Business Analytics
Sensitivity Analysis / Decision Tree
Running head:
RUSSO
M
ANUFACTURING REPORT
1
7
RUSSO MANUFACTURING REPORT
Russo Manufacturing Report
Name
Institution
Executive summary
The make or buy decision in manufacturing is usually essential to aid the growth and maximum profits of a company. Russo is meant to decide whether to manufacture a component part or purchase the component part from a supplier. This particular decision is fully dependent upon the demand for the products in the market. Such outsourcing decisions compares the costs to the benefits associated with producing a necessary product internally to the costs.
Research
is also dependent on the demand. When demand is low research becomes unfavorable and when demand is high it becomes favorable. Due to this I have observed various approaches to arrive at a more profitable decision that will optimize the various advantages and still maintain a risk averse status for the business. The final decision was for Russo to conduct the research though it comes with an extra cost and adapt a minimax regret approach to reduce the possibility of risk of loss. Russo will also need to purchase in order to reduce the costs incurred in manufacturing.
Introduction
Russo is a manufacturing company with a plant in Milan. Due to the ambiguity of the demand in the market, the company has to make a decision on whether to buy or make the component part from its plant in Milan. The profits are fully dependent on the demand for the product, hence, a loss will be incurred if the manufacturing is done under low demand but relative profits if a purchase decision is made under low demand. The decision to purchase for both medium and high demand scenarios results to higher profits as compared to the decision to manufacture.
Russo Manufacturing Report
The payoff table of Russo Manufacturing;
DEMAND
SUPP
L
Y
H
IGH
MEDIUM
LOW
MANUFACTURE
89.477
50.633
-10.780
PURCHASE
97.547
54.052
12.05
PROBABILITY
–
–
–
Decision Criteria for Russo Management
Optimistic Approach
Russo manufacturing has various options on whether to manufacture the parts or purchase. To be able to make the right decision Russo can use the optimistic approach, also known as the maximax approach. This approach involves choosing the option with the maximum possible payoff or the minimum possible cost .From the payoff table, for Russo to optimize their profits they will need to compare the maximum possible outcome for each of the two options. In this case, manufacturing under high demand will result to a profit of 894777 Euros while purchasing results to a profit of 97547 Euros. During medium demand manufacturing will result to a profit of 50633 Euros and 54052 for purchase in the best case scenario. Low demand will result to a loss of 10780 euros if Russo was to manufacture and a profit of 12.05 if they were to purchase. According to the optimistic approach, Russo manufacturing should consider the best possible outcome being to purchase the parts under high demand which will result to a profit of 97547Euros
Conservative Approach
The optimistic approach may involve a lot of risk and for this reason, Russo manufacturing can opt to use the conservative approach. This approach to decision making is also referred as the maximini approach. It involves choosing the option that has the largest payoff or lowest cost among the lowest set of possibilities. From the Russo manufacturing payoff table, the option that will maximize the minimum pay-off achievable is getting to purchase the parts which will result to a profit of 12,050 Euros. This approach ensures an organization plans for the worst possible outcome.
Minimax Regret Approach
The minimax regret approach minimizes the maximum regret. It is useful in a risk-neutral decision making. Essentially, this is a technique is adapted by individuals or companies who do not wish to make wrong decision. This is arrived at by subtracting the highest demand from the lowest, leading to the maximum regret under each demand, from the below table the least maximum regret is the medium supply by 3.418. Russo manufacturing will employ the minimax regret criterion in order to minimize the maximum regret. Therefore, they will need to manufacture under medium demand which will generate a profit of 50633 Euros.
REGREAT TABLE
DEMAND
SUPPLY
HIGH
MEDIUM
LOW
MANUFACTURE
8.070
3.418
22.834
PURCHASE
0.000
0.000
0.00
Maximum Regret
8.070
3.418
22.834
Probabilities if the Market Research is conducted
Conducting a market research will result to a cost of 14,243.71 Euro. The research is capable of indicating whether the market condition is favorable or unfavorable. The research is also fairly reliable and is more likely to obtain favorable result if the demand for the finished product is truly high, this means if the research is to be conducted during high demand possibilities there will be favorable results that will restore the Russo manufacturing confidence and further increase their profits. On the other hand, the report will generate less favorable result if the demand for the finished products is low, meaning despite Russ manufacturing having to incur a cost of 14,243.71 Euros in research, this won’t be beneficial and as a result the loss will increase to 25,023.71 Euros. Research conducted during medium demand will also generate favorable results but not greater like the one conducted during high demand.
