Forecasting QuestionsStudent NameUniversity Affiliate.docx

Forecasting Questions
Student Name
University Affiliate
Forecasting Questions
Problem 1: Planning
Step 1: Define – Create a list of all the tasks that require to be
completed so as to complete this examination appropriately and
keep a track of the tasks accordingly
Step 2: Plan – What information is available for solving the
problem? Lecture Notes and Canvas Handouts. The lecture
Notes provided is from Notes on PERT Chart, GRANTT Chart
and Activity Matrix.
Step 3: Execute - Create an activity matrix and a table to make
comparisons on your plan

Activity Matrix
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
A
A
x
x

x
S
GRANTT chart
GANTT CHART
PROJECT TITLE
CSE171B Midterm
COMPANY NAME
CSE171B
PROJECT MANAGER

Shen Cheng
DATE
2/11/2019
WBS NUMBER
TASK TITLE
TASK OWNER
START DATE
END DATE
DURATION
PCT OF TASK COMPLETE
FRIDAY
SATURDAY
SUNDAY
MONDAY
TUESDAY

1.1
Activity Matrix
Shen Cheng
2/7/20
2/7/20
1
100%

1.2
GANTT chart
Shen Cheng
2/7/20
2/11/20
1
100%

1.3
PERT Chart
Shen Cheng
2/7/20
2/11/20
1
100%

1.4
Keep track of each task and document
Completion
Shen Cheng
2/7/20
2/11/20
100%

2
Problem 2
2.1
Read the Specialty Packaging Corporation Case

Study
Shen Cheng
2/8/20
2/8/20
1
100%

2.2
Competitive Strategy
Shen Cheng
2/8/20
2/8/20
1
100%
2.3
Supply Chain Strategy
Shen Cheng
2/8/20

2/8/20
1
100%
2.4
Where does SPC lie in the zone of strategic fit
between IDU and responsiveness?
Shen Cheng
2/8/20

2/8/20
1
100%
2.5
Identify what SPC’s high-level SC strategy
should be for each of the SC drivers.

Shen Cheng
2/8/20
2/8/20
1
100%
3
Problem 3

3.1
Form Hypothesis
Shen Cheng
2/8/20
2/10/20
1

100%
3.2
Forecast Demand for clear plastic using the 5
Methods
Shen Cheng
2/8/20
2/10/20

1
100%
3.3
Identify the better method for Clear Plastic.
Shen Cheng
2/8/20
2/10/20
1
100%

3.4
Was the Hypothesis Correct?
Shen Cheng
2/8/20
2/10/20
1
100%

3.5
Forecast Demand for 2007 Clear Plastic.
Shen Cheng
2/8/20
2/10/20
1
100%

4.1
Why should SPC have a cycle inventory?
What are the following values for clear plastic?
Shen Cheng
2/10/20
2/10/20
1
100%

4.2
Shen Cheng
2/10/20
2/10/20
1
100%

4.3
Short-Term Discounting
Shen Cheng
2/10/20
2/10/20
100%

5.1
Should SPC have a safety inventory? Why? How much safety
inventory would you recommend
for SPC?
Shen Cheng
2/11/20
2/11/20
1
100%

6.1
Create table to compare your plan
Shen Cheng
2/11/20
2/11/20
1
100%

15 Minutes Each
F, G, H, I
15 Minutes Each
J
5 Minutes
K
300 Minutes
L
10 Minutes
M
5 Minutes
N
15 Minutes
O
55 Minutes
P
20 Minutes
Q, R
15 Minutes
S
30 Minutes
Keep track of each task and document completion

Step 4: Check – Is the work done correct in every detail? This
work is correct all ways because while working on the problem,
intense planning was conducted for execution. To make it more
clear and accurate, there was the use of lecture notes and canvas
handouts for reference.
Step 5: Learn and Generalize – This exercise has been great as
it has enabled me to stay on track and also become more
accurate and precise. This will help me produce high quality
results during finals.
Problem 2: Supply Chain Strategy for SPC
Step 1: Define the Problem - Establish and Analyze SPC’s
competitive strategy
Step 2: Plan – Step 2: The information available for solving the
problem include lecture notes, textbooks and the ‘Specialty
Packaging Corporation’ Case Study
Step 3: Execute – SPC’s competitive strategy should be the
Porter’s Five Forces Model. This is shown in the diagram

belowCompetitive Strategy
Porter’s Five (Six) Forces Analysis
New Entrants: Alpha Packaging SKS
Suppliers: Polystyrene Resin supplier
Competitors:
Amcor Berry Plastic Tetra Pak
Buyers:
Supermarket Consumers
Compliments:
N/A
Substitutes:
Ceraminc Glass
Eco-Friendly Materials
Explanation of the six forces:The Porter’s Model has five forces
and they will help SPC in the following ways; i. Competitors –
Competition is very high because most companies packaging
process is affordable as plastic is cheap. ii. New Entrants – The
force of new entrants is low as most new entrants are small
scale company’s iii. Complements – There are no complements
obtained iv. Suppliers – the supplier force is medium v. Buyers
– The buyer’s force is high vi. Substitutes – The large force of
substitute products is low.
Supply Chain Strategy
SPC Strategic FitEfficiency/Responsiveness SpectrumHighly
Efficient Somewhat Efficient Somewhat Responsive
Highly ResponsiveIn the manufacturing and supply of plastic
containers, Specialty Packaging Corporation (SPC) is supposed
to aim for high efficiency in its supply chain to be able to match
with customer’s demand. The following graph represents the
Implied Demand Uncertainty for SPC.
Implied Demand Uncertainty
High Responsiveness / Low Efficiency

Low Responsiveness / High Efficiency
Low
IDU High IDU
In the above figure, SPC lies at the lower part of the IDU and it
is responsive in the Zone of Strategic Fit due to the relatively
low demand of products prevailing. SPC is required to develop
strategies that will enable it to have a high-level supply chain
strategy. Therefore, SPC is required to identify with six drivers
that help in improving the supply chain and they are
Transportation, Facilities, Inventory, Information, Pricing and
Sourcing. Developing these factors will help in enhancing
efficiency in the supply chain process.
Step 4: Check – My assumptions on the company and products
are valid. I have also understood the SPC Manufacturing
process
Step 5: Learn and Generalize – SPC’s function in the supply
chain process should be cohesive and should also work towards
succeeding in its objectives.
Problem 3: Demand Forecasting For SPC
Step 1: Define – Establish the hypothesis and forecasting

method that Julie William should use
Step 2: The information available for solving the problem
include lecture notes, textbooks and the ‘Specialty Packaging
Corporation’ Case Study
Step 3: Execute
Static Method
Given Data
Year
Period
Quarter
Clear Plastic Demand ('000 lbs)
2002
1
I
2250
2
II
1737
3
III
2412
4
IV
7269

2003
5
I
3514
6
II
8143
7
III
3459
8
IV
7056
2004
9
I
4120
10
II
2766
11
III
2556
12
IV
8253

2005
13
I
5491
14
II
4382
15
III
4315
16
IV
12035
2006
17
I
5648
18
II
3696
19
III
4843
20

IV
13097
De-seasonalize the demand in order to run linear regression to
estimate various levels and trends. The equation to use is:
We are measuring demand on a quarterly basis therefore;
periodicity (p) is 4. We then start deseasonalizing demand at
period (t) = 3.
Excel formula used: = (D2+D6+2*SUM (D3:D5))/8
Year
Quarter
Period
Clear Plastic
Demand ('000 lbs)
De-Seasonalized
Demand
2002
I
1
2250
II
2
1737

