All organizations must select the projects they decide to pursue from among numerous opportunities. What
criteria determine which projects should be supported? Obviously, this is no simple decision. The consequences
of poor decisions can be enormously expensive. Recent research suggests that in the realm of information
technology (IT), companies squander over $50 billion a year on projects that are created but never
used by their intended clients. How do we make the most reasonable choices in selecting projects? What
kind of information should we collect? Should decisions be based strictly on financial analysis, or should
other criteria be considered? In this chapter, we will try to answer such questions as we take a closer look at
the process of project selection.
We will examine a number of different approaches for evaluating and selecting potential projects. The
various methods for project selection run along a continuum from highly qualitative, or judgment-based,
approaches to those that rely on quantitative analysis. Of course, each approach has benefits and drawbacks,
which must be considered in turn.
We will also discuss a number of issues related to the management of a project portfolio—the set of
projects that an organization is undertaking at any given time. For example, Rubbermaid, Inc. routinely
undertakes hundreds of new product development projects simultaneously, always searching for opportunities
with strong commercial prospects. When a firm is pursuing multiple projects, the challenges of
strategic decision making, resource management, scheduling, and operational control are magnified.
All projects have different characteristics like different opportunities,
benefits, risks etc. Companies should select the most suitable project for
them. Companies want the most
profitable project and use all their
tools efficiently when they conduct their projects on the other hand
organizations have limited resources and time and money pressures are the major
effect for selecting project. In a nutshell
selecting true project among lot
of alternatives is not an easy job. Project selection models and project
selection criteria help managers in order to decide which project is the most reasonable
for their organizations.
Project selection criteria and project
selection models are different from each other. Project selection criteria are related
to the product of project while project selection methods measure benefits of
the project or they compare the measurable benefits of project among others
(Heldman, 2004). Project selection
criteria and models may be marketing, financial or public perception sometimes
contains all of them but sometimes contain only one.
Project
selection criteria are an input for project initiation process.
According to guide to the PMBOK project selection criteria are concern with what
the product or service of the project will produce and how it will benefit the
organization. Also criteria contain the types of matter executive managers are
commonly thinking about. This involves factors like financial benefits, returns
on investment, market share, client retention and loyalty and public
perceptions. Ricardo Vargas says that
selection criterion is not a single it is a set of criteria and he explain
these criteria with multicriteria process.
Multicriteria process consists of financial criteria, strategic
criteria, urgency criteria, stakeholder criteria, human resources criteria and
risk criteria. Managers should not ignore one of criteria and all criteria
should be evaluated. Evaluation of selection criteria are formed by individual
opinion of selection committee. For
these reason the importance of the authority, political standing and individual
aspirations of selection committee members should not be underestimated.(Heldman,2004)
Project
selecting models or project screening models allow organizations to make the
best option among alternatives within the usual constraints of time and money.
PMBOK guide states that selection methods contain
measuring value or attractiveness to the project owner. Also project selecting
methods consist of considering the decision criterion and imply to calculate
value under uncertainty. PMBOK guide examines project selection under two
categories as benefit measurement methods and constrained optimization methods.
Benefit measurement methods include that comparative approaches, scoring
models, benefit contribution or economic models and constrained optimization
methods include mathematical models using linear, nonlinear, dynamic integer
and multi- objective programming algorithms.
Project selection models are capable of picking
potential winners from the large set of possible project choices (Pinto, 2010). There are five important issues which
organizations consider when evaluating screening models. These are realism,
capability, flexibility, ease of use, cost and comparability.
Realism: It refers that an impressive model
should reflect objectives and strategic goals of organizations. Model should
take into account the amount of capital, human resources and technical capacity
available to the company. Also model must consider technical and commercial
risk and including performance cost and time. (Tjahjana and others, 2009)
Capability: A model should be elastic in order to react changes
in the conditions under which projects are performed. In other words capability is able to simulate
different scenarios and optimize the decisions. For instance the model should
allow the organization to analyze different types of projects like long term
versus short term projects, project with different financial objectives or
project with different capabilities
Flexibility: The model should be easily modified if sample applications necessitate
changes. For instance model should allow regulation by reason of any changes in
tax laws, building codes or exchange rates.
Ease of Use: The model should be simple for both all people of organization and all
areas in organization. The preferences which are made for project selection
should be clear and easily understood by all members of organizations.
Additionally model should be timely and it should set up the screening
information immediately and employees should able to understand this
information without any special education or skills.
Cost: The model also should be cost
effective. Data gathering and modeling cost should be low relative to the cost
of the project.
Comparability: It should be extensive to be implemented to multiple projects. A useful model should promote general compare
of project alternatives. If the model is
too narrowly focused it may not useful in comparison of potential projects or
foster biases against others.
There are two predominant types
of project selection models. These are numeric and non-numeric models. (Burke,
2003) Numeric models pursue to use numbers as inputs for the decision process
included in selecting projects and values can be obtained from both objectively
and subjectively. Otherwise numeric models are subdivided as financial models
and scoring models according to Sekelani Banda.
