Perform Quantitative Risk Analysis

00:01 Hello and welcome.

00:02 This module will focus on the perform quantitative risk analysis process in the Bot guide.

00:10 The difficulty is rated as high.

00:13 Because many of you won't have dealt with true quantitative risk analysis in your projects. If you have dealt with quantitative risk analysis, then you can change that red down lower.

00:26 Memorization and exam importance are both ranked as medium once again because quantitative risk analysis is not done by many people in the way that the PMBOK guide suggests.

00:41 The Perform Quantitative Risk Analysis is one of six processes in total in the project risk management knowledge area.

00:51 It is one of five Planning processes.

00:55 Make sure you understand the distinction between quantitative risk analysis and qualitative risk analysis, qualitative risk analysis, which we covered in a separate module, is a subjective analysis of probability and impact and is done quickly on all risks in the project. Quantitative risk analysis takes time and money and computers generally.

01:21 And it uses mathematical modelling and statistical analysis to give us a quantitative or objective analysis of probability and or impact on our project.

01:34 So do make sure you understand the difference between those two.

01:41 The particular domain task that the perform quantitative risk analysis process helps us to understand better is develop the risk management plan by identifying, analyzing and prioritizing project risks and defining risk response strategies in order to manage uncertainty and opportunity throughout the project lifecycle.

02:03 Obviously, the key word in that sentence is analyzing, well, performing quantitative analysis.

02:12 The key theme of the quantitative analysis process is that while qualitative ranks them quantitative assigns an actual value to them using mathematical modelling and statistics.

02:26 But in order to do it, we do require that prioritized list of risks from qualitative analysis.

02:33 So generally speaking, we do quantitative after qualitative. So please make sure you know the difference and the relationship between qualitative and quantitative risk analysis. Here are some of the inputs that we may find useful in completing quantitative analysis.

02:55 First up, obviously our risk management plan because this is the plan that tells us how we're going to do this, what level and depth and content we're going to use. It's going to reflect our risk tolerance or risk aversion.

03:11 We'll also want our cost management plan and our schedule management plan because they will give us the quantities we need.

03:20 The dollars or the time are the usual quantities we want.

03:25 When we do quantitative analysis, we need to express it and either dollars or days. And that's why we need our cost management plan and our schedule management plan because they'll provide guidance on which particular metrics we're using and their particular approach to quantitative risk management that we may choose to use with them.

03:46 We'll also want whatever iteration of our risk register we currently have, whether it's the first iteration or the one hundredth iteration will always want that as an input to add quantitative risk analysis to it or to update previous quantitative risk analysis.

04:03 Because remember, these Planning processes and risk management aren't separate discrete processes that we do one after the other, then stop.

04:13 These are all interrelated and happening concurrently throughout the entire life of the project. So here the risk register is an input could be any form or iteration of the risk register.

04:27 Particular enterprise environmental factors will include industry standards for quantitative analysis.

04:34 And they may also include particular proprietary models owned by others that you're using.

04:42 You may have your own organizational process assets specifically addressing quantitative risk analysis as well.

04:48 And if you do, they will be a very useful input into this process.

04:56 The particular tools and techniques we may choose to use include data gathering and representation techniques, quantitative risk analysis and modelling techniques, and I'll show you some of those in a moment.

05:08 And of course, expert judgment.

05:11 And once again, remember you're an expert.

05:14 Your project team members are experts.

05:16 In this case, though, you may want to reach out to industry specialists in your particular area and their expertise and quantitative risk analysis of your particular risks.

05:31 So let's take a look at some data gathering and representation techniques.

05:36 A great way to get data from people or stakeholders is interviewing focus groups, workshops, surveys, questionnaires, they're all great way to get information and expert judgment, as well as being a tool or technique for deciding on quantitative risk analysis is also a great way of getting data from people as well.

06:04 Here's an example of a quantitative probability and impact assessment, and you may want to compare this example to the model on qualitative probability and impact assessment to see what the difference is between them.

06:20 In the qualitative risk assessment for the financial one, we gave it a probability of four out of five and an impact of three out of five. We multiplied those together to give a score of 12 out of a possible score of twenty five.

06:36 And we ranked it like that.