III
3
2412
3575
IV
4
7269
3784
2003
I
5
3514
3965
II
6
8143
4070
III
7
3459
4119
IV
8
7056
4272

2004
I
9
4120
4237
II
10
2766
4275
III
11
2556
4596
IV
12
8253
4969
2005
I
13
5491
5391
II
14
4382
6083
III

15
4315
6575
IV
16
12035
6509
2006
I
17
5648
6490
II
18
3696
6688
III
19
4843
IV
20
13097
Forecasting using Holt’s Method
We now forecast demand using Level and Trend corrected
exponential smoothing. The assumption is that the data has
level, L, and trend, T, only. Process:

Step 1: Regress the given data to compute the initial values of
the level, L0, and initial trend T0. Forecast, F1 = L0 + T0.
Step 2: Adapt Use two smoothing constants, α=0.06 and β=0.06,
to smooth respectively level and trend. L1 = αD1 + (1-α) [L0 +
T0], T1 = β [L1 – L0] + (1-β) T0, Forecast, F2 = L1 + T1
Step 3: Forecast. Ft+1 = Lt + Tt, Lt+1 = αDt+1 + (1-α) [Lt +
Tt], Tt+1 = β [Lt+1 – Lt] + (1-β) Tt
In order to obtain L0 and T0, I graphed the Demand for black
plastic and obtained the slope of the functions as L0 = 2042.8
and T0 = 286.61
Forecasting using Winter’s Method
Winter’s Method starts off similarly to the static method. We
de-seasonalize demand by running it through a regression
analysis, and then find the seasonal factors for it. Since the data
remains the same as the static method, the values are equal to: L
= 3046.5 and T = 226.87
Savg1 = (S1+S5+S9+S13+S17)/5 = 0.81, Savg2 =
(S2+S6+S10+S14+S18)/5 = 0.54, Savg3 =
(S3+S7+S11+S15+S19)/5 = 0.64, Savg4 =
(S4+S8+S12+S16+S20)/5 = 1.65
Initial Forecast = F1 = (L0 + T0) (S1) = 2665
Adaptation: Let α=0.06, β=0.06, γ=0.06, Lt+1 = α (Dt +1/St+1)
+ (1-α) (Lt + Tt), Tt+1 = β (Lt+1 – Lt) + (1 - β) Tt, St+p+1 = γ
(Dt +1/Lt+1) + (1 - γ) St+1
Demand Vs Forecast using Winter’s Method
The forecasting method that Julie Williams should use is the
Winters Forecasting Method as it has been able to forecast clear
plastic well. After analyzing the data, it is correct to say that
the greatest factor is the seasonality of data and there is a
negative significant trend. The forecasting results were as
follows and the annual demand was drawn to be 28770 in the
year 2007.

2007 Demand Forecast for Clear Plastic (‘000 lb.):
Year
Quarter
Period
Forecast Ft
2007
I
21
6090
II
22
4197
III
23
5042
IV
24
13441
Step 4: Check – I have gone through the work several times and
I have elaborated all numbers and equations appropriately. My
assumptions are also reasonable as the results that I obtained
make a lot of sense.
Step 5: Learn and Generalize – To establish the most
appropriate method of forecasting, we have to try all methods
and see how well they predict the actual demand. Through error
analysis, we have been able to see which method was the best
for Julie and Winters Model was finalized to be appropriate to
improve her supply chain and match with both supply and

demand.
Problem 4: Cycle Inventory for Polystyrene At SPC
Step 1: Define – Establish why SPC should have a cycle
inventory in place.
Step 2: Plan – Information for this question is available on
Lecture Notes, Textbooks and SCM text on ‘Short-Term
Discounting’
Step 3: Execute
SPC should have a cycle inventory so that it may be able to
minimize its total inventory costs. SPC can also minimize the
total cost of holding inventory and transportation through
calculating the optimal quantity of inventory per shipment.
Given data/data from problem 3
Variables: Annual demand for clear plastic: 37,974, Unit Cost
= $20.00, % Holding Cost = 10%, Fixed shipping cost per order
= $300, 1 unit = 1000 pounds (lbs)
a. Lot size per shipment to minimize total cost
D = annual demand = 37,974 S = 300 h = 0.10 C = 20,
Lot size per shipment to minimize total cost is approximately
3,375 units
b. Economic order quantity (EOQ)
The EOQ is similar with the Optimal Order Size which is also
the lot size per shipment. The total cost has been minimized
therefore the Economic Order Quantity is equal to 3,375 units.
c. Number of shipments/year of polystyrene resin in order to
meet the forecasted demand for clear plastic in 2007.
D = annual demand = 37,974 Q* = 3,375 units, Insert formula as
37,974/3,375 = 11.2515556Number of shipments/year of
polystyrene resin in order to meet the forecasted demand for

clear plastic in 2007 is approximately 11 shipments.
d. Cycle inventory
Q* = 3,375 units, Insert formula as 3,375/2 = 1,687.5. The
Cycle Inventory is approximately 1,688 units.
e. Cycle inventory holding cost
Holding cost = hC
Cycle inventory holding cost = (Q*/2) hC
(3,375/2) (0.10)(20) = 3,375
Cycle inventory holding cost is $3,375
f. Replenishment cycle time
a. ��ℎ�� = # days in a year /
# shipment/year
b. 365/11 =33.1818
Replenishment cycle time is approximately 33 days
g. Average flow time
D = annual demand = 37,974 Q* = 3,375 units
3375/2 (37,974) = 0.044438 Average flow time is around 0.044
year = 0.53 month = 16 days
1 year (365 days)
Q/2 = Avg

Inv = 1688
units
Replenishment cycle Time (T) = 33 days
Q* = lot size = 3,375
units
The graph shown above shows the clear plastic inventory
function as EOQ, Replenishment cycle time and total cycle
inventory.
Short Term Discounting:
Now, if the supplier offers a promotional discount of 25% per
unit at the beginning of the year, we determine the optimal
order quantity and the size of the forward buy below:
Given Data
d = discount = 25%, D = demand = 37,974, h = 10%, C = 20, Q*
= 3,375
Insert formulae to obtain 8224.556962, therefore optimal order
quantity at the discounted price is around 8225 units
Forward buy = 8,225 – 3,375 = 4,850 units
Step 4: Check – My work is correct and accurate as I used the
required texts and notes in every detail. Therefore, my
assumptions are correct and accurate.
Step 5: Learn and Generalize – After calculating the values of
optimal lot size and economic order quantity, SPC can also take

