Expected Monetary Value and Decision Trees

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About this lesson

The Expected Monetary Value (EMV) and Decision Trees are two quantitative risk analysis techniques that when paired can be used to select an optimum project approach.

Quick reference

Expected Monetary Value and Decision Trees

The Expected Monetary Value (EMV) and Decision Trees are two quantitative risk analysis techniques that when paired can be used to select an optimum project approach.

When to use

Quantitative risk analysis techniques are normally used following a qualitative analysis of project risks.  The quantitative analysis provides a more detailed understanding of project risks and options.  The EMV and Decision Tree approach is normally used to select between options during project planning.

Instructions

Different quantitative techniques are focused on different types of project risk and require different amounts and types of project data.

Decision Tree

Decision Tree Analysis: “A diagramming and calculation technique for evaluating the implication of a chain of multiple options in the presence of uncertainty,”  PMBOK® Guide. The Decision Tree considers a combination of decision options and random or uncertain events to create a family of project scenarios.  This is the Decision Tree.  Each scenario is project planned.  The project costs and the business impact of each scenario are determined.  (This process can literally take days to create multiple project baselines.)  A probability is assigned to each scenario based upon the likelihood of the random or uncertain events that are embedded within the tree. 

Expected Monetary Value

Expected Monetary Value (EMV) Analysis: “A statistical technique that calculatesthe average outcome when the future includes scenarios that may or may not happen.  A common use of this technique is with a decision tree analysis,” PMBOK® Guide.  The EMV is calculated by multiplying the probability of the random events times the cost and benefit impacts of each scenario.   The EMV for all the scenarios that are an outgrowth of a decision are added to determine the EMV of that decision path.  Normally you select the decision path with the highest EMV. See the example below.

 

 

Definitions are taken from the Glossary of the Project Management Institute, A Guide to the Project Management Body of Knowledge, (PMBOK® Guide) – Fifth Edition, Project Management Institute, Inc., 2013, Pages 536, and 539.

 

 

Project Management Institute, A Guide to the Project Management Body of Knowledge, (PMBOK® Guide) – Fifth Edition, Project Management Institute, Inc., 2013, Figure 11-16, Page 339. PMBOK is a registered mark of the Project Management Institute, Inc.

  • 00:03 Hi, this is Ray Sheen.
  • 00:05 I would like to talk about quantitative risk analysis methodology techniques.
  • 00:09 Expected monetary value and decision trees are straightforward calculations of risk.
  • 00:14 They are likely to show up on the PMP exam.
  • 00:16 The Project Management Body of Knowledge, the PMBOK guide, defines expected monetary
  • 00:21 value as a statistical technique that calculates the average outcome
  • 00:26 when the future includes scenarios that may or may not happen.
  • 00:29 A common use of this technique is with a decision tree analysis.
  • 00:33 This is the calculation.
  • 00:35 The EMV equals the probability of risk
  • 00:38 times the monetary impact of the risk condition to the project.
  • 00:41 It is essentially taking a risk matrix and multiplying the two sides.
  • 00:46 Positive risks, or risk opportunities, will have a positive EMV,
  • 00:50 and negative risks, or risk threats, will have a negative EMV.
  • 00:54 The EMV for a single given risk is not very helpful.
  • 00:57 However, aggregating the EMV for all the risks in a project scenario and comparing
  • 01:02 that aggregate value with the aggregate value of another scenario is helpful.
  • 01:08 Each scenario probably has some high and some low risks and
  • 01:11 may even have some risk threats and risk opportunities.
  • 01:15 Aggregating these EMVs and comparing them puts a risk value on the scenario.
  • 01:21 Let's work through an example of a decision tree with EMV calculation.
  • 01:25 First, I want to review what a decision tree is.
  • 01:28 The Project Management Body of Knowledge, the PMBOK guide,
  • 01:30 defines it as a diagramming and calculation technique for evaluating
  • 01:35 the implication of a chain of multiple options in the presence of uncertainty.
  • 01:40 This diagram branches for both decisions and for risks for random events.
  • 01:44 Let's go through an example.
  • 01:45 We will start with the primary decision.
  • 01:47 In this case, we have a factory that is unable to meet the demand for the product.
  • 01:51 So we need more manufacturing capacity.
  • 01:54 There are two options, we can build a new factory or upgrade our current facility.
  • 01:59 The new factory option will cost $120 million.
  • 02:02 It will expand the capacity, and at the same time,
  • 02:05 we can change our process in a way that allows us to lower product costs.
  • 02:10 Now, for the uncertainty,
  • 02:12 marketing is not sure how much additional demand there will be.
  • 02:15 There is a 60% probability of very strong demand and
  • 02:19 a 40% probability of weaker demand.
  • 02:21 The strong demand will result in a $200 million profit.
  • 02:25 But the weak demand will only give us a $90 million profit.
  • 02:29 The EMV for the strong demand is $200 million of profit,
  • 02:32 minus $120 million of cost for the new plant, for a total of $80 million.
  • 02:37 We multiply that times 60% to get an EMV of $48 million.
  • 02:42 The EMV for the weak demand path is $90 million of profit
  • 02:45 minus 120 million of cost, for a total of minus 30 million.
  • 02:50 We multiply this times 40% to get minus 12 million.
  • 02:54 The aggregated value for the path of building a new plant is 48 million,
  • 02:59 minus 12 million, or a total of 36 million.
  • 03:02 Now let's look at the upgrade path.
  • 03:04 To upgrade the existing manufacturing facility will cost $50 million.
  • 03:08 This will expand the capacity, but there is no change to the production process so
  • 03:13 there is no productivity savings.
  • 03:15 Again, there is a 60% probability of strong demand and
  • 03:18 40% probability of a weak increase in demand.
  • 03:21 The strong demand will generate 120 million of profit.
  • 03:25 The weak demand will generate 60 million of profit.
  • 03:28 The EMV for the strong demand is 120 million of profit minus the 50 million
  • 03:32 of upgrade costs, for a total of 70 million, times 60%.
  • 03:36 This is 42 million.
  • 03:38 The EMV for the weak demand path is 60 million minus 50 million, for
  • 03:41 a total of 10 million.
  • 03:43 Multiply this times 40% to get an EMV of 4 million.
  • 03:47 So the aggregate EMV for
  • 03:49 the upgrade path is 42 million plus 4 million, or 46 million.
  • 03:54 When we compare the two paths,
  • 03:56 we see that the build a new plant path has an aggregate EMV of 36 million,
  • 04:01 and the aggregate EMV for the upgrade path is 46 million.
  • 04:05 Therefore, the company should choose to do the upgrade.
  • 04:08 It's likely that you will see several decision trees and
  • 04:11 EMV questions on the PMP exam.
  • 04:13 If you're not familiar with this technique,
  • 04:15 be certain to do the exercises for practice.

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