Decision Tree

How the DPL Software Stacks Up Against Other Decision Tree Software Tools

As a market leader in decision analytic tools, we confidently stand by our claim that DPL is the most powerful, full featured application for decision tree and influence diagram modeling on the market today. DPL offers a dedicated, standalone graphical modeling interface for performing decision and risk analyses, Monte Carlo simulation, and Real Option valuation. The tool's flexibility and intuitiveness allow you to model the characteristics specific to your decisions with a precision unmatched by our competitors.

WSJ on Monte Carlo

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.

The #2 Reason Why Project Values Get Revised Down

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).

DPL 9 -- The Tool for Die-hard Decision Tree Fans

Are you a die-hard decision tree fan? Well then you've landed on the right blog. Let me first say that we here at Syncopation (publishers of class-leading decision tree software, DPL) have always prided ourselves on the fact that DPL's modeling interface offers a unique synergism of a Decision Tree and an Influence Diagram. We still hold those sentiments, but during the development of the latest DPL release we came to the realization that for certain users and/or decision-problems the Influence Diagram might be better off taking a backseat.

A Gentle Introduction to DPL Constraint Functions

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.

What is Hybrid Discrete Tree Simulation and When Should You Use It?

How do you tackle a model with 318 paths? Well, whatever you do, you better not do it 318 times! Even if you were able to calculate a billion paths a second, it would still take 30,000 years or so.

The model we recently shared as part of the March Madness promotion was solved using Hybrid Discrete Tree Simulation, one of DPL's decision tree evaluation methods.

Decision Trees without Decisions? What's that About?

It's surprising to me how often I encounter "decision models" that don't actually include any decisions. I'll answer the question suggested by the title straight away: I think it's a mistake not to include an explicit decision, for reasons that will follow.

Nobody ever wants to admit that their model is a worry analysis, a pointless forecast, an anxiety management device, etc -- they will always say there is a decision. The decision is implicit, of course, can't you see it?


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