Previous studies have indicated that the majority of infrastructure projects have cost overruns. The root causes are traced to political, technical and psychological reasons at the initial stage of ...the project. The consequence is either unintentional overoptimistic forecasting of perceived results or calculated interpretation of facts in favour of personal and political interests. These phenomena are called planning fallacies and strategic misrepresentation, respectively. A step-wise procedure to avoid planning fallacies and strategic misrepresentation is called the outside view. The outside view bypasses human biases by using past experience and empirical data from past projects. It has evolved into a professional practice through a method called reference class forecasting which has been shown to provide improved cost forecasting accuracy in the initial stage of a project. The study reported in this paper examined reference class forecasting as a means of improving cost forecasting in the planning stage of the project lifecycle. Data from the Icelandic Road Administration (ICERA) were assembled in a cost forecasting model to determine if it might be possible to improve forecasting accuracy. The results proved inconclusive; however, a comparison with findings from similar projects in the UK showed that although cost overruns followed a similar curve, the chance of occurrence is significantly lower at the planning stage after the decision to proceed has been taken.
The aim of this paper is to study the main areas in which artificial intelligence (AI) will impact the field of project management in relation to cost, risk and scheduling. The research model was ...based on a previous study of the ten project management knowledge areas presented in PMI’s PMBOK 6th edition, where project schedule, cost and risk management knowledge areas were identified as being the ones most likely to be affected by the development of AI. A group of graduates from a Master of Project Management program were assessed in an online questionnaire, reflecting the PMBOK’s elements of best practices and how AI will affect the project management profession in the future. Different elements of the three knowledge areas were considered to be affected more by AI than others. The schedule baseline is the element believed to be affected the most out of the project schedule management elements. For project cost management, the estimation of resource costs is believed to be affected the most. In the case of project risk management, the application of AI will have the strongest impact on the probability and impact formats.
A strong public project governance structure is instrumental to ensure the effective and efficient delivery of projects in the public domain. The Norwegian State Project Model is an example of such a ...structure; a standardized classification of projects into stages, with defined decision points, where requirements regarding documentation are specified. In Iceland, the public project governance structure has been criticised. This paper investigates the Icelandic framework by comparison to the Norwegian framework, through a desk analysis of both structures. Furthermore, the features and perceived utility of the Icelandic project governance structure are assessed by interviewing selected public stakeholders who are representatives of seven important organizations in the public sector. The study indicates that there is a significant difference between the frameworks where the Icelandic framework is lacking crucial elements of what constitutes best practices in modern project governance. In view of extensive plans for investments in infrastructure in the coming years, there is an urgent need for reforming the Icelandic project governance structure.
•Best practices in project governance are based on transparency, fairness, responsibility, and accountability.•This is the case with the Norwegian framework but the Icelandic framework lacks crucial elements.•It consists of basic instructions - quality assurance is dependent on the decisions of individual institutions or ministries.•Investment in infrastructure projects in Iceland in the next 20 years will be close to 10 billion euros for over 100 projects.•To ensure that public funds are well spent, the Icelandic Project Governance Framework should be reformed.
Projectification has become a buzzword. Although repeated claims of an increasing projectification were often supported by illustrative, case-based evidence, a systematic and complete measurement of ...projectification of an entire economy - including all sectors and project types - is still missing. A more precise and reliable measurement of the degree of projectification can be helpful for underlying the importance of project management both for research and practice. This paper presents the results of a comparative study in three Western economies: Germany, Norway, and Iceland. Projectification was measured as the share of project work on total work. This allows for a systematic comparison between countries and sectors. We show that although differences exist among the countries regarding their size and industry structure, the share of project work in advanced economies seems to be about one third. However, comparing the different countries demonstrates that important differences exist for individual sectors.
•A complete measurement of the degree of projectification of the German, the Norwegian and the Icelandic economy.•Measurement includes all sectors of the economy and all project types.•Projectification is 34.7% in Germany, 32.6% in Norway, and 27.7% in Iceland.•Results suggest that in advanced economies around one third of all economic activities is project work.•The comparison of the three economies reveals major differences on the level of individual sectors.