Market research will also help in the testing of the products in one or two markets on a small scale. This will intern help Russo in finding out the consumer response to the product and develop a better decision in regards to the choice of whether to manufacture of to purchase in the long run. It reveals the specific problems of the customers regarding new products. Thus, helps in controlling the risk involved in producing more or less products.
Russo Manufacturing Decision Tree
H: High; M: Medium; L: Low
SD
RUSSO
Favourable
WD
:
Weak Demand
No Research
Research
(vii) (viii)
Weak Demand
Strong demand
Non Favourable
WD
SD
M
L
M
L
H
H
WD
SD
H
L
L
H
L
H
H
L
M
M
M
M
Market Research
Market Research is essential and is a continuous process through which data is collected, investigated and interpreted about a particular market a company operates in or the service the company offers when selling in that market, and also on the potential and existing competitors and the past, present and potential customers who purchase and consumed the offered product. Conducting a market research is costly and for Russo it will result to a cost of 14,243.71 euro while generating the report has favorable results during higher demand than low demand. Low demand might lead to further losses of 25,023.71 euros.
Researching the market will help Russo gain valuable information that will help in identifying the success of the products, the best price they can set for the products, and the customers interested in purchasing and consuming the products. Though this is essential, I will recommend that Russo only does the research when the demand is relatively high meaning its medium or high. In medium and high demand, Russo should research markets because they will pave the way for better inventory management, business planning and time management.
Decision Strategy
Research is pivotal in the general growth of the company, it is able to indicate whether the market condition is favorable or unfavorable. In Russo’s case research only works well during high demand and is less favorable when the demand is low. To be able to optimize the merits of research and taking into attention the growth and profitability of Russo, a minimax regret approach is the best strategy to take. This approach is able to minimize the maximum regret, hence making it a risk-neutral decision making strategy.
Sensitivity Analysis
Scenario-Manufacture
High
Medium
Low
Weak demand
89.477
50.633
-10.780
0.1
89.4765472
50.63331369
-10.77961394
Scenario-Purchase
High
Medium
Low
Weak demand
97.547
54.052
12.055
0.1
97.54683071
54.05169216
12.05453291
Conclusion
Decision making being a vital component in the growth of Russo, considering research is important for the profits of the organization I propose the use of a minimax regret approach to optimize demand due to the uncertainty of the market. Regret will aid the deviation of any given decision from the optimal choice based on the specified set of possible scenarios for uncertain nature of the market. This approach will not require any specification of instrumental variables to control, and also does not require specific number of possible states in advance. This means that Russo will conduct research and purchase the parts under medium demand scenario. Nowadays, markets are not localized, they have become more global. Manufactures like Russo are finding it difficult to contact customers and even control the distribution channels while the competition is equally severe. The consumer needs in recent days are more difficult to predict. The market segmentation is even more complicated in such wide markets. As a result the marketing intelligence provided through marketing research not only help in framing the process but also in implementing the market strategies. Russo will be able to optimize profits if research is conducted while the risk of loss of profits is also looked into to maintain the confidence of the company. This will help identify new market opportunities for existing products. It also provides information on market share, competition, customer satisfaction levels, sales performances and channel of distribution.
Running
head:
RUSSO MANUFACTURING REPORT
1
Russo Manufacturing Report
Name
Institution
Running head: RUSSO MANUFACTURING REPORT 1
Russo Manufacturing Report
Name
Institution
Requirements:Everyone will be given the same case study but with different data, which you
will write a management report on. The report will be based on your Excel analysis. The report
has to be understandable as a standalone piece of work without referring to the Excel file. You
need to provide tables and figures from the Excel analysis to support your report.
The deadline for group assignment is 23:59 Friday 18th December 2020. Both the report and
the Excel file need to be submitted to Blackboard.
Word limit of the report is 1500 words. The data for each individual is posted in the Excel
spreadsheet along with the assignment brief.
The Russo Manufacturing company
The Russo Manufacturing Company must decide whether to manufacture a component part at
its Milan plant or purchase the component part from a supplier. The resulting profit is
dependent upon the demand for the product. If the demand for the finished product is low,
Russo will incur a loss of [i.] if it decided to manufacture the component part. On the other
hand, if Russo purchases the component part, it will not incur any production cost and the profit
is estimated to be [ii.] when the demand of the finished product is low. In a better scenario
when demand for the finished product is high, Russo will earn [iii.] if it manufactures the
component part in house, or [iv.] if it purchases the part. Finally, when demand for the finished
product is at medium level, Russo will earn [v.] profit if it manufactures the component part,
or [vi.] if the part is purchased from a supplier.
