Upfront Analysis Research Articles

Why projects fail? How contingency theory can provide new insights - comparative analysis of NASA's climate orbiter

When important projects fail, the investigation is often focused on the engineering and technical reasons for the failure. That was the case in NASA’s Mars Climate Orbiter (MCO) that was lost in space after completing its nine-month journey to Mars. Yet, in many cases the root cause of the failure is not technical, but managerial. Often the problem is rooted in management’s failure to select the right approach to the specific project. The objective of this paper is to enrich our understanding of project failure due to managerial reasons by utilizing di!erent contingency theory frameworks for a retrospective look at unsuccessful projects and perhaps more important, potential prevention of future failures. The evolving field of project management contingency theory provides an opportunity at this time to re-examine the concept of fit between project characteristics and project management, and o!er deeper insights on why projects fail. After outlining several existing contingency studies, we use three distinct frameworks for analyzing the MCO project. These frameworks include Henderson and Clark’s categorization of change and innovation, Shenhar and Dvir’s NTCP diamond framework, and Pich, Loch, and De Meyer’s strategies for managing uncertainty. While each framework provides a di!erent perspective, collectively, they demonstrate that in the MCO program, the choices made by managers, or more accurately, the constraints imposed on them under the policy of ‘better, faster, cheaper’, led the program to its inevitable failure. This paper shows that project management contingency theory can indeed provide new insights for a deeper understanding of project failure. Furthermore, it suggests implications for a richer upfront analysis of a project’s unique characteristics of uncertainty and risk, as well as additional directions of research. Such research may help establish new and di!erent conceptions on project success and failure beyond the traditional success factors, and subsequently develop more refined contingency frameworks. The results of such research may enable future project managers to rely less on heuristics and possibly lead to a new application of ‘‘project management design.” !2009 Elsevier Ltd and IPMA. All rights reserved.

Perspectives on Learning and Business Plans—More in Common Than Meets the Eye

In 2010, Palo Alto Software performed a survey of 2877 people and found that those who completed business plans were nearly twice as likely to successfully grow their businesses or obtain capital as those who did not write a plan.1 Thus, a business plan increases individuals' likelihood of success.2,3 Along the same vein, why would you embark on developing a skill or competency or better some aspect of your learning without developing a learning plan? The self-regulated learner would argue that you would not, and although a learning plan does not guarantee success, it can increase the likelihood of achieving your learning goals.4,–6 This article explores the components of structured learning plans, illustrating that they have more in common with business plans than first meets the eye. Whether you are in a mentor role, helping learners think through a plan, or a learner role, trying to change or redirect your own learning, a plan can provide an organized way of approaching the task. The motivations behind the development of a business plan are myriad but often revolve around issues of starting or redirecting a venture and addressing an issue of limited resources or expenditure of capital in the form of equipment, material costs, and development of a new technology or renovation. In all instances, the underlying theme is the management of change. Learning plans also focus on change. They frequently revolve around such areas as development of a new skill, mastery of a new subject, or addressing a targeted area for improvement. In other words, learning plans often focus on self-regulated learning, “renovating” oneself in a targeted learning area and trying to address the issue of one's personal limitations. The advantages to both types of plans lie in the formal analysis of one's current situation, determining pros and cons of initiating change, assessing requisite resources, creating action, and monitoring progress throughout implementation. The goal is to create a situation that affords one the best chance to succeed. Cohn and Schwartz7 outline typical components of a business plan in their review on the subject for a physician leadership audience. The table compares the components of a learning plan to a business plan and provides an example of how the process might play out. Although the components are presented in a numerical order, many of these may be completed simultaneously and at times in different order. TABLE Typical Components of a Business Plana Versus Learning Plan

