Expected Monetary Value and Decision Trees

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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 branch of each tree. 

Expected Monetary Value

Expected Monetary Value (EMV) analysis is a statistical technique that calculates the 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,  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) – Sixth Edition, Project Management Institute, Inc., 2017, Pages 704.

Project Management Institute, A Guide to the Project Management Body of Knowledge, (PMBOK® Guide) – Sixth Edition, Project Management Institute, Inc., 2017, Figure 11-15, Page 435. PMBOK is a registered mark of the Project Management Institute, Inc.

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  • 00:04 Hi, I'm Ray Sheen.
  • 00:06 I'd like to talk about a quantitative risk analysis methodology for
  • 00:10 calculating over all project risk.
  • 00:12 Expected monetary value and decision trees are straightforward calculations
  • 00:17 of that risk and they're likely to show up on the PMP exam.
  • 00:23 Expected monetary value is a statistical technique that calculates the average
  • 00:28 outcome when the future includes scenarios that may or may not happen.
  • 00:32 A common use of this technique is with a decision tree analysis.
  • 00:36 This is the calculation.
  • 00:37 The EMV equals the probability of risk times the monetary impact of the risk
  • 00:41 conditions to the project.
  • 00:43 Is essentially taking a risk matrix and multiplying the two sides.
  • 00:47 Positive risks or risk opportunity's will have a positive EMV, and negative risks,
  • 00:52 or risk threats will have a negative EMV.
  • 00:55 EMV for a single risk is not very helpful.
  • 00:58 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.
  • 01:11 And may even contain some risk threats and risk opportunities.
  • 01:15 Aggregating these EMVs and comparing them puts a risk value on each scenario.
  • 01:21 Let's work through an example on decision tree with EMV calculations.
  • 01:25 First, I wanna review what a decision tree is.
  • 01:28 The Project Management Body of Knowledge, the PMBOK Guide,
  • 01:31 defines it as a diagramming and calculating technique.
  • 01:35 For evaluating the implications of a chain of multiple options in the presence of
  • 01:40 uncertainty.
  • 01:41 This diagram branches for both decisions and risks or random events.
  • 01:45 Let's go through an example.
  • 01:47 We'll start with the primary decision.
  • 01:50 In this case, we have a factory that is unable to meet the demand for the product,
  • 01:54 so we need more manufacturing capacity.
  • 01:56 There are two options, we can build a new factory, or upgrade our current facility.
  • 02:02 The next note of the decision tree is the factory options.
  • 02:04 A new factory will cost 120 million dollars.
  • 02:08 It will expand the capacity and at the same time,
  • 02:10 we can change our processes in a way that allows us to lower lower production costs.
  • 02:15 Now for the uncertainty note,
  • 02:17 marketing is not sure how much additional demand there will be.
  • 02:21 There is a 60% probability of very strong demand and
  • 02:24 a 40% probability of a weak demand.
  • 02:27 The strong demand will result in $200 million of profit but
  • 02:31 the weak demand will only give us $90 million of profit.
  • 02:35 The EMV for the stronger man part has $200 million of profit minus
  • 02:40 $120 million of cost for the new plant for a total of $80 million.
  • 02:44 We multiply that times 60% to get an EMV for that part of $48 million.
  • 02:50 The EMV for the weak demand path is $90 million of profit minus $120
  • 02:55 million of cost, for a total of minus $30 million.
  • 02:58 We multiply that by 40% to get a minus $12 million.
  • 03:02 The aggregated value for the path of building a new plant is $48 million minus
  • 03:07 $12 million, or a total of $36 million.
  • 03:10 Now let's go back to the decision node and look at the upgrade path.
  • 03:14 To upgrade the existing manufacturing facility, will cost $50 million.
  • 03:18 This will expand the capacity, but there's no change in the product process, so
  • 03:22 there is no productivity savings.
  • 03:25 Again there is the 60% probability of strong demand and
  • 03:28 40% probability of a weak demand.
  • 03:30 The strong demand will generate a $120 million of profit.
  • 03:34 The weak demand will only generate $60 million of profit.
  • 03:38 The EMV for the strong demand is $120 million of profit minus the $50 million
  • 03:44 of upgrade, for a total of $70 million times 60%, and this is $42 million.
  • 03:50 The EMV for the weaker demand path is $60 million minus the $50 million for
  • 03:55 the upgrade for a total of $10 million.
  • 03:58 Multiply that $10 million times 40% and we get an EMV of $4 million.
  • 04:03 So the aggregate EMV for
  • 04:05 the upgrade path is $42 million plus $4 million, or $46 million.
  • 04:10 When we compare the two paths,
  • 04:12 we see the building of a new plant path has an aggregate EMV of $36 million, and
  • 04:16 the aggregate EMV for the upgrade path is $46 million.
  • 04:20 Therefore, the company should choose to do the upgrade.
  • 04:25 It's likely that you'll see a decision tree and EMV question on the PMP exam.
  • 04:30 Now if you're not familiar with this technique,
  • 04:33 make sure you do the exercise to practice

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