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Term
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Explanation
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brainstorming
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A group technique for generating ideas and solving problems based on encouraging spontaneous and free-wheeling contributions from participants. Brainstorming was
popularized by A. F. Osborn in the 1950's by his book Principles and Practices of Creative Thinking. Although numerous variations have been proposed, the basic principles of
brainstorming are to encourage the generation of as many ideas as possible, telling participants to withhold criticisms, using new perspectives to generate unusual ideas, and combining
and improving previously identified ideas. Although there is limited evidence that brainstorming provides more or better ideas than from individuals working independently, brainstorming
can be an enjoyable experience for participants and improve teamwork. Some project portfolio management tools include features intended to support
brainstorming.
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business case
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A structured proposal for a project or other business investment intended to support the decision of whether to undertake that
investment. A business case explains why a project is required for the business and what the new product, service, or project outcome is going to be. Typically, a business case will
present project financial metrics, such as the project's estimated net present value (NPV) and return on investment
(ROI). It may also present a cost benefit analysis for the project and identify major project risks and upside opportunities. A business case model is a model, often implemented
as a spreadsheet, for automating the preparation of business cases. Typically, such a model represents cash flow scenarios resulting from candidate projects
and computes NPV or ENPV, plus other project financial metrics.
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C
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capital allocation
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The portion of the capital budgeting process that deals with the allocation of the organization's available financial
resources across business units, programs, and projects. The goal is to
allocate resources in such a way as to maximize the benefits derived from those resources. Capital allocation is difficult in part because of the
many alternative ways that specified budget can be allocated across different entities and because of the difficulty of determining how much benefit would be produced under each option.
Optimizing the allocation of capital is one of the goals of project portfolio management.
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capital budgeting
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The process used by an organization to select and plan the expenditures that it will undertake over some defined, upcoming time period, for example, the next quarter,
next year, or next five years. Such expenditures might include investments in property, plants, equipment, R&D, advertising, and so forth. For project based organizations, a key component of capital budgeting is deciding which specific projects
to conduct and how much to spend on each. Since some expenditures may be quite large, capital budgeting may include determining how to finance those expenditures. These are important
decisions, as they impact risk and the future success of the organization.
Traditionally, to support the selection of projects for the capital budget, organizations have mainly relied on techniques for estimating the incremental financial
benefits available from proposed projects, such as net present value (NPV), internal rate of return (IRR), profitability index (PI), and payback period. Project portfolio
management (PPM) can improve on traditional project selection techniques by accounting for other types of project benefits in addition to
financial benefits and by identifying project portfolios that collectively generate the most value for their costs. Organizations that are implementing PPM typically do so such that
portfolio analyses are completed and recommended project portfolio are available to decision maker as the capital budget is being defined (see this paper
for a description of how PPM is implemented in support of capital budgeting).
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certain equivalent
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A method for valuing projects and other decision alternatives whose outcomes are uncertain. The certain equivalent (also called certainty equivalent or
risk-adjusted value) of an alternative is the amount that the decision maker would be indifferent between (1) having that monetary amount for certain or (2) having the
alternative with its uncertain outcome. The certain equivalent for a project is typically less than its expected
value and depends in part on willingness to accept risk. For example, a risk averse decision maker might have a certain equivalent of $500,000 for a project with equal chances of
yielding $0 and $2,000,000, even though the expected value for this project would be $1,000,000.
Decision theory, which provides a means for encoding a decision maker's preferences in a mathematical utility function, provides a means for calculating the certain equivalent. The utility function U provides a number that quantifies how satisfied the
decision maker would be, depending on the outcome. These utility functions can be indexed by risk tolerance, which quantifies the decision
maker's willingness to accept risk. The greater the decision maker's risk tolerance, the closer the certain equivalent of a gamble will be to its expected value.
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cloud computing
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A term being used to mean different things. Originally, a technology that mimics supercomputing capability (high-speed mathematical calculations) by simultaneously
applying the computing resources available from numerous servers available on a network. The concept is to divide a computational task into pieces and use specialized connections to
allow groups of servers (typically those involving low-cost PC technology) to simultaneously conduct the data processing chores.
