MIS275 – Decision Analytics Assignment 2 – Trimester 2, 2020 Page 1
DEAKIN BUSINESS SCHOOL
DEPARTMENT OF INFORMATION SYSTEMS AND BUSINESS ANALYTICS
MIS275 Decision Analytics
Assignment Two: Simulation of Technology Project Selection
Background
This is an individual assignment. The modelling work should be submitted online in the Assignment Folder as a
single MS Excel file with the required information in clearly labelled separate worksheets. In addition, you are
also required to submit a report that summarises your models and results. Your report must be in MS Word file
format. Any other file format, such as pdf, is NOT acceptable and will not be marked. In summary, two files
should be submitted – one MS Excel spreadsheet and one MS Word file.
The assignment has six sections:
1. Model description, conceptual model, and assumptions
2. Spreadsheet-based deterministic decision model
3. Scenario analysis
4. Spreadsheet-based stochastic decision model including justification for the choice of distribution
5. Simulated distribution for each output and a risk analysis
6. Report.
The requirements of each section are detailed below. The breakdown of marks (total is 30) is given in the
Assignment 2 Rubric at the end of this document.
Percentage of final grade 30%
Due date Sunday 27 September 2020 at 8pm AEDT
The assignment must be submitted by the due date electronically in CloudDeakin. When submitting
electronically, check that you have submitted the work correctly by following the instructions. Please note that
we will NOT accept any assignment or part of the assignment submitted after the deadline or via Email.
Any request for an extension must be negotiated at least one week prior to the above deadline by email. Deakin
policy for late submission: 5% will be deducted from the 30 marks allocated to this assessment task for each
day or part day that the assessment is late, up to five days. Penalties also apply on weekend days and public
holidays. When work is submitted more than five days after the due date, the task will not be marked, and the
student will receive 0% for the task.
Assurance of Learning
This assignment assesses following Graduate Learning Outcomes and related Unit Learning Outcomes:
Graduate Learning Outcome (GLO) Unit Learning Outcome (ULO)
GLO1: Discipline-specific knowledge and
capabilities: appropriate to the level of study
related to a discipline or profession.
GLO3: Digital literacy: using technologies to find,
use and disseminate information
GLO4: Critical thinking: evaluating information
using critical and analytical thinking and judgment
ULO1: Apply decision models optimisation techniques to
conceptualise and
represent a business scenario
ULO2: Apply optimisation software tools to find optimal
decisions for a given business scenario
ULO3: Interpret and analyse the results; investigate the
assumptions of the decision model
Feedback
Prior to submission
Students are able to seek assistance from the teaching staff to ascertain whether the assignment conforms to
submission guidelines. Please post your questions on CloudDeakin’s discussion forum for Assignment 2.
After submission
Your assignment feedback will be returned in the rubric via CloudDeakin with an overall mark and comments.
MIS275 – Decision Analytics Assignment 2 – Trimester 2, 2020 Page 2
Assignment Details:
Acme Group Inc. is a multinational strategy consultancy with global headquarters in Melbourne, Australia.
The company offers strategic solutions to its clients and has an annual revenue of $500M. In order to
maintain their competitive position in the marketplace Acme Group needs to continually look for
opportunities to invest in new technologies. The Chief Information Officer, Jane Porter, is currently
considering twelve technology proposals put forth by three divisions within the Group – Marketing, R&D,
and HR.
A number of the proposals are for joint projects, to be undertaken with partner organisations which Acme
Group has well-established strategic alliances.
Each division has provided Jane with the capital expenditures required for each project over the next three
years and, based on the expected revenue to be generated by each project, the NPV of each project as shown
below, and the ownership %.
Project
no.
Division Ownership
%
Capital expenditure* ($M) NPV* ($M)
Year 1 Year 2 Year 3
1 Marketing 100% 2.5 1.0 1.0 0.6
2 Marketing 33% 5.0 3.0 3.0 1.8
3 Marketing 50% 1.0 2.0 4.0 0.8
4 Marketing 100% 7.5 5.0 3.0 3.1
5 Marketing 75% 2.0 4.0 8.0 2.2
6 R&D 50% 10.0 3.0 3.0 1.8
7 R&D 100% 7.5 7.5 3.0 4.1
8 R&D 100% 8.0 7.0 6.0 2.8
9 R&D 67% 4.0 6.0 8.0 3.8
10 HR 100% 1.0 2.0 4.0 1.0
11 HR 50% 7.0 5.0 3.0 2.6
12 HR 100% 15.0 4.0 4.0 3.4
*The capital expenditures and NPV for each project are subject to the ownership %. For example, should project 5 be funded, capital
expenditures for the Acme Group will amount to 75% of the stated figures, or $1.5M, $3.0M, and $6.0M over the three years, for an
NPV of $1.65M. The other quarter of the expenditures will be funded by a strategic ally, which will be entitled to quarter of the
stated NPV. By contrast, the Acme Group will provide 100% of the required capital expenditures for project 1, for a NPV of $0.6M.
