Calculate the SMART weights for the non-monetary attributes and the aggregate benefit scores for the five agencies on the non-monetary attributes.
Coursework Assessment Brief
|
Module code/name |
AFM080 Analysing Risk for Decision Making |
|
Module leader name |
Ā |
|
Academic year |
2025/26 |
|
Session |
April to June 2026 |
Copyright Note to students: Copyright of this assessment brief is with the module leader(s) named above. If this brief draws upon work by third parties (e.g. Case Study publishers) such third parties also hold copyright. It must not be copied, reproduced, transferred, distributed, leased, licensed, or shared with any other individual(s) and/or organisations, including web-based organisations, without permission of the copyright holder(s) at any point in time.
Academic Misconduct: Academic Misconduct is defined as any action or attempted action that may result in a student obtaining an unfair academic advantage. Academic misconduct includes plagiarism, obtaining help from/sharing work with others be they individuals and/or organisations or any other form of cheating.
Referencing: You must reference and provide full citation for ALL sources used, including articles, textbooks, lecture slides and module materials. This includes any direct quotes and paraphrased text. If in doubt, reference it. Failure to cite references correctly may result in your work being referred for Academic Misconduct investigation. The University of London checks all assessed coursework for plagiarism using the Turnitin software for guidance. Further information is available here.
Important: This assessment falls under Generative AI policy Level One - Supportive use of Generative AI permitted. The use of Generative AI in a limited way is permitted for this assessment. Generative AI tools may be used to support students in the completion of this assessment but the work submitted must be a genuine demonstration of their own work, for example their subject knowledge or their own critical analysis. Students should not submit the outputs of Generative AI tools as if it is their own work ā doing so will be considered an assessment offence. Students should also acknowledge the use of any Generative AI tools used in this assessment.
Core information
|
Submission date |
Monday 13 July 2026 |
|
Submission time |
13:00 hours UK time |
|
% weighting of this assessmentĀ within total module mark |
100% |
|
Maximum word count and penalties |
|
|
Excluded from the word count |
|
|
Submitting your assessment |
Submit one single Excel spreadsheet to the submission link on the module VLE site by the deadline. Any bullet points/sentences in response to qualitative, non-numeric questions should be included in your Excel spreadsheet. Only your Student Reference Number (SRN) should be the identifier. Do not include your name. |
Assessment Brief and Requirements
-
If for any reason you have issues uploading your assignment to the dedicated submission link on the VLE you must immediately log an enquiry through your Student Portal and attach your assignment to that enquiry.
-
This individual coursework is 100% of your overall module mark for AFM080 Analysing Risk for Decision Making.
-
This individual coursework is marked out of a total of 100 marks.
Context
There are four (4) questions in this assessment. You must:
-
Review the 4 questions in the assessment.
-
Answer all questions and question parts.
-
Apply appropriate decision-making methods, techniques, and concepts to answer the questions.
-
Where instructed, you may answer qualitative, non-numeric questions using bullet points, phrases, sentences, or short paragraphs.
-
-
Present your analysis in a simple, efficient, and professional way.
-
Note any word count guidance for qualitative, non-numeric questions.
-
Clearly indicate parts of questions and your answers.
-
Clearly show your calculations, including general formulas used.
-
Clearly state any assumptions, where appropriate where required.
-
-
Submit as follows:
-
Excel spreadsheet with calculations.
-
Each question should be answered on a different sheet within the spreadsheet and renamed accordingly, e.g. Question 1 in sheet 1 renamed āQuestion 1ā; Question 2 on sheet 2 renamed āQuestion 2ā; etc.
-
-
-
Each question part should be clearly indicated.
-
Where possible, please indicate quantitative answers in bold red text within a cell with bold red borders.
-
Qualitative answers should be entered within Excel cells.
-
Note: The maximum of 100 marks for the submission will be awarded as follows:
-
Question 1 [15 marks maximum].
-
Question 2 [15 marks maximum].
-
Question 3 [15 marks maximum].
-
Question 4 [55 marks maximum].
Question 1 (15% of marks available)
A national children`s literacy charity would like to appoint an external agency to design and deliver a public engagement campaign to encourage more families to use local library services. Five agencies have submitted proposals, and the charity must decide between them.