Some project portfolio management tool providers, and other software vendors, are using the term in a more mundane way as a synonym
for software as a service (SaaS)—their applications are available via the Internet "cloud," provided from their Web servers and accessed by the
user's Web browser on demand.
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commercialization
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The process and steps for introducing a new product into the marketplace. Decisions around commercialization are often critical to market success, including when,
where, and how to launch the product. Commercialization is often the most expensive component associated with projects designed to create new consumer products, as it typically includes
the cost of advertising, sales promotion, and other costly marketing efforts.
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confidence interval
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A range of possible values defined for an uncertain quantify such that there is some specified probability (e.g., 90%) that the true or actual value of the quantity
lies within the range. The term has a different meaning in statistics, where it describes an interval or range for some statistic computed from a sample of observations from some
population (e.g., the mean value) such that the "true" population statistic can be expected to be located within that interval with specified level of certainty (90%).
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consequence model
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A model for simulating or otherwise relating results or outcomes that people care about to specified actions and conditions. Consequence modeling is the process
of constructing a consequence model and typically involves developing a description of cause-effect relationships or linkages. Various techniques are available for creating consequence
models, and many such models exist and have become well-established within various disciplines and application areas.
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contingency fund
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Resources set aside for expenses associated with unexpected but potential project or other business setbacks. For example, a
contingency fund might be established in the context of project portfolio management (PPM) to provide additional funding to projects that might go over
budget (although the PPM process would include reevaluating such projects to see if the additional funds are warranted and what changes should be made to the project plan in light of a
budget overrun).
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contingent valuation
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A method, generally associated with cost benefit analysis, for assigning monetary values, often to environmental concerns, based on
asking individuals about their willingness to pay to reduce adverse consequences, such as increased levels of pollution or noise, or their willingness to accept sums of money to put up
with such undesirable consequences.
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continuous risk
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A risk with a potential adverse outcome that could take on any number within some range. Continuous risks are characterized by
continuous probability distributions (e.g., probability density functions) that indicate the relative probability of the
possibilities. For comparison, see discrete risk.
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comfort zone biases
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A category of related cognitive biases with the common characteristic that they tend to promote comfortable, rather than reasoned behavior. Examples of comfort zone
bias include status quo bias, supporting evidence bias, and sunk
cost bias.
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correlation
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A statistical relationship between two or more variables such that systematic changes in the value of one variable tend to be accompanied by systematic changes in the
other. For example, as illustrated below, the height of parents and mature children can be shown to be correlated based on plotting parent heights versus child heights on a graph. If
there was no correlation, the plot would appear as dots spread across a roughly circular shape. Instead, the plot appears as an oval shape aligned along approximately a 45 degree line
from the origin of the graph. The shape demonstrates that taller parents tend to have taller children, but the relationship is not perfect, indicating that there are other factors
involved.
A sample correlation plot (parent vs. children height)
Correlation may be quantified by calculating a correlation coefficient, a number between -1 and 1 that indicates the strength and direction of a linear
relationship between two variables. Regression analysis is used to compute coefficient of correlations.
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cost benefit analysis
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A body of knowledge and related analytic techniques for evaluating decisions based on their advantages (benefits) and disadvantages (costs). While many decision-aiding
tools claim to do this, CBA is distinguished by its foundation in theory and how it computes costs and benefits. Like decision analysis
(DA), CBA is essentially a "megatool;" a coherent set of tools for identifying, estimating, and placing monetary values on the impacts of proposed actions and for making
choices.
A distinct characteristic of CBA, compared to many other decision aiding approaches, is that it does not quantify the costs and benefits of actions from the
perspective of responsible decision makers. Instead, CBA measures costs and benefits from the perspective of society at large. The goal is to identify all parties affected by a proposed
action and to estimate the monetary value of the effects it would have on their welfare. The US government began using CBA in the 1930s, and CBA continues to be the mostly widely used
approach for evaluating and prioritizing major projects undertaken by government agencies.
