Decision Analysis for Managers

Assignment 1: Issues and Trade-offs in Investment Decisions

Investigation - Issues and Trade-offs in Investment Decisions

Read about "socially responsible investing" (also referred to as "sustainable investing") and address the following questions (Approximately 500 words in total).

(1) What generally makes decisions by a socially responsible investor difficult or complicated? (compared to "normal" investment decisions)?

(2) What trade-offs must a socially responsible investor typically make?

(3) What major sources of uncertainty does a socially responsible investor face?

(4) Based on what you learnt from your reading and lectures, how would you characterise a "good" socially responsible investment decision?

Assignment 2: Case Study - BMAC Research & Development Decision

Following on from what you have learnt about the key elements of decision problems and Structuring/Modelling Decision Problems from your readings and lectures, this activity provides you with the opportunity to apply your knowledge to a case study on BMAC research and development (R & D) decision problem.

Read the BMAC research & development (R & D) decision case study below and address the following questions related to the case study (Approximately 500 words in total, excluding diagrams and references).

(1) What were the fundamental objectives of BMAC in their decision problem

(2) Construct an influence diagram to represent BMAC's decision problem

(3) Construct a decision tree to represent BMAC's decision problem

(4) Reflect on the roles that the two diagrams play in helping to understand/clarify and communicate the structure of BMAC's decision problem?

(5) Briefly discuss at least one example from your reading of the academic literature (published journal articles) in which influence diagrams or decision trees have been applied to structure a decision problem. Provide appropriate references in Harvard referencing format.

Case study: BMAC Research & Development decision
BMAC, a research and development (R & D) company, must decide whether to spend $2 million to continue with a particular drug development research project. The success of the project (as measured by obtaining a patent) is not assured, and at this point the decision- maker judges only a 65% chance of getting the patent. If the patent is awarded, the company can either license the patent for an estimated $25 million or invest an additional $10 million to create a production and marketing system to sell the product directly. If the company chooses the latter, it faces uncertainty of demand (categorized as high, medium or low demand) and associated profit from sales. The probabilities of the three levels of demand and associated revenues are summarised on the Table below.

Note/Reference

It is possible to construct the decision trees required in the assignment manually or by hand (i.e., without the need for specialised software). However, you can optionally use an Excel Add-in to construct decision trees (I strongly encourage you to try itA). Follow the link below for YouTube instructions on downloading a free Excel add-in for decision trees.

Assignment 3: Case Study - BMAC Research & Development Decision

In this assignment, you will continue with the analysis of the BMAC research & development (R & D) case study from assignment 2. For ease of reference, a copy of the case study is provided in the box below.

Case study: BMAC Research & Development decision

BMAC, a research and development (R & D) company, must decide whether to spend $2 million to continue with a particular drug development research project. The success of the project (as measured by obtaining a patent) is not assured, and at this point the decision- maker judges only a 65% chance of getting the patent. If the patent is awarded, the company can either license the patent for an estimated $25 million or invest an additional $10 million to create a production and marketing system to sell the product directly. If the company chooses the latter, it faces uncertainty of demand (categorized as high, medium or low demand) and associated profit from sales. The probabilities of the three levels of demand and associated revenues are summarised on the Table below.

Revisit the BMAC research & development (R & D) decision case study above and continue your analysis by addressing the following questions (approximately 500 words, excluding figures, excel spreadsheets and references).

1. Using your decision tree (from assignment 2) and the folding back the tree procedure, calculate the expected monetary value (EMV) of the two options at the root of the BMAC's decision problem i.e. (A) Continue with the R &D project at a cost of $ 2 Million or (B) Stop R & D project at no cost. Which alternative or strategy should BMAC pursue in order to maximize their revenues?

2. It may be expected that the EMV and hence your recommended strategy for BMAC obtained in in question 1 above critically depends on uncertain variables or chance events that are not within the control of the decision maker. Therefore, conduct a sensitivity analysis on your recommended strategy for BMAC and briefly explain the implications of your results to BMAC's decision problem.