Originally the management estimate the probability of weak demand to be [vii.] and of strong
demand to be [viii.]. However, the management is concerned about the accuracy of this
estimation and is contemplating of conducting extra market research to determine the
likelihood of different states of demand. The cost of the research is [ix.] and the research can
indicate if market condition is favourable or unfavourable. The research is fairly reliable,
meaning it is more likely to obtain a favourable result if the demand for the finished product is
truly high. On the other hand, the report will be less likely to generate a favourable result if the
demand for the finished product is truly low. The probabilities of obtaining a favourable report
given a certain market condition are:
P (F | low demand) = [x.]
P (F | medium demand) [xi.]
P (F | high demand) = [xii.]
Task:
Perform an analysis of the problem facing Allied Insurance and prepare a report that
summarizes your findings and recommendations. Be sure to address the following issues:
1. The payoff table of Russo Manufacturing, ignoring all the probabilities.
(5 marks)
2. Recommendations regarding which decision the management should take if they ignore
the probabilities and decide to apply the following decision criteria:
a. Optimistic Approach
(5 marks)
b. Conservative Approach
(5 marks)
c. Minimax Regret Approach
(5 marks)
3. Computation of the posterior probabilities of weak demand, medium demand and
strong demand given the market research is conducted. Briefly explain the meaning of
these probabilities.
(5 marks)
4. A decision tree illustrating the decisions and events that Russo is facing. All the payoffs,
probabilities and decision at each step need to be labelled carefully on the tree.
(25 marks)
5. A recommendation whether the market research should be undertaken. Explain clearly
the reasons for your recommendation.
(10 marks)
6. A decision strategy that Russo should follow if they take the recommended action in 5.
(10 marks)
7. A sensitivity analysis to illustrate how different decisions change if the prior probability
of [xiii.] change by 0.1 at a time.
(20 marks)
Presentation (10 marks)
The report must be written in a clear manner and including the required items. There is no need
to restate the questions in your report. Your report must have the following structure:
I. Executive summary
Give an overview of the problem, the solutions and the recommendation
II. Introduction
Introduce the case study and the objectives of the report
III. Main body
This section addresses all the questions associated with the case study.
IV. Conclusion
Conclude the case study and present your recommendations to the board of directors
based on the analysis.
>Sheet )
(thousand Euro) (thousand Euro) (thousand Euro) (thousand Euro) (thousand Euro) (thousand Euro) 0 40
. 0
.8 4.8 9
24.89 0.04 strong demand .99
0.71 0.02 weak demand 0.81 medium demand 0.23 0.54 medium demand .99
0.23 0.25 strong demand 0.12 0.03 0.04 0.35 strong demand 0.03 0.23 0.38 medium demand 0.06 0.20 medium demand 0.44 0.46 0.12 0.18 0.71 medium demand 0.20 0.02 0.05 0.36 strong demand 0.28 0.06 0.23 strong demand 10.99 0.43 0.24 0.02 0.12 weak demand 0.30 0.04 0.28 0.68 weak demand 9.16 0.25 23.01 0.03 0.38 0.59 weak demand 0.71 0.09 0.18 weak demand 0.02 0.19 weak demand 0.24 0.03 0.13 weak demand 24.64 0.06 0.03 0.27 0.30 0.44 medium demand 0.04 0.02 0.49 0.50 strong demand 0.02 0.02 0.11 0.22 weak demand 0.25 0.09 0.59 medium demand 0.24 0.16 0.22 0.62 medium demand 0.03 0.03 0.24 strong demand 7.29 0.08 0.42 0.04 0.39 weak demand 0.38 0.17 5.19 0.27 0.30 0.43 medium demand 0.12 0.04 0.09 0.35 0.56 weak demand 0.44 0.15 0.20 strong demand 0.30 0.35 0.01 0.12 0.87 weak demand 0.61 0.09 7.88 0.19 0.22 0.59 strong demand 55.60 0.03 0.17 5.85 0.09 0.22 strong demand 31.58 0.13 0.24 0.11 0.27 0.62 medium demand 0.06 0.04 6.15 0.21 0.35 0.44 weak demand 59.66 0.02 0.21 0.24 weak demand 0.57 0.08 0.25 0.37 strong demand 0.30 0.02 0.03 0.04 medium demand 0.22 0.07 26.77 0.04 0.40 0.57 weak demand 0.09 0.09 0.07 0.08 weak demand 0.06 0.07 4.51 0.30 0.31 0.39 strong demand 0.22 0.02 0.05 0.22 0.73 weak demand 0.84 0.08 4.00 0.07 0.46 medium demand 0.46 0.32 0.03 0.19 medium demand 0.31 0.36 0.06 0.19 strong demand &”Helvetica Neue,Regular”&12&K000000&P
thousand Euro 12.05 – – – DEMAND 0
0.000 0.00 8.070 3.418 22.834 0.1 0.1 89.477 50.633 -10.780 High Medium Low1
Student number
First name
Surname
[i.]