With CBA, costs and benefits are measured relative to a "do-nothing," status quo option. According to CBA, an action should be considered only if its net benefit
(benefit minus cost) is greater than zero. The best alternative, according to CBA, is the one that leads to the greatest net benefit (benefit minus cost).
To determine the monetary value of the impacts of proposed projects, CBA relies on the concept of market prices. In theory, a free market generates prices by balancing
aggregate demand with aggregate supply. Each individual adjusts his or her purchases until the value of the last item purchased is just worth what it cost. Thus, the prices that result
indicate the marginal benefit realized from each individual's consumption of each good.
Following this logic, CBA attempts to use market prices to value project impacts. For example, suppose a project is proposed to clean up a hazardous waste site. CBA
would use the price of similar real estate in the area to estimate the value of the property after cleanup. To value project impacts for which no market exists, CBA uses procedures that
indirectly reference market prices. For example, values for CBA are often obtained based on surveys or interviews with people to estimate their willingness to pay to obtain or avoid the
effects in question.
Although CBA is widely used and based on an internally consistent theory for decision making, the approach is considered controversial based on its limitations.
Perhaps most importantly, applications of CBA frequently conclude that the benefit of proposed government interventions do not justify the costs, and this may be due the fact that some
project benefits simply cannot be addressed through reference to prices that exist in the marketplace. Since CBA does not normally rely on methods for assessing and incorporating expert
judgments, it can fail to account for project outcomes that do not have immediate, tangible, economic implications. Likewise, CBA may fail to address important risks in situations where
there is little or no data for quantifying uncertainties.
Also, CBA ignores the way in which costs and benefits of proposed actions are distributed, a consideration that is often important to decision makers. CBA provides
little opportunity for stakeholders to contribute to the evaluation process, except perhaps, in framing the problem (e.g., identifying alternatives). On the other hand, CBA avoids the
necessity of decision makers providing subjective value judgments. It therefore appeals to some because it appears to be a more value-free guide to decision making. In truth, though,
CBA embodies strong value judgments.
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criterion
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Any quality, property, or characteristic used to assess or compare options in a multi-criteria analysis.
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critical path
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The subset of activities within a project whose duration determines the duration of the project. If a project along the critical path is delayed, then the project will
be delayed.
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D
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dashboard
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A software user interface that, like a dashboard on an automobile, organizes and presents information in a way that is intended to be easy to read. Most modern
software tools employ user interfaces that resemble dashboards, but vendors of project portfolio management (PPM) tools often use the term to ensure
that potential customers recognize the similarity. Typically, and unlike most automobile dashboards, a PPM dashboard is interactive — if the user clicks on an item, more detailed
information is provided. Whether or not the information displayed by a PPM dashboard is "real time," as it is with an automobile dashboard, depends on the tool and the type of
information presented.
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data mining
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The process of extracting from a (usually large) database information to assist decision making. Typically, data mining utilizes sophisticated software to identify
statistical patterns or relationships in online data (data accessible from a network) that may be commercially useful. Information obtained in this way is often used to help
organizations gain a better understanding of their customers and can be used to aid decisions regarding marketing and customer support.
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de Bono Six Hats
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A thinking tool for group and individual decision making. The method is designed to help people make better decisions by looking at the choice from different
perspectives, thereby producing a more comprehensive understanding of issues. The method is described in the book Six Thinking Hats by Dr. Edward de Bono.
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decision analysis (DA)
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A body of knowledge and related analytic techniques for implementing decision theory. DA provides numerous methods and
aids for addressing essentially all the steps involved in decision making, including problem definition, information collection, risk assessment, the identification and screening of
alternatives, the evaluation and selection of alternatives, and the communication of decisions. DA has sometimes been described as a "megatool" for decision making. Unlike most other
decision tools, DA is more like a tool box than a tool. DA is relevant to project portfolio management because it provides a framework for analyzing project selection decisions as well
as specific methods for quantifying project value and addressing project risk.
DA was initially developed in the 1960s and 1970s at Harvard, Stanford, MIT, Michigan, and other major universities. The term "decision analysis" was coined in 1964 by
Ron Howard, a professor at Stanford University. DA is generally considered a branch of the field of operations research, but also has links to management science, economics, systems
analysis and psychology. DA is an area of consulting specialty, and there are journals and a professional society devoted to the topic.