On building architecture-centric product line architecture

Software architects typically spend a great deal of time and effort exploring uncertainties, evaluating alternatives, and balancing the concerns of stakeholders. Selecting the best architecture to meet both the functional and non-functional requirements is a critical but difficult task, especially at the early stage of software development when there may be many uncertainties. For example, how will a technology match the operational or performance expectations in reality? This paper presents an approach to building architecture-centric product line. The main objective of the proposed approach is to support effective requirements validation and architectural prototyping for the application-level software. Architectural prototyping is practically essential to architecture design and evaluation. However, architectural prototyping practiced in the field mostly is not used to explore alternatives. Effective construction and evaluation of multiple architecture alternatives is one of the critically challenging tasks. The product line architecture advocated in this paper consists of multiple software architecture alternatives, from which the architect can select and rapidly generate a working application prototype. The paper presents a case study of developing a framework that is primarily built with robust architecture patterns in distributed and concurrent computing and includes variation mechanisms to support various applications even in different domains. The development process of the framework is an application of software product line engineering with an aim to effectively facilitate upfront requirements analysis for an application and rapid architectural prototyping to explore and evaluate architecture alternatives.

Measuring Readiness for RFID Adoption: Reflection from Iranian Supply Chain Companies

In order to benefit from RFID adoption, entire RFID infrastructure must first be established and supply chain companies should conduct considerable up-front analyses to assess their readiness. The purpose of this study is to survey the readiness of supply chain companies in Iran for RFID adoption. Therefore, facilities, conditions and necessary readiness for the successful adoption of RFID systems in Iranian grocery supply chain companies have been investigated. The study involved survey data from 89 Iranian grocery supply chain companies. The findings reveals that grocery supply chain companies in Iran are overall not ready for RFID adoption and to adopt these systems successfully; in the first step, technological, organizational, and environmental problems and challenges of supply chain companies must be wiped out. This subject, besides Iranian grocery supply chain companies, could be also extended to other supply chain companies in Iran. Key words: Radio frequency identification, Readiness for RFID adoption, Grocery supply chain. INTRODUCTION Radio frequency identification (RFID) is a small tag containing an integrated circuit chip and an antenna, and has the ability to respond to radio waves transmitted from the RFID reader in order to send, process, and store information. The RFID system consists of three basic components: a tag, a reader, and back office data pro-cessing equipment. The tag contains unique identification information of the item to which it is attached; the reader emits and receives radio waves to read the information stored in the tag, and the data-processing equipment processes all the collected data (Wu et al., 2006; Thornton, 2006; Sandip, 2005). At the present state of technology, simultaneous communication at a rate of 1,000 tags per second is possible, with an accuracy that exceeds 98% (Hunt et al., 2007). RFID technology is considered as ‘‘the next big thing’’ in management (Wyld, 2006, Ashon and Ilyas, 2008) and was introduced as one of the top ten technology in the world in 2004 and 2005 (Janz et al., 2005). In recent

Risk assessment of interruption times affecting domestic and non-domestic electricity customers

Legislation defined to protect domestic and non-domestic customers from long durations of interruptions includes additional requirements to system’s reliability-related performance that distribution network operators (DNOs) must consider in planning the operation and maintenance process of power supply systems. DNOs are required to restore the supply to interrupted customers that fall into “unprotected” customer class within a given period of time, otherwise penalties are applied. In order to meet these requirements, comprehensive strategies must be defined based on upfront analyses. Accordingly, this paper proposes a deterministic algorithm for estimating DNOs’ risk of experiencing interruptions with durations above imposed targets. Besides the Regulator-defined legislation, security of supply requirements are engaged in the development of the proposed methodology. Failure analysis of network components is used to identify interrupted customers that are grouped into power demand classes such that the duration of interruptions can be addressed following the security of supply requirements. Moreover, the penalty times defined by the Energy Regulator are engaged in the analysis and used as thresholds to quantify the penalty risk that DNOs are exposed to.The proposed methodology is applied to a typical UK distribution system, whose average reliability performance is also considered in the analysis.