The campaign steering group has identified five attributes that are relevant to its decision:
-
campaign team expertise
-
community relevance
-
digital engagement platform
-
volunteer support
-
campaign cost
For each of the non-monetary attributes, the steering group has allocated scores to each agency to indicate performance on that attribute, where 0 indicates the worst performance and 100 indicates the best performance.
|
Agency |
Campaign team expertise |
Community relevance |
DigitalĀ engagement platform |
Volunteer support |
Campaign cost |
|
Larkspur Communications |
100 |
65 |
80 |
20 |
Ā£180,000 |
|
Beacon Outreach |
75 |
40 |
100 |
0 |
Ā£145,000 |
|
CivicSpark Media |
45 |
100 |
0 |
45 |
Ā£120,000 |
|
Meadowfield Partners |
0 |
30 |
30 |
100 |
Ā£155,000 |
|
Northbridge Social Impact |
35 |
0 |
75 |
85 |
Ā£105,000 |
Applying SMART, the steering group considered a hypothetical agency with the worst performance (scores of 0) in all non-monetary attributes. The group then decided which attribute it would most like to improve for the hypothetical agency. The group decided that improving community relevance from the worst score of 0 to the best score of 100 would be the most desirable improvement, providing the most aggregate benefit.
Improvements in campaign team expertise, digital engagement platform, and volunteer support from worst to best performance were then determined to provide 55%, 45%, and 30%, respectively, as much aggregate benefit as the aggregate benefit achieved by improving community relevance from worst to best.
Required
Part A
Calculate the SMART weights for the non-monetary attributes and the aggregate benefit scores for the five agencies on the non-monetary attributes.
[Question 1, Part A: 3 marks]
Part B
Plot the agenciesā aggregate benefit scores and their campaign costs and draw the efficient frontier. Identify the agencies that lie on the efficient frontier.
[Question 1, Part B: 3 marks]
Part C
The charity is prepared to pay £30,000 for the gain in aggregate benefit from improving the digital engagement platform of the hypothetical worst agency from the worst digital engagement platform (score of 0) to the best (score of 100), all else remaining equal.
Based on the amount the charity is willing to pay to improve the worst hypothetical agencyās digital engagement platform, identify the agency that the steering group should choose for the public engagement campaign.
[Question 1, Part C: 4 marks]
Part D
Explain two limitations of relying on this SMART analysis as the main basis for selecting the agency and explain how the charity could address these limitations before making its final decision. The expected word count for this question is 100 words.
[Question 1, Part D: 5 marks]
[Question 1, Total: 15 marks]
Question 2 (15% of marks available)
A subscription-based meal-kit company is reviewing its pricing after a year in which many households have reduced their spending. The managers are deciding whether to reduce the standard subscription price in an attempt to increase customer orders.
If they decide to reduce the subscription price, they will then have to decide whether to launch a digital promotion campaign to increase awareness of the lower price.
If they decide to keep the subscription price unchanged, they expect the following changes in customer orders over the following year:
-
a 70% probability of maintaining the current average of 500 orders per day, which would result in £180,000 in annual profit; and
-
a 30% probability that the average will fall to 350 orders per day, which would result in £45,000 in annual profit.
If the subscription price is reduced, but no digital promotion campaign is used, they expect the following changes in customer orders next year:
-
a 60% probability of increasing orders to an average of 650 per day, which would result in £145,000 in annual profit; and
-
a 40% probability that the average will increase to 550 orders per day, which would result in £115,000 in annual profit.
If the subscription price is reduced and a digital promotion campaign is used, then the probability of increasing orders to an average of 650 per day would rise to 75% and the probability that the average will increase to 550 orders per day would be 25%. However, using the digital promotion campaign would decrease annual profit by £45,000 regardless of customer orders.
The managers would like to maximise annual profit and maximise the average number of customer orders per day. The utility functions for annual profit and for the average number of customer orders per day have been elicited from the managers and are shown below:
|
Average number of customer orders per day |
Utility |
|
350 |
0.00 |
|
500 |
0.65 |
|
550 |
0.90 |
|
650 |
1.00 |
Ā
|
Annual profit |
Utility |
|
Ā£45,000 |
0.00 |
|
Ā£70,000 |
0.25 |
|
Ā£100,000 |
0.65 |
|
Ā£115,000 |
0.75 |
|
Ā£145,000 |
0.90 |
|
Ā£180,000 |
1.00 |
Required
Part A
Plot the utility functions for the average number of customer orders and for annual profit. Interpret the two utility functions with respect to preferences and risk attitude.
[Question 2, Part A: 3 marks]
Part B
Further elicitation sessions with the managers show that the average number of customer orders per day and annual profit are mutually utility independent.
Recall that the utility function for two utility-independent attributes is as follows:
š¢(š„1, š„2) = š1 ā š¢(š„1) + š2 ā š¢(š„2) + š3 ā š¢(š„1) ā š¢(š„2)
where š3 = 1 ā š1 ā š2
The managersā elicitation sessions also found the following attribute weights:
š1 = 0.75
š2 = 0.45
Attribute 1 is the average number of customer orders per day. Explain how the attribute weights were found.
[Question 2, Part B: 4 marks]
Part C
With reference to your analysis, explain how the managers of the meal-kit company should proceed.