advantage of the economies of scale. I now have a better
understanding on short-term discounting.
Problem 5: Safety Inventory for Polystyrene Resin at SPC.
Step 1: Define – Establish whether SPC should have a safety
inventory
Step 2: Plan – Information is available on Lecture Notes and
Textbooks
Step 3: Execute
SPC is required to have a safety inventory for polystyrene resin
at SPC as the demand is uncertain and product storage problems
may occur if the actual demand exceeds the forecasts. SPC
should also ensure that it has maintained a safety inventory for
clear plastic. The amount of safety inventory that I would
recommend for SPC will vary due to certain circumstances.
The clear plastic peak reduces every second quarter of the year
and by using the Winter’s method, the tracking signal value at
period 13 is estimated to be 2.03. The forecasts as period 13
have a value of 11,825 and the actual demand is 13,673. Results
show that SPS is supposed to have a safety inventory of 2000
units to counteract the underestimation with the remaining left
over inventory which can also be used for other future periods.
Step 4: Check - My estimates on the amount of Safety Inventory
that SPC should hold seem reasonable and my assumptions are
true as I have used the required textbooks and lecture notes
appropriately.
Step 5: Learn and Generalize – I have learned that with a basic
understanding of safety inventory, a manager can reach at a
reasonable estimate on the amount of safety inventory required.
Problem 6: Execution of Your Plan
Step 1: Define - Using a table compare your plan from Problem
1 with its execution. Indicate the reasons for the difference
between the plan and its execution. Add at least one more
column.
Step 2: Information for the problem is obtained from Problem 1
solutions. Assumptions have been made by using the problem
solver, student and audience. Build a table to compare the plan

with the execution.
Step 3: Execute the Plan
Plan
Execution
Reason
Improvements
Problem 1:
0.6 Hours
Finished on time Hours Spent: 0.6
No difference, plan was well executed, and
work done accurately
No improvements needed because everything went
as planned.
Problem 2:
1.5 Hours
This problem was pretty straightforward,
.
No improvements needed because everything went as planned.
Problem 3:
5.0 Hours
Took much longer than I expected Hours Spent: 5.5
This problem was time consuming and getting correct data and
numbers was quite difficult.
In the future I will automate to process of forecasting using
Visual Basic.
Problem 4:
1.6 Hours
Also took longer than I expected Hours Spent: 1.8
Time Planning was unplanned hence I started the question late
The problem was executed well
Problem 5:
0.3 Hours
Finished Earlier than expected
Hours Spent: 0.4
No difference due to being on schedule going into this phase of

the project
I lacked more data information for extensive analysis of the
question
Problem 6:
0.4 Hours
No difference, plan was well executed, and work was clear and
accurate
No improvements were required as everything was planned well.
Step 4: Check – The work written is correct and accurate as
study was done through using observations.
Step 5: Learn and Generalize – The demand forecasting problem
was very time consuming as it has more problems to solve than
others.
staticyearperioddemandde seasonregress dseasonavg
seaforecasterrorabs errormsemad%
errormapets20021225032740.690.81266541541517238741518.4
518.451.002173735010.500.5419081711711007622939.834.912.
0032412357537280.650.642372-
4040677162091.670.562.6147269378439551.841.656524-
74574518958634310.252.56-
0.58200353514396541820.840.813404-
1101101540732963.120.62-
1.0462143407044090.490.54240225925913961529012.112.02-
0.1773459411946360.750.642949-51051015677232114.732.10-
1.7487056427248631.451.65802296696625373740213.691.711.
01200494120423750900.810.81414424242256053600.570.061.1
9102766427553170.520.5428971311312047673374.740.471.661
12556459655440.460.64352797197127187239537.993.453.8812

8256496957711.431.6595191263126338223746715.301.285.992
005135491539159980.920.814883-
60860838130247811.080.854.58144382608362250.700.543392-
99099042407251522.591.612.33154315657564520.670.644105-
2102103987494944.870.322.001612035650966791.801.6511017
-101810184385725278.460.53-
0.062006175648649069060.820.815622-
26264128144980.460.03-
0.11183696668871330.520.5438871911913919014805.160.290.
2819484373600.660.644682-1611613726334643.320.17-
0.06201309775871.731.6512515-5825823709394704.440.22-
1.3020072178140.8163612280410.5443822382680.6452602484
951.6514013
Demand and De Seasonalized Demand
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097de season
35753783.753965.3754069.6254118.754272.3754237.3754274.5
4595.8754969.255391.1256083.3756575.3756509.256489.56688
.25
Period
Units
Demand vs Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast2665.194590
210721907.697828757372371.718697707656523.885508821593
404.350573079182402.467788343692949.379796827448021.65
7453704014143.506555947642897.237747930013527.04089594
7229519.429398586444882.66253881613392.007707516334104
.70199506711017.20134346895621.818521684563886.7776671
02644682.3630941867912514.97328835136360.9745045530243
81.547626688965260.0241933065714012.7452332337

Time
Units
Demand and De Seasonalized Demand
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097de season
35753783.753965.3754069.6254118.754272.3754237.3754274.5
4595.8754969.255391.1256083.3756575.3756509.256489.56688
.25
Period
Units
Demand vs Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast2665.194590
210721907.697828757372371.718697707656523.885508821593
404.350573079182402.467788343692949.379796827448021.65
7453704014143.506555947642897.237747930013527.04089594
7229519.429398586444882.66253881613392.007707516334104
.70199506711017.20134346895621.818521684563886.7776671
02644682.3630941867912514.97328835136360.9745045530243
81.547626688965260.0241933065714012.7452332337
Time
Units
4 pointyearperioddemandlevelforecasterrorabs errormsemad%

errormapets2002122502173732412472693417200353514373334
17-97971882192.760.55-
5.0062143383537331590159042291828174.2012.375.31734594
096383537637638264429510.861.556.348705640434096-
29602960142982962841.955.24-1.7420049412041954043-
777712716185671.870.21-
2.061027664350419514291429134851765351.645.160.4011255
64125435017941794151859175770.206.382.7212825644254125
-413241322814483103850.044.17-2.00200513549147674425-
106710672685478104019.421.49-
3.021443825171476738538525042609938.790.63-
2.7815431556115171856856238618798419.841.32-
1.93161203565565611-642464244816286132453.383.34-
6.292006175648659565569089084581446130016.070.95-
5.7118369664246595289928994793821138878.444.36-
3.2519484365566424158115814672988139932.631.72-
2.10201309768216556-654265426578899165649.952.50-
5.732007216821226821236821246821
Demand and Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast3417373338
34.54096.2540434194.54350.254124.54424.54767.255171.2556
116555.7565956423.56555.56821682168216821
Time
Units
simple exyearperioddemandlevelforecasterrorabs errormsemad%
errormapets0505220021225048845052280228027852605280212
4.54124.541.0021737469548843147314788784692975181.1890.
592.003241245584695228322837656781274494.6631.553.0047
26947214558-
271127117579572273637.299.322.022003535144649472112071
2076354995243034.356.872.77621434498464925062506634209

92443116.9219.493.787345944364498103910395590357224230
.044.294.588705645934436-
262026205749721228937.134.643.342004941204565459347347
35135726208811.481.283.8910276644574565179917994945672
205965.036.504.8211255643434457190119014824504204474.3
66.765.7812825645774343-
391339135698623220047.403.953.60200513549146324577-
9149145324459210116.641.283.33144382461746322502504948
61619695.710.413.6815431545994617302302462480018587.01
0.474.06161203550454599-
743674367791491220661.793.860.05200617564850815045-
6036037354535211210.670.63-
0.2318369649985081138513857052589207237.492.080.431948
4349894998155155668267019713.210.170.53201309754754989
-810881089635507227861.913.10-
3.102007215475225475235475245475
Demand and Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast5052.254884
.1154695.28814558.2908144720.933365164648.5173632504449
8.186321455384435.835142168054593.045033637974564.6623
31619694456.742591722514342.698036219164577.4961540460
14632.306384803254617.288001715054599.150721612155045.
301678315425081.463577616494998.33576295954989.0156171
81935475.494680151025475.494680151025475.4946801510254
75.49468015102
Time
Units
holtyearperioddemandleveltrendforecasterrorabs errormsemad%
errormapets020432872002122502325287233080806400803.563.
561.00217372559284232558858817619033433.8616.932.00324
12281728225591471471247042726.112.043.0047269334929728

