Dennis wrote: "...I would use the trigen if (big if) I thought the ranges given were understating the risk - my respondents were risk accepting, giving optimistic estimates. I would use triangle if I thought they fully understood/appreicated the risk(s)." Personal approach to risk varies - some are timid, others reckess. Part of my role is to moderate extremes.
That's sort of the big problem with Monte Carlo risk simulation packages, isn't it? Unlike you, most of us don't know the future. We have to guess. I like to think we make informed quesses based on experience, but they're still guesses. Nobody knows what the objectively "correct" number is, so if we run it on one default and don't like the answer, we tweak it until we get the answer we wanted all along. In other words, we decide what number we want and then use pseudo-science to justify our gut instincts. it's the classic example of "garbage in, gospel out". Maybe in your world, not mine. They may not like the answer, but they are unlikely to manipulate it. I expect them to bounce the result against their gut. I have a healthy respect for years of experience and practiced judgement. If the result doesn't 'smell right', I'd look at our assumptions. Review is part of the process. Pseudo-science?
Monte Carlo systems can provide valuable information if:
There is good historical data showing activity durations and effort on similar work, and: The function of the estimate.
We map the distribution curve to each specific activity. PRA does this easily, not sure what software you're using.
They either include no lags or, as with Spider Project, the lags can be volume lags that can be varied according to the simulated distribution. Post-FEED schedules should have few lags. Pre-FEED plans have few activities - lags are managable. PRA seems to handle lags well.
But almost no one does any of that -- it’s too much work. Instead, they pluck three estimates out of thin air and then they run the simulation using a default. Really? Out of thin air? We don't ask people off the street. Respondents have knowledge, experience, judgement. And if they don't like the results fromthat default, they use another one. Not my experience. And, as Dennis suggests, the whole purpose is to satisfy a customer who knows nothing about the process but is impressed when told: "It must be accurate -- it came out of a computah!" Don't think I ever suggested this. My clients are more sophisticated than this, are you projecting?
I hesitate to suggest this, given your penchant for fabrication, but if you have twenty minutes this YouTube video might explain my approach to post-FEED schedule risk assessment - Contigency.
Dennis wrote: "...I would use the trigen if (big if) I thought the ranges given were understating the risk - my respondents were risk accepting, giving optimistic estimates. I would use triangle if I thought they fully understood/appreicated the risk(s)."
That's sort of the big problem with Monte Carlo risk simulation packages, isn't it? Nobody knows what the objectively "correct" number is, so if we run it on one default and don't like the answer, we tweak it until we get the answer we wanted all along. In other words, we decide what number we want and then use pseudo-science to justify our gut instincts. it's the classic example of "garbage in, gospel out".
Monte Carlo systems can provide valuable information if:
There is good historical data showing activity durations and effort on similar work, and:
We map the distribution curve to each specific activity.
They either include no lags or, as with Spider Project, the lags can be volume lags that can be varied according to the simulated distribution.
But almost no one does any of that -- it’s too much work. Instead, they pluck three estimates out of thin air and then they run the simulation using a default, And if they don't like the results fromthat default, they use another one. And, as Dennis suggests, the whole purpose is to satisfy a customer who knows nothing about the process but is impressed when told: "It must be accurate -- it came out of a computah!"
Fraternally in project management,
Steve the Bajan
Member for
18 years 1 month
Member for18 years2 months
Submitted by Waleed Mahfouz on Tue, 2015-04-21 14:12
For me, the difference is whether or not my respondents are risk adverse, risk accepting, or neutral. Of the two possible distrubutions you cite, I would use the trigen if (big if) I thought the ranges given were understating the risk - my respondents were risk accepting, giving optimistic estimates. I would use triangle if I thought they fully understood/appreicated the risk(s). Since it is relatively easy to change the risk distributions in the layout, I might run both just for grins. I would run BetaPert to model the risk adverse case.
Member for
18 years 6 monthsYou have my sympathy.
You have my sympathy.
Member for
20 years 7 monthsHuh. That there's pretty
Huh. That there's pretty rude, in't?
Dunning-Kruger is a sad thing, and pretty much incurable.
Cheeri-O.
Steve the Bajan
Member for
21 years 8 monthshttp://www.mediafire.com/view
http://www.mediafire.com/view/s8nm7i7ju64kv9v/Risk_-_PDF_-_The_best_fit…
http://www.mediafire.com/view/xg9mn7f9u20j0m5/Risk_-_PDF_-_Most_appropr…
Member for
18 years 6 monthsSteve; Where to begin. Dennis
Member for
20 years 7 monthsDennis wrote: "...I would use
Dennis wrote: "...I would use the trigen if (big if) I thought the ranges given were understating the risk - my respondents were risk accepting, giving optimistic estimates. I would use triangle if I thought they fully understood/appreicated the risk(s)."
That's sort of the big problem with Monte Carlo risk simulation packages, isn't it? Nobody knows what the objectively "correct" number is, so if we run it on one default and don't like the answer, we tweak it until we get the answer we wanted all along. In other words, we decide what number we want and then use pseudo-science to justify our gut instincts. it's the classic example of "garbage in, gospel out".
Monte Carlo systems can provide valuable information if:
But almost no one does any of that -- it’s too much work. Instead, they pluck three estimates out of thin air and then they run the simulation using a default, And if they don't like the results fromthat default, they use another one. And, as Dennis suggests, the whole purpose is to satisfy a customer who knows nothing about the process but is impressed when told: "It must be accurate -- it came out of a computah!"
Fraternally in project management,
Steve the Bajan
Member for
18 years 1 monthThe best PDF to represent
The best PDF to represent activities durations is Lognormal distribution
Please refer to the following paper
Member for
18 years 6 monthsClaire:For me, the difference
Claire:
For me, the difference is whether or not my respondents are risk adverse, risk accepting, or neutral. Of the two possible distrubutions you cite, I would use the trigen if (big if) I thought the ranges given were understating the risk - my respondents were risk accepting, giving optimistic estimates. I would use triangle if I thought they fully understood/appreicated the risk(s). Since it is relatively easy to change the risk distributions in the layout, I might run both just for grins. I would run BetaPert to model the risk adverse case.
Hope this helps.