According to DA, a good decision is one that (1) considers the full range of alternatives that are available to the decision maker, (2) accounts for what the decision
maker believes will be the consequences of choosing each alternative, and (3) is consistent with the decision-makers preferences for the various possible decision consequences. In other
words, making good decisions requires knowing what you can do, what you believe, and what you want.
DA employs various procedures and tools for understanding how the actions taken in a decision determine the consequences that may result, as well as the significance
of those consequences relative to the decision-maker's objectives. Analytic models are constructed that represent these two components (a consequence model that simulates decision
outcomes and a value model for measuring the decision-makers preferences for those consequences). Statistical and probabilistic reasoning is used to quantify risk and determine whether
additional information should be collected before committing to a course of action. The models allow sensitivity analysis, a process
that identifies the issues that make the most difference and helps decision makers avoid "paralysis by analysis."
DA is generally focused on two types of decisions: (1) one-time decisions where alternatives must achieve multiple and possibly competing objectives and (2) sequential
decisions where uncertainties and learning play an important role. In both cases, a major task for the decision analyst is constructing the value model that allows the overall
desirability of alternatives to be computed based on how they perform on a set of evaluation measures, or "attributes." Multi-attribute utility analysis
(MUA) is often used to construct the value model. To represent decision timing and uncertainty, sequential decisions are analyzed using decision trees and models known as influence diagrams. Decision analyses of project decisions often
include calculations of project expected net present value (ENPV) and may include valuations based on real options analysis.
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decision model
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An analytic representation (model) of a choice among possible actions or alternatives. A decision model represents the factors relevant to decision making and their
relationships.
Decision models fall into two categories: descriptive and prescriptive (a prescriptive decision model is also called a "normative" model). A
descriptive decision model describes how people typically make decisions and seeks to explain how various factors influence decision-making behavior, including why people often make
sub-optimal decisions.
In the context of project portfolio management, the term decision model usually refers to a prescriptive decision model designed to
indicate how people or organizations should choose based on principles of logic and rationality. For example, a decision model based on decision analysis seeks to identify choices that are logically consistent with the available alternatives, preferences, and beliefs of the
decision maker. Such a model would include performance measures that indicate the degree to which the possible outcomes of choosing each
alternative would achieve each decision objective. In addition to helping decision makers make good choices, some decision models can often be
"mined" to provide additional information and insights, including sensitivities and value of information (VoI).
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decision theory
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A theory of how individuals should make decisions, related to the concept of "rationality" used in economics. Also called subjective expected utility theory, or
simply utility theory, the theory is derived from a set of easily-accepted axioms (hypotheses) defining how rational people behave. For example, one such axiom (transitivity)
states that if a person prefers outcome A to outcome B and outcome B to outcome C, that person should prefer outcome A to outcome C. Another axiom (substitution) states that if a person
is participating in a lottery where the prize is A, and if that person is completely indifferent between receiving prize A and some alternative prize C, then that person should not care
if the lottery is modified by substituting prize C for the equally desirable prize A.
Decision theory shows that if these and a few other axioms are accepted, then it can be proven that there is a mathematical function called a utility function, denoted U, that aggregates all of the different considerations that must be taken into account when deciding among alternatives.
Furthermore, the best alternative (the one that is most preferred) will be the one that maximizes the value of U (or, if there are uncertainties, the expected value of U).
Thus, the major focus of decision theory is estimating the unknown function U. Multi-attribute utility analysis is a set of
techniques for estimating U for the common situation where there are multiple characteristics or "attributes" relevant to determining the desirability of alternatives.
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decision tree
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A graphic representation of a decision problem wherein the alternatives to decisions and possible outcomes to uncertainties are represented sequentially in a tree-like
diagram. A decision tree can be used as an aid for optimizing projects that require a sequence of choices using a computational approach based on dynamic programming. Decision trees are used in many project portfolio management tools as a means for addressing project risk. See the paper
chapter on methods for addressing risk for more information and an example.
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