supply Chain'. The questions required to analyse the inventory and finances of a company and give recommendations for its operations. It comprises of many different calculations and tables to support the answers.
¶ … Managing Operations Across the Supply Chain
Question (a) moving average demand predictions
The predictions in each quarter based on moving average calculations are as follows:
Y2Q1 = 1/N (y1q1 + y1q2 + y1q3 + y1q4)
where Y2Q1 represents forecasts for year 2 quarter 1 and y1q1 .. ynqn are actual demands for year n quarter n and N. represents the number of quarters used to calculate the average.
This nomenclature is used throughout the calculation where YnQn represents Year n Quarter n.
Y2Q1 = 1/4(18+19+18+17) = 18 kayak paddles
Y2Q2 = 1/4(19+18+17+18) = 18.25
Y2Q3 = 1/4(18+17+19+21) = 18.75
Y2Q4 = 1/4(17+19+21+18) = 18.75
Y3Q1 = 1/4(19+21+18+19) = 19.25
Y3Q2 = 1/4 (21+18+ 19+20) = 19.5
Y3Q3 = 1/4 (18+19+20+24) = 20.25
Y3Q4 = 1/4(19+20+24+28) = 22.75
Year
Y4Q1 = 1/4 (20+24+28+32) = 26
Y4Q2 = 1/4 (24+28+32+30) = 28.5
Y4Q3 = 1/4 (28+32+30+31) = 30.25
Y4Q4 = 1/4 (32+30+31+34) = 24.25
Year
Y5Q1 = 1/4 (30+31+34+40) = 33.75
Y5Q2 = 1/4 (31+34+40+42) = 36.75
Y5Q3 = 1/4 (34+40+42+38) = 38.5
Y5Q4 = 1/4 (40+42+38+59) = 44.75
Year 6
Y6Q1 = 1/4 (42+38+59+58) = 49.25
Y6Q2 = 1/4 (38+59+58+60) = 53.75
Y6Q3 = 1/4 (59+58+60+61) = 59.5
Y6Q4 = 1/4 (58+60+61+62) = 60.25
Managing Operations 2
Year 7
Y7Q1 = 1/4 (60+61+62+62) = 61.25
Y7Q2 = 1/4 (61+62+62+64) = 62.25
Y7Q3 = 1/4 (62+62+64+65) = 63.25
Y7Q4 = 1/4 (62+64+65+66) = 64.25
Year 8
Y8Q1 = 1/4(64+65+66+68) = 65.75
Y8Q2 = 1/4(65+66+68+69) = 67
Y8Q3 = 1/4(66+68+69+68) = 67.75
Y8Q4 = 1/4 (68+69+68+67) = 68
Question (b) exponential smoothing demand predictions
FQ2 = FQ1 + ? (dq1 -- FQ1)
Where FQ2 = forecast demand in quarter 2, ? is the smoothing coefficient, (dq1 - FQ1) is the forecasting error, FQ1 is the forecast demand for the previous period and dq1 is the actual demand for the corresponding period.
Year1 (Y1)
F (Y1Q2) = 17+0.1(18-17) = 17.1 given initial forecast of year 1 quarter 1 of 17
F (Y1Q3) = 17.1+ 0.1(19-17.1) = 17.29
F (Y1Q4) = 17.29+0.1(18-17.29) = 17.36
Year 2
F (Y2Q1) = 17.36+0.1(17-17.36) = 17.325
Y (Y2Q2) = 17.325 + 0.1(19-17.325) = 17.493
F (Y2Q3) = 17.493 + 0.1(21 -- 17.493) = 17.844
F (Y2Q4) = 17.844 + 0.1(18-17.844) = 17.86
Year 3
F (Y3Q1) = 17.86 + 0.1(19-17.86) = 17.974
F (Y3Q2) = 17.974 + 0.1(20-17.974) = 18.177
F (Y3Q3) = 18.177 + 0.1(24-18.177) = 18.759
F (Y3Q4) = 18.759 +0.1(28-18.759) = 19.683
Managing Operations 3
Year 4
F (Y4Q1) = 19.683 + 0.1(32 -- 19.683) = 20.915
F (Y4Q2) = 20.915 + 0.1(30 -- 20.915) = 21.824
F (Y4Q3) = 21.824 + 0.1(31 -- 21.824) = 22.742
F (Y4Q4) = 22.742 + 0.1(34 -- 22.742) = 23.868
Year 5
F (Y5Q1) = 23.868 + 0.1(40 -- 23.868) = 25.481
F (Y5Q2) = 25.481 + 0.1(42 -- 25.481) = 17.133
F (Y5Q3) = 27.133 + 0.1(38 -- 27.133) = 28.22
F (Y5Q4) = 28.22 + 0.1(59 -- 28.22) = 31.298
Year 6
F (Y6Q1) = 31.298 + 0.1(58 -- 31.298) = 33.968
F (Y6Q2) = 33.968 + 0.1(60 -- 33.968) = 36.571
F (Y6Q3) = 36.571 + 0.1(61 -- 36.571) = 39.014
F (Y6Q4) = 39.014 + 0.1(62 -- 39.014) = 41.313
Year 7
F (Y7Q1) = 41.313 + 0.1(62 -- 41.313) = 43.382
F (Y7Q2) = 43.382 + 0.1(64 -- 43.382) = 45.444
F (Y7Q3) = 45.444+ 0.1(65 -- 45.444) = 47.4
F (Y7Q4) = 47.4 + 0.1(66 -- 47.4) = 49.26
Year 8
F (Y8Q1) = 49.26 + 0.1(68 -- 49.26) = 51.134
F (Y8Q2) = 51.134 + 0.1(69 -- 51.134) = 52.921
F (Y8Q3) = 52.921 + 0.1(68-52.921 = 54.43
F (Y8Q4) = 54.43 + 0.1(67 -- 54.43) = 55.657
Managing Operations 4
Question ( c ) to determine the best performing forecasting procedure, the demand data are plotted. See accompanying Microsoft Excel spreadsheet. The moving average gives better performance in this case.
