Hi, I need some exercises and examples on EMV calc...

Discussion in 'General Discussions' started by Purba, Jun 10, 2017.

  1. Purba

    Purba Member
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    Hi, I need some exercises and examples on EMV calculation in decision tree of Risk management chapter, can someone help?
     
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  2. Priyamwada

    Priyamwada Well-Known Member
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    Purba,

    We have received your query.
    Kindly allow us 24 hrs of time while we revert with an update.

    Happy Learning!!
    Priyamwada Singh - Global Teaching Assistant
     
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  3. Krishnakumar Kuppusamy(4034)

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    To calculate the Expected Monetary Value in project risk management, you need to:

    1.Assign a probability of occurrence for the risk
    2. Assign the monetary value of the impact of the risk when it occurs.
    3. Multiply Step 1 and Step 2.
    The value you get after performing Step 3 is the Expected Monetary Value. This value is positive for opportunities (positive risks) and negative for threats (negative risks). Project risk management requires you to address both types of project risks.

    Example:
    Expected Monetary Value Example for Project Risk Management
    Suppose you are leading a construction project. Weather, cost of construction material, and labor turmoil are key project risks found in most
    construction projects:

    • Project Risks 1 - Weather: There is a 25 percent chance of excessive snowfall that’ll delay the construction for two weeks which will, in turn, cost the project $80,000.
    • Project Risks 2 - Cost of Construction Material: There is a 10 percent probability of the price of construction material dropping, which will save the project $100,000.
    • Project Risks 3 - Labor Turmoil: There is a 5 percent probability of construction coming to a halt if the workers go on strike. The impact would lead to a loss of $150,000. Consider your industry and geographic area to determine whether this risk would have a higher probability.
      Note: Regardless of the type of project, the golden rules of project risk management do not change. Hence, though this example is from the construction industry, the theory is applicable to other industries, such as software development and manufacturing.

      Next, let's see how to quantify the project risks by calculating the Expected Monetary Value of each risk.
    Expected Monetary Value Calculation for Project Risk Management
    In this Expected Monetary Value example, we have two negative project risks (Weather and Labor Turmoil) and a positive project risks (Cost of Construction Material). The Expected Monetary Value for the project risks:

    • Weather: 25/100 * (-$80,000) = - $ 20,000
    • Cost of Construction Material: 10/100 * ($100,000) = $ 10,000
    • Labor Turmoil: 5/100 * (-$150,000) = - $7,500
    Note: Though the highest impact is caused by the Labor Turmoil project risk, the Expected Monetary Value is the lowest. This is because the probability of it occurring is very low

    This means that if the:
    • Weather negative project risks occurs, the project loses $20,000,
    • Cost of Construction Material positive project risks occurs, the project gains $10,000, and
    • Labor Turmoil negative project risks occurs the project loses $ 7,500
    The project’s Expected Monetary Value based on these project risks is:

    -($20,000) + ($10,000) – ($7,500) = - $17,500

    Therefore, if all risks occur in the construction project, the project would lose $17,500. In this scenario, the project manager can add $17,500 to the budget to compensate for this. This is a simplistic Expected Monetary Value calculation example. Another technique used to calculate complex Expected Monetary Value calculations is by conducting Decision Tree Analysis. This analysis helps while making complex project risk management decisions. For more details, read this article on Using a Decision Trees Example in Project Risk Management to Calculate Expected Monetary Value.

    As a project manager, you may apply different production techniques to minimize risk. For example, if this example was based on software development or manufacturing, the project manager could use Lean thinking to reduce waste and minimize risk. However, the method for computing Expected Monetary Value during project risk management would not change.


    Decision Tree Example

    Suppose your organization is using a legacy software. Some influential stakeholders believe that by upgrading this software your organization can save millions, while others feel that staying with the legacy software is the safest option, even though it is not meeting the current company needs. The stakeholders supporting the upgrade of the software are further split into two factions: those that support buying the new software and those that support building the new software in-house. Confusion reigns in the meeting room with stakeholders pointing out negative risks for each option!!!

    By exploring all possibilities and consequences, you can quantify the decisions and convince stakeholders. This is known as Decision Tree Analysis. The following Decision Trees example uses Decision Tree Analysis to help make an informed Project Risk Management decision. The computations involve calculating the Expected Monetary Value. Read on to learn more about Decision Trees and Decision Tree Analysis.

    Decision Trees Example - Building the Decision Tree to Use in Decision Tree Analysis
    In this scenario, you can either:

    • Build the new software: To build the new software, the associated cost is $500,000.
    • Buy the new software: To buy the new software, the associated cost is $750,000.[​IMG]
    • Stay with the legacy software: If the company decides to stay with the legacy software, the associated cost is mainly maintenance and will amount to $100,000.
    Looking at the options listed above, you can start building the decision trees as shown in the diagram. By looking at this information, the lobby for staying with the legacy software would have the strongest case. But, let’s see how it pans out.

    The Buy the New Software and Build the New Software options will lead to either a successful deployment or an unsuccessful one. If the deployment is successful then the impact is zero, because the risk will not have materialized. However, if the deployment is unsuccessful, then the risk will materialize and the impact is $2 million. The Stay with the Legacy Software option will lead to only one impact, which is $2 million because the legacy software is not currently meeting the needs of the company. Nor, will it meet the needs should there be growth. In this example, we have assumed that the company will have growth


    • In this example, Decision Trees analysis will be used to make the project risk management decision. The next step is to compute the Expected Monetary Value for each path in the Decision Trees. Let's see how this helps in this Decision Trees example.



    • Decision Trees Example - Calculating Expected Monetary Value for each Decision Tree Path
      The diagram depicts the decision tree. Now, you can calculate the Expected Monetary Value for each decision. The Expected Monetary Value associated with each risk is calculated by multiplying the probability of the risk with the impact. By doing this, we get the following:[​IMG]
      • Build the new software: $ 2,000,000 * 0.4 = $ 800,000
      • Buy the new software: $ 2,000,000 * 0.05 = $ 100,000
      • Staying with the legacy software: $ 2,000,000 * 1 = $ 2,000,000




      Now, add the setup costs to each Expected Monetary Value:
      • Build the new software: $ 500,000 + $ 800,000 = $ 1,300,000
      • Buy the new software: $ 750,000 + $ 100,000 = $ 850,000
      • Staying with the legacy software: $ 100,000 + $ 2,000,000 = $ 2,100,000


      View the image above, to see how all the figures above look like in a Decision Tree after conducting a Decision Tree Analysis. Now let's make the decision in this Decision Trees example. This will illustrate the role of Decision Trees in Project Risk Management.
    Decision Trees Example - Making the Decision
    Looking at the Expected Monetary Values computed in this Decision Trees example, you can see that buying the new software is actually the most cost efficient option, even though its initial setup cost is the highest. Staying with the legacy software is by far the most expensive option.
    When you conduct a SWOT Analysis to determine whether a business idea is worth pursuing, there is no quantified data to support your decision. Decision Trees and Decision tree analysis help you quantify the data, which is then useful in convincing stakeholders. It is a critical part of Project Risk Management.


    Reference: Brighthub.com
     
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  4. Purba

    Purba Member
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    Thanks KK
     
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