This document provides a glossary and tutorial for building hierarchical pairwise comparison models in Super Decisions V3.0 software. It explains key terms like alternatives, criteria, judgments, and priorities. It then walks through creating a simple three-level hierarchy to choose the best car out of three alternatives based on criteria of prestige, price, miles per gallon, and comfort. Screenshots and step-by-step instructions demonstrate how to construct the decision network and enter pairwise comparison judgments to derive final priorities for a recommendation.

1. Super Decisions V.3.0
Tutorial 1 – Building Hierarchical Pairwise Comparison Models

2. Glossary
 Alternative
 an alternative is a node representing one of the
choices or outcomes for a decision model. The
alternatives are grouped together in a single
cluster.
 Cluster
 a cluster is a collection of nodes that have some
logical relationship together in a frame.
 Comparison Group
 consists of a parent node linked to a group of
children nodes that will be pairwise compared with
respect to the parent node for importance,
preference or likelihood.
 The children nodes must be in a cluster together;
the parent node may be in a different cluster or in
the same cluster as its children nodes, and may
have children groups in several clusters.
 Criterion
 a criterion is a decision factor, something that must
be considered when making a decision. A criterion
is represented by a node in a SuperDecisions model.

3. Glossary
 Goal
 a goal in a model is a single node in a cluster with
links only “from” it.
 In hierarchical models there should be only one
goal. In hierarchies criteria nodes are linked from
the goal and judgments are made about their
importance with respect to the goal.
 Hierarchy
 In a hierarchy the goal is at the top, the criteria
are in a separate cluster connected from the goal,
the subcriteria are in clusters connected from a
parent criterion.
 Clusters are often arranged hierarchically with the
goal cluster at the top of the window, the criteria
cluster below that, the subcriteria clusters below
that and the alternative cluster at the bottom.

4. Glossary
 Inconsistency
 if element A is preferred to element B by 2
 and element B is preferred to element C by 3,
 then element A should be preferred to element C by their
product, 6.
 If it is not 6, then there is inconsistency.
 All such triples of judgments for a comparison group are
checked for consistency and SuperDecisions gives a
measure of the inconsistency as a decimal number that
should be less than about 0.10.

5. Glossary
 Judgments
 a dominance judgment is entered for each pair of children nodes in a
comparison group using the Fundamental Scale: 1-Equal, 3-Moderate, 5-
Strong, 7- Very Strong, 9-Extremely Strong,plus numbers in between for
intermediate judgments, as well as decimals for finer distinction.
 The judgment modes in SuperDecisions are:
 Graphical – use ratios of bars or relative areas in a circle
 Verbal– use a continuous sliding scale on which the words from the Fundamental
Scale are indicated
 Matrix– enter the dominance judgments as numbers in a table or matrix for each
pair
 Questionnaire–use a questionnaire form in which the appropriate whole number
from the Fundamental Scale is selected to indicate dominance for each pair
 Direct–this mode allows the direct entry of priorities for a group of children nodes;
numbers which do not add up to 1.0 can also be entered and they will be
normalized to give the priorities

6. Glossary
 Link or Connection
 a link goes from one node to another. A node most often
has links to several other nodes.
 Model
 a SuperDecisions model may be a simple network
contained in a single window, or a complex model of 2 or 3
or more levels consisting of a main network with attached
sub-networks linked together.
 Network
 any collection of clusters, nodes, and their connections in
a single window (a window is a box or frame). A network
may be either a hierarchy or a feedback structure.

7. Glossary
 Node
 a node is an element or factor in a decision such as the
goal, a criterion, a subcriterion, or an alternative. Nodes
are smaller rectangular frames inside a cluster frame.
 Normalization
 mathematical procedure of summing a group of numbers
and dividing each by the sum so that the resulting numbers
will sum to 1; the numbers are then said to be normalized
to 1. Priorities are sets of numbers normalized to 1. To
obtain priorities from any group of numbers apply the
procedure above.
 Priority
 Priorities result from making a set of pairwise comparison
judgments on a group of children nodes. The priorities sum to 1.

