Methods and Technologies
Information for the professional analysts ...
So, we have number of multicrireia alternatives to compare.
The task can be solved in two steps:
Step 1. We create Plan of analysis
Step 2. We run the Analysis
Let's take a close look at these steps.
1. We create Plan of analysis. This Plan includes the hierarchical structure of parameters: up to seven
"artificial" General parameters describing the general features of alternatives
(for example Safety, Efficiency etc.) and unlimited number of the parameters influencing every
General Parameter.
So, we have three levels of hierarchy: the purpose of analysis on the top, General parameters at the second level
and parameters of the alternatives at the third level.
This structure allows us not just estimate alternatives 'in general', but also analyze the most important general
features of every alternative, and even we can see the influence of every parameter at the final result.
We have to assign the weight coefficient to every parameter and every General parameter. It is a numeric coefficient
showing power of influence of this element at the element of the higher level of the hierarchy.
You can assign the weight coefficient directly in the numeric form, or they can be calculated automatically as the result
of pairwise comparison procedure: the weight coefficients are calculated as eigenvector of the matrix of pairwise comparisons 
see the Analysis of Hierarchies by T. Saaty. During this procedure user just has to answer number
of questions like "Which of these two parameters is more important?"
We also have to assign an Utility Function to every parameter in the Plan. The Utility function maps the values of
parameter to the scale between 0 and 1. Utility Function allows prioritize different values of the Parameter.
2. So, we have created Plan of analysis  the structure which reflects our understanding of the problem, our
preferences and requirements. Now we can run the analysis for the selected alternatives.
2.1 At the first phase the system calculates ratings of the alternatives separately for every General parameter.
We use for this purpose the most popular 'simple weighing' method:
R_{ij }= S_{k} W_{kj} * U_{kj}
, where R is rating of the alternative "i" on General parameter "j",
W is the weight coefficient of the parameter "k" of the alternative "i" in General parameter "j",
U is the value of the Utility function of the parameter "k" of the alternative "i" in General parameter "j".
In other words, we just sum up the values of the Utility function for every parameter multiplied by corresponding
weight.
2.2 At the second phase of the analysis the system calculates final ratings of the alternatives using the same
'simple weighing' method. And now we use the weight coefficients of the General parameters and the calculated ratings of the
alternatives as values of the Utility function for every General parameter. E.a. the final rating of the alternative is
a sum of its rating on every General parameter multiplied by corresponding weight of the General parameter.
Well, our task of comparison of multicriteria alternatives has been solved. We calculated the final ratings for
every alternative and individual rating for every General parameter. This approach allows us not only estimate
alternatives "in general", but understand their weak and strong aspects.
You should remember that 'simple weighing' method belongs to "compensatory" methods. It means that, for example,
some alternative with rather weak main parameters may get a very high rating due to its good values on the minor
parameters.
To eliminate this compensatory effect the system provides Pareto analysis of the alternatives on all parameters and on
a subset of the most important parameters. So in previous example the results of the Pareto analysis will show you
that in spite of high rating this alternative is dominated by some other alternatives on a subset of the most important
parameters. This allows you to get rid of the serious mistakes in the decision making.
And at last you can run a Benefit / Cost analysis of the alternatives based on the results of the multicriteria analysis.
This procedure provides you with the ratings of the alternatives calculated from their pairwise comparisons on the Benefit
/Cost chart.
The Estimation and Choice system allows you to process even incomplete data  if no more than 50% of values for some
parameter are missing, the missing values will be restored as average from the existing values.
The group model
ESTIMATION & CHOICE supports the group decision making and provides tools to coordinate group of experts.
Click the link Group model and learn the theory behind the group decision making.