3. Now consider a more realistic scenario for BMAC in which the costs and revenues, if they decide to continue with the project, will be spread out over time. In particular, if BMAC decides to continue the project, they will have to come up with the $2 million this year (Year 1). Then there will be a year of waiting (Year 2) before they know if they are successful (that is, the patent is granted). If they decide to license the technology, they would receive the $25 million distributed as $5 million per year beginning in Year 3. On the other hand, if they decide to sell the product directly, they will have to invest $5 million in each of Years 3 and 4 (to make up the total investment of $10 million). Their net proceeds from selling the product, then, would be evenly distributed over years 5 through 9. Now modify your decision tree (1) above to take account of the time value of money (that is, replace net revenues with NPVs).

Question: Calculate the (discounted) EMV of your recommended strategy and recommend the strategy or alternative that BMAC should pursue in order to maximize the NPV.

4. Compare/contrast your recommended strategy for BMAC that you arrived at in Question (1) with that in Question (3) and discuss the implications of taking account of the time value of money through discounting, generally in project appraisal and particularly in the case of BMAC.

Assignment 4: Case Study Analysis - AMECO Relocation Decision Problem

Introduction to the case study

This case study is based on a real case; of course, anonymized for obvious reasons. The case study considers the problem of Agricultural Machinery Exporters Company (AMECO), a company considering relocating its manufacturing facilities from the UK to an overseas country. In making its decision, the company needs to take into account a number of political risks that it will face if it decides to go ahead with the relocation. The decision problem is made complex by the large number of combinations of possible events that can occur and the challenges that arise from the need to structure the problem in a way which makes analysis of the problem tractable. Note that all of the monetary values presented in the case have already been expressed as present values to avoid the additional complication of applying discounted cash flow analysis to the data. Carefully read the case study and answer the question that follow.

AMECO Relocation Decision Problem

Agricultural Machinery Exporters Company (AMECO), which has its headquarters in the UK, is considering opening a manufacturing plant in an overseas country and transferring much of its current UK-based production to the new plant. After extensive data collection and visits by managers to a number of possible countries, Almeria has been identified as the most promising country for a new plant. A site near the capital, Lasia, appears to be highly suitable and a new state-of-the art manufacturing facility could be constructed there very quickly.

The decision on whether to go ahead with the move to Almeria will be based on the level of monetary savings in production costs that it is hoped would be generated over the next 10 years by opening a plant there. However, there are a number of risks associated with these savings and, for simplicity, the level of savings is categorised as either high, medium or low. If a move to Almeria does go ahead, AMECO will review the success of its investment after the first five years and will have the option of withdrawing from that country and returning operations to the UK if this appears to be appropriate.

Almeria has a relatively new democracy which was created following the overthrow of a military dictatorship that had ruled the country for nearly thirty years. However, there is considerable poverty and unemployment rates have recently been as high as 38%. The current government is therefore keen to attract foreign investors, but it only has a narrow majority in the country's parliament. Despite the efforts of the government, widespread corruption has persisted and Almeria is ranked 5th in the World league table of corruption. Corruption is partly responsible for the neglect of the country's road and rail systems which are now amongst the worst in the region.

If a decision is made to relocate to Almeria there is a risk that a new government will come into power and nationalize all foreign investments. There is thought to be only a 0.05 probability of this happening during the first five years, but if it did occur, the loss of assets would cause AMECO to be worse off by $75 million (in present value terms) compared to the returns that would have been generated by continuing manufacturing in the UK. Nationalization would also cause AMECO's association with the country to end immediately. There is also an estimated 0.3 probability that within the next five years, restrictions will be imposed by the government on the convertibility of local currency into foreign currency. This would reduce savings by an estimated $43 million (nationalization and currency restrictions can be assumed to be mutually exclusive events).

