Technical Terms Used in Project Portfolio Management (Continued)

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enterprise management

A collection of management principles and techniques focused on helping the organization achieve its highest-level objectives, such as increasing shareholder value. Enterprise management typically includes strategic planning, long-term investment strategy, organizing and resourcing, performance assessment, and leading and directing the organization.

enterprise project management (EPM)

A broad term that refers to processes for improving the conduct and coordination of projects across an enterprise. The term predates project portfolio management (PPM), and, like project management and program management, EPM is mainly focused on "doing projects right," not on doing the "right projects." Thus, though tools to support EPM often include dashboards that can show work progress at various level of detail, project prioritization and portfolio optimization capabilities are generally not included.

enterprise project portfolio management (EPPM)

Project portfolio management applied at the enterprise level; that is, to all projects and programs conducted by the organization. EPPM may be implemented by establishing a hierarchy of project portfolios that are managed both individually and collectively to maximize the value derived by the enterprise.

enterprise resource planning (ERP)

Refers to a process and/or comprehensive software system aimed at centrally managing and coordinating the broad set of activities needed to successfully run a business enterprise, including product planning, material purchasing, inventory control, distribution, accounting, marketing, finance, and HR. Most ERP software products are composed of modules, with each module focused on one business process — some ERP systems include a module for project portfolio management. Customers can purchase as many modules as they require. A single, central repository contains the information needed to support planning and decision making across the various modules and associated business functions. ERP systems typically use or are integrated with a relational database.

An oft cited example illustrating the ERP concept is a system wherein when the sales department records a new customer order information is routed to the inventory and warehousing department to retrieve and package the order, to the finance department to prepare an invoice for billing, and to the manufacturing department for purchased product replacement.

event tree

A graphical representation, similar to a decision tree, showing the sequence of events that might occur following some initial event (the difference between a decision tree and an event tree is that an event tree does not contain branches representing decision alternatives). Event trees are used to understand risk and to identify actions for improving performance. Event trees are most commonly used in accident analysis, where each event is represented by two branches corresponding to the possibility that an event either does or does not occur (e.g., a safety system works or fails). However, event trees may show three or more branches for an event depending on the number of event outcomes needed to distinguish possibilities. Like decision trees, event trees are frequently used in project portfolio management to analyze risk.

expected commercial value (ECV)

A method often used to assign a value to a project that is intended create a new product. Also called, estimated commercial value, ECV represents an application of expected net present value (ENPV). Scenarios are defined to represent possible project outcomes. Each scenario is assigned a probability to indicate its likelihood, and a project value is estimated for each scenario. The expected commercial value is obtained by multiplying each scenario's value by the scenario probability and adding the results. ECV the prioritization metric most often used by project portfolio management tools aimed at new product development projects.

Typically, the scenarios defined for computing ECV are highly simplified. In particular, it is common to represent the product development project as having two stages, which may be represented in a decision tree.

Decision tree for computing ECV

The first stage is the product development stage. Recognizing uncertainty, the probability of the project being technically successful is P_ts. The second stage is the product launch, the success of which is likewise uncertain. The probability of commercial success (assuming the project is technically successful) is P_cs. If D is the development cost, C is the cost of commercially launching the project, and PV is the present value of future earnings for a commercially successful project, then ECV may be computed using the formula:

In reality, of course, technical and commercial success are not yes/no outcomes. There may be varying degrees of technical success and, assuming the product is launched, commercial sales could be anywhere within a range of possibilities. Thus, the simplifications typically used for the calculation of ECV may lead to inaccurate project valuations. Also, because ECV is a simplified version of ENPV, it has the limitations of the more general approach (including the potential for omitting non-financial sources of project value and inadequate accounting of risk and organizational risk tolerance). On the other hand, depending on the application, the simple ECV formula may provide a reasonably adequate method for ranking product development projects.

expected internal rate of return (EIRR)

