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Project Management

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LESSON 11
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.
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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:
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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 academic 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
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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.
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Table of Contents:
  1. INTRODUCTION TO PROJECT MANAGEMENT:Broad Contents, Functions of Management
  2. CONCEPTS, DEFINITIONS AND NATURE OF PROJECTS:Why Projects are initiated?, Project Participants
  3. CONCEPTS OF PROJECT MANAGEMENT:THE PROJECT MANAGEMENT SYSTEM, Managerial Skills
  4. PROJECT MANAGEMENT METHODOLOGIES AND ORGANIZATIONAL STRUCTURES:Systems, Programs, and Projects
  5. PROJECT LIFE CYCLES:Conceptual Phase, Implementation Phase, Engineering Project
  6. THE PROJECT MANAGER:Team Building Skills, Conflict Resolution Skills, Organizing
  7. THE PROJECT MANAGER (CONTD.):Project Champions, Project Authority Breakdown
  8. PROJECT CONCEPTION AND PROJECT FEASIBILITY:Feasibility Analysis
  9. PROJECT FEASIBILITY (CONTD.):Scope of Feasibility Analysis, Project Impacts
  10. PROJECT FEASIBILITY (CONTD.):Operations and Production, Sales and Marketing
  11. PROJECT SELECTION:Modeling, The Operating Necessity, The Competitive Necessity
  12. PROJECT SELECTION (CONTD.):Payback Period, Internal Rate of Return (IRR)
  13. PROJECT PROPOSAL:Preparation for Future Proposal, Proposal Effort
  14. PROJECT PROPOSAL (CONTD.):Background on the Opportunity, Costs, Resources Required
  15. PROJECT PLANNING:Planning of Execution, Operations, Installation and Use
  16. PROJECT PLANNING (CONTD.):Outside Clients, Quality Control Planning
  17. PROJECT PLANNING (CONTD.):Elements of a Project Plan, Potential Problems
  18. PROJECT PLANNING (CONTD.):Sorting Out Project, Project Mission, Categories of Planning
  19. PROJECT PLANNING (CONTD.):Identifying Strategic Project Variables, Competitive Resources
  20. PROJECT PLANNING (CONTD.):Responsibilities of Key Players, Line manager will define
  21. PROJECT PLANNING (CONTD.):The Statement of Work (Sow)
  22. WORK BREAKDOWN STRUCTURE:Characteristics of Work Package
  23. WORK BREAKDOWN STRUCTURE:Why Do Plans Fail?
  24. SCHEDULES AND CHARTS:Master Production Scheduling, Program Plan
  25. TOTAL PROJECT PLANNING:Management Control, Project Fast-Tracking
  26. PROJECT SCOPE MANAGEMENT:Why is Scope Important?, Scope Management Plan
  27. PROJECT SCOPE MANAGEMENT:Project Scope Definition, Scope Change Control
  28. NETWORK SCHEDULING TECHNIQUES:Historical Evolution of Networks, Dummy Activities
  29. NETWORK SCHEDULING TECHNIQUES:Slack Time Calculation, Network Re-planning
  30. NETWORK SCHEDULING TECHNIQUES:Total PERT/CPM Planning, PERT/CPM Problem Areas
  31. PRICING AND ESTIMATION:GLOBAL PRICING STRATEGIES, TYPES OF ESTIMATES
  32. PRICING AND ESTIMATION (CONTD.):LABOR DISTRIBUTIONS, OVERHEAD RATES
  33. PRICING AND ESTIMATION (CONTD.):MATERIALS/SUPPORT COSTS, PRICING OUT THE WORK
  34. QUALITY IN PROJECT MANAGEMENT:Value-Based Perspective, Customer-Driven Quality
  35. QUALITY IN PROJECT MANAGEMENT (CONTD.):Total Quality Management
  36. PRINCIPLES OF TOTAL QUALITY:EMPOWERMENT, COST OF QUALITY
  37. CUSTOMER FOCUSED PROJECT MANAGEMENT:Threshold Attributes
  38. QUALITY IMPROVEMENT TOOLS:Data Tables, Identify the problem, Random method
  39. PROJECT EFFECTIVENESS THROUGH ENHANCED PRODUCTIVITY:Messages of Productivity, Productivity Improvement
  40. COST MANAGEMENT AND CONTROL IN PROJECTS:Project benefits, Understanding Control
  41. COST MANAGEMENT AND CONTROL IN PROJECTS:Variance, Depreciation
  42. PROJECT MANAGEMENT THROUGH LEADERSHIP:The Tasks of Leadership, The Job of a Leader
  43. COMMUNICATION IN THE PROJECT MANAGEMENT:Cost of Correspondence, CHANNEL
  44. PROJECT RISK MANAGEMENT:Components of Risk, Categories of Risk, Risk Planning
  45. PROJECT PROCUREMENT, CONTRACT MANAGEMENT, AND ETHICS IN PROJECT MANAGEMENT:Procurement Cycles