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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 – 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

  • The maximum word count is 3,000 words or equivalent.

  • The coursework is mostly quantitative (numerical calculations) with some qualitative, non-numeric answers.

  • The numerical calculations are deemed equivalent to 1,800 words.

  • Note the word count guidance for the qualitative, non-numeric questions.

  • The submission should be made in the form of an Excel spreadsheet file that includes calculations as well as qualitative answers.

  • If you exceed the maximum word count by over 10%, your mark will be reduced by 5 marks.

  • If you exceed the maximum word count by more than 20%, you will receive zero marks for this coursework.

Excluded from the word count

  • No appendices are required.

  • No footnotes are required.

  • No bibliographies or reference lists are required.

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 ā€˜Question 1’; Question 2 on sheet 2 renamed ā€˜Question 2’; 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 agencies’ 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 agency’s 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 Ā£180,000 in annual profit; and

  • a 30% probability that the average will fall to 350 orders per day, which would result in Ā£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 Ā£145,000 in annual profit; and

  • a 40% probability that the average will increase to 550 orders per day, which would result in Ā£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) = š‘˜1 āˆ™ š‘¢(š‘„1) + š‘˜2 āˆ™ š‘¢(š‘„2) + š‘˜3 āˆ™ š‘¢(š‘„1) āˆ™ š‘¢(š‘„2)

where š‘˜3 = 1 āˆ’ š‘˜1 āˆ’ š‘˜2

The managers’ elicitation sessions also found the following attribute weights:

š‘˜1 = 0.75

š‘˜2 = 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 consultants’ 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 consultants’ 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 consultants’ study.

[Question 3, Part B: 5 marks]

[Question 3, Total: 15 marks]

Question 4 (55% of marks available)

Required

  1. 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]

  1. 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]

  1. 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.

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AFM080 Analysing Risk for Decision Making (What the unit is actually about)

AFM080 is basically about learning how people and organisations make decisions when things are uncertain. Instead of just guessing or going with “what feels right”, the unit pushes you to use structured tools like decision trees, utility theory, SMART analysis, and expected value calculations. The idea is to turn messy real-world choices into something you can actually compare properly using numbers, probabilities, and trade-offs.

A big part of it is accepting that decisions are rarely clean. You’re balancing risk, cost, outcomes, and preferences all at once. So the module trains you to think like a decision analyst, not just a student doing calculations.

Common areas covered:

  • Multi-criteria decision making (like SMART weighting)

  • Risk and uncertainty using probabilities

  • Utility functions and risk attitude

  • Expected value and expected utility

  • Decision trees and information value (perfect vs imperfect info)

  • Trade-offs between cost, benefit, and risk

Why students struggle with this assignment

This coursework is not difficult because the theory is “hard”, it’s difficult because everything is layered. You’re not doing one method at a time, you’re combining several methods in one Excel-based workflow. That’s where most students start losing marks.

The biggest issue is that the assignment looks like maths, but actually tests decision reasoning. A lot of students try to jump straight into calculations without fully understanding what the result means in decision terms, especially in Questions 1 and 2.

Other common pressure points:

  • SMART weights feel simple, but small mistakes completely change the final ranking

  • Efficient frontier requires both correct plotting and correct interpretation

  • Utility functions are easy to copy but hard to explain in a meaningful way

  • Decision trees with imperfect information often confuse students more than expected value itself

  • Question 4 is long and requires real-world application, not theory dumping

Getting support with AFM080 assignments

A lot of students look for help here because the marking is not just about getting the right numbers, it’s about showing clear decision logic across Excel models, probability reasoning, and written interpretation. Missing even one step in linking calculations to decisions can drop marks quickly.

At Assignment Experts, students often get support with this exact type of coursework where:

  • SMART models need correct weighting and justification

  • Decision trees need proper structure and expected value logic

  • Utility questions need clear interpretation, not just graphs

  • Question 4 needs a properly applied real-world decision analysis, not generic theory

The main value is making sure the Excel work and written reasoning actually match what the module is testing, not just producing numbers.