University of the Cumberlands Reducing a Complex Projects Value Summary

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Question Description

At the top of your paper provide the reference to your Journal Article. Use a scholarly source as described above. Utilizing a non-scholarly/non-peer-reviewed source will result in significant point deduction.

Introduction

Give a brief overview of the chapters 11 and 12 of Kloppenborg covered for the week. Be sure to cite any reference to the text. Include the text in a reference section at the end.

Summary (cite article when appropriate)

Give a summary of the article or case study.

Relevant Points (cite article when appropriate)

Identify the relevant points of the article or case study that coincide with the chapter covered for the week.

Critique

Provide a balanced criticism of the article or case study. What were the strengths and weaknesses of the study? How do the findings support the field of project management? How could it have been altered to better support the field?

Application of Concept(s)

Apply the concept(s) to your career, field, industry, etc. Provide a real world application not a general statement. This section should demonstrate how you can take the findings of this article or case study and utilize them in a practical way in your career, field or practice. Make the application specific to your own experience. Do not just provide a general overview of the usefulness of the findings. Be specific; not general.

References (this does not count toward the required paper length)

Every paper typed in this course should be in APA formatting (title page, reference page, NO abstract page, in-text citations, running head, page numbers, Times New Roman 12 font, 1 inch margins, double-spacing, 3 page content etc…).

Lastly, add the summary of the research paper that you developed about 300 words separately. Do not copy the research paper itself.

