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PROJECT SELECTION
Broad Contents
Introduction
Project decisions
Types of project selection models
Criteria for choosing project model
The nature of project selection models
Numeric and non-numeric models
11.1 Introduction:
Project selection is the
process of choosing a project or set
of projects to be implemented by
the organization.
Since projects in general require a substantial investment in terms of money
and resources, both of which are limited, it is of vital
importance that the projects that an
organization selects provide good returns on the resources and
capital invested. This
requirement must be balanced with the need for an organization
to move forward and develop.
The high level of uncertainty in the modern business environment
has made this area of project
management crucial to the continued success of an organization
with the difference between
choosing good projects and poor projects literally representing
the difference between
operational life and death.
Because a successful model must capture every critical aspect of
the decision, more complex
decisions typically require more sophisticated models. “There is
a simple solution to every
complex problem; unfortunately, it is wrong”. This reality
creates a major challenge for tool
designers. Project decisions are often high-stakes, dynamic
decisions with complex technical
issues—precisely the kinds of decisions that are most difficult
to model:
• Project
selection decisions are high-stakes because of their strategic implications. The
projects a company chooses can define the products it supplies,
the work it does, and the
direction it takes in the marketplace. Thus, project decisions
can impact every business
stakeholder, including customers, employees, partners,
regulators, and shareholders. A
sophisticated model may be needed to capture strategic
implications.
• Project
decisions are dynamic because a project may be conducted over several budgeting
cycles, with repeated opportunities to slow, accelerate,
re-scale, or terminate the project.
Also, a successful project may produce new assets or products
that create time-varying
financial returns and other impacts over many years. A more
sophisticated model is needed
to address dynamic impacts.
• Project
decisions typically produce many different types of impacts on the organization.
For
example, a project might increase revenue or reduce future
costs. It might impact how
customers or investors perceive the organization. It might
provide new capability or
learning, important to future success. Making good choices
requires not just estimating the
financial return on investment; it requires understanding all of
the ways that projects add
value. A more sophisticated model is needed to account for all
of the different types of
potential impacts that project selection decisions can create.
11.2 Project Decisions:
Project decisions often entail risk and uncertainty. The
significance of a project risk depends on
the nature of that risk and on the other risks that the
organization is taking. A more sophisticated
model is needed to correctly deal with risk and uncertainty.
Project selection is the process of evaluating individual
projects or groups of projects, and then
choosing to implement some set of them so that the objectives of
the parent organization will be
achieved. This same systematic process can be applied to any
area of the organization’s
business in which choices must be made between competing
alternatives. For example:
- A manufacturing
firm can use evaluation/selection techniques to choose which machine to adopt in a part-fabrication process.
- A television
station can select which of several syndicated comedy shows to rerun in its 7:30 p.m. weekday time-slot
- A construction
firm can select the best subset of a large group of potential projects on which to bid
- A hospital can
find the best mix of psychiatric, orthopedic, obstetric, and other beds for a new wing.
Each project will have different costs, benefits, and risks.
Rarely are these known with certainty.
In the face of such differences, the selection of one project
out of a set is a difficult task.
Choosing a number of different projects, a
portfolio,
is even more complex. In the following
sections, we discuss several techniques that can be used to help
senior managers select projects.
Project selection is only one of many decisions associated with
project management.
To deal with all of these problems, we use
decision aiding models.
We need such models
because they abstract the relevant issues about a problem from
the plethora of detail in which
the problem is embedded. Reality is far too complex to deal with
in its entirety. An “idealist” is
needed to strip away almost all the reality from a problem,
leaving only the aspects of the “real”
situation with which he or she wishes to deal. This process of
carving away the unwanted reality
from the bones of a problem is called
modeling the problem.
The idealized version of the
problem that results is called a model.
The model represents the problem’s
structure,
its form. Every problem has a form,
though often
we may not understand a problem well enough to describe its
structure. We will use many
models in this book—graphs, analogies, diagrams, as well as
flow graph and network models
to
help solve scheduling problems, and
symbolic
(mathematical) models for a number of
purposes.