17-445244525048335131761.2415.31-
2.7620035351436382973349-165165404409210864.690.94-
3.506214338272903638149514953742782115569.7811.63-
2.0073459407828838273683683227491104210.651.52-
1.868705645272974078-297829783932602128442.205.28-
3.8320049412047822954527407407351406611879.881.10-
3.8010276649382874782201620163569203127072.907.29-
1.9611255650652774938238223823760756137193.218.47-
0.0812825655172875065-319131914295950152338.653.22-
2.172005135491578528655172626396554314070.470.04-
2.3314438259702805785140314033822960140732.032.29-
1.3315431561342735970165516553750758142438.362.56-
0.15161203567452946134-590159015692427170349.033.06-
3.59200617564869552896745109710975428401166819.431.14-
3.0118369670312766955325932595717005175688.194.90-
1.0019484371592677031218821885668070177945.182.380.242
01309777662877159-593859387147725198745.342.27-
2.772007218053228341238628248915
22501737241272693514214334597056412027662556825654914
38243151203556483696484313097
Demand and Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast23302325.22
559.417282817.1208209923349.323714568913638.4052691587
53827.434071504244078.017183051584527.156846047094782.
29196461714938.494725000295064.904338750495516.6973200
56185785.344212131325970.272651518286134.3676029965567
45.267134015346955.335731490557030.973804483887158.887
687401478053.313168437418340.596795205468627.880421973
518915.16404874156
Time

Units
22501737241272693514214334597056412027662556825654914
38243151203556483696484313097
Demand and Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast23302325.22
559.417282817.1208209923349.323714568913638.4052691587
53827.434071504244078.017183051584527.156846047094782.
29196461714938.494725000295064.904338750495516.6973200
56185785.344212131325970.272651518286134.3676029965567
45.267134015346955.335731490557030.973804483887158.887
687401478053.313168437418340.596795205468627.880421973
518915.16404874156
Time
Units
winteryearperioddemandleveltrendavg seaforecasterrorabs
errormsemad%
errormapets0304722720021225032132230.81266541541517238
741518.4518.451.002173733342170.541872135135953382757.7
93.892.003241234832130.642259-
153153713362346.332.111.704726939102261.656097-
1172117239708646916.134.03-
1.6520035351440992240.813339-1751753237894104.981.00-

2.326214341922160.5423492062062769213769.631.60-
1.987345943512120.642819-64064029583041418.502.64-
3.348705647132211.6675855295292938454287.500.94-
1.9920049412048862190.813998-1221222628433942.960.33-
2.4810276649642100.542764-222365593550.070.01-
2.7511255650172010.65335880280227345739631.362.85-
0.4412825654002121.6586213653652617623934.420.370.48200
513549156052110.814558-93393330858643516.991.31-
1.7114438257302060.543155-1227122739409449128.002.00-
4.0115431558392000.643802-51351338535949311.890.79-
5.04161203563992221.649933-2102210263751659317.471.09-
7.73200617564865622180.825444-2042046024685703.620.21-
8.4018369665952070.56376973735692915431.970.11-
8.6919484366852000.654398-4454455497735389.200.48-
9.61201309772582231.6611422-1675167566251259412.790.64-
11.502007210.816090220.544197230.645042241.6513441
Demand and Forecast
demand2250173724127269351421433459705641202766255682
565491438243151203556483696484313097forecast2665.194590
210721872.238610328932259.256037905946096.679092646073
339.066782875962349.349563139042819.243717023297585.09
7211435493998.230148511152764.176991690343357.52245482
0438620.856258849564558.011574122063154.92820442176380
2.103661308849932.650049608615443.80700819583768.67266
4068224397.5170183944411422.3221643186089.566489907794
197.427599044435042.2004405455413440.5589011818
Time
Units
TIM-125/225

Management of Technology II:
Supply Chain Management
“Excel Tutorial”
Last modified:01/18/2012
written by:
R.Polany and S.Desa
UC Santa Cruz, Baskin School of Engineering
Table of Contents
Purpose
...............................................................................................
...................................... 1
Context
...............................................................................................
....................................... 1
Important Note for Mac users
...............................................................................................
...... 1
Tutorial platform
...............................................................................................
...................... 1
Solver Add-In
...............................................................................................
........................... 1
Problem Definition

...............................................................................................
....................... 2
Treatment
...............................................................................................
................................... 3
Execution: Pre-Processing (Setup)
............................................................................................ 4
Step 0:
...............................................................................................
..................................... 4
Execution: Processing
...............................................................................................
................. 5
Step 1: Build a ScenarioParameters worksheet
...................................................................... 5
Step 2: Build the BaseCase NPV analysis worksheet
............................................................. 6
Step 3: Create the +10% DevCost Worksheet
........................................................................ 8
Step 4: Create the -10% DevCost Workshet
..........................................................................10
Step 5: Create the +20% DevCost Workshet
.........................................................................11
Step 6: Create the -20% DevCost Worksheet
........................................................................12
.......................................................................13
........................................................................14
Step 9: Create the DevelopmentCost_Sensitivity summary
worksheet ..................................15
Step 10: Worksheet Tab Review
................................................................................ ...........16
Step 11: Graph the Change in NPV ($) vs. Change in DevCost

(%) ......................................17
Step 12: Create the +10% SalesVol
Worksheet.....................................................................21
Step 13: Create the -10% SalesVol Worksheet
.....................................................................23
Worksheet.....................................................................24
.....................................................................25
Worksheet.....................................................................26
.....................................................................27
Step 18: Create the SalesVolume_Sensitivity summary
worksheet .......................................28
Step 19: Graph the Change in NPV ($) vs. Change in Sales
Volume (%) ..............................29
Step 20: Using Solver to Determine Max Development Cost
.................................................30
Results: Post-Processing
...............................................................................................
...........36
Step 21: The Trade-off for Change in NPV ($) vs. Change in
DevCost (%) ...........................36
Step 22: The Trade-off for Change in NPV ($) vs. Change in
Sales Volumes (%) .................37
Step 23: Determine Maximum Development Cost with Solver
...............................................38
Step 24: Relationship of Development Cost to Sales Volume
................................................39
Conclusions
........................................................................................... ....
...............................40
Works Cited

