Advanced Decision Support Systems for Business Development

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DECISION SUPPORT TOOLS
1

Table of Contents
Question 1.......................................................................................................................................3
1.......................................................................................................................................................3
2.......................................................................................................................................................3
3.......................................................................................................................................................4
4.......................................................................................................................................................4
5.......................................................................................................................................................4
Question 2.......................................................................................................................................5
1.......................................................................................................................................................5
2.......................................................................................................................................................6
3.......................................................................................................................................................6
4.......................................................................................................................................................6
Question 3.......................................................................................................................................8
1.......................................................................................................................................................8
2.......................................................................................................................................................8
3.......................................................................................................................................................8
4.......................................................................................................................................................9
5.......................................................................................................................................................9
6.....................................................................................................................................................10
Question 4.....................................................................................................................................11
Question 5.....................................................................................................................................13
References.....................................................................................................................................14
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Question 1
1.
Time
between
arrivals
Number of
occasions
Relative
frequency
Cumulativ
e relative
frequency
10 15 15.00% 15.00%
15 30 30.00% 45.00%
20 25 25.00% 70.00%
25 20 20.00% 90.00%
30 10 10.00% 100.00%
Total 100
The above table makes the calculation easier and accordingly all the given problems can be
solved with the help of above table. The required probability will be determined by p.
Accordingly, the required p (time between arrivals will be at least 20 minutes) = 0.55 (0.25 +
0.20 0.10). Thus, the probability for the time between arrivals will be 20 minutes or more will be
0.55 or 55%.
2.
Appointmen
t length
Number of
occasions
(Frequency
)
Relative
frequenc
y
Cumulativ
e relative
frequency
7 40 40.00% 40.00%
12 20 20.00% 60.00%
15 20 20.00% 80.00%
20 10 10.00% 90.00%
30 10 10.00% 100.00%
Total 100
The required probability will be 0.40+0.20, i.e., 0.60. Thus, the probability that the appointment
time will be 12 minutes or less will be 0.60 or 60%.
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3.
To perform monte-carle simulation, cumulative frequency will be required which have been
computed in the above two tables.
Pati
ent
no.
Rand
om
no.
Time
betw
een
arriv
als
Time
of
arriv
als
Rand
om
No.
Appoint
ment
length
(Service
time)
Tim
e of
servi
ce
ende
d
Tim
e of
servi
ce
start
ed
Waiti
ng
time
Idl
e
ti
me
Cyc
le
tim
e
Peop
le
waiti
ng
1 - 0 99 30 30 0 0 0 30 0
2 97 30 30 24 7 37 30 0 0 7 0
3 61 20 50 74 15 65 50 0 13 15 0
4 4 10 60 97 30 90 65 5 0 35 1
5 7 10 70 63 15 85 95 25 0 40 1
6 1 10 80 3 7 87 110 30 0 37 2
7 31 15 95 99 30 125 117 22 0 52 2
8 45 15 110 91 30 140 147 37 0 67 2
9 13 10 120 9 7 127 177 57 0 64 2
10 7 10 130 15 7 137 184 54 0 61 2
After performing simulation for 5 times, total waiting time will be 30 minutes (5 + 25 minutes).
It can be clearly observed that for determining the waiting time, random number is a must. As
such, different random number will change the waiting time.
4.
At the end of the first hour or 65 minutes, total idle time will be 13 minutes.
5.
The largest queue of students that forms are only 2.
4

Question 2
1.
Calculation of total variable cost for
producing 2 rooms:
Particulars Amount
(in $)
Direct construction
material
160000
Labour cost 67500
Variable overhead
cost 81000
Total 308500
Calculation of total variable cost
for producing 4 rooms:
Particulars Amount
(in $)
Direct construction
material
320000
Labour cost 54675
Variable overhead
cost 131220
Total 505895
Calculation of total variable cost
for producing 8 rooms:
Particulars Amount
(in $)
Direct construction
material
640000
Labour cost 35872.27
5

Variable overhead
cost 172186.95
Total 848059.22
2.
Learning curve theory is widely used in the industry or sector where the same production process
is continuously used or applied. In other words, learning curve is applied where similar process
is performed continuously. As such, business operations where are of such nature each and every
time different order is taken order with aim of satisfying all the customers having varied or
different needs.
As per the learning curve theory, in case of a repetitive work the time taken to perform a task
decreases as it assumes that the concerned expert get specialized skills in performing that
particular task.
Learning curve theory helps to determine the labour cost as this theory is likely to affect majorly
the cost associated with the labour (be it wages, salaries or any cost affecting directly or
indirectly the labour cost). Furthermore, it helps to identify the relationship that exist between the
cost-volume and profit elements.
3.
Learning curve and experience curve are highly related but still the scope and ambof these
concepts are totally different. To understand the similarity and difference, following statement
will be helpful. Learning curve is a narrower concept whilst experience curve is a broader term
as it comprises various aspects including learning curve.
Furthermore, learning curve is a qualitative aspect and on the other hand experience curve is
more than a qualitative field of study as it encompasses several branches of study covering
learning curve along with other aspects.
4.
80% cost experience curve indicates that if the manufacturer of a product or service doubles, the
cost associated with the manufacturing decreases by 20% and this process goes on. This decrease
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in cost happens due to experience curve as it assumes that cumulative average cost goes on
decreasing. This arises due to reduction in number of labour hours.
7

Question 3
1.
50 100 150 200 250 300 350 400
0
500
1000
1500
2000
2500
3000
3500
Administrative costs
Patients per day
Administrative costs ($)
2.
The range of activity depicts the lowest and highest price.
Range of activity for number of patients will be 75 to 375.
In the same manner, range of activity for administrative cost will be 820 to 3220.
3.
To estimate the administrative costs, linear regression equation model can be an important role.
Two variables form part of linear regression, dependent and independent variable.
In the given case, number of patients per day will be independent variable and conversely the
administrative cost will be dependent variable. x1 = 75, x2 = 375. y1 = 820, and y2 = 3220.
8

Where,
x1 = lowest value of number of patients, and
x2 = highest value of number of patients.
On the other hand,
y1 = lowest value of administrative costs, and
y2 = highest value of administrative costs.
Slope, b = (y2 - y1) / (x2 – x1)
In the given case, slope = (3220-820) / (375-75) = 8.
In the same manner, Intercept will be y1 – bx1.
Substituting the values, intercept can be easily determined as computed below:
Intercept, a = 820 – 8 (75) = 220.
All these values will help will help to determine the regression equation,
Regression equation = y = 220 + 8 x.
4.
In the given case, the number of patients per day is 200.
Through this, administrative cost can be easily determined with the help of regression equation
formed earlier.
Accordingly, administrative cost can be predicted =220+8*200 = 1820.
5.
Range of emergency appointments = 20 to 42.
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Range of patients = 75 to 375
Range of administrative costs = 820 to 3220.
6.
Slope = (6029500-2725*23440)/ (12 * 731875 – 2725 * 2725 ) = 6.25
Regression equation: y = 534.13 + 6.25x
10

Question 4
1.
2.
To reach the break-even point, 62500 roses need to be sold off. In the given case, sales volume
will be 50000. Thus, the break-even point will be 50000.
All the break even points have been determined through taking the 25% mark up percentage.
Native break-even point = 50000 + 250000 = 9x = 33333 units
Imported Break-even point = 250000 = 8 x = 31250 units.
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Native break-even point = 50000 units
Imported break-even point = 208333 units
Justification or reason:
To cover the deficit arising in native sales, efforts should be made to increase the sales so that the
higher amount of profit can be gained therefrom.
Fixed cost should be allocated amongst all the three segments.
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