This document outlines steps to establish a hybrid parametric model for project selection and decision making in an organization. The model combines known methods with a weighted scoring approach. Key steps include: collecting project information; defining selection criteria and weights; constructing quantitative indicators; developing decision logic; implementing the model; evaluating results and providing feedback; and ongoing model controlling and improvement. The goal is to reduce biases while capturing important factors for value-maximizing project choices.

1. Hybrid Parametric Model
Establishing an Analytical Project Selection and Decision Model For Your
Organization
EM730.1
Technology Management
G. Ersen Celebi
2012

2. Introduction:
In this study we propose to provide a guidance for the organizations about
the challenges and important details they need to consider while they are (re-)
constructing their portfolio management and/or Project Selection Process or
Decision Model.
This study will not offer you a product, which is already available in the
market, or a certain model; instead it will be helping you to find out what you may
be missing in your current model and giving you some ideas that you can use
and/or adopt to your current or future project selection model.
You may also find out all the details useful and decide to use entirely or
adopt it as basement and add your decision constraints and/or variables to solve
more complex decision problems.
Please contact to author before citing and/or using it either officially or
unofficially.
2

3. Project Selection Models
 Models are useful because they address
fundamental limitations of human problem solving.
 Models work because they break a complex problem
into pieces and enabling computers to do the
calculations on behalf of humans.
3

4. How a Decision Model Should Work?
 “Humans have limited information processing skills,
can be biased, and are often inconsistent when
making choices.“ [3]
 People are good at creative tasks like generating
alternatives. They are also good at recognizing
structure and at making the sort of "small", well-
defined judgments that are required in order to
provide inputs to models.
4

5. How a Decision Model Should Work?
 Because a successful decision model must capture
every critical aspect of the decision, more complex
decisions require more sophisticated models.
 “There is not a simple solution to every complex
problem” [H. L. Mencken]. This reality creates a
major challenge to constructing a one ideal model
which should solve all project selection problems.
 Project decisions are often high-stakes, dynamic
decisions with complex technical issues.
5

6. Challenges
 Strategic implications of a project selection decision
makes the model more sophisticated to be able to
capture them.
 Also necessity of capturing dynamic decision support
needs enforce the model to be more sophisticated.
 A support model should reflect and react accordingly
to different types of impacts of the decision on the
organization as well.
6

7. Benefits of a Model
 Reduces errors, biases, and inconsistencies in
human judgments.
 It can help the organization to make value-
maximizing choices.
 Controls the role of politics.
7

8. Benefits of a Model
 Directs organizations to better choices and
alternatives.
 Improves the competition for resources by
constructing proposal evaluation process.
 Clarifies the information needed and how it should
be used for decision process.
8

9. Benefits of a Model
 It makes it easier for all counterparts and promotes
the consensus among them by requiring the
agreement on the rules instead of decision.
 Model can increase the defensibility of the decisions
by transparency and agreed logic behind the model
itself.
 It allows organization to perform “what if” analyses
based on the records and improve, optimize the
9 model by learning from the past.

10. Decision Models
Decision analysis is a
theory and collection
of associated [1]
methods for making
decisions under
uncertainty.
10

11. Decision Models
The approach involves
constructing and analyzing a
model of the decision
problem to identify the
choice, or sequence of
choices, leading to
outcomes most consistent
[4] with the preferences of the
decision maker.
11

12. Constructing a Project Selection Model
As it has already been mentioned that there are
a lot of merits, factors, indicators, approaches, which
possibly can be used as part of your model, you may
find this study as a structured approach to develop a
model that suits exactly to your or an organization’s
needs.
In case you find some steps too structured or
complicated feel free to simplify it accordingly to your
needs.
12

13. Constructing a Project Selection Model
By following the steps you can establish a model
or Decision Support System (DSS) to Select Projects
in your organization.
The facts and the suggestions provided in this
study supposed to be useful regardless either you
are working on a formula in a spreadsheet or an
Enterprise Solution.
13

14. Constructing a Project Selection Model
There is where
our model
should fit
[3]
14

15. Constructing Hybrid Parametric
Project Selection Model
We will be constructing a model by keeping it simple but also
referring to possible complications and alternatives.
The Model will be combination of known methods and mainly
based on weighted scoring method with extended capabilities.
It would be possible to implement this model by a simple tool
and it should be evolving by the time and reach to capability to
decide itself when the all information (parameters) provided
accurately but it requires improvements and validation to
achieve this; therefore better to use it as a pre-decision source
and make the final decision as a committee or a human being
until the desired maturity level has been reached.
15

16. Hybrid Parametric Selection Model
Please see the
scope and the
each stages in
order to
establish your
model.
16

17. Collecting Project Information
 This phase is basically for collecting, gathering as
much information as possible and storing them into
your Project DB.
 It is important the break down the information in a
structured way and in detail to be able to use all the
possible indicators.
 The level of the information that you need to
breakdown depends on your intention that you are
planning to use in the further stages.
17