Insurance can be purchased to cover both of these political risks for the first five years of operations by paying a total premium which has a present value of $16 million. (Note that the insurance can only be purchased at the start of the five years). If the company does purchase political risk insurance and nationalization occurs in the first five years then the insurance will only cover the loss of assets. It is expected that any savings generated before nationalization would be canceled out by the costs of relocation and so would have present value of $0. If nationalization does not take place it is thought that there is a 0.6 probability that in the first five years the investment would generate high savings having an estimated present value of $85 million. There is also an estimated 0.25 probability that medium savings, with a present value $48 million, would be earned in the first five years and a 0.15 probability these savings will be low and only amount to $5 million. If no political insurance has been purchased, currency restrictions would reduce these savings by the estimated amount given above.

At the end of the first five years the company would have to decide whether to continue to operate the plant in Almeria for another five years or whether to transfer operations back to the UK. However, this decision will only be considered if the savings in the first five years have been low. If a decision to withdraw is made then the plant will be sold for a return with an estimated present value of $10 million. If AMECO decide to continue operations in Almeria for a further five years the risk of nationalization during this period is estimated to be 0.15. However, the risk of restrictions on the convertibility of local currency is estimated to be the same as that in the first five years.

The total insurance premium to cover these risks for the second five years would have a present value of $12.8 million. If insurance is purchased and nationalization occurs in the second five years then it is assumed that gross savings made before nationalization will again be cancelled out by the costs arising from the disruption. For simplicity, the present values of other costs and savings occurring under each set of conditions in the second five years are assumed to be the same as those in the first 5 years, with a 20% reduction to take into account the time value of money. However, it is thought that the probabilities of high, medium and low returns in the second five year period will be dependent on the level of returns achieved in the first five years as shown in the table below.

For example, the table shows that if savings in the first five years have been high then there is a 0.60 probability that high savings will be maintained in the next five years, a 0.3 probability that only medium savings will be generated and a 0.10 probability that savings will be low. The other two rows can be interpreted in a similar manner. It can be assumed that if the company stays in Almeria for ten years, it will sell the plant at the end of this period and hence generate extra returns with a present value of $6 million.

Question (approximately 500 words in total, excluding decision tree diagram)

Using decision tree analysis, structure the decision problem faced by AMECO and recommend the alternative or strategy that the company should pursue to maximize expected savings. Explain/justify your recommendations.

Guidance notes:
• Present your decision tree diagrams, clearly showing all probabilities and net values at the end of the branches
• Follow the conventions of constructing decision trees, such as the basic shapes distinguishing decision nodes from chance nodes
• Explain/justify your recommendations

More guidance notes on applying decision tree analysis on the AMECO decision problem

A decision tree model can be used to analyze this decision. Because of the size of the problem, it is suggested that you break down the decision trees into four sub-trees as follows:

Decision Tree 1: Depicts the decision that face the company in planning for the first 5 years of potential operation in Almeria
Decision Tree 2: Depicts the decision for second 5 years if savings in the first 5 years are high Decision Tree 3: Depicts the decision for second 5 years if savings in the first 5 years are
medium

Decision Tree 4: Depicts the decision for second 5 years if savings in the first 5 years are low Decision trees 2, 3 and 4 are best constructed first so that the optimal expected savings that they indicate can be ‘rolled back' and added to the savings for the first five years in decision tree 1.

Assignment 5: From Data to Decisions: Data Analytics

Data-driven decision-making (DDDM) is the process of using data to inform your decision-making process. Data analytics is at the heart of DDDM. Data analytics refers to the process and practice of analysing data to answer questions or to extract meaningful insights that an organization can use to inform its strategy and, ultimately, reach its objectives. Therefore, data only has value if it is turned into information. In the context of the DIK pyramid (Wallace, 2007) (see seminar 1), managers can then use this information in combination with their experience and judgement to create knowledge and ultimately improve their decision-making.
This introduction sets the context of this assignment. Your task is to independently apply data analytics techniques that you learnt in the seminars to extract meaningful insights or information from data. In the context of the DIK pyramid, you then draw out some knowledge or what you have learnt from the data. In particular, follow the steps below.

Step 1: Develop some 3 - 5 questions that you seek to answer from data.