Demand
Exp Smooth
Mov Avg
Table 1, Actual Demand, each Quarter, Predictions using Exponential Smoothing and Moving Averages
Managing Operations 5
Question 2 Production Plan, Problem 6-Page 412
Level production Plan
Based on relationship 13-1 from the text Managing Operations across the Supply Chain,
Level Production P = (?Di + EI -- BI) / N
Where P = level production rate, Di = demand for period I, EI = desired level of ending inventory, BI = beginning inventory and N = number of planning periods.
The level production plan gives the average rate of demand.
Given Planning Data
Month
January
February
March
April
May
June
Demand
200,000
150,000
200,000
400,000
550,000
250,000
Current workforce = 25 workers
Average monthly output = 10,000 sets of decks per month
Inventory holding cost = $0.25
Regular worker wage rate = $1.00 per deck per hour
Overtime wage rate = $1.30 per deck per hour
Hiring cost = $500.00
Firing cost = $500.00
Beginning Inventory = 50,000
Table 1, Level Production Data with beginning worker level of 25
Month
Demand per Month
Regular Production
OT/Sub-contract
Ending Inventory
Workforce Required
Hire
Fire/
Layoff
January
200,000
291,667
0
141,667
30
5
0
February
150,000
291,667
0
283,334
30
0
0
March
200,000
291,667
0
375,001
30
0
0
April
400,000
291,667
0
266,668
30
0
0
May
550,000
291,667
0
8,335
30
0
0
June
250,000
291,667
0
50,002
30
0
0
Total
1,750,000
1,750,00
0
1,125,007
5
0
Level production P = (200,000+150,000+200,000+40,000+550,000+250,000 -50,000+50,000)/6
= 291,667 Deck sets per month
Number of workers required = 291,667/worker production rate = 291,667/10,000 = 29.2 say 30.
Managing Operations 6
Ending inventories for the month are calculated using the relationship:
Ending inventory = previous month ending + current month production -- demand .
So for January, ending inventory = 50,000 + 291,667 -- 200,000 = 141,667
Other months are calculated in a similar manner.
Using Table 1 Data
Total Cost of Level Production = Regular Production Cost + Inventory Cost + Hiring Cost
Total Cost = 1,750,000($1.00) + 1,125,007($0.25) + 5($500)
= $2,033,751.75
Table 2, Chase Production Plan Using Overtime, beginning worker level = 25
Month
Demand per Month
Regular Production
Overtime Production
Ending Inventory
Workers
Required
Hire
Fire/
Layoff
January
200,000
150,000
50,000
50,000
15
0
10
February
150,000
150,000
0
50,000
15
0
0
March
200,000
150,000
50,000
50,000
15
0
0
April
400,000
150,000
250,000
50,000
15
0
0
May
550,000
150,000
400,000
50,000
15
0
0
June
250,000
150,000
100,000
50,000
15
0
0
Total
1,750,000
900,000
850,000
300,000
0
10
The lowest demand of 150,000 was used as the basis for regular monthly production in Table 2
Workers required = Regular Production/output rate per worker = 150,000/10,000 = 15
Total Cost for the Chase Production Plan using Overtime,
Total Cost = Regular Production Cost + Overtime Cost + Inventory Cost + Hiring or Firing Cost
= 900,000($1.00) + 850,000($1.30) + 300,000($0.25) + 10($500)
= $900,000 + $1,105,000 + $75,000 + $5,000
= $2,085,000
Table 3, Chase Production Plan Using Workforce Change
Month
Demand per Month
Regular Production
Overtime Production
Ending Inventory
Workers
Required
Hire
Fire/
Layoff
January
200,000
200,000
0
50,000
20
5
February
150,000
150,000
0
50,000
15
5
March
200,000
200,000
0
50,000
20
5
April
400,000
400,000
0
50,000
40
20
May
550,000
550,000
0
50,000
55
15
June
250,000
250,000
0
50,000
25
30
Total
1,750,000
1,750,000
0
300,000
40
40
Managing Operations 7
From Table 3, Chase Production Plan Using Workforce Change
Total Cost = Regular Production Cost + Inventory Cost + Hiring Cost + Firing Cost
+ 1,750,000 ($1.00) + 300,000 ($0.25) + 40 ($500) + (40 ($500)
= $1,865,000
Question 3 Med-Chem Products Case, Pages 415-416
Part 1
The current system in use is one of competition between the operations personnel and the marketing personnel. In this system, each department attempts to optimize its own individual goals, often at the expense of the other department's goals. So for example, when marketing deploys special promotions, it achieves goals of obtaining increased number of orders. This promotion is not coordinated with operations and so it destroys the operations' goals of minimizing inventory or reducing out-of-stock situations. The system also gives greater degree of power to marketing as it is seen that they can make changes to the vitally important forecasts at any time that they choose. Another indication of the type of system in use is in regard to the Boston Consulting Group (BCG) product classification. An accurate application of this system of classification relies on data on Market Growth Rate and Relative Market Share ( Kerin, Hartley, Rudelius, Clements, and Skolnick, 2009, p. 295). It is stated in the case that accurate collection of data concerning sales was lacking. If this is the case then the application of the BCG product classification is also inaccurate.
This system hinders the ability of Med-Chem to achieve its objectives rather than help it. The goals were stated as minimizing production costs. Since inventory costs may form a major part of production costs, it is important that accurate forecasts be made and that limits be set on the Managing Operations 8
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