Feasibility analysis and proof of concept for thermoelectric energy harvesting in mobile computers

Thermoelectric (TE) energy harvesting in compact microelectronic systems necessitates detailed upfront analysis to ensure unacceptable performance degradation is avoided. TE integration into a notebook computer is empirically investigated in this work for energy harvesting. A detailed finite element model was constructed first for thermal simulations. The model outputs were then correlated with the thermal validation results of the selected system. In parallel, a commercial TE micro-module was empirically characterized to quantify maximum power generation opportunity from the combined system and component data set. Next, suitable “warm spots” were identified within the mobile computer model to extract TE power with minimum or no notable impact to system performance, as measured by simulated thermal changes in the system. The prediction was validated by integrating a TE micro-module to the mobile system under test. Measured TE power generation density in the vicinity of the heat pipe was 1.26 mW/cm3 using high CPU load. The generated power scales down with lower CPU activity, and will scale up in proportion to the utilized opportunistic space within the system. The technical feasibility of TE energy harvesting in mobile computers has hence been experimentally proven for the first time.

Weaponizing Anthropology: Social Science in Service of the Militarized State (review)

David H. Price, Weaponizing Anthropology: Social Science in Service of the Militarized State. Petrolia and Oakland, CA: CounterPunch and AK Press, 2011. 219 pp. With dedications to Laura Nader, David H. Price delivers a powerful anthropological manifesto. From Nader, he acknowledges, we have been taught to study up and confront power. More, as Weaponizing Anthropology proves an example of, Nader tells us that this means that we will have to work harder than those aligned with power. In Price's upfront analysis, the powerful are the social scientists behind the Human Terrain of the US armed forces who have adapted (should I say abducted?) anthropology for their counterinsurgency warfare ambitions. As Price shows beyond any doubt, their ambitions are intellectually soiled, representing a kind of anthropology that without self-insight is a bad version of the obsolete cataloguing exercises of Peter Murdock and the like-minded. Moreover, the Human Terrain anthropologists have the power, backed by secrecy and military might, to ignore the usual academic standards of peer-review, critical reflection, and intellectual openness. In short, they are as intellectually closed as the societal and cultural descriptions they present. At the same time, military people today claim the role as global humanitarians. Here the Human Terrain is seen as merely a tool in the global war on terror, with mainstream US media acting as cheerleaders for the program (95). In the process, ethical research standards as we have come to know them no longer exist. Torture has been accepted by the powerful as they set out to defend Western liberal democracy, but also, it seems, as a tool in the very production of ethnographic data. In the warzone, the Human Terrain proponents say, the anthropologist has to finish his interview within no more than seven minutes, before sniper attacks can be expected. How deep an understanding, rapport or trust develops in 7 minutes? asks Price (158), adding that uniformed Human Terrain social scientists have killed and even cold-bloodedly executed hand-cuffed informants, and they have themselves been killed in action-slash-fieldwork. Price exposes real ethical and political consequences for anthropology, and in his critical assessment he revisits well-known anthropological debates. Even if the colonial legacy in anthropology has been discussed endlessly, Price's work proves this to be perhaps more important than ever. Just as it was becoming passe to remark on anthropology's status as colonialism's wanton stepchild, he states in the opening sentence of the book, George Bush's Terror War rediscovered old militarized uses for culture, and invigorated new modernist dreams of harnessing anthropology and culture for the domination of others. Here is again a political of global ambitions that presents a fundamental ethical dilemma for the everyday work of the anthropologist. But such a is not only ethically indefensible and politically questionable. It is also epistemologically faulty, as Price shows, because it is an anthropological that creates something misshapenly Frankenstinean (182). A rich history of anthropological thought, debate, and controversy is glossed over as something completely homogenous, a manual set for use, and in the process profound epistemological differences are (183). Anthropology becomes a monster, and Price expends quite some effort in identifying the intellectual roots for this monstrous project. Even with well-respected, old-time anthropologists, Price can delineate how the Human Terrain anthropologists not only misrepresent their thoughts, but many do it in ways that are pure plagiarism. No references are given, context is removed, and the usual peer-review process is made nearly impossible. Anthropology becomes a closed business. Price does a great job in identifying and disclosing all those misquoted sources. Victor Turner is one such old-time giant whose writings are shamelessly decontextualized and cannibalized by the Human Terrain anthropologists. …