Financial models contain payback period, return on investment, net
present value and internal rate of return.
Also financial models can be named as profitability model.
Non numeric modals do not use numbers as input
for decision making. The sacred cow, the operating necessity, competitive
necessity, product line extension and comparative benefit model are types of non-numeric
modals.
The Sacred Cow:
In this case the project is suggested by a senior or powerful official
in the organizations. Sacred means that will be maintained until successfully
concluded, or until the boss, personally, recognizes the idea as a failure and
terminates it. Element enjoys adopted managers protection whose confirmation
present the action to create the project.
The Operating
Necessity: If the project is needed in spite of controlling
the system operating and if the system worth saving the estimated cost of the
project, project cost will be checked in order to make sure they kept as low as
is persistent with project success, however the project will be funded.
Sustaining operational functionality more important than cost at crisis
atmosphere.
The Competitive
Necessity: The decision to take on a project is based on
a will to continue the organization’s competitive position in the sector. But
only few companies volunteer to sacrifice market share after great cost and
time spent. If response against to competitive threat is not active, project
will encounter difficulty in alignment with strategic goals of organization.
Product Line
Extension: A project to develop and present new products
judged on the degree to which it fits the firm’s current product line, fills a
gap, strengthens a weak link, or extends the line in a new, desirable
direction. Marketing try product
extensions or product modification to reposition the product or service
preferably with clients. These decisions could be made intuitively without
requiring too much analysis (Kureshi, 2001).
Comparative Benefit
Model: This situation refers to an organization has
many projects for selecting however projects do not have easily comparable components.
In such a case selection of project should be made by a team of managers who
decide to seek the project which has the most suitable.
Checklist model, Simplified scoring models,
Analytic hierarch process, Profile models and Financial models are more common
project screening approaches and these models will be explained separately.
Organizations spend lots of time and effort
trying to make the best project selection decisions possible. The factors which
are listed below can be considered when evaluating project alternatives. These
factors are generalized under risk and commercial factors, internal operating
issues and other factors. This list is only a partial of list of various
elements because a company must deal with more components when encountering new
project alternatives.
Risk
Commercial
Internal
operating ıssues
Additional
factors
Techical
risk
Expected return of investment
Need to develop
(train employees)
Patent protection
Financial risk
Paybak period
Change in workforce size or compasition
Impact on company’s image
Safety risk
Potential market share
Change in physical environment
Strategic fit
Quality risk
Long-term market dominance
Change in manufacturing or service operations
resulting from project
Legal exposure
Initial cash outlay
Ability to generate future business or new
markets
In the
simplified scoring model, each criterion is ranked according to its relative
importance. Our choice of projects will thus reflect our desire to maximize the
impact of certain criteria on our decision. In order to score our simplified
checklist, we assign a specific weight to each of our four criteria:
Criterion
Importance Weight
Importance Weight
3
Profit
Potential
2
Development Risks
2
Cost
1
Example: Scoring Models
Using the criterion weighting values we
developed above, SAP Corporation is attempting to determine the optimal project
to fund. As you can see in Table, although adding a scoring component to our
simple checklist complicates our decision, it also gives us a more precise
screening model—one that more closely reflects our desire to emphasize certain
criteria over others.
Table 2 (Simple Scoring Model)
Project
Criteria
Importance Weight
(A)
Score (B)
Weighted
Score (A)x(B)
Project Alpha
Cost
1
3
3
Profit Potential
2
1
2
Development Risk
2
1
2
Time to Market
3
2
6
Total Score
13
Project
Criteria
Importance Weight
(A)
Score (B)
Weighted
Score (A)x(B)
Project Beta
Cost
1
2
2
Profit Potential
2
2
4
Development Risk
2
2
4
Time to Market
3
3
9
Total Score
19
Table 2 (Continued)
Project
Criteria
Importance Weight
(A)
Score (B)
Weighted
Score (A)x(B)
Project Gamma
Cost
1
3
3
Profit Potential
2
3
6
Development Risk
2
3
6
Time to Market
3
1
3
Total Score
18
Project
Criteria
Importance Weight
(A)
Score (B)
Weighted
Score (A)x(B)
Project Delta
Cost
1
1
1
Profit Potential
2
1
2
Development Risk
2
2
4
Time to Market
3
3
9
Total Score
16
SOLUTION
Table 1 (Simplified Checklist
Model for Project Selection)
Project Criteria High Medium Low
Project Alpha Cost X
Profit Potential X
Time to
Market X
Development Risk X Project Beta Cost X
Profit Potential X
Time to
Market X
Development Risk X Project Gamma Cost X
Profit Potential X
Time to
Market X Development Risk X Project Delta Cost X Profit Potential X
Time to
Market X
Development Risk X
In
Table 2, the numbers in the column labeled Importance Weight specify the
numerical values that we have assigned to each criterion: Time to Market always
receives a value of 3, profit potential a value of 2, development risk a value
of 2, and cost a value of 1. We then assign relative values to each of our four
dimensions. The numbers in the column labeled Score replace the X’s of Table 1
with their assigned score values:
(High =
3, Medium = 2, Low = 1)
In
Project Alpha, for example, the High rating given Cost becomes a 3 in Table 2
because High is here valued at 3. Likewise, the Medium rating given Time to
Market in Table 1 becomes a 2. But notice what happens when we calculate the
numbers in the column labeled Weighted Score. When we multiply the numerical
value of Cost (1) by its rating of High (3), we get a Weighted Score of 3. But
when we multiply the numerical value of Time to Market (3) by its rating of
Medium (2), we get a Weighted Score of 6. We add up the total Weighted Scores
for each project, and according to Table, Project Beta (with a total of 19) is
the best alternative, compared to the other options: Project Alpha (with a
total of 13), Project Gamma (with a total of 18), and Project Delta (with a
total of 16).
