Project portfolio risk analysis with the consideration of project interdependencies

PurposeComprehensive project portfolio risk (PPR) analysis is essential for the success and sustainable development of project portfolios (PPs). However, project interdependency creates complexity for PPR analysis. In this study, considering the interdependency effect among projects, the authors develop a quantitative evaluation model to analyze PPR based on a fuzzy Bayesian network.Design/methodology/approachIn this paper, the primary purpose is to comprehensively evaluate project portfolio risk considering the interdependency effect using a systematical model. Accordingly, a fuzzy Bayesian network (FBN) is developed based on the existing studies. Specifically, first, the risks in project portfolios are identified from the project interdependencies perspective. Second, a fuzzy Bayesian network is adopted to model and quantify the interaction relationships among risks. Finally, the model is implemented to analyze the occurrence situation and characteristics of risks.FindingsThe interdependency effect can lead to high-stake risks, including weak financial liquidity, a lack of cross-project members and project priority imbalance. Furthermore, project schedule risks and inconsistency between product supply and market demand are relatively sensitive and should also be prioritized. Also, the validity of this risk evaluation model has been proved.Originality/valueThe findings identify the most sensitive risks for guaranteeing portfolio implementation and reveal interdependency effect can trigger some specific risks more often. This study proposes for the first time to measure and analyze project portfolio risk by a systematical model. It can help systematically assess and manage the complicated and interdependent risks associated with project portfolios.

Risk Analysis in Early Phase of Complex Infrastructure Projects

Infrastructure construction projects are complex with a very long life-cycle, a complex organizational plan, a complex resource management, technical complexities, contractual complexities and macro-environmental factors. The complexity of an infrastructure project leads to the existence of interdependent risks, which are hard to anticipate and control. As the investment is major for these types of projects, the risks and opportunities are critical to the project success or failure, the risk factors need to be identified and analyzed before any decision-making process. While upfront planning is important, not all events and scenarios can be foreseen as the project can take several years to complete and may involve many companies and stakeholders. In this planning stage of the project, a robust risk analysis method is indispensable for identifying and analyzing the major risk and opportunity factors. In this paper, a formalized multi-criteria decision-making process is developed based on a strategic risk analysis in a complex environment: (1) in a very early stage and at a strategic level, (2) before the contracting phase in order to develop a risk allocation plan and negotiate it with the project owner.

Understanding Interdependent Climate Change Risks Using a Serious Game

Anthropogenic climate change calls for rapid and enormous cuts in emissions of CO2 and other greenhouse gases to mitigate future impacts. Even with these, however, many changes will continue to occur over the next 20–30 years adding to those already observed. Adaptation is crucial and urgent, but identifying strategies is complex and requires dialogue and cooperation among stakeholders, especially for infrastructure that exhibits interdependent risks in that failure in one type may impact others. A serious game was codeveloped with infrastructure operators to communicate climate projections and climate hazards to them; identify potential interdependencies, cascading impacts, cumulative effects, and vulnerability hot spots; and engage them to improve cooperation and enable a shared understanding of cross-cutting climate risks and interdependencies. In the game, players provide present-day infrastructure services in the Inverclyde district, Scotland, as they experience a plausible decade of 2050s weather characterized by a sequence of hazard events. This sequence was extracted from climate model projections to ensure scientific plausibility. The infrastructure operators were responsible for drinking water and gas supplies, road and rail transport, wastewater treatment, and civil infrastructure. When playing the game the participating U.K. infrastructure providers felt that although there were challenges, they could cope with 2050s climate change. None of the projected hazard events were anticipated to cause catastrophic impact cascades on infrastructure. The game was positively received, and the study suggests it is a useful tool to both communicate climate hazards and explore potential interdependent risks by bringing together stakeholders’ individual expertise in an engaging way.

Organizing Project Actors for Collective Decision-Making about Interdependent Risks

The way project actors are organized is crucial in determining how they will be able to collectively cope with nontrivial complex problems and risks. Current project organizations are generally based on single-criterion decomposition, whether product, process, or organization based. The proposed approach forms complementary clusters of actors based on the interdependencies between the risks they manage. More precisely, distinction has been made between the interdependencies connecting two risks that are owned by different actors and those owned by the same actor. We argue that interdependency between two risks managed by the same actor is less dangerous, meaning that clustering algorithm is tailored to distinguish mono- and biactor risk interdependencies. The complementary structure offered by interdependency-based clustering tends to put together strongly interconnected actors, albeit they were often initially not grouped together. It increases the likelihood of a better communication, coordination, and collective decision-making in complex situations. Some risks remain out of proposed clusters and are declared transverse, which means that their owners act as information hubs and are not involved in a single cluster. An industrial application is presented with operational results and perspectives for further work are drawn from it.

Best Paper Selection

Humbert M, Ayday E, Hubaux JP, Telenti A. Quantifying Interdependent Risks in Genomic Privacy. ACM Transactions on Privacy and Security 2017;20(1):3 https://dl.acm.org/citation.cfm?id=3035538 Yuan J, Malin B, Modave F, Guo Y, Hogan WR, Shenkman E, Bian J. Towards a privacy preserving cohort discovery framework for clinical research networks. J Biomed Inform 2017;66:42-51 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5316314/ Ohno-Machado L, Sansone SA, Alter G, Fore I, Grethe J, Xu H, Gonzalez-Beltran A, Rocca-Serra P, Guraraj AE, Bell E, Soysal E, Zong N, Kim HE. Finding useful data across multiple biomedical data repositories using DataMed. Nat Genet 2017;49(6):816-9 https://www.nature.com/articles/ng.3864 Wan Z, Vorobeychik Y, Xia W, Clayton EW, Kantarcioglu M, Malin B. Expanding access to large-scale genomic data while promoting privacy: a game theoretic approach. Am J Hum Genet 2017;100(2):316-22 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5294764/ Gilbert M, Bonnell A, Farrell J, Haag D, Bondyra M, Unger D, Elliot E. Click yes to consent: incorporating informed consent into an internet-based testing program for sexually transmitted and blood-borne infections. Int J Med Inform 2017;105:38-48 https://www.sciencedirect.com/science/article/pii/S1386505617301697?via%3Dihub

Communal Risk Information Sharing: Motivations Behind Voluntary Information Sharing for Reducing Interdependent Risks in a Community

This article extends our understanding of risk communication related to communal risk and risk information sharing. Building on research from risk communication, organizational behavior, and social psychology, it examines individual-, relation-, and community-level motivations to share information about a devastating plant disease. This disease can bring about substantial economic risk to everyone in a farming community. We tested our hypotheses using a national sample of U.S. tomato and potato growers ( N = 452). Our findings show that growers were motivated to share information about a communal risk based on (a) individual-oriented concerns for economic costs, (b) relation-oriented concerns for reciprocation and the information recipient’s trustworthiness, and (c) community-oriented concerns comprising a sense of shared responsibility and community cohesiveness.