Episode 253: Quantifying the Qualitative Risk Analysis (Free)




The Project Management Podcast show

Summary: Play Now: This episode is sponsored by The Agile PrepCast for The PMI-ACP Exam: This interview with Ricardo Viana Vargas was recorded at the PMI Global Congress 2013 North America in New Orleans. At this year's PMI Global Congress Ricardo Viana Vargas (http://www.ricardo-vargas.com) proposed a mathematical process to turn the results of a qualitative risk analysis into numeric indicators to support better decision making regarding response strategies. It was titled "Adopting the Quadratic Mean Process to Quantify the Qualitative Risk Analysis". Or in short... Quantifying the Qualitative Risk Analysis. We review the five-level scale for probability, the mathematical "quadratic mean" process involved to calculate the numerical exposure, and how you can quite easily apply this on your own projects. Below are the first few pages of the transcript. The complete transcript is available to Premium subscribers only.  Podcast Introduction Cornelius Fichtner: We are back here at the PMI Global Congress 2013 in New Orleans and with me is Ricardo Viana Vargas. Podcast Interview Cornelius Fichtner: Hello Ricardo! Ricardo Vargas: Hi! Hi Cornelius. How are you? Cornelius Fichtner: I'm very well, thank you! How is the congress going for you? Ricardo Vargas: Oh yeah, very well, very well. For me, it's a great experience because the first congress I attended was in 1998 long bit. And so far, 15 congress in a row and I have never missed it once. So it's very nice. And now you see people that you met 10 years ago and it's a great opportunity for me to meet people networking, talk to people. Now, so I have the great presentations we are having here. Cornelius Fichtner: And I did not attend last year and I don’t recognize anybody anymore it seems. Ricardo Vargas: It's interesting. There is some core group that is always here. There is maybe a floating group that comes… Cornelius Fichtner: …and goes. Ricardo Vargas: Comes and goes, come not so often. But for me, it's great to be here. Cornelius Fichtner: So we are standing here in the middle of the exhibition hall and you will probably hear dear listeners in the background. Yes, there are still people here. There are still people drinking coffee being served. Exhibitors are showing off their wares and we are in the middle of this hustle and bustle and we want to talk about adapting the quadratic means process to quantify the qualitative risk analysis. And yes when I read this for the first time, I thought: "Oh my God! Why did I ask Ricardo to talk about this topic?" Because it seems extremely complex to convey in an audio-only podcast. But luckily a friend of mine, Josh Nankivel, attended your presentation this morning. And I can tell you, he liked it. So it was a good presentation you gave. And he said: "You know, it's not all that complex." Tell us about it. Ricardo Vargas: Yes, yes, of course. It's very hard to analyze things using the title. So when I created this concept, I was concerned about how we can translate some qualitative into some numbers. And then it was very hard for me to put the title in the proper way. The root of the concept, it's a way of doing the average of the impact. So this what became this title quite complex. But the concept behind is very, very simple. You can use an Excel spreadsheet and do it in 10 minutes. Cornelius Fichtner: Okay. Ricardo Vargas: In 10 minutes. So there is no rocket science behind this. Cornelius Fichtner: Okay. Just as a reminder for me and the listeners, qualitative risk analysis, high, medium, low. Quantitative, you have a dollar value assigned to it, right? Ricardo Vargas: Yes. Cornelius Fichtner: And you say, this will cost us this much. Ricardo Vargas: Yeah, that's perfect. Let me explain to you: What is the challenge when we use these both methods? Of course when you think about quantitative risk analysis, you see more deep analysis. You get into dollar value. You can have a more valuable approach. But the challenge is that it's mu