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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 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 promotes
teamwork and can be an enjoyable experience for participants. Some project portfolio management tools include features intended to support
brainstorming.
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breakthrough project
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A project that requires or produces a significant or radical change for the business. An example would be a project aimed at
achieving a major competitive advantage by leapfrogging competitor products. Breakthrough projects may involve new technologies or processes with the potential of making existing
products or processes obsolete.
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bubble diagram
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Also called a bubble chart, a graphic display that uses color coding, shapes, and other visual cues to indicate how items differ in terms of multiple
attributes. Project portfolio management tools often include capability to display bubble diagrams wherein candidate projects are represented by the bubbles. The x and y axes represent key project attributes, and bubble size and/or color indicate other attributes. The
displays are used for portfolio mapping, and indicate the distribution of available projects across various dimensions. Oftentimes, tool
vendors argue that the bubble charts help suggest projects to add or remove from the portfolio in order to improve portfolio balancing,
although it is rare to find explanations for how to measure good versus bad balance on a bubble chart.
Sample Bubble diagram
A weakness of bubble charts is that executives often find them complex and not very helpful for project selection. In truth, bubble charts are not decision models, but simply informational displays.
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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
describe the consequences of doing versus not doing the project, forecast cash flows, and present financial summary 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. The model makes it easy to input alternative cash flow scenarios, for example, optimistic, most likely, and
pessimistic scenarios, while showing the impact NPV and/or computing ENPV, along with 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 the expenditure of 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 each proposed project, expressed, for example, as a 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 the recommended project portfolio is identified for decision makers 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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Relates to a method for valuing projects and other decision alternatives that involve risk. 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 the decision maker's 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, the term referred to 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 on
demand via the user's Web browser.
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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 somewhat 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 (e.g., 90%).
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conjoint analysis
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A method often used in the field of market research to quantify how people value the various features or attributes that make up a product or service. Subjects are
asked to state their preferences for paired comparisons of products defined by two or more attributes, for example, a low cost computer
with 2GHz processor, 512 MB RAM, and a 15 inch monitor versus a higher cost computer with 4 GHz processor, 2 GB RAM and a 21 inch monitor. In some versions, the subjects indicate their
strength of preference, for example, on a 1 to 10 scale. The approach requires answers to be provided for many such questions, however, since most people find the questions easy,
conjoint studies can often be conducted by mail survey or over the internet.
The data obtained from a conjoint analysis may be used to derive a utility function for quantifying customer preferences for
products with various combinations of attributes. A specific mathematical form for the utility function is assumed (e.g., additive) and the data from the conjoint analysis is used to
set the parameters of the function so as to best fit the data. The utility function may then be used to predict future customer choices. The technique may be used to quantify
preferences for items other than products, and some project prioritization tools use conjoint analysis as a method for ranking projects.
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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. Project
portfolio management tools that prioritize projects based on the likely consequences of those projects contain consequence models. 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 for 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 to consequences based on asking individuals
about their willingness to pay to obtain desired outcomes or to reduce or willingly accept adverse outcomes. Contingent valuation is often used to value environmental consequences such
as increased levels of pollution or noise.
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continuous risk
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A risk with a potential adverse outcome within a range of possibilities. 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 their effect is to promote behavior that is comfortable rather than reasoned. 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 on a graph parent heights versus child heights. 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 coefficient of correlation—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 correlation coefficients.
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cost benefit analysis
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A decision making theory and collection of related analytic techniques for evaluating decisions based on comparing benefits and costs. While many decision-aiding tools
claim to do this, CBA is distinguished by its foundation in theory and by its rigorous process for computing costs and benefits. Like decision
analysis (DA), CBA is essentially a "megatool;" a coherent set of concepts and techniques that may be used to identify, estimate, and place monetary values on the impacts of
proposed actions.
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. Thus, CBA is most applicable for government decision
making. CBA requires identifying all parties affected by a proposed action and estimating the monetary value of the effects the action 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 formally 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 benefit gain (i.e., the alternative with the largest net
benefit).
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 costs. 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
might use real estate prices to estimate the value of the cleanup effort. The market values of similar properties close to and far from the waste site would be compared to determine the
value loss suffered by those living near to the site. Removing the site would, presumably, eliminate the property value differences and create this much added value for home owners.
This monetary value could be compared to the costs of the project to determine whether the project should be conducted. 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 compelling theory for decision making, the approach is considered by many to be controversial. CBA ignores the way in which
the costs and benefits of proposed actions are distributed, a consideration that is often important to decision makers. Also, numerous applications of CBA have demonstrated that the
approach frequently concludes that the benefits of proposed government interventions do not justify the costs. This result 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 lacking data for quantifying uncertainties. 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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cost of capital
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The cost a company effectively pays in order to obtain cash (from debt and equity sources) to finance its operations. It is the return that is required on company
investments to compensate the investor, taking into account the risk involved. The cost of capital is generally calculated on a weighted average basis (see WACC).
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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 an activity 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 user interface for a software package that, like a dashboard on an automobile, organizes and presents information in a way that is intended to be easy to read and
absorb. 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. However, 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 making decisions based on decision theory. DA provides numerous
methods and aids for addressing essentially all the steps involved in formal decision making, including problem definition, information collection, risk assessment, the identification
and screening of alternatives, the evaluation and selection of alternatives, and the communication and implementation 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. A collaborative, step-by-step process for applying DA within organizations, called the Dialogue Decision Process, was developed in the late 1970s by SRI
International and has been refined by the Strategic Decisions Group. DA is an area of consulting specialty, and there are journals and a professional society devoted to the topic.
Dialogue Decision Process
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-maker's preferences for those consequences). 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, 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 relative to 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 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 support system (DSS)
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A computer software program and associated database intended to aid managers in making decisions. A DSS may include a decision
model, simulation programs, and algorithms. Alternatively, a DSS may merely provide information
useful for supporting decisions. The term is an old one that is not used much now, as its definition is so broad as to not be particularly useful. A project
portfolio management tool is an example of a DSS.
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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 and denoted U, that will aggregate 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).
The major focus of decision theory is estimating the 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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