06:38 But that's qualitative risk analysis.

06:40 It was subjective.

06:42 It was done quickly.

06:44 Now, if we were to perform quantitative risk analysis on the same risk this time, instead of taking somebody's word or opinion on what the probability is, we would do some serious research to give us an actual percentage probability of that risk manifesting.

07:02 And this research may take time, and it may take consulting experts and paying them for their time. We'll also want to get an actual value of the impact.

07:13 In this case, we're using dollars.

07:16 We could just as easily use days.

07:20 And this financial impact, we may need to bring in quantity surveyors or other professionals to tell us the actual financial impact if that manifests. So in this instance, instead of a probability of four out of five and an impact of three out of five, that qualitative risk analysis gave us for a total assessment of 12 out of 25.

07:42 Here we have a 46 per cent probability.

07:47 And a $35,000 impact, and if we multiply those two together, we get a quantitative risk assessment of sixteen thousand one hundred dollars. Now, here's a little tip, one way to build up a transparent, defensible contingency reserve.

08:08 Is to simply aggregate or add up all of your quantitative probability and impact assessments.

08:15 And this example, we've added them all up and we've got $50,674 as the total quantitative risk uncertainty.

08:26 Now that could become a contingency reserve, it's defensible.

08:30 It's transparent.

08:32 Keep in mind with your contingency reserve, though.

08:35 If that technical risk doesn't eventuate, then you must return the $20,489 back to the organization and not simply keep it aside for other unidentified risks. So that's an example of how quantitative risk analysis differs from qualitative risk analysis.

08:56 And keep in mind, even though I've used dollars here, we could have just as easily used days and count the contingency reserve for time on our project. Other aspects of quantitative risk analysis and modelling that you need to know about include sensitivity analysis usually represented in a tornado diagram.

09:18 Now, sensitivity analysis takes a look at different parts of your project. In this instance, the diagram takes a look at software, human resources, hardware testing and installation, and gives us a range of sensitivity both negative and positive.

09:37 So we can see that the software part of our project is highly sensitive to risk, and there's so much uncertainty in there that we could have a highly positive or a highly negative outcome, whereas the other end of that tornado diagram is the installation. It's not very sensitive to risk, so this way gives us a way to look at which parts of our projects are most sensitive to risk. And of course, the value in that information is we can focus on those areas. Now we're going to take a closer look at a specific type of quantitative risk analysis and modelling.

10:14 This is called a decision tree and it shows how to make a decision between two or two alternative strategies or choices.

10:24 When you have some information about probability, you will probably get some form of decision tree in the exam.

10:32 So we'll go through the slowly and but you must understand the logic behind it.

10:39 So let's take a look at this example.

10:42 Here we have the decision are we going to build a new plant or factory or upgrade our existing factory? Now, if we build our new factory, we'll see that it costs us one hundred and twenty million dollars.

11:00 That's that negative one hundred and twenty.

11:02 That's the cost of building our new factory.

11:06 It's big. It's exciting if we simply upgrade our existing plant or factory. It's not going to cost us $120 million dollars.

11:15 It's going to cost us $50 million.

11:18 The upgrade isn't as exciting and we don't need to start from pure foundations again. So we've got that information.

11:26 A cost of $120 million to build a new factory and $50 million to upgrade an existing factory.

11:33 Now, regardless of whether we choose to build a new factory or upgrade our existing factory, our marketing team have told us that there is a 65 percent chance of strong demand for our product and 35 percent chance of weak demand for our product.

11:50 And you'll see that represented with both the building and the upgrading options. 65 percent chance of strong demand and 35 percent chance of weak demand. So let's take a look at what happens if we build a new factory.

12:05 Well, if strong demand eventuates in the market and there's a 65 percent chance of that happening, we will make $200 million.

12:14 Wow, that's fantastic.

12:16 But we would have spent $120 million on building the factory to make that $200 million.

12:23 So that gives us a neat path value of $80 million.

12:27 And there's a 65 percent chance of making $80 million.

12:32 Now, if weak demand eventuates in the market, we would have spent $ 120 million to make $90 million.

12:41 So that gives us a net path value there of negative $30 million.

