Describing the Problem in Detail

Posted: August 27th, 2021

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                                                                   Assignment 2                

Describing the Problem in Detail

Wal-Mart Company wants to expand its operations by adopting new investment projects in its retail business. The company has eight projects with different positive NPV that it intends to implement to raise additional funds. Therefore, all projects are economically viable as they have a positive NPV. Additionally, the organization’s financial management proposes to make a minimum revenue stream of $600 million by picking the best possible strategies from the sought advice on simulation. Furthermore, the company can implement the project at the beginning orend of the investment period to generate the required funds. However, regarding the first option and availability of funds, only six projects can be implemented at the start of the investment period, and each project would fetch out $80 million. Still, each project would generate $100 million if the financial manager decides to implement the project at the end of the period. However, this option has a high risk of failure. Equally, the six out of eight projects to be invested at the start of the investment period would not fetch the required returns though it has a lower risk of failure. Therefore, the financial manager wants to implement a simulation method to maximize its returns and increase the probability of generating the $600 million target. Hence, to attain the set target, the company cannot execute more than six projects at the beginning of the investment period.

Consequently, the manager estimated the projects’ demand to be as shown in table 1 below, as with the following equations.

Table 1: Projects’ demand and probability at the beginning of the period

Projects’ Demand	1	2	3	4	5	6
Probability	8%	16.50%	40%	29%	6.5%	0.00%

Equation Formulation                                                                   

Let an investment project that generates $80 million be represented by X, and those generating $100 million be represented by Y. Therefore,the function would be as follow;

Hence;

            Additionally, the finance manager can implement all the eight projects at the end of the investment period as their demand will have appreciated due to changes on timelines. More so, the bottom line is that the manager intends to generate a maximum profit of $600 million. Therefore, the last-minute projects’ implementation would be based on the following demand-oriented probabilities.

Table 2: Projects’ demand and probability at the end of the investment period

Projects’ Demand	1	2	3	4	5	6
Probability	8.5%	18.50%	45%	30%	8.5%	1.00%

Let all the projects implemented at the end of the financial period be represented byZ.

Therefore,

            The company manager faces another strategy problem of intending to increase his probability of generating the targeted $600 million. As such, the manager has the discretion of choosing a single simulation from the six alternatives listed above. Hence, from the advanced investment of only six projects at the start of the investment period, the manager will generate a maximum profit stream of $600 million as the projects generate an average of $106.41, as shown in the simulation.

Explaining the Motivation

The motivation to implement six projects at the start of the investment period is that six different simulations would be run for more than 1000 trials to generate the maximum possible value of profits.

Table 3: Projects’ demand, probability, and minimum profit per simulation

Projects’ Demand	1	2	3	4	5	6
Probability	8%	16.50%	40%	29%	6.5%	0.00%
Minimum profit per simulation	≥$77.41	≥$82.41	≥$87.41	≥$92.41	≥$97.41	≥$102.41

Moreover, the manager would anticipate different recording ranges of minimum revenue streams from the table for six other simulations. There was the anticipated benefit of implementing 2 or 0 players at the end of the investment period due to increased demand. Unfortunately, the manager would experience simulation risk if only a few projects are implemented in advance at the start of the investment period. Nonetheless, there is a motivation that the manager is destined to benefit once he implements more than five or six projects at the start of the investment period. This is because it offers the chance to reduce the risks associated with the depreciation of value for the projects’ remainder period. For example, for the six simulations, one project’s sale would generate maximum possible revenue compared to the implementation of six projects, as illustrated by the table below.

Table 4: Projects’ demand and maximum profit per project implemented

Projects	1	2	3	4	5	6
Maximum profit per project implemented	$132.04	$127.04	$122.04	$117.04	$112.04	$107.04

Modeling and Simulating the Problem Using Analytic Solver Platform

The primary objective of conducting the simulation is to provide the finance manager with the best investment strategy to increase the probability of generating the targeted $600 million. Therefore, six simulations were conducted with 1000 trials in every simulation. Thus, a total of 6000 trials were done. The six simulations were based on the projects invested in advance at the beginning of the investment period. Equally, the first simulation conducted was done on condition that the first project was invested in advance. Still, the second simulations were carried out because only two projects were invested in advance. Similarly, the third simulation was performed on the condition that only three projects were invested in advance. Also, the fourth simulation was conditioned on advance investment in the four projects were. The fifth simulation was also conditioned that only five projects were invested in advance. Finally, the sixth simulation was done; its condition was that only six projects were invested in advance at the beginning of the investment period.

Discussion the Results

The simulation’s minimum revenue is $77.41, with a maximum income of $132.04 and an average of $106.41. Notably, the simulation results indicate that investing in one project has the lowest minimum expected revenue of $77.41. Likewise, investing in two projects generates $82.41, three projects with $87.41, and four projects would generate $92.41. Investing in five projects would increase the revenue stream to generate $97.41, and investing in six projects would generate maximum returns of $102.41 in the investment. More so, the project’s maximum possible income streams were also considered, with the trend being the opposite. Project one generated the maximum returns of $132.04, project two generating $127.04, project three $122.04, and four $117.04. The trend gradually declined in project five with $112.04 and finally six generating $107.04. Therefore, the result exposes the risk of investing in fewer projects at the beginning of the investment period. Also, it signals the strength in investing in the six projects at the beginning of the period as it reduces risk. Additionally, the simulation indicates that investing in only six projects at the start of the investment period will generate a maximum profit stream of $600 million as the projects generate an average of $106.41. Therefore, the finance manager should concentrate on investing in the six projects at the beginning of the investment period. It will increase the probability of achieving the $600 million target and reduce investment risk. Thus, by doing so, the company will be able to expand its operations as intended.