Early failure prediction in feature request management systems: an extended study

Online feature request management systems are popular tools for gathering stakeholders’ change requests during system evolution. Deciding which feature requests require attention and how much upfront analysis to perform on them is an important problem in this context: too little upfront analysis may result in inadequate functionalities being developed, costly changes, and wasted development effort; too much upfront analysis is a waste of time and resources. Early predictions about which feature requests are most likely to fail due to insufficient or inadequate upfront analysis could facilitate such decisions. Our objective is to study whether it is possible to make such predictions automatically from the characteristics of the online discussions on feature requests. This paper presents a study of feature request failures in seven large projects, an automated tool-implemented framework for constructing failure prediction models, and a comparison of the performance of the different prediction techniques for these projects. The comparison relies on a cost-benefit model for assessing the value of additional upfront analysis. In this model, the value of additional upfront analysis depends on its probability of success in preventing failures and on the relative cost of the failures it prevents compared to its own cost. We show that for reasonable estimations of these two parameters, automated prediction models provide more value than a set of baselines for many failure types and projects. This suggests automated failure prediction during requirements elicitation to be a promising approach for guiding requirements engineering efforts in online settings.

SOFC Power Generation from Biogas: Improved System Efficiency with Combined Dry and Steam Reforming

Solid oxide fuel cell systems (SOFC) can improve the efficiency of electrical power generation from biogas compared to small scale CHP units. The SOFC requires a reforming step converting biogas into synthesis gas (hydrogen and carbon monoxide). . Dry reforming of methane with the carbon dioxide contained in biogas is a promising approach to produce high caloric SOFC fuel gas, but carbon formation is predicted for all typical biogas compositions. To avoid carbon formation and to compensate fluctuating biogas compositions additional supply of steam is essential leading to a combined dry and steam reforming. The paper describes the system approach, upfront analysis, biogas monitoring results, process unit design and evaluation as well as the system setup to demonstrate a biogas to electricity route with a gross efficiency of 45 % using a commercial 1 kW SOFC stack.

Working effectively with non-state actors to deliver education in fragile states

This viewpoint uses evaluation reports from Nepal, Afghanistan, and Yemen in order to learn lessons about how donors and governments can work more effectively with non-state actors to deliver education in fragile states. The evaluation framework draws on the Development Assistance Committee principles for good international engagement in fragile states. The analysis concludes that a more effective partnership requires better regulation of non-state actors, increased efforts to build community capacity to hold schools and local government to account for the quality of services, and more upfront and systematic analysis of the conflict dynamics of investment in the education sector.

A report on the XP workshop on agile product line engineering

Software Product Line Engineering (SPLE) promises to lower the costs of developing individual applications as they heavily reuse existing artifacts. Besides decreasing costs, software reuse achieves faster development and higher quality. Traditionally, SPLE favors big design upfront and employs traditional, heavy weight processes. On the other hand, agile methods have been proposed to rapidly develop high quality software by focusing on producing working code while reducing upfront analysis and design. Combining both paradigms, although is challenging, can yield significant improvements. In this workshop, we discussed the challenges, the research questions and the tradeoffs that need to be addressed for such an integration to enjoy success.

Two decades of Ripple Down Rules research

AbstractRipple Down Rules (RDR) were developed in answer to the problem of maintaining medium to large rule-based knowledge systems. Traditional approaches to knowledge-based systems gave little thought to maintenance as it was expected that extensive upfront domain analysis involving a highly trained specialist, the knowledge engineer, and the time-poor domain expert would produce a complete model capturing what was in the expert’s head. The ever-changing, contextual and embrained nature of knowledge were not a part of the philosophy upon which they were based. RDR was a paradigm shift, which made knowledge acquisition and maintenance one and the same thing by incrementally acquiring knowledge as domain experts directly interacted with naturally occurring cases in their domain. Cases played an integral part of the acquisition process by motivating the capture of new knowledge, framing the context in which new knowledge would apply and ensuring that previously correctly classified cases remained so by requiring that the classification of the new case distinguish it from the system’s classification and be justified by features of the new case. RDR has moved beyond its first representation which handled single classification tasks within the domain of pathology to support multiple conclusions across a wide range of domains such as help-desk support, email classification and RoboCup and problem types including configuration, simulation, planning and natural language processing. This paper reviews the history of RDR research over the past two decades with a view to its future.