[ii.]
[iii.]
[iv.]
[v.]
[vi.]
[vii.]
[viii.]
[ix.]
[x.]
[xi.]
[xii.]
[xiii.]
(
thousand Euro
s1
9
0
6
4
Mehmet Hiram
Abas
–
11
3
8
7
12
5
87.20
4
0.20
61.59
0.76
0.23
23.70
0.1
0.35
0.46
weak demand
s20006880
Shakir
Afridi
-14.74
8.38
60.35
98.61
58.57
28.96
0.28
0.34
5.38
0.04
0.25
0.71
strong demand
s19006667
Yash
Aggarwal
–
24.89
12.25
7
0.81
52.48
66.82
0.12
14.66
0.02
0.30
0.68
s19004814
Ghaith Maher S
Alnahdi
-27.86
10
1
31.58
44.88
39.87
59.66
0.54
0.40
17.62
0.11
0.18
medium demand
s18006477
Mohamed Yusuf
Al Sadiq
-28.61
11.02
86.18
49.26
4
9.16
62.75
0.42
0.24
15.76
0.44
0.53
s18003315
Arthur
Andersson
-28.54
7.10
76.87
8
6.15
59.28
41.24
0.06
1
5.85
0.16
0.36
0.48
s20005179
Aaveg
Bagdi
-17.50
8.82
57.17
6
0.38
28.69
60.53
0.72
5.24
0.03
0.43
s18003050
Lidia
Barkhanoeva
-16.36
13
1
26.77
4
7.29
20.28
3
0.32
0.49
15.18
0.09
0.66
s19004550
Bibiane Frederika Whilemina Ma
Beerens
-15.88
13.73
87.45
7
0.57
52.94
67.45
21.21
0.61
s18002952
Paoloenrico
Bianchi
-18.00
14.32
65.76
60.29
37.11
24.40
0.50
3.97
0.39
s17005332
Karl
Bork
-26.87
13.90
58.74
75.12
22.36
31.61
0.56
0.05
13.42
0.74
s19004217
Prateek
Chotrani
-11.78
12.76
111.58
9
0.87
49.36
29.04
23.01
s19000854
Andrew
Dadlani
-17.37
13.10
130.56
73.29
22.43
26.58
24.88
0.59
s19006295
Manuela Larissa
Diago Garcia
-13.74
13.32
56.01
51.35
22.51
49.50
7.99
0.13
0.63
s18005601
Axel
Ehrnrooth
-1
5.19
115.56
79.36
47.80
6
4.00
12.54
0.86
s19003830
Emaan
Faisal
-27.30
8.39
59.26
81.99
22.53
3
4.51
0.27
26.12
s19004492
Vedant Anil
Farande
-23.13
119.97
69.21
29.66
38.29
0.15
s18000143
Carl
Fehrling
-29.23
5.63
69.52
97.84
48.78
63.09
23.04
0.31
0.51
s19003523
Ki
Fung
-21.98
13.78
135.73
65.91
24.64
66.86
0.62
0.22
23.29
0.78
s17001507
Daria
Jakubowska Claramunt
-18.86
9.46
71.15
101.40
59.15
58.11
0.60
3.96
0.84
s19003855
Bengt
Jonsson
-18.19
14.47
50.72
50.40
28.91
19.34
s19002991
Jonathan
Khazaal
-18.25
12.04
128.13
57.19
49.92
24.18
12.86
0.01
s17002026
Yuvraj
Kukreja
-12.30
7.03
77.18
81.26
43.70
22.98
7.52
0.67
s18002708
Bence
Kun
-23.71
6.07
101.98
52.97
3
7.88
28.22
6.50
0.08
0.33
s18000334
Adnane
Lahlou Mimi
-18.43
10.59
84.02
38.13
32.03
55.60
0.17
12.70
s18000548
Adrian
Lindqvist
-16.44
8.58
57.97
55.48
22.17
56.18
0.10
12.91
0.73
s19000617
Yuchen
Liu
-24.00
84.08
51.17
51.96
56.74
20.22
0.58
s19003472
Amina
Mammadzada
-18.13
14.45
128.08
83.82
46.15
27.15
s18006913
Maximilien
Moeremans D’Emaus
-14.13
14.33
104.24
35.31
28.19
24.32
16.90
s19001484