12:46 And there's a 35 percent chance of losing $30 million. So if we want to figure out the expected monetary value of building a new plant, we simply add together.

13:00 65 percent of $80 million and 35 percent of negative $30 million.

13:08 And if you calculate those and add them up, they give us an expected monetary value of that particular note of $41.5 million.

13:18 Okay, let's take a look now at the same exercise, though, with upgrading our existing plant, not building a new one, simply upgrading our existing one.

13:27 Remember, the upgrade only costs $50 million, not $120 million.

13:33 But the demand doesn't change.

13:35 So if strong demand eventuates from our product.

13:42 Will only make one hundred and $20 million, not $200 million.

13:46 Remember, our big flash new factory could make many, many more products.

13:51 Our upgraded plant can't quite make as many products.

13:55 So if strong demand eventuates will make $120 million, so we would have spent $50 million to make $120 to give us a net par value of $70 million.

14:08 And there's a sixty five percent chance of that occurring.

14:12 If weak demand eventuate for our Produkt.

14:17 Will make $60 million.

14:19 And we would have spent $50 million upgrading the plant to make $60 million.

14:24 Therefore, we have a net pass value of $10 million and there's a 35 percent chance of that occurring.

14:31 So we simply now add together a 65 percent chance of making 70 million and a 35 percent chance of making 10 million.

14:41 Add those two together and we get an expected monetary value of $49 million for upgrading the existing plant.

14:50 So when we now compare those to expected monetary values. For the building, the new plant or factory, we hadn't expected monetary value of $41.5 Million for upgrading the existing plant or factory.

15:05 We have an expected monetary value of $49 million.

15:09 So therefore, based on our quantitative risk assessment, we would choose to upgrade the existing plant.

15:18 But can you see the information and our decision as only as good as the information going into it? So if our marketing people are completely wrong with their forecasts of strong and weak demand? Then the model doesn't mean anything, so it's only as good as the information that's going on now for the exam.

15:37 You may get a decision tree like this or you may get a shorter one.

15:41 The key thing is to multiply the probability and impact together over all of the links in the chain and add them together.

15:54 Computer modeling when it comes to doing quantitative risk analysis, we are generally using computers of some sort to do mathematical modelling or some form of statistical analysis.

16:06 So in the exam, if you see any reference to linear regression techniques or any form of statistical analysis, we're generally using computers.

16:15 And it's going to be focused on quantitative risk analysis.

16:19 And the two most popular ways of doing this are with Monte Carlo, or it's often called What If analysis as well.

16:26 They're very similar, and what they basically do is take a computer and look at all the possible outcomes and the probability of each and give you a range of uncertainty.

16:38 So out of all the possible outcomes, you can see the probability of each and which ones are the most likely and which ones are the least likely.

16:46 You may have use something like this before.

16:50 There's many great bits of software out there to help you do quantitative risk analysis. We won't go into them in depth, just know for the exam.

16:59 Quantitative risk analysis involves computer simulations, mathematical modelling, statistical analysis, decision trees, all hard technical analysis. And remember, that's how quantitative analysis differs from qualitative analysis, which is subjective done by experts very quickly. The single output from this process is simply project document updates, and of course, the main project document you will update will be the risk register.

17:31 And just to stress this, the risk register is a very live document in your project. It's not something you do once pet yourself on the back and then put it away and store it. It's not.

17:42 The risk register is a document that you were referring to all the time you're examining and re-examining.

17:48 Did you identify all the risks? Are there any new risks? Are there risks that have disappeared now? Was your analysis correct? Was it too optimistic? Too pessimistic? Well, your responses correct? Were your proactive ones put in place? Were your reactive ones all ready to go? And one of the other reasons I found to keep your risk register as a very live document. It's not just because of the technical information that it contains, but it also creates buy-in and understanding from project team members and understanding that you take risk management seriously on your project. So in summary, the quantitative risk analysis assigns an actual time or dollar value to risk using mathematical or statistical methods.

18:37 It's not usually done on all risks, and it's usually done after qualitative risk analysis with that prioritized list of risks.

18:48 So thank you very much.

18:49 This has been an introduction and overview to the perform quantitative risk analysis process and the PMBOK guide.