Download ST464 Lab 1

ST4004 Lab 1
The purpose of this lab is to practice with simple spreadsheet models. The problems to be
solved are outlined in Lecture03.pdf. There is no need to submit your solutions; they do
not count for credit. Example layouts are shown at the end of this document.
Norseman Direct
Breakeven Analysis.
Set up a collection of inputs. These could be, under the heading 'Mailing Inputs' to do
with the fixed cost of printing, the variable costs of printing and mailing and the numbers
mailed. Similarly, in connection with orders the quantities average order, cost of order
and response cost go in. In connection with responses, the response rate and number of
responses take part.
Named Ranges.
You should name the ranges. For example, if one has the fixed cost of printing in b4, then
click the range naming box and type in FCostPrint. From then on, one can use FCostPrint
in place of $B$4.
You can edit names by going to Formulas>Define Name. You should paste a list using
Formulas>Name Managers.
Formatting
Key variables of interest have a blue thick border around them. These are the inputs.
Where there is a decision variable this is marked with a red border.
Data Tables
This is a way of looking at the effect of varying variables on the output of interest. The
functionality is available under Data>What If Analysis? > Data Table.
The tables can be one way or two way. The column input is a collection of different
values for an input variable all gathered in a column. Similarly for a row input.
Questions
Answer the questions asked in the lecture;
•How does response rate affect profit?
•What is the break-even response rate?
•Is 3% response rate enough to go ahead?
•What uncertainties exist, and how might they affect the results?
MySolutions.Com
This problem is in two stages.
Fitting
Given the data that are presented, fit a model. There are a number of different ways of
doing this. In Excel, one way is to plot the data on a scatterplot. Then click on the data
and add a trendline. It is worth doing some formatting at this stage, so that the graph is
easy to read.
When fitting the trendline, it is possible to get the model printed on the graph. In this
way, one can read off the coefficients. A number of different trendlines are possible. You
should fit linear, exponential and power curves to these data.
In order to decide on 'best fit' a number of criteria are possible. One of these is mean
absolute percentage error (MAPE). It is defined to be the arithmetic mean of the APEs.
APE is just abs(Observed-Expected)/Observed. The expected is got by fitting the model
for each particular value of x.
Prediction
Conditional on a particular model (and there are good reasons not to condition on
particular values), one can make predictions of demand for many different Unit Prices.
Set up a worksheet that makes these predictions. The object that can be changed is Unit
Price. This will, through the model, yield a Predicted demand. Given the predicted
demand, and unit cost, one can calculate expected profit.
Solution
Of primary interest in this case is the value of Unit Price that maximises profit.
Sensitivity of the solution to variations in costs and price are also of interest. A keen eye
should notice that the solution may be sensitive to the fitted model and consider
examining alternatives. Solver and Data Tables can help with these.
Questions
To recap, the questions in lectures were;
 What price should MySolutions.com charge for their product?
 How does this depend on the cost price of their product?
 Comment on other aspects which may influence the actions to be taken - for
example is this realistic?
Figure 1. An example of Norseman Direct Model
Figure 2. MySolutions fitting
Figure 3. MySolutions predictions