A modification of the internal rate of return (IRR) sometimes used to prioritize projects (such as new product development projects) whose costs and future cash flows are highly uncertain. In the formula for computing IRR, project costs are replaced by the expected value of initial-year project costs, and project cash flows are replaced by the year-by-year expected value of project cash flows. Thus, The EIRR is the solution to the equation:

In other words, to use the EIRR, alternative project cost and future cash-flow scenarios are defined. For example, the various stages and associated cash flows for the project (such as development, testing, and commercialization) may be represented in a decision tree. Probabilities are assigned to each scenario. The expected value of project costs and expected value of each year's net cash flow are computed by multiplying probabilities by cash flows and adding. The EIRR is then computed as the discount rate that equates the discounted value of expected future cash flows with the expected project cost.

When applied to multi-stage, high-risk projects, the EIRR behaves in an intuitive way. For early stage projects with a low probabilities of ultimate success, expected cash flows tend to be low so the EIRR tends to be low. However, if such a project is funded, its EIRR tends to grow (assuming initial project outcomes are successful) as project costs are sunk and early-stage failure scenarios are avoided. A late stage project (one that has successfully avoided early and middle stage risks) tends to have a very high EIRR. Because of the strong influence of project stage on the EIRR, typical advice is that project-by-project comparisons using EIRR be conducted only for projects at the same stage of development and that separate budgets be established for funding projects within the different stages.

As a project prioritization metric, the EIRR has the advantages and disadvantages described for the IRR, plus the advantages and difficulties associated with assigning probabilities to alternative scenarios.

expected net present value (ENPV)

An enhancement of the net present value approach that explicitly addresses uncertainty. Depending on how it is applied, ENPV can produce estimates of uncertainty in the value of the overall project portfolio and adjust project value to account for risk. It can also be coupled with methods for quantifying the non-financial or indirect components of project value. It is, therefore, a useful tool for computing project and project portfolio value. However, the computations necessary to compute ENPV can be difficult, and the method is often best reserved for very large and risky projects.

With ENPV, rather than calculate a single time-stream of project cash flows and other project impacts, alternative scenarios are defined representing the range of possibilities. Simulation techniques are often used to generate the alternative scenarios, which may be represented in as a decision tree (a graphic structure wherein alternative sequences of choices and outcomes are displayed as branches in the tree and the various paths through the tree represent the alternative scenarios) or event tree (similar to a decision tree, but without nodes and branches representing alternative choices). Probabilities are associated to each scenario in the tree. A project NPV is computed for each scenario, and the ENPV is the probability-weighted sum of the values.

As described under net present value, selecting discount rates is often problematic. If risk is important, risk-adjusted discount rates are often used, with different risk-adjusted rates being appropriate for different scenarios. Alternatively, techniques based on risk tolerance can be used to account for risk (these techniques generally involve using a risk-free discount rate for computing EPNV).

In addition to the difficulties mentioned above related to selecting the discount rate, another limitation of ENPV is that historical data is generally unavailable for estimating probabilities. Thus, probabilities must typically be assigned subjectively.

expected value

Term used to represent the result of a mathematical computation performed using probabilities. Suppose there is an uncertain (random) variable X that may produce various "payoffs" (values). Suppose the possible payoffs are denoted x₁, x₂,..., x_N, and suppose that these alternative payoffs occur with probabilities p₁, p₂,...p_N, respectively. The expected value of the variable is sum of each possible payoff multiplied by its probability:

If instead of there being a finite number of payoffs, the uncertain variable can take on a continuum of possible values (e.g., any value between 0 and 1), then its expected value is computed by weighting the possible values using the variable's probability density function and using integral calculus.

The expected value may be interpreted as the average return one would expect over many "trials" or opportunities for the uncertainty to occur. See expected commercial value and expected net present value for examples of measures based on expected value.

expert system

A computer system programmed to behave like a human with expertise in a particular field or problem area—it uses human knowledge and reasoning techniques to provide advice for solving problems. Expert systems represent an application or subfield of artificial intelligence. Although various methods can be used to simulate the performance of an expert, most expert systems consist of two components: (1) a knowledge base that contains subject matter expertise and (2) an inference engine that applies heuristics or reasoning rules similar to those used by experts in the given field. Expert systems are typically used as an aid to human workers or to supplement some information system. Some project portfolio management tools are advertised as including components that operate as expert systems.