The CEO, Edgar Burroughs, after consulting with the Chief Financial Officer, John Clayton, has given Jane an
overall three-year budget of $100 million for the set of projectsshe approves, with a maximum of $40 million
available in any one year.
Jane has now tasked you with developing a spreadsheet‐based decision model that can use to explore the
twelve investment alternatives and their associated risks.
As a starting point, she wants you to develop a spreadsheet model using the Deterministic model worksheet
provided in the assignment spreadsheet. This worksheet has four sections: Inputs, Decisions, Calculated
values, and Summary values and Outputs.
Jane wants the spreadsheet to automatically update all tables and results each time she the enters 0s and
1s in cells O26:O37. In that way, so can see the results for any set of projects that she wants to consider
funding.
MIS275 – Decision Analytics Assignment 2 – Trimester 2, 2020 Page 3
The information that Jane is particularly interested in is the following:
1. Number of projects undertaken in each division
2. Capital expenditures ($M) - company wide and by division. Jane also wants to see the calculated
values in cells P26:AA37, in case she needs to see a full breakdown of capital expenditure.
3. Whether any expenditure limits are exceeded.
4. Table of ROI by project. Jane prefers to compare percentages rather than absolute numbers. For this
reason, she wants you to divide each of the project NPVs through by the total capital expenditure
for each project and report the ROI percentage.
When you have completed the deterministic decision model, Jane wants you to use this as the basis for
developing a spreadsheet-based stochastic decision model in the other worksheet.
In this Stochastic model worksheet, she wants you to apply triangular distributions to each capital
expenditure and to each NPV.
Jane wants you to treat all of the capital expenditures in the page 2 table as the most likely values. Jane then
wants you to set the minimum and maximum values at 15% below and 30% above the most likely values, to
counter the common bias of under-estimating costs.
She also wants you to treat all of NPVs in the page 2 table as the most likely values. She then wants the
minimum and maximum values set at 20% below and 15% above the most likely values, to counter the
common bias of over-estimating the NPV.
Once you have completed the development of your Stochastic model, Jane wants you to do some
preliminary analysis for her.
She wants you to consider three sets of projects that satisfy the four budget constraints and look promising
in terms of total NPV. Her one stipulation is that each set must include at least project from each division.
She wants you to perform a comparative analysis of the three sets and write up your findings in a report. In
particular she wants you to provide a clear analysis of the risks faced with each the three sets of projects.
MIS275 – Decision Analytics Assignment 2 – Trimester 2, 2020 Page 4
Your submission will be assessed across these six sections for a total unit mark of 30%:
Section 1: Model description, conceptual model, and assumptions (File: MS Word; 5 marks)
• Provide a brief overview of the model
• Include a conceptual model
• Note any relevant assumptions.
Section 2: Spreadsheet-based deterministic decision model (Files: MS Word & Excel; 5 marks)
Complete all parts of the spreadsheet-based deterministic decision model. All cells displaying calculated
values, summary values and output values must contain the underlying Excel formulas.
Section 3: Scenario analysis (Files: MS Word & Excel; 5 marks)
This section relates to Topic 7. Use Excel’s scenario analysis to investigate the impact that best and worst
scenarios, for both capital expenditure and NPV, have on the summary values and output values. The choice
of best and worst scenarios is yours.
Section 4: Spreadsheet-based stochastic decision model including justification for the choice of
distribution (Files: MS Word & Excel; 5 marks)
This section relates to Topic 8. Complete all parts of the spreadsheet-based stochastic decision model.
Justify the choice of probability distribution.
Section 5: Simulated output distribution and a risk analysis (Files: MS Word & Excel; 5 marks)
This section relates to Topic 9. This requires you to undertake a risk analysis based on simulation modelling,
in order to quantify the risks associated with problem.
Section 6: Report (File: MS Word; 5 marks)
The report should be a standalone document. It should include:
1. A brief description of the stochastic model (maximum 100 words)
2. The conceptual model and any assumptions behind the model.
3. The deterministic decision model copied from the spreadsheet.
4. The best- and worst-case scenarios chosen, and a discussion of the consequences.
5. The stochastic decision model copied from the spreadsheet.
6. Justification for the choice of probability distribution.
7. Risk analysis report based on the simulation modelling.
MIS275 - Decision Analytics Assignment 2 – Trimester 2, 2020 Page 5
Rubric for Assignment 2
Performance Levels