LOGICAL DECISIONS
Contents
- What is Logical Decisions?
- How does Logical Decisions help people think about their problems?
- Why is Logical Decisions a “prescriptive” decision making tool?
- Why do we need a tool like Logical Decisions now?
- Can you give an example?
- How many levels can you build into your goals hierarchy?
- Once you build your goals hierarchy, is your final decision already made for you?
- After assessing preferences is your decision making process complete?
- What is the value of this approach to decision making?
- How is Logical Decisions different from other software-based decision making aids?
- Can you give an example of this?
- Which benefits and features of Logical Decisions best capture customers’
interest? - How could the ability to perform Monte Carlo simulations be valuable?
- What advanced knowledge to you need to use Logical Decisions?
- Earlier you mentioned that Logical Decisions has uses in politics. Why politics?
- How does Logical Decisions help build consensus?
What is Logical Decisions?
Logical Decisions is an organizational decision making tool. It helps organizations address difficult problems by identifying the important differences among the possible choices. Logical Decisions captures differences by evaluating each alternative on a set of variables called “measures” and it the importance of those differences by incorporating value judgments about the relative importances of the measures. Logical Decisions provides several methods for capturing preference judgments, ranging from quick and easy to very sophisticated. Once the judgments have been captured, LDW can work through the implications of those judgments for the particular data and decisions at hand and identify the best alternative.
How does Logical Decisions help people think about their problem?
When people think about a decision, they don’t really start out with a defined hierarchy of goals, objectives and weights. For example, let’s say you want to make a rational choice about buying a sports car. In this case you may be thinking in amorphous terms like, “I like red, and I want a fast car,” etc.
Part of the usefulness of Logical Decisions is that it gives you a structure that lets you identify and organize all of your desired outcomes.
The process of defining this structure helps you to understand what you want in detail. In the jargon of decision analysis, Logical Decisions is a prescriptive decision making tool, as opposed to a descriptive, or normative tool. A prescriptive tool is one that
tries to amplify the ability of the unaided human decision maker to track and reason through information.
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Why is Logical Decisions a “prescriptive” decision making tool?
People don’t process multiple dimensions of information very well. They can only look at three or four aspects of a problem at once before the unaided mind gets confused. Instead of only having three or four things, you can now look at the whole broad spectrum of things and remember it all. That’s the paradigm, to take a complicated
messy problem and add structure to it, break it down into bite size chunks, solve the bite size chunks and put it all back again to get the overall answer.
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Why do we need a tool like Logical Decisions now?
Decision making today is simultaneously helped and cursed by an abundance of data. Whenever individuals, companies or government agencies have to make important decisions, there is never a shortage of data to help with the decision.
The problem today is not “Where do I get enough data to make an informed decision?” The real problem is “How can I make sense of the data to arrive at the best
decision?”
Logical Decisions for Windows helps by acting as a filter that not only helps you look at the data associated with your choices, but also to organize it in a way that is more useful than a simple database.
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Can you give an example?
In the real world, we might have to decide between competing vendors for a service agreement, or where to relocate a new company headquarters, or which military bases should be closed.
In our sports car example, your final decision might depend on a combination of criteria — say performance, quality and price. While price is a pretty simple issue to deal with, you might have lots of data that could be used to assess performance — top speed, miles per gallon, acceleration, etc. Likewise, quality might be a function of many different known and unknown elements.
Logical Decisions helps you to aggregate your data into something else — something that makes sense. In the sports car example, it lets you build an overall rating for “quality” and for “performance.” These ratings, in turn, help you rate car choices against your third factor: price.
Thus, Logical Decisions lets you build a pyramid structure for decision making. The raw data becomes the foundation beneath “quality” and “performance”. These rankings combine with price to form the tip of the pyramid, which is a ranking of actual choices between individual sports cars. By the way, the pyramid is called a “goals hierarchy”.
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How many levels can you build into your goals hierarchy?
There is no limit. In our example, you could structure it so that your performance rating is a function of a combination of raw data, plus several other ratings, which are themselves derived from objective data. It can extend as far as you need it to.
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Once you build your goals hierarchy, is your final decision already made for you?
No. You still have to tell the software which elements are more important. Is MPG more important than acceleration? At what price are you willing to sacrifice overall performance? This intermediate step is called “Assessing Preferences.”. LDW gives you seven different ways to assess your preferences. You choose the method that you are most comfortable with.
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After assessing preferences is your decision making process complete?
Yes and no. The final rankings are calculated on the fly, so, in that respect, they are finished. However, you may find that you need additional definition to your preferences in order to come up with rankings that make sense. That’s why Logical Decisions gives you many ways to visualize the chain that led to the ultimate rankings.
Part of this results process is to help you understand why the answers came out like they did. You use the results display to identify gaps, and come to an understanding. You have to understand and agree with why a particular decision came out the way it did. Your intuitions should match the rankings.