The public sector plays a pivotal role in setting the pace for climate action innovation through policy development and inter-organization collaborations for sustainable energy solutions. There is ...generally a lack of a proper understanding of innovation in the public sector compared to the private sector, with the public sector being considered slow, bureaucratic adopters of innovation. This study investigated the understanding and approach to innovation in public energy organizations, determining if and how these organizations innovate and their ability to innovate, especially towards climate action, in Kenya while comparing them with Iceland, a developed economy with equivalent geothermal energy potential. A questionnaire survey was conducted in public energy organizations in Kenya and Iceland. Statistical analysis was used to validate and evaluate the collected data. The study findings revealed that innovation collaboration systems in organizations positively predicted the employees’ innovation awareness, confirming that energy sector innovations shall require public–private sector collaboration in developing innovative, incremental, and disruptive energy solutions. Employee knowledge and skills, on the other hand, were found not to be a predictor of an organization’s innovation awareness. Furthermore, employees’ motivation to innovate, as well as organizational innovation strategy, management structure and leadership, were found to positively predict an organization’s readiness to innovate. Finally, the Kenyan energy sector was benchmarked against the Icelandic energy sector indicating some noteworthy differences in the prioritization of energy sector climate action initiatives, with most organizations identifying themselves as innovation generators and innovation adopters and the least being innovation imitators, showing the organizations’ commitment to developing new technologies, markets and policies towards sustainable energy solutions.
The purpose of this study is to explore how Artificial Intelligence (AI) might augment the project management profession in each of the 10 categories of project management knowledge areas, as defined ...in the Project Management Body of Knowledge (PMBOK) of the Project Management Institute (PMI). In a survey, a group of project management experts were asked to state their insights into AI’s likely effect on project management in the next 10 years. Results clearly illustrated that AI will be an integrated part of future project management practice and will affect project management knowledge areas in the near future. According to these findings, the management of cost, schedule, and risk, in particular, will be highly affected by AI. The research indicates that AI is very useful for processes where historical data is available and can be used for estimation and planning. In addition, it is clear that AI can monitor schedules, adjust forecasts, and maintain baselines. According to the findings, AI will have less impact in knowledge areas and processes that require human leadership skills, such as developing and managing teams and the management of stakeholders. The results indicate proprietarily the project management knowledge areas as defined by PMI that AI is likely to augment and sustain.
The “projectification” of Western societies has been consolidated by a number of studies and now calls for various adaptations in the managerial framework of project management. Faster rates of ...change in complex environments antagonize the traditional risk assessment approach and demand a more dynamic approach. A framework commonly used for understanding the challenges of complexity in the modern business environment is VUCA. VUCA stands for volatility, uncertainty, complexity, and ambiguity. In order to mitigate the impact of a VUCA environment on complex projects, organizations and project leaders need to know the type and severity of challenges they are dealing with in each unique project. This study explores the VUCA framework in the context of projects and suggests that the VUCA approach can enhance the conventional risk assessment procedure. The study also drafts an accessible diagnostic tool to assess the VUCA dimensions a project is facing, so that project managers can effectively isolate “fat tail” risk events. The tool is tested on five complex projects in the manufacturing industry and its effectiveness is discussed.