Models may be quite simple to understand, or they may be
extremely complex. In general,
introducing more reality into a model tends to make the model
more difficult to manipulate. If
the input data for a model are not known precisely, we often use
probabilistic information; that
is, the model is said to be
stochastic
rather than
deterministic.
Again, in general, stochastic models are more difficult to
manipulate. We live in the midst of
what has been called the “knowledge explosion.” We frequently
hear comments such as “90
percent of all we know about physics has been discovered since
Albert Einstein published his
original work on special relativity”; and “80 percent of what we
know about the human body
has been discovered in the past 50 years.” In addition, evidence
is cited to show that knowledge
is growing exponentially.
Such statements emphasize the importance of the
management of change.
To survive, firms
should develop strategies for assessing and reassessing the use
of their resources. Every
allocation of resources is an investment in the future. Because
of the complex nature of most
strategies, many of these investments are in projects.
To cite one of many possible examples, special visual effects
accomplished through computer
animation are common in the movies and television shows we watch
daily. A few years ago
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they were unknown. When the capability was in its idea stage,
computer companies as well as
the firms producing movies and television shows faced the
decision whether or not to invest in
the development of these techniques. Obviously valuable as the
idea seems today, the choice
was not quite so clear a decade ago when an entertainment
company compared investment in
computer animation to alternative investments in a new star, a
new rock group, or a new theme
park.
The proper choice of investment projects is crucial to the
long-run survival of every firm. Daily
we witness the results of both good and bad investment choices.
In our daily newspapers we
read of Cisco System’s decision to purchase firms that have
developed valuable communication
network software rather than to develop its own software. We
read of Procter and Gamble’s
decision to invest heavily in marketing its products on the
Internet; British Airways’ decision to
purchase passenger planes from Airbus instead of from its
traditional supplier, Boeing; or
problems faced by school systems when they update student
computer labs—should they invest
in Windows-based systems or stick with their traditional choice,
Apple®. But can such
important choices be made rationally? Once made, do they ever
change, and if so, how? These
questions reflect the need for effective selection models.
Within the limits of their capabilities, such models can be used
to increase profits, select
investments for limited capital resources, or improve the
competitive position of the
organization. They can be used for ongoing evaluation as well as
initial selection, and thus, are
a key to the allocation and reallocation of the organization’s
scarce resources.
11.2.1 Modeling:
A model is an object or concept, which attempts to capture
certain aspects of the real
world. The purpose of models can vary widely, they can be used
to test ideas, to help
teach or explain new concepts to people or simply as
decorations. Since the uses that
models can be put are so many it is difficult to find a
definition that is both clear and
conveys all the meanings of the word. In the context of project
selection the following
definition is useful:
“A model is an explicit statement of our image of reality. It is
a representation of the
relevant aspects of the decision with which we are concerned. It
represents the decision
area by structuring and formalizing the information we possess
about the decision and,
in doing so, presents reality in a simplified organized form. A
model, therefore,
provides us with an abstraction of a more complex reality”.
(Cooke and Slack, 1991)
When project selection models are seen from this perspective it
is clear that the need for
them arises from the fact that it is impossible to consider the
environment, within which
a project will be implemented, in its entirety. The challenge
for a good project selection
model is therefore clear. It must balance the need to keep
enough information from the
real world to make a good choice with the need to simplify the
situation sufficiently to
make it possible to come to a conclusion in a reasonable length
of time.
11.3 Criteria for Choosing Project Model:
When a firm chooses a project selection model, the following
criteria, based on Souder (1973),
are most important:
1. Realism:
The model should reflect the reality of the manager’s decision
situation, including the
multiple objectives of both the firm and its managers. Without a
common measurement
system, direct comparison of different projects is impossible.