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Article Planning, Tracking, and Reducing a Complex Project’s Value at Risk Project Management Journal Vol. 50(1) 71–85 ª 2019 Project Management Institute, Inc. Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/8756972818810967 journals.sagepub.com/home/pmx Tyson R. Browning1 Abstract Uncertainty, risk, and rework make it extremely challenging to meet goals and deliver anticipated value in complex projects, and conventional techniques for planning and tracking earned value do not account for these phenomena. This article presents a methodology for planning and tracking cost, schedule, and technical performance (or quality) in terms of a project’s key value attributes and threats to them. It distinguishes four types of value and two general types of risks. The “high jumper” analogy helps to consider how high the “bar” is set for a project (its set goals) and therefore how challenging and risky it will be. A project’s capabilities as a “jumper” (to clear the bar and meet its goals) determine the portion of its value at risk (VaR). By understanding the amounts of value, risk, and opportunity in a project, project managers can design it for appropriate levels of each. Project progress occurs through reductions in its VaR: Activities “add value” by chipping away at the project’s “anti-value”—the risks that threaten value. This perspective on project management incentivizes generating results that eliminate these threats, rather than assuming that value exists until proven otherwise. Keywords project value, uncertainty, project planning, project monitoring, technical risk, earned value, value at risk Introduction: Why Is Consistent Project Success So Elusive? Despite the presence of a copious body of knowledge about project management practices, completing complex projects to their full scope, on time and within budget, remains extremely difficult. It seems rare that complex projects actually achieve all of their goals. According to the Standish Group’s Chaos Reports (e.g., Standish, 2001) over the past 20 years, about two-thirds of small (up to six people and six months) information technology (IT) projects failed to meet all of their goals—even after receiving 250% of their proposed budget. Including larger projects, over 20% of U.S. IT projects are over budget, and 20% are behind schedule (www.itdashboard.gov). Perhaps even worse, as reported by the U.S. Government Accounting Office (www.gao.gov/ assets/120/117799.pdf), over 70% of U.S. IT projects are poorly planned and/or underperforming. Although equally extensive data on non-IT projects are less available, many large and complex design, development, and construction projects have also exhibited high-visibility problems—for example, the F-35 aircraft (e.g., IDA, 2010), Boston’s Central Artery Tunnel (the “Big Dig”), and Denver International Airport (e.g., Calleam, 2008), just to mention a few. Granted, complex projects are quite challenging. Yet, knowing this, why can’t planners make better estimates of project costs, durations, and results—and why can’t they correctly measure an ongoing project’s progress? A number of potential explanations could contribute to this. First, there is always poor project definition and planning (Pinto, 2013). Second, projects may aim at the wrong targets—setting the wrong goals— because of poor understanding of customers and other stakeholders, or deliberately, to increase the chances of project approval (Flyvbjerg, 2014). Third, when the path to a project’s chosen destination (goals) is complex, novel, dynamic, uncertain, and ambiguous, this translates into not knowing exactly what to do (and when to do it) throughout the project. Fourth, add to this a generally poor understanding of uncertainty and risk throughout many projects, including the failure to apply proper techniques of risk management (Hubbard, 2009) and an unfortunate preference among some for blissful ignorance (Browning & Ramasesh, 2015). Some project managers naively assume that their plans will become reality, only to be surprised by unexpected problems along the way. For 1 Texas Christian University, Neeley School of Business, Fort Worth, TX, USA Corresponding Author: Tyson R. Browning, Texas Christian University, Neeley School of Business, Fort Worth, Texas, USA. Email: t.browning@tcu.edu 72 example, one common problem, the “green until red” status syndrome, has project status as “green” (good) until it suddenly becomes “red” (very bad). What happened to a gradual decay through “yellow” (potential problems)? Problems are often hidden as long as possible, until they are more difficult to solve. Part of this has to do with behaviors and incentives, but another key factor has to do with the absence of appropriate monitoring systems. Fifth, we cannot discount the poor application of project management tools— not just a lack of use, but also misuse and sometimes overuse. Sixth, many project managers fail to account explicitly for rework, which can unexpectedly consume double-digit percentages of project time and cost budgets (e.g., Cooper, 1993; Love, Irani, & Edwards, 2003). Seventh, with the reality of uncertainty and rework, existing project management tools may simply be inadequate for planning, scheduling, monitoring the quality of interim results, integrating sub-project results, and supporting fuzzy tradeoffs in time, cost, and quality. With existing tools, it is actually still hard to tell if a project is really making appropriate progress. This list could go on, but it already motivates the need for better methods and practices. This article presents an approach to conceptualizing, planning, and monitoring project value and the risks to it. The approach does not solve all of the problems in the preceding paragraph, but it does address several—specifically, improving project definition and planning, clarifying the implications of project goals, including appropriate activities at appropriate times in the project, accounting for uncertainties, providing improved monitoring of project status, making accommodations for rework, and supporting tradeoffs in project time, cost, quality, value, risk, and opportunity. The approach elaborates on techniques originally developed by Browning et al. (Browning, 2014; Browning, Deyst, Eppinger, & Whitney, 2002)—two papers strongly recommended as background reading. After briefly discussing the foundational concepts of project quality, value, goals, uncertainty, risk, and opportunity, this article notes some shortcomings of the conventional earned value management (EVM) method. Using the analogy of a “high jumper” helps consider how high the “bar” is set for a project, and therefore how challenging and risky it will be. Taking a project’s capabilities as a “jumper” (to clear the bar and meet its goals) into account helps determine how much of the project’s value is being put at risk by uncertainties about its outcomes. By understanding the amounts of value, risk, and opportunity in a project, project managers can design and tailor the project for appropriate levels of each. The approach is also helpful for comparing projects in terms of difficulty. Project progress occurs through reductions in the portion of its value being put at risk. Activities add value by chipping away at the project’s “anti-value,” the consequential uncertainties (risks) that threaten value. From this perspective, projects must prove their value through progress in risk reduction rather than assume that value exists until proven otherwise. This article describes these concepts Project Management Journal 50(1) and presents a detailed example of their application to a drone aircraft development project. Foundational Concepts An approach for planning, tracking, and reducing a project’s value at risk requires a clear definition and overview of some foundational concepts, including work quality, project value, uncertainty, risk, opportunity, and value at risk (for further details, see Browning, 2014, and Browning et al., 2002). Interim Work Quality In a classic paper about rework in projects, Cooper (1993) highlighted two key drivers of project progress: the quality of activities’ results and the length of time it takes to discover any problems with them. Most project planning and tracking methods assume that all work is done correctly. Operations managers call this 100% yield, which can be difficult to achieve in well-understood, repetitive activities, so it is even less realistic for the activities in complex, novel projects. Moreover, because it is possible to start work based on assumptions (in lieu of complete and accurate information), value-adding activities often experience a “garbage in, garbage out” problem—beginning work without a sure foundation and then having to fix things later (Browning, 2003). Meanwhile, their successor activities start, assuming complete and accurate inputs from their predecessors. The longer it takes to discover any problems (Cooper’s second rework driver), the more the flawed results will have undermined downstream activities, thereby amplifying the cascade of rework and its cost and schedule impacts (Browning & Eppinger, 2002). Cooper thus distinguished real progress in projects from perceived progress, with the former always lagging behind the latter. Undiscovered rework accounts for the difference between them. Real progress and “added value” depend on results (accomplishments), not “doings” (activities). Most project management methods and software tools do not address these effects; they focus on activities planned and done rather than on the value of their results. What Is Project Value? A project’s value1 depends on its actual result, not just on what activities it does. The value of a project’s result depends on its stakeholders’ preferences for a combination of attributes, called