[Question 2, Part C: 3 marks]
Part D
Explain why this recommendation may differ from a recommendation based only on expected annual profit. In your answer, discuss the role of utility functions, risk attitudes, and multiple objectives. The expected word count for this question is 100 words.
[Question 2, Part D: 5 marks]
[Question 2 total: 15 marks]
Question 3 (15% of marks available)
A renewable energy cooperative is deciding between two possible locations for a new battery storage facility. Both locations are viable, but the cooperative has funding and management capacity to develop only one site. The sites being considered are Harbour Exchange, a former logistics site close to an existing electrical substation, and Moorfield Industrial Estate, a more straightforward site on the edge of the town.
A preliminary technical assessment of Harbour Exchange found a 70% probability that the grid connection and site preparation works will be relatively straightforward, which would lead to development costs of £35 million. However, if major grid reinforcement and ground remediation works are required, development costs will rise to £80 million.
The preliminary technical assessment of Moorfield Industrial Estate was much more certain: the site is ready for development, and the battery storage facility is certain to cost £55 million.
The renewable energy cooperative is considering hiring external technical consultants to undertake a more detailed feasibility study of Harbour Exchange. However, the cooperative has found that even the best external consultants use methods that are not perfectly accurate and have an estimated 75% probability of giving the correct indication of whether the Harbour Exchange development will be straightforward or problematic.
Required
Part A
Assuming the renewable energy cooperative wants to minimise expected costs, calculate the expected value of the imperfect information from the external consultantsā detailed feasibility study and state how much the cooperative should pay the external consultants.
[Question 3, Part A: 10 marks]
Part B
Assuming that the external consultantsā detailed feasibility study is perfect and gives a certain indication of whether Harbour Exchange will be straightforward or problematic, calculate the value of the perfect information from the external consultantsā study.
[Question 3, Part B: 5 marks]
[Question 3, Total: 15 marks]
Question 4 (55% of marks available)
Required
-
Select and describe a real decision problem from your workplace or personal experience. Be sure to identify and describe the relevant stakeholders, the various objectives, attributes, performance on attributes, and the decision made.
[Question 4, Requirement 1: 20 marks]
-
Identify any concepts and methods from this course that are relevant to your decision problem and explain how you would use them to make an appropriate decision.
[Question 4, Requirement 2: 15 marks]
-
Apply the relevant concepts and methods from this course to your decision problem and compare the decision outcome to your own real decision.
[Question 4, Requirement 3: 20 marks]
Your answers to the above requirements should draw specifically from the application of decision analysis concepts and methods including, as appropriate, SMART, decision trees, sensitivity analysis, risk and utilities, measuring probabilities, etc. and include relevant data as necessary.
As stated in Requirement 1, a good answer would be based on a real decision problem that led to a real decision that was made. By referring to a real decision problem, you will be able to reflect on your personal experience to address the question requirements. The decision problem should be sufficiently complex and include sufficient data (that you collect or generate) for relevant decision analysis methods to be fully applied (more than one decision analysis method is expected). Refer to the practical examples from the textbook and module material for an indication of the types of decision problems (including levels of detail and types and amounts of data) that would be appropriate to analyse for this question.
The expected word count for this question is 1,000 words.
[Question 4, Total: 55 marks]
How your work is assessed
Within this assessment you may be assessed on the following aspects, as applicable and appropriate to this assessment, and should thus consider these aspects when fulfilling the requirements of each section:
-
The strengths and quality of your overall analysis and evaluation;
-
Appropriate use of relevant theoretical models, concepts, and frameworks;
-
The rationale and evidence that you provide in support of your arguments;
-
The credibility and viability of the evidenced conclusions/recommendations/plans of action you put forward;
-
Structure and coherence of your considerations and reports;
-
The accuracy of any calculations;
-
Appropriate and relevant use of, as and where relevant and appropriate, real world examples, academic materials and referenced sources. Any references should use a consistent referencing system e.g. Harvard, APA, or Vancouver;
-
Academic judgement regarding the blend of scope, thrust and communication of ideas, contentions, evidence, knowledge, arguments, conclusions;
-
Each assessment requirement(s) has allocated marks/weightings.
According to the Higher Education Qualifications Framework (HEQF) at Masters level (Level 7), the grade standards represented by the mark ranges are:
|
Mark range |
Grade standard |
|
86 - 100 |
Distinction at very high level |
|
70 - 85 |
Distinction |
|
60 - 69 |
Merit |
|
50 - 59 |
Pass |
|
40 - 49 |
Fail standard |
|
0 - 39 |
Bad fail standard |
A link to the criteria representing each grade standard may be found here: https://www.ucl.ac.uk/teaching-learning/sites/teaching-learning/files/migrated-files/UCL_Assessment_Criteria_Guide.pdf and you are advised to review the criteria relating to Level 7.