...............................................................................................
...............................41
Page 1
Purpose
In this tutorial, you will develop intermediate-level Excel skills,
as follows:
Pre-processing
1. Setting Up Excel Workbooks
a. Linking worksheets
b. Writing formulas
c. Formatting Spreadsheets
Software
Automation
Rapid
Problem
Solving
Processing
2. Exploring Scenarios
a. Entering parameters
b. Adjusting parameters

c. Performing sensitivity
analysis,
d. Optimization
e. Simulation
f. Summarizing results
Post-
Processing
3. Presenting Results
a. Graphing
b. Generating reports
c. Exporting content
d. Drawing conclusions
Figure 1: Structured Approach to Rapid Problem Solving with
Software Automation
This tutorial will walk you through the Pre-Processing,
Processing, and Post-Processing
approach to developing software automation utilizing Microsoft
Excel. The lessons you learn
will teach you how to solve new problems rapidly, and,

efficiently. You will then apply this new
knowledge to solving Supply Chain problems in the coursework
homework, exams, and project.
Important Note:
The skills identified above are essential for the subsequent work
you will be performing in the
TIM-125/225 coursework. We recommend you invest the time
now and develop your skills as
the coursework ramps up quickly. This tutorial can also help
you identify your strengths and
weaknesses using Excel, so that you can get the help you need
and stay current with the
coursework. You will be in very good shape for the course, once
you can 1) Duplicate the
results of this tutorial, 2) Achieve equal to or better quality and
3) Understand the process.
Page 1
Context
In TIM-105/205 (1), you were taught how to create and
implement a quantitative financial model
(i.e., NPV Analysis) for product development and
commercialization (2). We will use this
context1 to develop your Excel skills as listed above.
Important Note for Mac users
Tutorial platform
This tutorial is currently written for use on the Microsoft
Windows operating system, loaded with

Microsoft Excel 2010. So please beware: Some of the Graphic
User Interface features are
slightly different in a Mac environment.
Solver Add-In
As part of this tutorial, we walk you through how to use the
Solver Add-In to Excel and there are
issues with compatibility of this Add-In and the Mac version of
Excel.
Therefore, please first read “Getting Started with Excel” on the
TIM-125/225 course webpage
before working through this tutorial and specifically attempting
the portion with the Solver Add-
In. You will need to make sure that your version of the
Microsoft Excel is capable of performing
the prescribed computations in Excel, and can utilize the Solver
Add-in.
If you find that your version of Excel does not support the
Solver Add-In, two possible
resolutions are:
1) Work on a UCSC SOE Windows computer with Excel 2010,
with the Solver Add-In
enabled, in one of the labs.
2) Update to the Mac Excel 2011 with Service Pack 1 software:
a. Mac Excel 2011: Office for Mac 2011 Service Pack 1 (14.1.0)
needed.

Download Service Pack:
http://support.microsoft.com/kb/2525412
b. Mac Excel 2008:
http://www.solver.com/mac/dwnmacsolver.htm
1 The NPV Analysis is adopted from Ulrich, K. T., and
Eppinger, S.D., Product Design and Development, Fourth
Edition, McGraw-Hill, 2008. Chapter 15.
Page 2
Problem Definition
Use the following Base Case scenario parameters:
(a) The total project length is four (4) years.
(b) The total Development Cost is $25,000,000.
(c) The average sales price (wholesale) is $2,500 per unit.
(d) The average production cost is $1,250 per unit.
(e) The total Ramp-up costs are estimated at $2,500,000.
(f) Ongoing market and support costs are $200,000 per month.
(g) Development time is 12 months.

(h) Production ramp-up time is 6 months.
(i) Ramp-up starts 9 months after the start of product
development and continues for 6
months.
(j) Ongoing “market and support" starts one quarter before
Production (of the product) and
selling (“sales” of the product ) start.
(k) Production (of the product) and selling (“sales” of the
product) occur immediately after
the end of the ramp-up period, and concludes at the end of year
4 (four).
(l) Assume that you could sell 35,000 units per year.
(m) The annual discount factor is 10% (i.e., 2.5% per quarter).
Answer the following questions:
(1) What is the NPV of the Base Case scenario?
(2) What is the maximum development cost beyond which the
development of the product cannot be
justified? (i.e., what is the development cost which makes
NPV=0). Use the Solver Add-In to
answer this question. Show your work.
(3) Explain the trade-off law for NPV versus development cost.
(4) Explain the trade-off law for NPV versus sales volume.
(5) Create a graph of the trade-off law relationship for the

(Change in NPV, $) (y-axis) versus
(Change in Development Cost, %) (x-axis). What is the equation
of the Regressed trendline?
Give the answer in the standard form for an equation of a line:
y=mx+b.
(6) Create a graph of the Trade-off law relationship for the to
the (Change in NPV, $) (y-axis) versus
(Change in Sales Volume, %) (x-axis). What is the equation of
the Regressed trendline?
Give the answer in the standard form for an equation of a line:
y=mx+b.
(7) If there is a 10% increase in development cost, by how much
does the sales volume need to
increase, to compensate for the drop in NPV?
Page 3
Treatment
1. Build a Base Case NPV Scenario
2. Use the Base Case to create: +/- 10%, +/- 20%, +/- 30%
Development Cost analysis
3. Use the Base Case to create: +/- 10%, +/- 20%, +/- 30% Sales
Volume analysis
4. Create a worksheet with summary tables
5. Graph the results to determine the slope of the line using
Regression Analysis trendline.
6. Use the Solver Add-In to automate the determination of the
Maximum development cost

for the project at which the project is no longer economically
practical (i.e., NPV=0).
7. Follow Ulrich’s (2) method (p.320) to determine the impact
of 10% increase in
development cost on NPV and the sales volume needed to
compensate for the drop.
8. Check the work.
9. Copy and Paste content into MS Word.
10. Label each Figure (i.e., Figure #: Title) and Table (i.e.,
Table #: Title).
11. Explain each Figure and Table.
12. Explain the Results.
13. Discuss the Conclusions.
Important Notes
As you work through this tutorial, it is essential that:
1) Worksheet tab names are formatted exactly as presented in
the tutorial, matching letter for
letter. This is important because we will be using linked
worksheets that will reference the
precise spelling of the tabs. A deviation from the exact spelling
will cause the worksheets
links to fail. Therefore, pay attention to UPPERCase and
lower_case, and spacing, as it
pertains to the formatting of the tab names. We used a
consistent nomenclature, therefore
you need to adhere to the format we used. You can change it

later (and improve it) once
you understand how it works; and
2) The numerical scenario data values and formulas must
entered in each corresponding cell
position, exactly as presented. If the tutorial defines to enter
something in a Cell B1 then
enter that specific information in Cell B1; otherwise the links
will fail, in relation to the rest of
this tutorial. We use the Fixed Cell References “$” and will
discuss this symbol latter; and
3) Save your work often. A simple approach is to email the file
to yourself so you have an
easily accessible copy in case your computer crashes, that you
can get from another
computer to continue working to meet deadlines.
Page 4
Execution: Pre-Processing (Setup)
Step 0:
Below is a checklist for you to make sure you have everything
you need before you get started:
1. Make sure that Microsoft Excel is loaded on your computer.
2. Enable the “Solver Add-In” with Excel
Windows OS instructions:
Useful video guide:
http://office.microsoft.com/en-us/excel-help/video-install-and-
activate-the-analysis-

toolpak-and-solver-VA101956375.aspx?CTT=1
� Excel 2010: http://office.microsoft.com/en-us/excel-
help/load-the-solver-add-in-HP010342660.aspx?CTT=1
Mac OS instructions:
� Excel 2011: Office for Mac 2011 Service Pack 1 (14.1.0)
needed.
Download Service Pack:
� Excel 2008: http://www.solver.com/mac/dwnmacsolver.htm
3. Enable the “Excel Analysis ToolPak” and “Analysis Toolpak
– VBA” within Excel.
Windows OS instructions:
help/load-the-analysis-toolpak-HP010021569.aspx?CTT=3
help/load-the-analysis-toolpak-HP010021569.aspx
help/load-the-analysis-toolpak-HP001127724.aspx
Mac OS instructions:

� Excel 2011:
http://www.microsoft.com/download/en/details.aspx?displaylan
g=en&id=17198
� Excel 2008: Not Available. VBA is not Supported.
4. Recommend to print a hard-copy of this Tutorial (double-
sided).
5. Have a copy of your TIM-105/205 Lecture Notes on NPV
Analysis.
6. Have textbook: Ulrich, K. T., and Eppinger, S.D., Product
Design and Development, Fourth
Edition, McGraw-Hill, 2008, Chapter 15.
activate-the-analysis-toolpak-and-solver-
VA101956375.aspx?CTT=1
activate-the-analysis-toolpak-and-solver-
VA101956375.aspx?CTT=1
http://office.microsoft.com/en-us/excel-help/load-the-solver-
add-in-HP010342660.aspx?CTT=1
http://office.microsoft.com/en-us/excel-help/load-the-analysis-
toolpak-HP010021569.aspx?CTT=3
toolpak-HP010021569.aspx

toolpak-HP001127724.aspx
http://www.microsoft.com/download/en/details.aspx?displaylan
g=en&id=17198
Page 5
Execution: Processing
Step 1: Build a ScenarioParameters worksheet
Create a worksheet and name the worksheet Tab:
ScenarioParameters
The worksheet is formatted as follows with the parameters:
Figure 1: ScenarioParameters worksheet format
Cell A1 and Cell B1 have been MERGED. Then the SCENARIO
INPUT PARAMETERS typed
inside this single merged cell.
The project schedule, from inception through end of the
production and selling will look like
Figure 2.
Figure 2: Complete Project Time Line from Inception to End
Observe how, that the production and selling concludes at the
“end of year four (4)”, as defined
in the problem statement. But, given the other events that occur
beforehand, the production and

selling does not start until Year 2-Q2.
Page 6
Step 2: Build the BaseCase NPV analysis worksheet
Now we show you how to build and setup the BaseCase scenario
to look as follows:
Figure 3: Base Case NPV Analysis
Note: The clean looking format for the number values is
utilizing a format configuration of:
NUMBER, Decimal Places=0 with 1000 Separator (,) and
format -1,234. You can achieve this
format by selecting all the cells. Then in the Number ribbon
(Figure 4), click the Show Number
tab icon, , and configure the number format (Figure 5). Rows 11
and Row 14 are configured
to Decimal places = 2.
Figure 4
Figure 5
Note: We use the symbol “$” on purpose and it is very

important. It is called a Fixed Cell Reference.
Putting the “$” sign before the column or row variable, causes
the link to remain fixed to that cell
reference. “One of the major ways to control a cell reference is
to set either the column or row reference
or both references. This is typically done by using a dollar sign
("$") before the column or row reference
(e.g., "$A4", "A$4", or "$A$4"). The dollar sign indicates that
the reference will not change, even if the
formula is copied and pasted.”2 This is useful when you need to
reference a specific input parameter but
want to copy and paste formulae. Using the ("$") saves time in
programming the worksheets and ensures
accuracy.
2 http://www.sjsu.edu/depts/geography/resource/swdocs/xl-
guide/edit/celref.htm
Click here to show the
Format Cells:Number
options.
Page 7
The programming format to create the BaseCase worksheet is as

follows:
If you have programmed the BaseCase worksheet as defined
above, and made the correct
links to the ScenarioParameters worksheet, then the Project
NPV, $ will equal, precisely,
$62,166.18; rounded to 0 decimal places, it is $62,166. Recall
this value is in thousands.
Therefore, the conclusion is that the project has a high NPV
value of $62,166K and should be
pursued.
CELL CELL FORMULAE COPY TO
B6
=(-1)*ScenarioParameters!$B$3/4*(1/1000)
Note: Dividing by (1/1000) converts the dollar value from
Millions to Thousands. We do
this to simply the presentation of the spreadsheet.
C6:E6
E7 =(-1)*ScenarioParameters!$B$6/2*(1/1000) F7
F8 =(-1)*ScenarioParameters!$B$7/4*(1/1000) G8:Q8
G9 =(-
1)*(ScenarioParameters!$B$5)*(ScenarioParameters!$B$2/4)*(
1/1000) H9:Q9
G10 =ScenarioParameters!$B$2/4 H10:Q10

G11 =G9/G10 H11:Q11
G12
=(ScenarioParameters!$B$4*ScenarioParameters!$B$2/4)*(1/10
00) H12:Q12
G13
=ScenarioParameters!$B$2/4
Note: Dividing by 4 converts from Yearly to Quarterly
H13:Q13
G14 =G12/G13 H14:Q14
B16 =SUM(B6+B7+B8+B9+B12) C16:Q16
B17 =B16
C17
=C16/(1+(ScenarioParameters!$B$8/100)/4)^B3
Note: ScenarioParameters!$B$8/100 converts the parameter of
10 to 10%.
Then, division of by 4 converts from Yearly to Quarterly value
as needed.
Therefore, you get 1+(.025)=1.025 which is the needed value.
Lastly, the cell B3 is
shifted one to the left for the periods, so we start at one (1) for
the exponential factor.
This setup allows to quickly change the Discount Factor in the
ScenarioParameters,

worksheet to automatically update the entire workbook.
D17:Q17
B19 =SUM(B17:Q17)
Page 8
To quickly create a worksheet that is derived on the BaseCase
worksheet, we will use the
worksheet COPY feature of the BaseCase worksheet and then
make a few small changes.
To copy the worksheet, you will RIGHT-CLICK on the Tab of
worksheet BaseCase.
Then select “MOVE OR COPY…”
Figure 6: Right Click to Copy a Worksheet
Select the BaseCase worksheet, and Check the box to CREATE
A COPY.
Figure 7: Create a Worksheet Copy
Also, select MOVE TO END so the new worksheet will be
positioned at the end of the group of
worksheets. The Tan bame will be called BaseCase (2). So
rename the worksheet by double
clicking on the Tab, and typing a tab name of: +10% DevCost.

The name must be entered precisely to match this tutorial as we
will link to this Tab name later.
Then hit enter to save the Tab name. You can also right click on
the Tab and select a color to
help you identify the sheets. You can see that in we colored
ours a light blue,
Sugges ted Referen c e:
Watch a short and very useful video on YOUTUBE to show you
the process of how to:
Move or Copy a Worksheet (3)
http://www.youtube.com/watch?v=OucSxFiLyBc
http://www.youtube.com/watch?v=OucSxFiLyBc
Page 9
Once you have the +10% DevCost worksheet created. It is quick
to edit the worksheet
parameters as follows:
The tab name to enter is: 10% DevCost
1. Cell A1, change to: Development Cost Analysis
2. Cell B1: change to: 10%
3. Cell B6: change to: =(-
1)*(ScenarioParameters!$B$3/4*(1/1000))*(1+$B$1)
a. Note: Multiplying by (-1) to create the negative effect of
cost.