Thus the
simple scoring model consists of the following steps:
• Assign
importance weights to each criterion: Develop logic for differentiating among
various levels of importance and devise a system for assigning appropriate
weights to each criterion. Relying on collective group judgment may help to
validate the reasons for determining importance levels. The team may also designate
some criteria as “must” items. Safety concerns, for example, may be stipulated
as nonnegotiable. In other words, all projects must achieve an acceptable
safety level or they will not be considered further.
• Assign
score values to each criterion in terms of its rating (High = 3, Medium = 2,
Low = 1): The logic of assigning score values is often an issue of scoring
sensitivity—of making differences in scores distinct. Some teams, for example,
prefer to widen the range of possible values—say, by using a 1-to-7 scale
instead of a 1-to-3 scale in order to ensure a clearer distinction among scores
and, therefore, among project choices. Such decisions will vary according to
the number of criteria being applied and, perhaps, by team members’ experience
with the accuracy of outcomes produced by a given approach to screening and
selection.
•
Multiply importance weights by scores to arrive at a weighted score for each
criterion: The weighted score reflects both the value that the team gives each
criterion and the ratings that the team gives each criterion as an output of
the project.
• Add
the weighted scores to arrive at an overall project score: The final score for
each project becomes the sum of all its weighted criteria.
The
pharmaceuticals company Hoechst Marion Roussel uses a scoring model for selecting
projects that identifies not only five main criteria—reward, business strategy
fit, strategic leverage, probability of commercial success, and probability of
technical success—but also a number of more specific subcriteria. Each of these
19 subcriteria is scored on a scale of 1 to 10. The score for each criterion is
then calculated by averaging the scores for each criterion. The final project
score is determined by adding the average score of each of the five
subcategories. Hoechst has had great success with this scoring model, both in
setting project priorities and in making go/no-go decisions. The simple scoring
model has some useful advantages as a project selection device. First, it is
easy to use it to tie critical strategic goals for the company to various
project alternatives. In the case of the pharmaceutical company Hoechst, the
company has assigned several categories to strategic goals for its project
options, including Business strategy fit and Strategic leverage. These
strategic goals become a critical hurdle for all new project alternatives.
Second, the simple scoring model is easy to comprehend and use. With a
checklist of key criteria, evaluation options (high, medium, and low), and
attendant scores, top managers can quickly grasp how to employ this technique.
Limitations of Scoring Models
The
simple scoring model illustrated here is an abbreviated and unsophisticated
version of the weightedscoring approach. In general, scoring models try to
impose some structure on the decision-making process while, at the same time,
combining multiple criteria. Most scoring models, however, share some important
limitations. A scale from 1 to 3 may be intuitively appealing and easy to apply
and understand, but it is not very accurate. From the perspective of
mathematical scaling, it is simply wrong to treat evaluations on such a scale
as real numbers that can be multiplied and summed. If 3 means High and 2 means
Medium, we know that 3 is better than 2, but we do not know by how much.
Furthermore, we cannot assume that the difference between 3 and 2 is the same
as the difference between 2 and 1. Thus in Table, if the score for Project
Alpha is 13 and 19 is the score for Project Beta, may we assume that Beta is 46
percent better than Alpha? Unfortunately, no. Critics of scoring models argue
that their ease of use may blind novice users to the sometimes-false
assumptions that underlie them. From a managerial perspective, another drawback
of scoring models is the fact that they depend on the relevance of the selected
criteria and the accuracy of the weight given them.
In
other words, they do not ensure that there is a reasonable link between the
selected and weighted criteria and the business objectives that prompted the
project in the first place. Here’s an example. As a means of selecting
projects, the Information Systems steering committee of a large bank adopted
three criteria: contribution to quality, financial performance, and service.
The bank’s strategy was focused on customer retention, but the criteria
selected by the committee did not reflect this fact. As a result, a project
aimed at improving service to potential new markets might score high on service
even though it would not serve existing customers (the people whose business
the bank wants to retain). Note, too, that the criteria of quality and service
could overlap, leading managers to double-count and overestimate the value of
some factors.Thus, the bank employed a project selection approach that neither
achieved its desired ends nor matched overall strategic goals.