Previous studies have indicated that the majority of infrastructure projects have cost overruns. The root causes are traced to political, technical and psychological reasons at the initial stage of ...the project. The consequence is either unintentional overoptimistic forecasting of perceived results or calculated interpretation of facts in favour of personal and political interests. These phenomena are called planning fallacies and strategic misrepresentation, respectively. A step-wise procedure to avoid planning fallacies and strategic misrepresentation is called the outside view. The outside view bypasses human biases by using past experience and empirical data from past projects. It has evolved into a professional practice through a method called reference class forecasting which has been shown to provide improved cost forecasting accuracy in the initial stage of a project. The study reported in this paper examined reference class forecasting as a means of improving cost forecasting in the planning stage of the project lifecycle. Data from the Icelandic Road Administration (ICERA) were assembled in a cost forecasting model to determine if it might be possible to improve forecasting accuracy. The results proved inconclusive; however, a comparison with findings from similar projects in the UK showed that although cost overruns followed a similar curve, the chance of occurrence is significantly lower at the planning stage after the decision to proceed has been taken. Fruhere Studien haben gezeigt, dass die Mehrheit der Infrastrukturprojekte Kostenuberschreitungen haben. Die Ursachen sind verfolgt zu politischen, technischen und psychologischen Grunden in der Anfangsphase des Projekts. Die Folgen sind entweder unbeabsichtigt zu optimistischen Prognosen der empfundenen Ergebnisse oder berechneten Interpretation von Fakten zugunsten von personlichen und politischen Interessen. Diese Phanomene werden als Planungs Tauschungen und strategische Tauschung sind. Eine stufenweise Vorgehensweise zu vermeiden Planung Tauschungen und strategische Tauschung ist die Aubetaenansicht aufgerufen. Die Aubetaenansicht umgeht menschliche Vorurteile durch Erfahrungen aus der Vergangenheit und empirischen Daten von fruheren Projekten verwendet wird. Es hat sich zu einem professionellen Praxis durch ein Verfahren namens Referenzklasse Prognosen entwickelt, die eine verbesserte Kostenprognosegenauigkeit in der Anfangsphase eines Projekts zu schaffen gezeigt wurde. Die Studie, die in dieser Veroffentlichung untersuchten Referenzklasse Prognose als Mittel zur Kostenprognosen in der Planungsphase des Projektlebenszyklus zu verbessern. Die Daten der islandischen Strabetaenverwaltung (Iceras) wurden in einem Kostenprognosemodell zusammengebaut, um zu bestimmen, ob es moglich sein konnte, Prognosegenauigkeit zu verbessern. Die Ergebnisse bewiesen nicht schlussig; aber ein Vergleich mit den Ergebnissen aus ahnlichen Projekten in Grobetabritannien zeigten, dass, obwohl Kostenuberschreitungen eine ahnliche Kurve gefolgt, die Moglichkeit des Auftretens ist deutlich niedriger in der Planungsphase, nachdem die Entscheidung getroffen wurde, um fortzufahren.
In this rapidly changing and fast-growing world, sustainability is an important paradigm. However, the constantly growing level of uncertainty leads to increased strain in decision making. This ...results in a growing need for a more effective and extensive approach for identifying project risk in particular events that are not easily detected but can have a severe impact, sometimes referred to as Black Swans or “fat tail” events. The VUCA meter is a normative approach to identify project risk by assessing in a structured way events that may be volatile, uncertain, complex, and ambiguous and might contribute to the project risk. In this study, the VUCA meter is benchmarked against a traditional risk identification process as recommended by PMI®. Firstly, two workshops, each referring to the respective risk identification method, were conducted. Secondly, a Delphi survey was run to investigate if the VUCA meter would capture Black Swan risk events that are bypassed by the traditional risk identification approach. The results clearly indicate that the VUCA meter can be developed to be a significant addition to the conventional risk identification process for large projects that are at an early stage. The VUCA meter facilitates a discussion that gets people to think beyond the traditional framework for identifying project risk factors. As a consequence, “fat tail” events, that are not apprehended with the conventional technique, are captured by the VUCA meter.
Decision Skills in Engineering Programs - a Key for a VUCA Era Siegfried, Rouvrais; Haraldur, Audunsson; Liliane, Esnault ...
2020 IFEES World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC),
2020-Nov.-16
Conference Proceeding
Open access
Judgment and decision skills are now essential graduate attributes for the future engineer, in particular for facing the more frequent than ever volatile, uncertain, complex and ambiguous (VUCA) ...world in both professional and societal situations. One of the responsibilities of engineering programs is to train students to be agile and capable of taking decisions in challenging VUCA situations. This paper presents conceptual and practical results of an European project which explored, designed and iteratively analysed innovative educational learning and teaching activities to train decision-making skills. Following a design-based research approach, including both quantitative and qualitative analysis, the four VUCA dimensions were categorized, the relevant decision skills were defined, and activities to train decision skills were tested and evaluated. One outcome of this work is a rational selection of learning activities based on experiential learning to train specific decision-making skills, which can be integrated in the engineering curriculum. These learning and teaching activities are freely available for adaption in engineering programs. In addition, six reference models are proposed and delineated, in an effort to support the integration processes for curriculum revisions.
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