The DPL update 9.00.15 is now available for download. This is the first generally available (i.e., non-beta) version of DPL 9 Fault Tree. While most of the changes relate to fault tree features and documentation, we also encourage DPL Professional, Enterprise and Portfolio users to apply the update.
This update includes the following fixes/changes/enhancements:
ENH: Accommodate long names better in cutset viewer
The DPL maintenance update 9.00.14 is now available for download. It includes the following fixes/changes/enhancements:
The DPL maintenance update 9.00.11 is now available for download. It includes the following fixes/changes/enhancements:
The DPL maintenance update 9.00.02 is now available for download. It includes the following fixes/changes/enhancements:
Decision analysis is most often used on high stakes, one-of-a-kind decisions. However, the same techniques and tools can be used to shed light on a variety of decisions, including those where the stakes are, say, "A BRAND NEW CAR!!!".
The vast majority of DPL users are also heavy Excel users, and they sometimes ask us about the pros and cons of the various Excel versions. Oftentimes they have no choice in the matter -- the corporate IT department is rolling out a new version of Office, and they just need to know what they're in for. DPL has been closely integrated with Excel from the earliest days, so we definitely have an opinion. This post summarizes the highs and lows of recent Excel history, from the perspective of power users doing analytical work.
I'm going to use a light-hearted example to introduce a simple but powerful new feature in DPL 9: Perform and Continue. If you've used DPL, you probably know about the perform feature, a way of creating "perform links" which reduce the redundancy in a decision tree. Often when building an asymmetric tree there are sections which are repeated -- some groups of nodes are the same on different paths.
The DPL maintenance update 8.00.14 is now available for download. It includes the following:
BUG: Invalid node data after changing a conditioned value node to a discrete chance node (#2010)
BUG: Spurious "too few initializers" error running a model with init links (#2001)
BUG: DPL may stop responding compiling a model with hundreds of DDE linked nodes (#1997)
CHG: Default stack size increased to 16M (necessary for some very complex model structures)
Ears always tingle in the decision analytics community when a mainstream publication talks about the things we do, and last Friday, the stimulus was provided by this article in the Wall Street Journal on Monte Carlo. Usually I reluctantly read these pieces fully expecting to cringe at the reinforcement of misconceptions and/or zombie fallacies, but in this instance I have to admit I was positively surprised.
In an earlier post I argued that the #1 cause of downward project revisions in portfolio analysis is a phenomenon called "winner's curse", whereby the error in estimating project values, together with screening criteria, results in more negative surprises than positive ones. In this post, I'll talk about the #2 reason (which might be the #1 reason in some portfolios).
The management science news of the week is that Howard Raiffa has died.
Raiffa was one of the founders of the field of Decision Analysis, and indeed of Game Theory and Bayesian Statistics.
In this space we often write about the do's and don'ts of probability assessment and working with uncertainty in general. One of the most fundamental don'ts is that you should not use words to define probabilities. You should more than avoid it, you should never do it. A 15% chance of something happening is exactly that: a 15% chance. Write it as 0.15 if you like, but don't call it a "moderate risk" or say it "probably won't happen".
A topic of considerable lament in portfolio management circles is the frequent downward revision of project valuations. Anecdotally, it just seems like news tends to bring the project value down more often than it pushes it up. Senior management often views this as something sinister, a sign of deception or flawed execution: "Last year you bozos told me this was a blockbuster!".
In our tireless commitment to advancing decision quality through superior analytic tools, we at Syncopation are always working at the leading edge of applied decision science, striving to be the first to bring you innovations that will change your practice for the better.
The limits of conventional decision trees
Have you done work in decision analysis that was truly exceptional, either in its quality, impact or degree of benefit to the stakeholders? Why not share your experiences with your peers and be recognized for your contribution?
The Decision Analysis Society of INFORMS conducts an annual competition to recognize outstanding use of decision analysis in solving actual real world problems.
There's a handy feature in DPL for displaying risk profiles in an intuitive way: the "decumulative" switch. Decumulative doesn't sound all that intuitive, but it is when you see it. Here's a typical risk profile displayed in decumulative form:
The DPL maintenance update 8.00.12 is now available for download. It includes the following:
In most DPL models, decisions are made to maximize or minimize some quantity, and they can and should be left unconstrained. You can never have too much NPV, for example. However, some decision problems require making tradeoffs among several decisions where not all possible decision policies (i.e., combinations of decision alternatives) are feasible. For example, your company may only be able to launch one or two new products a year.
In some sports leagues, particularly those with youth competitors, there is a Mercy Rule by which a game is ended early if one team has built up an insurmountable lead. For example, in little league baseball the rule may be to end the game if one team is ahead 10 runs after 4 or more innings. While the team that's behind may theoretically have a chance, it's much more likely that grinding out the rest of the game would only humiliate the losing team and result in everyone getting home late on a school night.