18. Collecting Project Information
With other words you will be limited by the level
of the information that you can gather in this stage
when you are designing your decision model.
The level that you can set in this stage is the
maximum detail level for all projects that you can
gather. The information should be available for all
the projects. You can not consider any information
as a criteria (parameter) if you can not compare all
the projects for this specific information field.
18

19. Collecting Project Information
 Very simple sample of
the project data.
 It is possible to set
main subjects in this
phase by summarizing
the information
gathered.
19

20. Defining Criteria and Weights
You can develop, choose your criteria (input
parameters for the decision problem) based on the
extraction from the previous step.
Then you need to decide on weights by
evaluating corporate objectives. It has been
suggested, to complete this task as a group or
involvement of the decision committee, based on the
best practice.
You should also decide the weights itself and
values of them.
20

21. Defining Criteria and Weights
There are a lot of
options that you can
consider to implement
for your model in this
stage.
21

22. Defining Criteria and Weights
 You can introduce importance and weights per your
needs. It is possible to extend or minimize the list or
use some figures based on any prioritization theory.
 More accurate results you can achieve while you are
indicating more Corporate specific criteria in to
model.
22

23. Defining Criteria and Weights
Differently from most of the
known models I would
suggest weighting profiles as
well.
You can weight members of
decision committee for each [1]
subject in order to reflect and
balance subject matter
expertise to selection
decisions.
23

24. Defining Criteria and Weights
The impact on the decision from different
members might be limited or maximized in that way.
For instance, CEO may have maximum weight on
Strategy related subjects while it is minimum or 0 in
a specific technical area.
24

25. Constructing Quantitative
Indicators
Once you have completed your criteria list then
you can decide what calculations you need. You may
have some figures but these figures should be
transformed to meaningful values in order to be
decision variable.
For instance, PV and Interest Rate to NPV.
Definitions of the outputs for the input parameters
should be finalized in this phase.
25

26. Constructing Quantitative
Indicators
 It is also possible to leverage your decision logic by
additional screening process as illustrated in slides
13 and 18.
 Use some of the criteria in your list for screening to
establish this process. You can eliminate some of
the projects and make ranking easier.
26

27. Constructing Quantitative
Indicators
27

28. Develop your Decision Logic
It is time to complete the Logic in order to allow
you to get ranked project list based on the
prioritization that you have designed in the previous
phases.
Although the transformations have been
completed in the previous phase; however you still
need to describe the decision logic.
Consider if you need any further transformation
to compare the figures among the projects. You may
find some important indicators are missing and
review the previous phases is needed.
28

29. Develop your Decision Logic
 You may have a formula of the grant total and/or well
defined comparisons at the end of this stage.
 Remember that different orders in calculations
possibly directs you to different results.
 We have selected the all criteria we need to use for
decision.
 Defined and calculated some parameters for
analysis.
29

30. Develop your Decision Logic
 Probably all committee members provided their
input.
 As a results now we have all the selected criteria and
the results ready to compare and decide.
 There are couple of possible options again how to
make the final decision.
 We can implement AHP* or Integer Programming if
you transformed all the parameters to integer results
or you can decide by a brainstorming with the
30 committee.

31. Implementation of Model
31

32. Implementation of Model
As it has been discussed and built during this
study you can find a very simple implementation in
the previous slide.
The weights that we have defined earlier for
profiles and the Subjects have been used. (Please
refer to slides 21-22-23)
Assumed that a screening process in place and
some of the candidates have already been
eliminated.
32

33. Implementation of Model
As you can also see again a simple calculation
has been indicated for final decision. (Comparison)
We are in the point to decide. As discussed
before in that point depending on the maturity of the
tool; we can decide based on results or review and
have the final word as a committee.
33

34. Evaluation of the Results and
Feedback
 You should continuously review the results and
design your evaluation process to optimize your
decision support system and model.
 Very common result and feedback could be
reviewing and editing the weights for some of the
profiles based on the results.
 Weights for some subjects may need to be reviewed
if the Corporate Strategy or Financial Expectations or
Processes have been changed.
34

35. Model Controlling and
Improvement
 Implementation and verification of the necessary
changes initiated in evaluation phase.
 This change might be consists of adding/removing a
criterion, new formula for a output parameter, using
a different set of parameters in Decision Logic,..,etc.
 You may decide to make some changes on the
model itself as a result of this process.
35

36. Suggestions
 Consider project relations once your model met the
expected quality.
 When you are designing and/or optimizing your
model, make a change on one variable at a time to
ensure the impact is accurate.
 If you are able to use any integer programming or
AHP* consider using your budget and/or approved
cash flow as a input parameter to achieve better
results from the model.
36

37. References
1. http://www.prioritysystem.com
2. Program Portfolio Alignment, Edgardo
Gonzalez
3. Building Project Management through
Strategic Alignment, Fadi Samara
4. http://www.tutorialspoint.com
5. Project Selection Processes, Criteria and
Methods, Ersen Celebi
37