For example, Project A may strengthen a firm’s market share by
extending its facilities,
and Project B might improve its competitive position by
strengthening its technical
staff. Other things being equal, which is better? The model
should take into account the
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realities of the firm’s limitations on facilities, capital,
personnel, and so forth. The
model should also include factors that reflect project risks,
including the technical risks
of performance, cost, and time as well as the market risks of
customer rejection and
other implementation risks.
2. Capability:
The model should be sophisticated enough to deal with multiple
time periods, simulate
various situations both internal and external to the project
(for example, strikes, interest
rate changes), and optimize the decision. An optimizing model
will make the
comparisons that management deems important, consider major
risks and constraints on
the projects, and then select the best overall project or set of
projects.
3. Flexibility:
The model should give valid results within the range of
conditions that the firm might
experience. It should have the ability to be easily modified, or
to be self-adjusting in
response to changes in the firm’s environment; for example, tax
laws change, new
technological advancements alter risk levels, and, above all,
the organization’s goals
change.
4. Ease of Use:
The model should be reasonably convenient, not take a long time
to execute, and be
easy to use and understand. It should not require special
interpretation, data that are
difficult to acquire, excessive personnel, or unavailable
equipment. The model’s
variables should also relate one-to-one with those real-world
parameters, the managers
believe significant to the project. Finally, it should be easy
to simulate the expected
outcomes associated with investments in different project
portfolios.
5. Cost:
Data gathering and modeling costs should be low relative to the
cost of the project
and must surely be less than the potential benefits of the
project. All costs should be
considered, including the costs of data management and of
running the model.
Here, we would also add a sixth criterion:
6. Easy
Computerization:
It should be easy and convenient to gather and store the
information in a computer
database, and to manipulate data in the model through use of a
widely available,
standard computer package such as Excel, Lotus 1-2-3, Quattro
Pro, and like programs.
The same ease and convenience should apply to transferring the
information to any
standard decision support system.
In what follows, we first examine fundamental types of project
selection models and the
characteristics that make any model more or less acceptable.
Next we consider the
limitations, strengths, and weaknesses of project selection
models, including some
suggestions of factors to consider when making a decision about
which, if any, of the
project selection models to use. We then discuss the problem of
selecting projects when
high levels of uncertainty about outcomes, costs, schedules, or
technology are present,
as well as some ways of managing the risks associated with the
uncertainties.
Finally, we comment on some special aspects of the information
base required for
project selection. Then we turn our attention to the selection
of a set of projects to help
the organization achieve its goals and illustrate this with a
technique called the Project
Portfolio Process.
We finish the chapter with a discussion
of project proposals.
11.4 The Nature of Project Selection Models:
There are two basic types of project selection models,
numeric
and
nonnumeric.
Both are
widely used. Many organizations use both at the same time, or
they use models that are
combinations of the two. Nonnumeric models, as the name implies,
do not use numbers as
inputs. Numeric models do, but the criteria being measured may
be either objective or
subjective. It is important to remember that the
qualities
of a project may be represented by
numbers, and that
subjective measures are
not necessarily less useful or reliable than
objective
measures.
Before examining specific kinds of models within the two basic
types, let us consider just what
we wish the model to do for us, never forgetting two critically
important, but often overlooked
facts.
• Models do not
make decisions—people do. The manager, not the model, bears
responsibility for the decision. The manager may “delegate” the
task of making the decision
to a model, but the responsibility cannot be abdicated.
• All models,
however sophisticated, are only partial representations of the reality they are
meant to reflect. Reality is far too complex for us to capture
more than a small fraction of it
in any model. Therefore, no model can yield an optimal decision
except within its own,
possibly inadequate, framework.
We seek a model to assist us in making project selection
decisions. This model should possess
the characteristics discussed previously and, above all, it
should evaluate potential projects by
the degree to which they will meet the firm’s objectives. To
construct a selection/evaluation
model, therefore, it is necessary to develop a list of the
firm’s objectives.