8. Glossary
 Sensitivity
 To perform sensitivity with respect to a criterion in a
hierarchy means to vary the priority of that node,
maintaining the same relative proportion of the other
nodes with respect to the goal, and see how the outcome
changes.
 Supermatrix
 the judgment data for a model is stored in supermatrices
(think of an Excel spreadsheet).
 Synthesis
 after judgments are made the model is synthesized to give
the best alternative; that is, the one with the highest
synthesized priority.

9. SuperDecisions Opening Screen

10. Main Menu Commands
 File
 Usual File commands, Export Supermatrices to .txt files, Print model report,
Old files have .mod extensions, new files have .sdmod extensions
 Design
 Create and delete subnetworks, make node connections (alternatve method),
work with formulas for combining results from subnets.
 Assess/Compare
 Perform pairwise comparisons, enter direct priorities, improve consistency.
 Computations
 Synthesize results, display supermatrices, perform sensitivity, sanity check (to
look for incomplete comparisons.
 Help
 About SuperDecisions version information, link to online Help, Sample models
and tutorials

11. Relative Decision Model
 This tutorial will show how to use the SuperDecisions
software to create a simple AHP (Analytic Hierarchy Process)
decision model for selecting the best of three cars.
 The alternatives are pairwise compared against the criteria,
thus it is a “relative” model

12. A Three-Level Hierarchy to
Choose the Best Car
Goal
Buy Best Car
Prestige Price MPG
(Miles per
gallon)
Comfort
Acura TL Toyota Camry Honda Civic

13. The Cars
 Acura TL
 Cost $30,000-$35,000
 Miles per Gallon 20/29 (City/Hwy)
 Prestige is very good
 Comfort is excellent
 Toyota Camry
 Cost $22,000 - $28,000
 Miles per gallon 22/30 (City/Hwy)
 Prestige is good
 Comfort is good
 Honda Civic
 Cost $16,000 - $20,000
 Miles per gallon 29/38 (City/Hwy)
 Prestige is medium to low
 Comfort is medium to low

14. The Decision Hierarchy as it appears in the
SuperDecisions Software
Custer
All links are
from node to
node. A link
from one
cluster to
another is
automatically
created if some
node(s) in a
cluster are
connected to
some node(s)
in another
cluster
See the SuperDecisions model: Tutorial_1_Acura_Relative_Model.sdmod
Get it from Help>Sample Models>Tutorial Models
Cluster
Node
Link

15. Building the Decision Hierarchy
 File>New, choose Simple Network and enter a name for your
model. It will be saved in your documents folder by default –
or select another folder. (Alternatively just start building on
the blank canvas, select File>Save As and enter a name for
the .sdmod file).

16. Clicking the + menu icon to create a new cluster will
open the Create/EditDetails panel where you will enter
its name and description.
Click “+” Menu Icon to Create
a new Cluster

17. Enter Cluster Details
1. Click + menu icon to
open Create/Edit
details panel for new
cluster information.
2. Enter Name
3. Enter Description
4. Click Save to create
cluster
5. Mouse over cluster title
bar for popup of
description

18. Add Goal Node to Goal
Cluster
 Click “Add Node” Enter node name and description in Create/Edit node
details panel.

19. Add the Rest of the Clusters
and Nodes
Click on the
minimize icon to
minimize or
expand.
Note: Prefacing Cluster and
node names with numbers
allows you to control their
order in the supermatrices as
they are appear in
alphabetical order there.
IMPORTANT!
The cluster holding the
alternatives must be named
Alternatives to show results in
the Synthesize results
command (prefacing with a
number is OK).

20. Connect Goal Node to
Criteria Nodes
1. Click the
Goal Node
to select it.
2. Open the
Make/Show
Connections
panel
3. The Goal
appears as
the parent
(from) node
4. Click the
criteria
nodes to
connect it to
them.
Note: If you have not clicked a parent node to select it, the field will be blank.
Click it and choose the node you want for the parent.
Note: Click below the panel to firmly record (turn blue) the last checked box.

21. Connect each Criterion Node to
each Alternative Node
A shortcut method is demonstrated here to make connections

22. Making Multiple Connections
at Once

23. Putting Subcriteria into a Hierarchical
Model
 Create separate
clusters for the
subcriteria of the
criteria that will
have subcriteria.
 Price has
subcriteria of
initial cost and
maintenance,
which then
connect to the
cars.
 Comfort has
subcriteria of Ride
and Driving
Performance
which then
connect to the
cars.
 Prestige and MPG
have no
subcriteria and
connect directly
to the cars.