Teresa
Nava
-18.92
13.47
118.76
44.00
43.74
24.90
0.14
26.04
0.65
s19006625
Khush
Oberoi
-10.78
12.05
89.48
97.55
50.63
54.05
14.24
s20001029
Sethanan
Osatis
-22.31
6.31
142.16
88.93
53.41
42.60
s19004347
Amanvir
Patel
-26.36
10.87
12
0.21
94.80
54.85
0.69
s18004908
Karsang
Paturel
-12.57
9.57
73.17
49.63
52.69
17.75
s17004605
Nansi
Petrova
-22.25
14.95
132.84
60.59
59.59
55.03
s20006025
Esha
Pilinja
-25.65
11.46
147.04
45.21
57.38
0.07
20.45
0.55
s19002989
Juan Jose
Salazar Puig
-15.75
11.03
141.53
64.16
38.73
48.09
4.72
0.37
s18006638
Nicola
Scaramuzzo
-25.35
8.72
111.22
94.44
39.54
35.68
18.46
0.93
s00908268
Samuel
Sinclair
-19.96
14.22
54.83
90.73
33.89
23.49
s19007079
Anurag
Singhi
-24.83
7.79
141.40
89.93
48.56
26.92
6.30
0.85
s19000865
Marius
Slinning
-18.42
14.55
55.38
45.39
27.58
34.80
s17001105
Tim
Soliman
-24.23
5.70
57.15
81.29
40.97
57.52
13.37
s19005587
Nishanth
Srinivas
-17.88
11.04
69.80
97.14
59.85
28.25
0.47
s18007190
Shubham
Tantia
-17.71
14.14
68.28
58.91
34.49
46.88
23.78
0.79
s19001451
Gabriele
Valente
-29.29
10.37
63.97
35.32
55.50
56.24
22.28
0.75
Khush Data
s19006625
Khush Oberoi
Comment
1 -10.78
Demand for the finished product is low and Russo manufactures the parts.
2 12.05
Russo purchases the component part, hence no production cost and demand of the finished product is low.
3 89.48
when demand for the finished product is high and Russo opts to manufactures
4 97.55
Demand is high and Russo purchases the part
5 50.63
Demand for the finished product is at medium level and Russo manufactures the component part.
6 54.05
Russo purchases parts under medium level.
7 0.30
Probability of weak demand
8 0.35
Probability of strong demand
9 14.24
The cost of the research
10 0.01
11 0.12
12 0.87
13 weak demand
Minimax regreat Approach
MINIMAX REGREAT APPROACH
DEMAND
SUPPLY
HIGH
MEDIUM
LOW
MANUFACTURE
89.477
50.633
-10.780
PURCHASE
97.547
54.052
PROBABILITY
REGREAT TABLE
SUPPLY HIGH MEDIUM LOW MANUFACTURE
8.070
3.418
22.834
PURCHASE
0.00
Maximum Regreat
Payoff Table
DEMAND
SUPPLY HIGH MEDIUM LOW
MANUFACTURE 89.477 50.633 -10.780
PURCHASE 97.547 54.052 12.05
PROBABILITY – – –
Sensitivity Anaysis
DEMAND
SUPPLY HIGH MEDIUM LOW
MANUFACTURE 89.477 50.633 -10.780
PURCHASE 97.547 54.052 12.05
PROBABILITY 0.1
0.1 0.1
0
Scenario-Manufacture
High
Medium
Low
Weak demand
0.1
89.4765471956
50.633313687
-10.7796139387
Scenario-Purchase
Weak demand 97.547 54.052
12.055
0.1
97.5468307129
54.0516921618
12.0545329082