A list of objectives should be generated by the organization’s
top management. It is a direct
expression of organizational philosophy and policy. The list
should go beyond the typical
clichés about “survival” and “maximizing profits,” which are
certainly real goals but are just as
certainly not the only goals of the firm. Other objectives might
include maintenance of share of
specific markets, development of an improved image with specific
clients or competitors,
expansion into a new line of business, decrease in sensitivity
to business cycles, maintenance of
employment for specific categories of workers, and maintenance
of system loading at or above
some percent of capacity, just to mention a few.
A model of some sort is implied by any conscious decision. The
choice between two or more
alternative courses of action requires reference to some
objective(s), and the choice is thus,
made in accord with some, possibly subjective, “model.” Since
the development of computers
and the establishment of operations research as an
subject in the mid-1950s, the use of
formal, numeric models to assist in decision making has
expanded. Many of these models use
financial metrics such as profits and/or cash flow to measure
the “correctness” of a managerial
decision. Project selection decisions are no exception, being
based primarily on the degree to
which the financial goals of the organization are met. As we
will see later, this stress on
financial goals, largely to the exclusion of other criteria,
raises some serious problems for the
firm, irrespective of whether the firm is for profit or
not-for-profit.
When the list of objectives has been developed, an additional
refinement is recommended. The
elements in the list should be
weighted.
Each item is added to the list because
it represents a
contribution to the success of the organization, but each item
does not make an equal
contribution. The weights reflect different degrees of
contribution each element makes in
accomplishing a set of goals.
Once the list of goals has been developed, one more task
remains. The probable contribution of
each project to each of the goals should be estimated. A project
is selected or rejected because it
is predicted to have certain outcomes if implemented.
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These outcomes are expected to contribute to goal achievement.
If the estimated level of goal
achievement is sufficiently large, the project is selected. If
not, it is rejected.
The relationship between the project’s expected results and the
organization’s goals must be
understood. In general, the kinds of information required to
evaluate a project can be listed
under production, marketing, financial, personnel,
administrative, and other such categories.
The following table 11.1 is a list of factors that contribute,
positively or negatively, to these
categories.
In order to give focus to this list, we assume that the projects
in question involve the possible
substitution of a new production process for an existing one.
The list is meant to be illustrative.
It certainly is not exhaustive.
Table 11.1: Factors Contributing to Various Organizational
Categories
Some factors in this list have a one-time impact and some recur.
Some are difficult to estimate
and may be subject to considerable error. For these, it is
helpful to identify a range of
uncertainty.
In addition, the factors may occur at different times.
And some factors may have
thresholds,
critical values above or below which we
might wish to
reject the project. We will deal in more detail with these
issues later in this chapter.
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Clearly, no single project decision needs to include all these
factors. Moreover, not only is the
list incomplete, it also contains redundant items. Perhaps more
important, the factors are not at
the same level of generality:
profitability
and
impact on organizational image
both affect the
overall organization, but
impact on working conditions
is more oriented to the
production
system. Nor are all elements of equal importance.
Change in production cost
is usually considered more important
than impact on current
suppliers.
Shortly, we will consider the problem of generating an acceptable list of
factors and
measuring their relative importance. At that time we will
discuss the creation of a Decision
Support System (DSS) for project evaluation and selection.
The same subject will arise once more in the next lecture(s)
when we consider project auditing,
evaluation, and termination.
Although the process of evaluating a potential project is
time-consuming and difficult, its
importance cannot be overstated. A major consulting firm has
argued (Booz, Allen, and
Hamilton, 1966) that the primary cause for the failure of
Research and Development (R and D)
projects is insufficient care in evaluating the proposal before
the expenditure of funds. What is
true for such projects also appears to be true for other kinds
of projects, and it is clear that
product development projects are more successful if they
incorporate user needs and satisfaction
in the design process (Matzler and Hinterhuber, 1998). Careful
analysis of a potential project is
a sine qua non
for profitability in the
construction business. There are many horror stories
(Meredith, 1981) about firms that undertook projects for the
installation of a computer
information system without sufficient analysis of the time,
cost, and disruption involved.