project value attributes (PVAs).2 Stakeholders generally want more of some PVAs (such as features, functions, reliability, size, speed, availability, design aesthetics, etc.) and less of others (such as price, operating cost, weight, project duration, delivery time, etc.). Different stakeholders have competing preferences for some attributes—such as a customer or client who wants a lower price versus employees who want higher wages and shareholders who want greater profitability. PVAs may also include stakeholder objectives such as the creation of new business opportunities or the enlargement of potential value for future projects. Overall project value is a Browning 73 Table 1. Four Types of Project Value Actual value A project’s final value at completion, based on how things turn out and where the project ends up Desired value The value that stakeholders ideally desire (explicitly and tacitly) from a project Goal value (GV) The value of a project that meets its chosen goals/ targets/objectives/requirements Likely value (LV) The estimated value of an incomplete project, given its resources and capabilities composite of the relevant PVAs. Most of a project’s value depends on a few (e.g., 5–10) salient PVAs. Major problems with any of these may doom a project. However it is ascertained, a project’s actual value cannot be known for sure until the project is complete and its result delivered (and sometimes not even until well after that). Until then, measures of project value are just estimates, forecasts, or predictions, fraught with uncertainty. Four Types of Project Value It is helpful to distinguish four types of project value (see Table 1): actual, desired, goal, and likely (Browning, 2014). A project’s actual value is its final value at completion, based on how things turn out and where the project ends up. Prior to that point, we can distinguish three other types of project value. First, a project’s desired value is the value its stakeholders ideally desire (explicitly and tacitly). Because stakeholders may not know exactly what they want until they see it—and may otherwise have difficulty articulating their desires and preferences—project planners can only do their best to estimate a project’s desired value with improved stakeholder understanding. Second, as project planners set goals for a project, they establish a goal value (GV), which may or may not match the project’s desired value. GV is the value of a project that meets its chosen, explicit goals (which may or may not align with stakeholders’ ultimate desires). Some projects aim at the wrong targets (choose the wrong goals) by mistake; others admit early on that their aims are short of what stakeholders might ideally want; others settle on a compromise among competing stakeholders. Either way, a project’s GV and its desired value may not be identical. Third, depending on the resources and capabilities of the performing organization, an incomplete project has a likely value (LV), a forecast of where it is likely to end up, which could be more or less than its GV. As a side point, note that a project’s actual value may evolve post-completion. For example, a project may lead to greater-than-expected benefits, as in the case of the Sydney Opera House, which was initially deemed a failure but ultimately gained accolades. On the other hand, Motorola’s Iridium satellite project met its goals but saw its value plummet soon afterward as desired value quickly shifted. In this article, we focus on project GV and LV, implicitly assuming that desired value is fairly well known and stable, although the approach described herein can still be useful in situations with dynamic value. Uncertainty P<1 Opportunity (+) Risk (–) Certainty P=1 Issues Figure 1. Project events categorized as certain or uncertain, and furthermore in terms of a positive or negative effect on a project’s value. Project Goal Value (GV) A project sets a goal for each PVA. (For simplicity, we use the term goals as a near synonym for a project’s targets, requirements, and objectives.) Meeting these goals will provide some amount of value, the project’s GV. For example, if a project develops a product with a particular combination of PVAs set at particular levels, it might expect to sell a number of units at a particular price, generating revenue. Falling short of the goals causes a value loss, either directly through contractual penalties or indirectly in terms of lesser revenue from future sales, whereas exceeding a goal may bring value rewards, either directly via contractual bonuses or indirectly from increased future revenue. Marketers and business developers commonly plan business cases around such projections. Overall project GV depends on a combination of the GVs of each PVA. The combination may occur in various ways, each with pros and cons. Later in the article, a detailed example compares two approaches to determining a project’s overall value as a function of the values of its PVAs. Project Likely Value (LV) Prior to its completion, a project has many potential outcomes—ranges of eventual, actual values for each PVA. The positions and sizes of these ranges, and the relative likelihoods of the outcomes within them, depend on the project’s resources and capabilities. We quantify a project’s LV as the probabilistically weighted average (expected value or mean) of its distribution of potential outcomes. As with GV, the LVs of all PVAs combine to determine a project’s overall LV. Uncertainty, Risk, and Opportunity A project’s planned activities imply a chosen path toward its goals. This path is fraught with uncertainties—events that might or might not occur (probability <1), some of which could interdict the accomplishment of the project’s goals and thereby affect its LV (Figure 1). Consequential uncertainties yield opportunities or risks depending on if they affect a project’s LV positively or negatively, respectively. 74 Project Management Journal 50(1) Better outcomes Additional value opportunity GOAL Portion of project’s goal value at risk Project outcomes Project’s goal value Worse outcomes Figure 2. A distribution of project outcomes, some of which exceed the goal and others of which fall short. Project Value at Risk (VaR) The left side of Figure 2 shows a distribution of project value outcomes. The greater the uncertainty in the project’s outcomes, the wider this distribution will be. Increasing knowledge and predictability of project outcomes narrows the distribution. Increasing a project’s resources and capabilities will typically shift the distribution upward, toward better outcomes. Some of the project’s outcomes meet or exceed the GV “bar,” whereas others fall short. The upside and downside of this uncertainty drive opportunity and risk, respectively. Outcomes that exceed the goal may provide some additional value opportunity, whereas outcomes that fall short put the project’s GV at risk. The actual amounts of opportunity and risk depend not only on the shape of the outcome distribution but also on the rewards and penalties of the outcomes. For example, in a new laptop computer with a goal of a 15-hour battery life, missing the goal by 15 minutes will not hurt as much as missing it by 5 hours, so the fact that both of these potential outcomes fail to meet the goal does not imply that they carry equal risk. The fact that the distribution of possible outcomes is wide enough to include an outcome 5 hours below the goal puts the project’s value at much greater risk than the outcome of only 15 minutes less. Later, we will quantify these differences to find a project’s overall value at risk (VaR). Some Problems With Earned Value Management (EVM) EVM is perhaps the most prominent method for planning and tracking project progress mentioned in A Guide to the Project Management Body of Knowledge (PMBOK Guide®) – Sixth Edition (Project Management Institute, 2017) and a number of other project management publications (e.g., Fleming & Koppelman, 2010; Project Management Institute, 2011), and it is the subject of dedicated conferences. EVM provides a clear boost in project management capability and maturity over the lack of any formal method. In light of the concepts and challenges mentioned above, however, EVM has significant shortcomings. First, despite some exceptions (e.g., Solomon & Young, 2007), most EVM implementations do not account for the quality or performance level of deliverables. Second, in taking a deterministic view of activity durations and costs, EVM does not account for their uncertainty, variation, and unpredictability—thus ignoring risk and opportunity as well. Third, EVM tracks what Cooper (1993) called “perceived progress,” assuming that completed activities have perfect quality outputs and will not experience rework (even though rework has been shown to cause double-digit percentage overages in cost and duration). Fourth, EVM takes a linear view of activity progress, failing to account for the common situation where “the last 10% of an activity (or a project) takes half the time” because the tough parts were put off. The method does not force users to distinguish between easy and hard activities (or parts of activities), giving equal credit for both. Some versions of EVM even give half credit just for starting activities, making it easy to “game” project status simply by beginning a lot of work (often prematurely, which further increases the risk of rework). Fifth, the “value” managed by EVM does not clearly correspond to any of the four types discussed earlier (Table 1). EVM does not account for stakeholder value preferences, the value of new information about project outcomes, or a project’s VaR. Sixth, the value added by activities is partly a function of when those activities occur in a project, regardless ...
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School: University of Virginia