b. Note: Dividing ScenarioParameters!$B$3 by 4 converts from
Yearly to Quarter.
c. Note: Multiplying ScenarioParameters!$B$3 by (1/1000)
converts from Millions to
Thousands.
d. Note: Multiplying by (1+$B$1), in which $B$1 is the 10% for
sensitivity value. Also, notice
the use of “$” before the Column ‘B’ and Row ‘1’. Putting the $
sign before the column
and row, causes the link to remain fixed to that cell reference. It
called Fixed Cell
References. “One of the major ways to control a cell reference
is to set either the column
or row reference or both references. This is typically done by
using a dollar sign ("$")
before the column or row reference (e.g., "$A4", "A$4", or
"$A$4"). The dollar sign
indicates that the reference will not change, even if the formula
is copied and pasted.” (4)
4. Copy B6 to C6:E6.
Figure 8: +10% DevCost Analysis
If you have followed this process correctly, then the result is a
Project NPV of $59,756K for the
10% DevCost worksheet, as shown in Figure 8.
Page 10

Step 4: Create the -10% DevCost Workshet
Create a copy of the 10% DevCost worksheet.
The tab name to enter is: -10% DevCost
Once you have the -10% DevCost worksheet created, it is quick
to edit the Worksheet
1. Cell B1: Change to -10%
Figure 9: -10% DevCost NPV Analysis
-10% DevCost worksheet, as shown in Figure 9.
Page 11
Step 5: Create the +20% DevCost Workshet
Create a copy of the -10% DevCost worksheet.
Once you have the 20% DevCost worksheet created, it is quick
to edit the Worksheet

1. Cell B1: Change to 20%
Figure 10: +20% DevCost NPV Analysis
Page 12
Repeat a copy of the 20% DevCost worksheet.
-20% DevCost worksheet, as shown in Figure 11.

Create a copy of the -20% DevCost worksheet.
Once you have the 30% DevCost worksheet created, it is quick
Figure 12: 30% DevCost NPV Analysis
Page 14
Create a copy of the 30% DevCost worksheet.

-30% DevCost worksheet, as show in Figure 13.
Page 15
Step 9: Create the DevelopmentCost_Sensitivity summary
worksheet
Now we want to consolidate all the results into one worksheet,
to rapidly discern the results.
To do this, Insert a new, blank worksheet. This is done under
the HOME->INSERT menu
option.(or you use the Shift+F11 shortcut).
Figure 14: Insert Sheet (Shift+F11)
Name the Tab: DevelopmentCost_Sensitivity
Format and program the worksheet as follows:

Figure 15: Cell Programming for the
DevelopmentCost_Sensitivity worksheet
You will notice that the text in Cell A1 is formatted into in
three lines, within one Cell. This is
done using the ALT-ENTER command to create a Line Break,
within the Cell. Type “Change
In”, then press ALT-ENTER on the keyboard, type
“Development”, then press ALT-ENTER
again, type “Cost,%”, then press ENTER on the keyboard. This
process will create the three line
break, within one Cell. Then you can Center the text using the
built-in alignment tool .
Page 16
Figure 16: Format of the DevelopmentCost_Sensitivity
Worksheet
In Figure 16, is shown the final output format for the
DevelopmentCost_Sensitivity worksheet.
These results are now fully linked to all the worksheets, which
are connected to the
ScenarioParameters worksheet. Now, if you change one
parameter in the scenario, the
Sensitivity Analysis is instantly updated for you. You are now

capable of rapidly solving new
problems!
Step 10: Worksheet Tab Review
You can make sure your worksheet tab names look as follows.
You can drag and drop to move
them to different positions along the horizontal workbook axis.
Page 17
Step 11: Graph the Change in NPV ($) vs. Change in DevCost
(%)
Next, you want to graph the relationship between the (Chain in
NPV, $ Thousand)(y-axis) vs.
(Change in Development Cost, %)(x-axis).
To do this, you Insert a Chart. You can select the Scatter with
Smooth Lines and Markers.
Figure 17: Chart Format Option
Next, Select the Data.
Figure 18: Select the Data

Then ADD a data series:
Figure 19: Add a Data Series
Page 18
Configure the Series as follows, in which you type the text into
the white box. If you see “={1}” in
the Series Y values white space, delete it. Then enter the
information below
Figure 20: Edit Data Series X and Y axis
SERIES NAME: Change in NPV ($) vs Change in Dev Cost (%)
SERIES X VALUES:
=DevelopmentCost_Sensitivity!$B$2:$B$8
SERIES Y VALUES:
=DevelopmentCost_Sensitivity!$G$2:$G$8
Lastly, using the LAYOUT Ribbon, you will find all the options
to Label each axis and change
the units of the graph along with other visual tools
Figure 21: Layout Ribbon Tool to Label Charts
The end result, should look similar to the following chart in

Figure 22:
Figure 22: Change in NPV ($) vs. Change in DevCost (%)
Page 19
One last useful technique is to determine the slope of the line.
There is a useful tool in Excel
called Trendline. You can search to learn more about Excel
Trendline.
Suggested Reference:
Watch a short and very useful video on YOUTUBE to show you
the process of how to:
Use Trendline and Regression Analysis (5):
http://www.youtube.com/watch?v=6rOlGbLeQxI
The shortcut approach is to right-click on the line, and selects
the ADD TRENDLINE.
Figure 23: Add Trendline Shortcut (right-click)
Then format the Trendline as follows:
Figure 24: Trendline Configuration

For this data series, we set the Regression
Line to Linear, because we are assuming
linearity in the data with the Base Case
crossing at x=0 and y=0, set Intercept to
equal 0. Restated, we are including the
BaseCase, which crosses both the X and Y
axis at exactly zero and therefore, zero will
be the Intercept of the equation.
Also, the important feature here is to check
the box to: Display Equation on Chart. This
will automate the regression analysis and put
the equation of the line on the chart.
http://www.youtube.com/watch?v=6rOlGbLeQxI
Page 20
The new Chart will look as show in Figure 25. Nnotice a thin
black line was created inside the
original line and the equation of the line is now visible:

Figure 25: Change in NPV ($) vs. Change in DevCost (%)
The equation in this example, in y=mx+b format, is . In
which m=-24100 and
b=0. That translates to a trade-off law: For each 10% increase
(x-axis value) in development
cost, there is a $2410 (in thousands) reduction in NPV.
To format the textbox containing the equation, like in Figure
25, click on the floating textbox that
contains the equation, and then change the Font Color and Font
Size and Fill the box with a
color, all to help it stand out. In this example, the font has been
increased to size 18, colored
Red, and filled with a White background to make it easier to
read against the grid lines. You can
also move the textbox and change its location, as necessary.
Figure 26: “Paste Special”
to Insert Graphics
You can copy the Chart in Excel, then open an MS Word
document and then can use the “Paste Special” option to insert
as a image (JPEG, BITMAP, or PNG) to ensure it is inserted
uniformly into the document. The format of BITMAP is the
least
compressed and therefore will increase the size of your

document the most. However, “what you see it what you get”,
so
is a safe option until you are comfortable adjusting the graphic
formats that minimize the file size and maximize readability.
When you paste images into MS Word, you can automate the
process of the sequential
numbering and labeling of the Figures/Table using Insert
Captions.
Useful Instructions Adding/Deleting Captions for Figures &
Tables:
http://office.microsoft.com/en-us/word-help/add-or-delete-
captions-HP001228982.aspx
Page 21
Step 12: Create the +10% SalesVol Worksheet
Create a copy of the BaseCase worksheet.
The Tab name to enter is: 10% SalesVol
Once you have the 10% SalesVol worksheet created, it is quick
1. Cell A1, change to Sales Volume Analysis
2. Cell B1: change to 10%