Later, we will consider the problem of conducting an evaluation
under conditions of uncertainty
about the outcomes associated with a project. Before dealing
with this problem, however, it
helps to examine several different evaluation/selection models
and consider their strengths and
weaknesses. Recall that the problem of choosing the project
selection model itself will also be
discussed later.
11.5 Types of Project Selection Models:
Of the two basic types of selection models (numeric and
nonnumeric), nonnumeric models are
older and simpler and have only a few subtypes to consider. We
examine them first.
Non-Numeric
Models:
These include the following:
1. The Sacred Cow:
In this case the project is suggested by a senior and powerful
official in the
organization. Often the project is initiated with a simple
comment such as, “If you have
a chance, why don’t you look into . . .,” and there follows an
undeveloped idea for a
new product, for the development of a new market, for the design
and adoption of a
global database and information system, or for some other
project requiring an
investment of the firm’s resources. The immediate result of this
bland statement is the
creation of a “project” to investigate whatever the boss has
suggested.
The project is “sacred” in the sense that it will be maintained
until successfully
concluded, or until the boss, personally, recognizes the idea as
a failure and
terminates it.
2. The Operating Necessity:
If a flood is threatening the plant, a project to build a
protective dike does not
require much formal evaluation, which is an example of this
scenario. XYZ
Steel Corporation has used this criterion (and the following
criterion also) in
evaluating potential projects. If the project is required in
order to keep the
system operating, the primary question becomes: Is the system
worth saving at
the estimated cost of the project? If the answer is yes, project
costs will be
examined to make sure they are kept as low as is consistent with
project
success, but the project will be funded.
3. The Competitive Necessity:
Using this criterion, XYZ Steel undertook a major plant
rebuilding project in
the late 1960s in its steel bar manufacturing facilities near
Chicago. It had
become apparent to XYZ’s management that the company’s bar mill
needed
modernization if the firm was to maintain its competitive
position in the
Chicago market area. Although the planning process for the
project was quite
sophisticated, the decision to undertake the project was based
on a desire to
maintain the company’s competitive position in that market.
In a similar manner, many business schools are restructuring
their
undergraduate and Masters in Business Administration (MBA)
programs to
stay competitive with the more forward looking schools. In large
part, this
action is driven by declining numbers of tuition paying students
and the need to
develop stronger programs to attract them.
Investment in an
operating necessity
project takes precedence over a
competitive necessity
project, but both types of projects may
bypass the more
careful numeric analysis used for projects deemed to be less
urgent or less
important to the survival of the firm.
4. The Product Line Extension:
In this case, a project to develop and distribute new products
would be judged
on the degree to which it fits the firm’s existing product line,
fills a gap,
strengthens a weak link, or extends the line in a new, desirable
direction.
Sometimes careful calculations of profitability are not
required. Decision
makers can act on their beliefs about what will be the likely
impact on the total
system performance if the new product is added to the line.
5. Comparative Benefit Model:
For this situation, assume that an organization has many
projects to consider,
perhaps several dozen. Senior management would like to select a
subset of the
projects that would most benefit the firm, but the projects do
not seem to be
easily comparable. For example, some projects concern potential
new products,
some concern changes in production methods, others concern
computerization
of certain records, and still others cover a variety of subjects
not easily
categorized (e.g., a proposal to create a daycare center for
employees with small
children).
The organization has no formal method of selecting projects, but
members of
the selection committee think that some projects will benefit
the firm more than
others, even if they have no precise way to define or measure
“benefit.”
The concept of comparative benefits, if not a formal model, is
widely adopted
for selection decisions on all sorts of projects. Most United
Way organizations
use the concept to make decisions about which of several social
programs to
fund. Senior management of the funding organization then
examines all
projects with positive recommendations and attempts to construct
a portfolio
that best fits the organization’s aims and its budget. |