Why projects fail? How contingency theory can provide new insights – A comparative analysis of NASA’s Mars Climate Orbiter loss

When important projects fail, the investigation is often focused on the engineering and technical reasons for the failure. That was the case in NASA’s Mars Climate Orbiter (MCO) that was lost in space after completing its nine-month journey to Mars. Yet, in many cases the root cause of the failure is not technical, but managerial. Often the problem is rooted in management’s failure to select the right approach to the specific project. The objective of this paper is to enrich our understanding of project failure due to managerial reasons by utilizing different contingency theory frameworks for a retrospective look at unsuccessful projects and perhaps more important, potential prevention of future failures. The evolving field of project management contingency theory provides an opportunity at this time to re-examine the concept of fit between project characteristics and project management, and offer deeper insights on why projects fail. After outlining several existing contingency studies, we use three distinct frameworks for analyzing the MCO project. These frameworks include Henderson and Clark’s categorization of change and innovation, Shenhar and Dvir’s NTCP diamond framework, and Pich, Loch, and De Meyer’s strategies for managing uncertainty. While each framework provides a different perspective, collectively, they demonstrate that in the MCO program, the choices made by managers, or more accurately, the constraints imposed on them under the policy of ‘better, faster, cheaper’, led the program to its inevitable failure. This paper shows that project management contingency theory can indeed provide new insights for a deeper understanding of project failure. Furthermore, it suggests implications for a richer upfront analysis of a project’s unique characteristics of uncertainty and risk, as well as additional directions of research. Such research may help establish new and different conceptions on project success and failure beyond the traditional success factors, and subsequently develop more refined contingency frameworks. The results of such research may enable future project managers to rely less on heuristics and possibly lead to a new application of “project management design.”

Reflections on e-Learning Readiness in Albanian Education

Nowadays e-Learning has been identified to be the future of learning worldwide since the very powerful platform of the Internet has accelerated the speed of communication. Adoption of e-learning has become the latest trend across universities all over the world. Albania is part of a global shift from material resources to knowledge and intellectual resources as the basis for economic growth. Educators across Albania are aware that students must have an education that enables the students to participate successfully in and contribute to the knowledge economy. E-Learning readiness is an initial part of eLearning development. In order to benefit from e-learning, higher education institutions in Albania should conduct considerable up-front analysis to assess their readiness. In this paper we are trying to examine the status of e-Learning readiness in Albania, analyzing and discussing several components and criteria based on literature.

Virtual aluminum castings: An industrial application of ICME

The automotive product design and manufacturing community is continually besieged by Hercule an engineering, timing, and cost challenges. Nowhere is this more evident than in the development of designs and manufacturing processes for cast aluminum engine blocks and cylinder heads. Increasing engine performance requirements coupled with stringent weight and packaging constraints are pushing aluminum alloys to the limits of their capabilities. To provide high-quality blocks and heads at the lowest possible cost, manufacturing process engineers are required to find increasingly innovative ways to cast and heat treat components. Additionally, to remain competitive, products and manufacturing methods must be developed and implemented in record time. To bridge the gaps between program needs and engineering reality, the use of robust computational models in up-front analysis will take on an increasingly important role. This article describes just such a computational approach, the Virtual Aluminum Castings methodology, which was developed and implemented at Ford Motor Company and demonstrates the feasibility and benefits of integrated computational materials engineering.