What is the value of this approach to decision making?
The big benefit is that you can take a lot of objective information about a certain aspect of a problem and aggregate it into an intermediate measure. Then do the same thing with several other aspects. In the end, you have a big overall picture that you can’t get by just staring at the numbers, or even by looking at scatter graphs, data clustering, tab analysis, or most other typical tools.
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How is Logical Decisions different from other software-based decision making
aids?
Any decision making process has a judgmental element concerning what considerations are most important. Logical Decisions is unique in the way it lets you explicitly put into an analysis what your preferences are. Logical Decisions lets you link your underlying data to a conclusion, via a clear set of preferences. This link is one of our big advantages over some of the competitors. There is a direct link, or audit trail that you can get between the preferential stuff and the raw data.
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Can you give an example of this?
Take horsepower. In the sports car example, Logical Decisions would have you work directly with horsepower numbers, whereas another product would make you convert that to a 1-10 ranking, or some other sort of abstract scale before you could proceed.
Logical Decisions lets you work with data in your terms, and not have to engage in too much abstraction, beyond the level that you choose to define. Why is it so important provide an audit trail from your data to your decision?
In the real world decisions are both complicated and political. Anything you can think of — like where to locate the next interstate highway — anything you think of is going to have constituencies who are battling back and forth to get their way. So any decision you make today needs a clear justification for why you are doing what you are doing — especially for political questions.
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Which benefits and features of Logical Decisions best capture customers’ interest?
The goals hierarchy that you can expand and collapse is very useful to people. In general, you could say that LDW offers the most sophisticated tools for preference assessment. Very few of our competitors give you a graphical, point and click way to
adjust weights.
Also the availability of the trade-off method, in which the software infers relative preferences from the choices you make between pairs of alternatives. Until Logical Decisions, this was only taught in universities. There was no tool out there to actually do it.
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How could the ability to perform Monte Carlo simulations be valuable?
Any problem that has uncertainty associated with it can benefit from LDW’s Monte Carlo simulation feature. For example, how do you make a rational sports car buying decision when you don’t know exactly what the resale value of your car is going to be? If you can estimate a likely high and likely low resale cost, Logical Decisions will use the simulation capability to understand how the uncertainty might affect the results..
Really the advantage will come when you are trying to combine several different aspects that have probabilities. You don’t know what the resale value is, you don’t know what the stopping distance is, etc. You can combine those and take a look at what the total uncertainty in desirability is.
What advanced knowledge to you need to use Logical Decisions?
You can use LDW without any advanced knowledge, but some knowledge does help. Knowledge about probabilities is good. While the math is taken care of in the program, you should probably be a numbers-oriented person. This is not really “touchy-feely” stuff. You should also be familiar with graphs and that sort of thing. It also helps if you have a passing familiarity with decision analysis, and that whole paradigm, and concepts of facilitation.
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Earlier you mentioned that Logical Decisions has uses in politics. Why politics?
Because it’s a perfect example of an environment that desperately needs better tools for making decisions, and for communicating the rationale behind them. In the old days, selecting a site for the new airport when sort of like this: your uncle owned this great piece of land, so that is where the guys in city hall would decide build the airport.
Now, these types of decisions — even ones that are made within a company — are much more open and above board. There really needs to be better justification and consensus building than before.
In a sense, Logical Decisions is not just a tool for making decisions, it is a tool for building consensus in a political environment. One of the ways the program really helps that is related to what we just talked about. It is often easy to get agreement about the objective data — what the numbers are. Most reasonable people can be talked into agreeing with that sort of thing. Then here is the stuff we don’t necessarily agree on, like “Should we worry when they say our air contains 27 parts per million of a particular chemical?” How important is that piece of data? These are areas for human judgment, and they are perfectly valid areas for disagreement.
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How does Logical Decisions help build consensus?
Whatever the concern is, Logical Decisions lets you separate out the objective and subjective elements, and to combine these aspects to arrive at an overall outcome. Often you will find out the best alternative really is best over a lot of different subjective viewpoints. So that no matter how you feel about it, it is pretty clear that the way it goes is this way.
I wonder if you could you use Logical Decisions to build consensus in public debate?
You would hope that if you were having some sort of public participation meeting, or viewing a presentation that they were covering in this sort of logical way, so it is sort of an interactive process where you are trying to get an opinions out of the public and incorporate them into your analysis, or process.
A lot of arguments happen in public meetings because one person is talking about subject A. “This project is great because of subject A.” Then the next person says it is bad because of subject B. Something like Logical Decisions could be used as a systematic tool that says subject A plugs in over here, and subject B plugs in over here and it is all part of the same big picture. Such a tool would help focus discussions and stop these sort of arguments where people are just going back and forth and not listening to each other.
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