24. Remove Unintended Loops
A loop will appear on a cluster when a node or node(s) are
connected to other node(s) in the same cluster.

25. Show Nodes a Parent Node is
Connected To
Click on Make/Show Connections icon, then click on a node to select it.
The nodes it is connected to will have red outline borders around them..

26. Unweighted Supermatrix before
Making any Pairwise Comparisons
All the nodes connected from a parent node have priorities in the column below that
node; for example, the nodes in the Criteria cluster are connected from the Goal
node and each is equally weighted at 0.25 before entering judgments. The priorities
of the nodes in each cluster in a column sum to 1.0. Supermatrices are square; there
is a column and a row for each node. The nodes are grouped by the cluster they are
in.
Cluster names
Node names
Priorities of
the Criteria
nodes
Tip: To show the unweighted supermatrix from the menu select Computations> Unweighted
SuperMatrix> Graphical. To export as a .txt file select File>Export>Unweighted SuperMatrix.

27. Hiding the Information Panel
and Minimizing Clusters

28. Moving to Making Judgments
 Click on the Goal Node to select it.
 Click the Judgments tab to enter the assessments mode
where you make pairwise comparisons.
• The Questionnaire Mode opens by default on a new
model with the selected node (Goal node in this case) as
the parent node. On other models it will open on the last
mode used for that node.

29. 5 Pairwise Comparison Modes

30. More About Judgments
Choose tab indicating whether
comparing nodes or clusters
(cluster comparisons not possible
in hierarchies)
Chooser parent node for
comparison
Choose cluster containing children
nodes to be compared with
respect to parent node
Restore button will bring back
original judgments if you revisit
and make changes to original
judgments for this group.
There are 5 possible modes for entering assessments.
Judgments entered in one mode will appear as the
equivalent judgment in any other mode except for the
questionnaire that rounds off judgments from other
modes.
All judgements are automatically
saved when moving back to the
network tab or to another set of
comparisons.

31. Example of a Pairwise comparison Matrix in
SuperDecisions and in traditional AHP
 Only 3 judgments
are necessary
 In the AHP Theory
view you see 9 judgments
Acura Civic Camry
Acura 1 8 4
Civic 1/8 1 1/4
Camry 1/4 4 1
Diagonal elements are always 1,
so they do not need to be
displayed. The elements below
the diagonal are always inverses
of the judgment in the reciprocal
cell above, so they do not need to
be displayed (e.g. 1/8 8).
aij = 1/ aji
AHP reciprocals are shown in red in
SuperDecisions. For example, 4.0
means for 1/4 and a red arrow
points to dominant element (double
click to invert)..

32. Start Making Judgments
1. Left-click on Goal node to select it then click on the Judgments tab to get to the
Questionnaire assessment mode.
2. Switch to the Matrix mode by clicking on the matrix tab. Change the comparative phrase
1Prestige is ????times more Preference than 2Price by left-clicking on it and choosing
importance.
.
Note the copy to clipboard commands. You can then paste into

33. Enter Judgments (Matrix Mode)
1. Enter judgments in cells by typing numbers from the Fundamental 1-9 Scale.
The direction of the arrow indicates which criterion is more important. Double-
click arrow to change the dominant element. In the phrase above the matrix
the first element is the dominant one. Up arrows are red and point to the
column element, side arrows are blue and point to the row element..
2. The current parent node is the Goal node and the Criteria nodes are being
compared with respect to the Goal for importance. The inconsistency should
be less than 0.10. Inconsistency=0.07685; Derived Priorities
Mark completed
and move to next
comparison

34. Changing Comparison Word in
Verbal Phrase
1. Original Comparison phrase that appears for (Prestige, Price)
2. Better to use the word “Importance” for
comparing criteria with respect to the goal, so left-
click on Preference and choose Importance
3. Importance is now the comparison
word in the verbal phrase

35. Show Completed Judgments
Mark Judgments set complete so
clicking the Make/Display
Connections icon and selecting the
goal will show a red outline around
cluster with completed judgments.

