DecisionMaking Principles for Business DecisionMakers

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Decision-Making Principles for Business
Decision-Makers
1. The primary question to ask when facing a
problem is Whats my objective?
2. Having specified the goal, you now have to
address the manner in which you can model the
problem. Remember most problems arent
mathematical or computational in nature.
3. Once youve formulated a model, you have to
decide on the technique to compute or search for
the solution.
4. Any problem worth solving is worth thinking
about. Dont rush to give an answer. Think about
different ways to manipulate the information that
youve got at hand.
5. Sometimes finding a solution can be really
easy. Dont make it harder on yourself than you
have to.
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Decision-Making Principles for Business
Decision-Makers
6. Beware of obvious solutions. They might be
wrong. Sometimes the answers are so clear that
they just have to be right, until someone shows
you that things werent quite as clear as you
thought.
7. Dont be misled by previous experience.
Experience is usually an asset, but you have to
use it carefully. Dont be led into solving all
of your problems with an old familiar technique.
8. Start solving. Dont say I dont know how.
Most people dont plan to fail, they just fail to
plan.
9. Dont limit yourself to the search space that
is defined by the problem. Expand your horizon.
10. Dont be satisfied with finding a solution.
Finding a solution always means the start of the
process.
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Simulation Project
Simulation
The process of building a logical or mathematical
model of a system or a decision problem, and
experimenting with the model to obtain insight
into the systems behavior or to assist in
solving the decision problem.
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Example of Monte Carlo Simulation
Daves Candies is a small family-owned business
that offers gourmet chocolates and ice cream
fountain service. For special occasions such as
Valentines Day, the store must place orders for
special packaging several weeks in advance from
their supplier. One product, Valentines Day
Chocolate Massacre, is bought for 7.50 a box and
sells for 12.00. Any boxes that are not sold by
February 14 discounted by 50 and can always be
sold easily. Historically, the store has sold
between 40 and 90 boxes each year with no
apparent trend (either increasing or decreasing).
Daves dilemma is deciding how many boxes to
order for the Valentines Day customers. If
demand exceeds the purchase quantity, Dave loses
profit opportunity. On the other hand, if too
many boxes are purchased, he will lose money by
discounting them below cost.
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Cost 7.50 Sales Price 12.00 Discount
Price 6.00
Profit Formula 12D 7.50Q 6(Q-D) if D ?
Q Profit 12Q 7.50Q if D gt Q Q Order
quantity D - Demand
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Problem Statement

• The input to a simulation model of this situation
  would be
• The order quantity Q (the decision variable)
• The various revenue and cost (constants)
• The demand D (uncontrollable and probabilistic)
• The model output we seek is the net profit

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Project demand
Simulation Procedure 1.    Select the order
quantity (for example, Q 60) 2.    Roll a
die 3.    Determine the demand D from the
foregoing table 4.    Using Q 60, compute the
profit using the equation 5.    Record the profit
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10 replications of simulation (using Q60)
Average 246
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1000 replications (using Q60)
Ave. 237.57 Max. 270 Min. 151.35 SD 48
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• Procedure for Monte Carlo Simulation on
  Spreadsheets
• Develop the spreadsheet model
• Generate random outcomes for each probabilistic
  variable according to its probability
  distribution and apply the outcomes to the
  appropriate formulas
• Repeat step 2 a sufficient number of times to
  create a distribution of results.
• Compute summary statistics and collect output
  data in a frequency distribution or histogram for
  analysis.

Random Number Generation  Tools/Data
Analysis/Random Number Generation Histogram  Tools
/Data Analysis/Histogram
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1. Create the simulation model
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2. Generate random numbers
From the menu bar, select Tools/Data
Analysis/Random Number Generation. The
random-number-generation dialogue box will appear
as in the following figure.
You are asked to specify some values such as
Number of Variables (columns of values you want
generated), Number of Random Numbers (number of
data points you want generated for each
variable), the type of distribution (default
distribution is discrete), input range (a
discrete distribution must contain two columns
the left column contains the outcomes, and the
right column contains the probabilities
associated with the outcomes), output range (the
upper-left cell reference of the output table
that will store the outcomes).
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3. Perform analysis

• Statistics
• Charts