3. Cell G9: change to:
=(-1)*(ScenarioParameters!$B$5)*(
(ScenarioParameters!$B$2/4) *(1+$B$1))*(1/1000)
a. Note: ScenarioParameters!$B$2 is the link to Sales &
Production Volume (units/year).
b. Note: ScenarioParameters!$B$5 is the link to the Unit
Productions Cost ($/unit).
c. Note: Dividing ScenarioParameters!$B$2 by 4, converts
Volume from Yearly to Quarterly
d. Note: Multiplying (ScenarioParameters!$B$2/4) by
(1+$B$1), in which $B$1 is the
sensitivity value, creates the change in measure for sensitivity.
e. Note: Multiplying (1/1000), converts from Millions $ to
Thousands $.
=(ScenarioParameters!$B$2/4)*(1+$B$1)
b. Note: Dividing ScenarioParameters!$B$2 by 4, converts
Volume from Yearly to
Quarterly.
c. Note: Multiplying (ScenarioParameters!$B$2/4) by (1+$B$1),
in which $B$1 is the

=(ScenarioParameters!$B$2)*((ScenarioParameters!$B$4/4)*(1
+$B$1))*(1/1000)
b. Note: ScenarioParameters!$B$4 is the link to Unit price
($/unit).
c. Note: Dividing ScenarioParameters!$B$4 by 4, converts
Volume from Yearly to Quarterly
d. Note: Multiplying (ScenarioParameters!$B$4/4) by
(1+$B$1), in which $B$1 is the
e. Note: Multiplying (1/1000), converts from Millions $ to
Thousands $.
=(ScenarioParameters!$B$2/4)*(1+$B$1)
b. Note: Dividing ScenarioParameters!$B$2 by 4, converts
Volume from Yearly to Quarterly.
c. Note: Multiplying (ScenarioParameters!$B$2/4) by (1+$B$1),
in which $B$1 is the

7. Copy G9 to H10:Q10.
8. Copy G10 to H10:Q10.
9. Copy G12 to H10:Q10.
10. Copy G13 to H10:Q10
Page 22
Figure 27: 10% Sales Volume NPV Analysis
10% SalesVol worksheet, as show in Figure 27.
Page 23
Create a copy of the “10% SalesVol” worksheet.
The Tab name to enter is: -10% SalesVol
Once you have the -10% SalesVol worksheet created, it is quick
1. Cell B1: change to: -10%

Figure 28: -10% Sale Volume NPV Analysis
-10% SalesVol worksheet, as show in Figure 28.
Page 24
Create a copy of the “-10% SalesVol” worksheet.
1. Cell B1: change to 20%
20% SalesVol worksheet, as shown in Figure 29.
Page 25
1. Cell B1: change to -20%

Figure 30: -20% SalesVol NPV Analysis
Project NPV of $43,311 for the
Page 26
Create a copy of the “-20% SalesVol” worksheet.
30% SalesVol worksheet, as show in Figure 31.
Page 27

Figure 32: -30% Sales Volume NPV Analysis
Project NPV of $33,884 for the
Page 28
Step 18: Create the SalesVolume_Sensitivity summary
worksheet
Create a new worksheet and name the worksheet Tab:
SalesVolume_Sensitivity
Format and program the worksheet as follows:
Figure 33: Programming format for SalesVolume_Sensitivity
Summary Table
Figure 34: SalesVolume_Sensitivity Summary Table Results
As shown in Figure 34, the table is linked to all the Sales
Volume worksheets and provides a

clearly organized summary of the SalesVolume_Sensitivity.
Page 29
Step 19: Graph the Change in NPV ($) vs. Change in Sales
Volume (%)
Lastly, graph the relationship between the (Change in NPV, $
Thousands) vs. (Change in
Sales Volume, %) as shown in Figure 35.
Figure 35: Change in NPV ($) vs. Change in Sales Volume (%)
The equation in this example, in y=mx+b format, is .
That translates to a trade-off law: For each 10% (x-axis value)
increase in Sales Volumes, there
is $9,427.50K increase in NPV.
Page 30
Step 20: Using Solver to Determine Max Development Cost
Note: Recall that in TIM-105 (1), you were given a problem on
the Final Exam to determine the
maximum development cost, for which a project would no
longer be feasible. Note, that on the

Final Exam, we also gave you (via email), a process for solving
the problem.
Now, we will walk you through an alternative method for
solving this problem using an Add-In
tool in Excel called SOLVER. This tool will be extremely
helpful later in this course (TIM-
125/225) and in your project. You can reference the “Getting
Started in Visual Basic” on the
TIM-125/225 course website to learn more.
A fast approach (i.e., takes under 1 minute for the author to do)
to solving the maximum
development cost problem is using the Solver Excel Add-in, to
quickly determine what is the
maximum development cost is the as follows:
On the ScenarioParameters worksheet, create a Cell Reference
link to the NPV value in the
BaseCase worksheet.
As shown in Figure 36, on ScenarioParameters Cell B1 enter:
=BaseCase!B19. This will make
a cell reference to the cell B19 of the BaseCase, which contains
the NPV we want the Solver
Add-In to optimize.
Figure 36: Programming of the ScenarioParemeters link to the
BaseCase NPV

Next, Open the Solver in the DATA: Analysis Ribbon:
Figure 37
Figure 38: Solver Configuration
To configure Solver to perform a simple optimization, to
determine the optimal values in Cell
$B$3, that makes Cell $B$11 equal to Value of 0 (zero), Solver
will automatically make many
Page 32
rapid changes in Cell $B$3 until Cell $B$11 reaches zero (0).
Then it will stop and insert the
solution in cell $B$3. This process will be almost instantaneous.
Select the GRG Nonlinear
Solving Method.
You need to also adjust a few of the OPTIONS to adjust for the
accuracy of the optimizations.
You can find the Options next the Solving Method (see Figure
38).
Figure 39: Adjustment of Options for Constraint Precision

Set the OPTIONS: ALL METHODS: CONSTRAINT
PRECISION to: 0.00001
Do not check any of the boxes.
Page 33
Figure 40
Set the Convergence for the GRG NonLinear Engine to:
0.000001
Leave the Derivate as Forward, and leave the Multi-start and
Required Bonds unchecked.
Now click the Solve button to run the optimization.
If you did it correctly, then the result will be a maximum
development cost = $89,487,343.115
In the next windows that popups up, you will have the option to
KEEP or RESTORE the results.
And, o have Reports generated for your work. These reports are
good to include with your work
and results.
Page 34

Figure 41: Solver Results
If you agree with the on-screen result, then select the Keep
Solver
Solution
. Or, you can
Restore the Original Values and investigate your framework.
Before clicking OK, select the Reports (e.g., Answer) that you
want to include with your results.
When you click OK, Solver will automatically create and insert
a new worksheet called
ANSWER REPORT with this information.
(Hint: Submit these reports to help earn the Extra Credit in
TIM-125/225 Homework #1)
An Example of the Solver Results Answer Report for this
problem is show in Figure 42.
Figure 42: Example of Solver “Answer” Report.

Select the Reports that
can help you study the
results of the optimization.
Page 35
Figure 43: Maximum development Cost after using Solver
After you Keep the Solver

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