Brain lipid composition in postnatal iron‐induced motor behavior alterations following chronic neuroleptic administration in mice

Several studies have shown that deficient uptake or excessive break down of membrane phospholipids may be associated with neurodegenerative and psychiatric disorders. The purpose of the present study was to examine the effects of postnatal iron administration in lipid composition and behavior and whether or not the established effects may be altered by subchronic administration of the neuroleptic compounds, clozapine and haloperidol. In addition to motor activities such as locomotion, rearing and activity, a targeted lipidomics approach has been used to investigated the brains of eight groups of mice (four vehicle groups and four iron groups) containing six individuals in each group treated with vehicle, low dose clozapine, high dose clozapine and haloperidol. Lipids were extracted by the Folch method and analyzed using reversed-phase capillary liquid chromatography coupled on-line to electrospray ionization mass spectrometry (LC/ESI/MS). Identification of phosphatidylcholine (PC) and sphingomyelin (SM) molecular species was based on their retention time, m/z ratio, head group specific up-front fragmentation and analysis of the product ions produced upon fragmentation. A comparison between the Ve-groups and Fe-groups showed that levels of PC and SM molecular species and motor activities were significantly lower in Fe-Ve compared to Ve-Ve. The effects of neuroleptic treatment with and without iron supplementation were studied. In conclusion our results support the hypothesis that an association between psychiatric disorders and lipid and behavior abnormalities in the brain exists.

Opportunity Development in a Knowledge-Intensive Venture: A Case Study

Literature on entrepreneurship research has shown surprisingly limited interest in the origin of ventures and discovery of opportunities for profit. Lately, however, this matter has been criticized and a more elaborate conception of how opportunities arise has been called for. The present investigation concerns how a business opportunity is discovered and exploited. An in-depth case study of a knowledge-intensive venture in the mobile Internet industry has been carried out, and our findings point to the need of reconceptualizing this phenomenon into opportunity development, carried out over time and involving several actors. The process observed was iterative in nature; the opportunity and venture were developed in parallel, thus contrasting with a traditional linear view. Furthermore, the business was extremely difficult to analyze ex ante, implying too strong a focus on up-front analysis in existing theory. Much interaction was evidenced as well, imposing difficulties to steer the venture.

Learning-by-Doing in the Newsvendor Problem - A Laboratory Investigation of the Role of Experience and Feedback

We investigate learning-by-doing in the newsvendor inventory problem. An earlier study observed that decision makers tend to anchor orders away from the expected profit maximizing order. We study enhancements to the learning environment suggested by the behavioral literature. Extended experience improves performance some but feedback enhancements do little. A manipulation with a strong positive effect constrains inventory policy to a standing order for multiple periods, precluding responses to short term fluctuations in demand. With experience, our newsvendors collectively achieve over 90% of expected profit potential. It turns out that this kind of hands-on learning is more effective than providing newsvendors with an upfront statistical analysis that includes the expected profitability of orders. The results speak to the kinds of training and decision support that might improve the performance of inventory decision makers.

Discovery Partners International

Discovery Partners International (Nasdaq: DPII) is a leader in collaborative drug discovery. DPI's integrated discovery framework encompasses a broad spectrum of capabilities in chemistry, biology, informatics, computational modeling and synthesis automation. DPI's approach to drug discovery places a heavy emphasis on up-front interdisciplinary analysis of its client's problems. By drawing on the collective expertise of its chemists, biologists and computational scientists, lead discovery and optimization strategies with the highest likelihood of success are formulated and then executed using the company's extensive capabilities and high output technology platforms.

Neural space-mapping optimization for EM-based design

We propose, for the first time, neural space-mapping (NSM) optimization for electromagnetic based design. NSM optimization exploits our space-mapping (SM)-based neuromodeling techniques to efficiently approximate the mapping. A novel procedure that does not require troublesome parameter extraction to predict the next point is proposed. The initial mapping is established by performing upfront fine-model analyses at a reduced number of base points. Coarse-model sensitivities are exploited to select those base points. Huber optimization is used to train, without testing points, simple SM-based neuromodels at each NSM iteration. The technique is illustrated by a high-temperature superconducting quarter-wave parallel coupled-line microstrip filter and a bandstop microstrip filter with quarter-wave resonant open stubs.