Step 2: Find some data (see guidance on data sources in Box 1 below), download it onto an Excel spreadsheet, analyse the data and interpret the results with a view to answering the questions that you set out in step 1. Note, your analysis should include (but not limited to) the following:
• A selection of descriptive analytics (numerical measures) appropriate for your data, questions or information required from the data - see seminar 1
• A selection of descriptive analytics (data visualization) appropriate for your data, questions or information required from the data - see seminar 2
• Predictive analytics (regression analysis) - see seminar 4
• And anything else you learnt in any of the seminars.

Step 3: Write a short report, structured around your answers to the questions you set out in step 1 (approximately 1,000 words, excluding Tables, Figures/charts and references).
In your report, include some tables summarising the results of your analysis (step 2) and some data visualisation in the form of figures or charts (step 2). Also ensure that you clearly tell us your source of data (e.g., if it is from Statistica, MarketLine or Financial Times) or your own sources. If you use publicly available data (e.g., from the World Bank, office of national statistics of your country, etc), ensure you appropriately acknowledge your data source.

Box 1: Guidance on data and sources
A note on sources of data: The "UK Data Service" is one of the University library's databases for data from a wide range of sectors. Researchers may access open data collections without the need to register or login:

Go to university library website; under Find, click Databases, then find UK Data Service. Alternatively, this link will take you directly to all Databases (A-Z Databases (lincoln.ac.uk). Then find the relevant database (UK Data Service) and login using your usual University login details and you will be ready to search your data.

Of course, you may use your own data sources and you are encouraged to do so e.g., if you have access to data from an organisation that you previously worked for or are familiar with. However, ensure it is good quality data. The quality of University library recommended data sources above is guaranteed. Finally, ensure you have a reasonable sample size of data (a sample size of least 30 to around 100 observations or lines of data; you can use larger datasets, if you like - the more the better!). Needless to say, the data should be relatively recent (perhaps during the last 20 years). You will upload your Excel spreadsheet containing your data on blackboard separately as part of your submission.

If you are interested in financial data, particularly stock market data

For example, following gives you access to historical stock market data for companies trading on the London Stock Exchange's FTSE 100.

Assignment 6: Ethical Decision-Making
Over the past few decades ethical decision-making (EDM) has received considerable attention from scholars and practitioners. Understanding how managers identify and respond to ethical issues in the decision-making process is generally recognised as paramount for the success of any organization. In this assignment you are invited to critically engage with some literature on EDM, particularly Mark S. Schwartz (2016) which critically explores the EDM theory and practice. The second reading (book chapter) builds on the previous topic's discussion of big data and analytics with a focus on issues of ethics, privacy, security and legality in data acquisition and use.

Following on from what you have learnt in the lecture and from your critical reading of the following literature, answer the questions below.

Readings (available from the Reading list on Blackboard)
• Mark S. Schwartz (2016) Ethical Decision-Making Theory: An Integrated Approach, Journal of Business Ethics, 139:755-776.

• Chapter 9: Managing the Ethics, Security, Privacy and Legal Aspects of Data-Driven Decision-Making. In: Simone Gressel, David J. Pauleen and Nazim Taskin (2021), Management Decision-Making, Big Data & Analytics. Sage: London.

Questions
1. In general, identifying and appropriately responding to ethical issues in the decision- making process is important for the success of any organisation. Do you agree? Why/Why not? (100 words)

2. Discuss what managers or decision makers can learn or take away from Schwartz (2016). For example, how can they apply these findings in their approaches to EDM? (200 words)

3. Informed by your reading of Chapter 9 (Gressel, Pauleen and Taskin, 2021), reflect on the legislation on data privacy/security in your country. Do you think it is appropriate? Why?/Why not? (200 words)

Assignment 7: Self Reflection

In your own words/opinions, reflect on what you have learnt throughout the course (including your learning from the lectures, seminars and working through the assignments) and make some recommendations to managers in order to improve their decision-making. You may structure your reflection around Kolb's (1984) Experiential Learning Theory (ELT).

Attachment:- Answers Template.rar