36. Improve Consistency
(available only from Matrix Mode)
 Click on the Inconsistency button (at top left corner of matrix)

37. Improve Consistency
• Choose Basic Inconsistency Report.
• The first cell, Prestige versus MPG, has a Current Value of red 3 in it meaning that
MPG are more important than Prestige (see previous view of matrix), but the Best
Value of 1.05 (in blue) means that optimally in view of the other judgments Prestige
should be a little more important than MPG and if you revise the judgment to a blue
judgment of 1.05, the New Inconsistency value would be 0.01.
• To return to that cell in the matrix, left-click on either the Current or Best Value cell.
You can use the suggested value, or some other value, or leave it as it is and go to
row 2. The second most inconsistent judgment is MPG versus Comfort.
• If you have changed the value in the first row, you must return to the Matrix mode to
update the table and start the inconsistency improvement process over again.

38. Matrix after Improving
Judgment of MPG vs Prestige
New judgment Better Inconsistency of 0.01.
Although the original inconsistency of 0.07 passes the 0.10 test, it can be improved.

39. Newly calculated Priorities
now appear in unweighted
Supermatrix

40. Other Comparison Modes
Graphical
Verbal Tracking triangle – shows
which cell you are on in the
corresponding matrix view. Click
the next cell to move to the next
judgment.
Click and drag on circle
(NOT the bars) to change
judgment. Such judgments
usually involve decimal
values. This is okay.
Click button to invert dominance. You
want to end up with the dominant
element, the Acura, better on Prestige,
listed first.

41. The Questionnaire Mode
The Assessment/Compare command opens the questionnaire mode by default. Choose the judgment
on the left or right side of the zero on the questionnaire line that is nearest to the more important, more
preferred, or more likely, node. Here price is more important than prestige. If necessary, and it is here,
change the verbal phrase so it reads correctly, as explained below.
In the view above the questionnaire opened with the wrong dominance word,
“moderately to strongly more Preference”. Left click on the dominance phrase itself
to get the menu of possible phrases and select the most appropriate word.

42. Direct Data Assessment Mode
Click the Invert box when the priorities are inversely related to the data. For
example if you enter actual dollar cost for the three cars for Price data, the
priorities should be inverted as the lower cost is more preferred.
Enter direct data in the Direct mode. It may be already normalized, as
shown here, or it may be numbers representing costs or distances which
the software will normalize to get the priority vector
Important! Click <Enter> or move
away from last judgment entered
to make sure it has registered

43. Weaknesses of using Direct Data
 Data may not be as good as judgments in determining your personal
priorities. It would usually be better to use your judgment about
what the price of a car means to you rather than use the the data
directly. Suppose you are a poor college student. See the two
results below. Which do you think more accurately reflects the
reality?
Comparing cars for price using judgments Priorities from judgments Priorities from data

44. Compare Cars for Prestige and Price
Prestige Comparisons
Price Comparisons

45. Compare Cars for MPG and Comfort
MPG Comparisons and Priorities
Comfort Comparisons and Priorities

46. The Supermatrices
1. Computations>Unweighted Supermatrix: matrix
containing the priorities from the pairwise
comparisons.
2. Computations>Weighted Supermatrix: The
unweighted supermatrix components have been
multiplied by cluster weights. In a hierarchy
there are no cluster weights and the weighted
supermatrix is the same as the unweighted.
3. Computations>Limit Supermatrix: The limit matrix
is obtained by raising the weighted supermatrix
to powers until it converges to give the answer.

47. The Unweighted
Supermatrix
after all Judgments
Completed
The priorities from the pairwise comparison sets are inserted into the column of the parent node.
•For example the priorities of the criteria are in the Goal Node column.
•The priorities of the cars with respect to the criteria are in the relevant Criteria columns

48. Limit Supermatrix
Final results are obtained from the Limit Supermatrix. The limit supermatrix (for a
hierarchy) s obtained in the software by raising the unweighted supermatrix to
powers until it goes to zero, then backing up one power. The Limit Supermatrix in
displayed by the software is the sum of all the powers. It is done this way in order
to display the priorities of all the nodes with respect to the goal.. To obtain the Limit
Supermatrix select Computations>Limit matrix>Graphical.
• The raw values come from the Limit Supermatrix; they are the results, and the
priorities of the alternative cars are obtained from them..