Complete.

Running Head: JOURNAL CRITIQUE

1

Journal Critique
Institutional Affiliation
Date

JOURNAL CRITIQUE

2

Browning, T. R., (2019). Planning, Tracking, and Reducing a Complex Project's Value at
Risk. Project Management Journal, 50(1), 71-85.
Introduction
The eleventh chapter of the book focuses on the establishment of a risk management
plan which will focus on the potential risks experienced during project management.
Furthermore, the chapter provides information on the methods which can be employed to
identify the risks as well as how to analyze those risks. Plan risk management, as defined in
the book, focuses on the process where the activities which are associated with risk
management will be conducted. The risk management will be undertaken in situations where
the project will face a potential risk, which will hinder the project's success (Kloppenborg,
Anantatmula, & Wells, 2019).
The authors further established the meaning of project risk, which can be described as
an event or something that will hinder the project success since it will harm the project team
and its abilities. Project managers will formulate a risk management plan which will feature a
mitigation strategy and risks that will be monitored and regarded as the main priority. Further
information provided by the authors under the identification of risk will focus on information
gathering, the review of the information gathered, root cause analysis, and the registration of
the risk. The information provided under risk analysis focuses on qualitative and quantitative
analysis, which will be conducted and the determination of the cause and effect of the risk.
The last information provided towards the end of the chapter will focus on plan risk
responses.
The twelfth chapter focuses on project quality and what will be featured under the
project quality management plan. At the beginning of the chapter, the authors' information
revolves around risk and quality. One concept which has been featured in this particular

JOURNAL CRITIQUE

3

chapter will focus on the contemporary quality concepts which will be developed and will
feature total quality management, quality gurus, lean six sigma as well as other ideas
(Kloppenborg, Anantatmula, & Wells, 2019).
Other in...

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