F

figure of merit

A number purporting to represent some measure of the quality of an alternative relative to other alternatives. Figures of merit generally do not actually measure the desirability of alternatives because they ignore or do not adequately represent the attributes of the alternative that are important given the objectives of the decision maker. Nevertheless, figures of merit are often used as a simple (and often misleading) way of distinguishing alternatives. For example, figures of merit are frequently used in advertising, where a high number can make a product seem better than competitors even though the number reported doesn't necessarily measure a characteristic actually valued by consumers. For example, "pixel count" is a figure of merit often used to sell high definition televisions. However, pixel count doesn't directly measure picture quality (instead, more complex measures such as contrast ratio, color saturation, and color accuracy contribute more to perceived picture clarity).

Less analytically sophisticated project portfolio management tools frequently compute figures of merit for projects. Typical, the figure of merit is based on a scoring model that weights and adds scores assigned by the user through a scoring process. The resulting numbers are presumed to relate to project attractiveness but do not indicate the actual values of projects.

force field analysis

A decision-aiding technique that involves identifying the forces for and against a specific alternative. Oftentimes, the conclusions are represented in a diagram, such as that shown below.

Example force field analysis

Force field analysis may include assigning scores to represent the relative strength of the various forces and ranking the alternatives based on total scores. Although force field analysis is attractive due to its simplicity, it suffers from the errors and limitations commonly associated with scoring models.

framing

The process of creating a simplified, conceptual view of some real-world situation for the purpose of facilitating judgments or decisions. Studies in psychology suggest that people create frames naturally whenever they are asked to make judgments. One explanation for this is that people want to minimize their cognitive effort, and framing the situation in a simplified way allows them to limit focus and more easily derive conclusions. Importantly, studies have shown that the way information is presented can strongly influence the way people frame a decision, and the frame that is adopted can make a big difference in the choice that is made. Framing bias has been identified as an important source of error in decision making.

Given the influence that framing has on decisions, it should not be surprising that framing is a major focus of research aimed at improving decision making. Within a formal decision-making process, framing consists of a sequence of steps that ultimately produce a decision model. In this context, the term framing is typically used to describe the steps that establish the basic design for the model, as opposed to the subsequent steps that include implementing the model (e.g., in software) and providing its quantitative inputs. This is the way the term is used, for example, within the dialogue decision process recommended for decision analysis.

With regard to project portfolio management, framing reefers to the process of designing the model to be used to evaluate and prioritize candidate projects. Key questions addressed include the scope of application; how projects will be categorized;, grouped, and otherwise organized; the types of information about projects to be collected; the project benefits to be measured and the metrics to be used; and the logic to be applied to estimate the value of projects and project portfolios.

free cash flow (FCF)

An estimate of a company's internally generated cash flow and the recommended basis for evaluating projects based on financial NPV. The free cash flow from a project represents the project's contribution to money that the company could pay out to shareholders without affecting its existing assets or operations. Calculating a project's free cash flows requires accounting for the impact of taxes and the capital structure of the firm. For example, one approach is to deduct from project revenue operating costs, depreciation, and taxes. Then add deprecation expense back in, subtract capital expenditures not charged against earnings, and subtract changes in net working capital. Some project portfolio management tools compute project financial value based on free cash flows. Experience, however, often shows that the uncertainties associated with the selection of the discount rate overwhelm any additional accuracy gained.

full cost accounting (FCA)

A systematic approach for identifying and reporting the "true" costs required to obtain the benefits that motivate conducting a project. Rather than count only direct, one-time project expenditures, full cost accounting computes the total cost of ownership, including indirect costs as well as the future costs that must be paid throughout the lifecycle of any value-generating products or assets produced by the project. Full cost accounting also includes the opportunity costs incurred from using resources needed by the project. Full cost accounting is essential for project prioritization, as project choices require weighing the true benefits and costs of alternatives.