49. Exporting Supermatrices
The following files may be exported as .txt files using the File>Export
command:
Unweighted Supermatrix
Weighted Supermatrix
Limit Supermatrix
Cluster Matrix
Import into Excel using the File>Open command . Be sure to select All Files
for type of file with the Open command so the .txt file you exported will
appear. Click yes through the wizard to open in Excel.

50. Synthesize to get Overall Results
 Select Computations>Synthesize to get the results,
the Normals, that are the priorities of the
alternatives. You MUST name the Alternatives cluster
with some variation of the word alternatives to get
an answer.
Acura TL 0.344
Toyota Camry 0.200
Honda Civic 0.456
The Raw values come from the
Limit Supermatrix. The
Normalized values are obtained
from the Raw values by summing
and dividing each by the sum.
The Ideals are obtained by
dividing each Normals value by
the largest Normals value.

51. Reports
 The Computations>Full Report command and the
File>Print command both generate the same HTML file
of reports about the model. You may use the Print
Preview version, or save as an .html file. The report
gives the names and descriptions of the nodes and
clusters and important priorities.

52. Sanity Check
 The Computations>Sanity Check will reveal incomplete
comparisons and duplicate goals, among other things.
Each time you finish a set of comparisons you must mark
it complete before proceeding to the next set.
Unintentionally skipped comparisons will also be caught
by the Sanity Check.

53. WARNING! No Alternatives Found
This error message will appear if there is no cluster named some
version of the word alternatives, IN ENGLISH, but for example,
3alternatives is an acceptable name. The SuperDecisions
software uses this word to find for which nodes it should deliver
synthesized priorities extracted from the raw values in the limit
supermatrix. To obtain synthesized priorities for any other nodes
go to the limit supermatrix, get the raw values, and normalize
them yourself. The Normals are the raw values divided by their
sum. The Ideals are the raw values divided by the largest raw
value.

54. Raw Values from Limit Supermatrix

55. Graphical Sensitivity
1. To do graphical sensitivity select
the Computations>Sensitivity
command
2. Select Edit>Independent Variable
to get to the Sensitivity input
selector box and change the
Independent Variable to the Goal.
The first graph that appears has
the first node by alphabetical
order, selected as the “with
respect to” node. It is generally
not the one you want. Select
Edit>Independent Variable and
choose the Goal as the
independent variable.

56. Putting Subcriteria into a Hierarchical
Model  Create separate
clusters for the
subcriteria of the
criteria that will have
subcriteria.
 Price has subcriteria
of initial cost and
maintenance, which
then connect to the
cars.
 Comfort has
subcriteria of Ride
and Driving
Performance which
then connect to the
cars.
 Prestige and MPG
have no subcriteria
and connect directly
to the cars.

57. Getting Backups
SuperDecisions software version 3.0
does not have an automatic backup
system, nor an un-do command.
It is imperative that you save your
model frequently using versioning:
car1.sdmod, car2.sdmod,
car3.sdmod, and so on.

58. Exporting Supermatrices
 The following files may be exported as .txt files using the File>Export
command:
Unweighted Supermatrix
Weighted Supermatrix
Limit Supermatrix
Cluster Matrix
 Import the .txt file into Excel using the File>Open command. In order to
see the .txt files you must show all the files, *.* rather than *.xls or xlsx
files, so select All Files for type of file with the Excel File>Open command
so the .txt file you exported will appear. Click the .txt file to select it.
 Use the Excel import wizard by clicking yes repeatedly to import the
supermatrix and display it in Excel. You may select it and copy to the
clipboard from Excel then paste into a document or powerpoint slide.
Tip: It is generally easier to select the number of decimals to display and set
the border styles in Excel before you copy.

59. Reports
 The Computations>Full Report command and the
File>Print command both generate the same HTML file
of reports about the model. You may choose Print
Preview to view the report, or save it as a .html file. It
gives the names and descriptions of the nodes and
clusters and important priorities.
 Note: do not use this report for the assignment!