The challenges of managing complexity in projects : an Australian perspective

Project Management (PM) as an academic field is relatively new in Australian universities. Moreover, the field is distributed across four main areas: business (management), built environment and construction, engineering and more recently ICT (information systems). At an institutional level, with notable exceptions, there is little engagement between researchers working in those individual areas. Consequently, an initiative was launched in 2009 to create a network of PM researchers to build a disciplinary base for PM in Australia. The initiative took the form of a bi-annual forum. The first forum established the constituency and spread of PM research in Australia (Sense et al., 2011). This special issue of IJPM arose out of the second forum, held in 2012, that explored the notion of an Australian perspective on PM. At the forum, researchers were invited to collaborate to explore issues, methodological approaches, and theoretical positions underpinning their research and to answer the question: is there a distinctly Australian research agenda which responds to the current challenges of large and complex projects in our region? From a research point of view, it was abundantly clear at the forum that many of the issues facing Australian researchers are shared around the world. However, what emerged from the forum as the Australian perspective was a set of themes and research issues that dominate the Australia research agenda.

Managing complexity and insitutionalization : power and politics in ERP implementation in an Australian university

This chapter reports a case study of ERP implementation in an institution of higher education. The ERP is one based on integration of administrative tasks based on Oracle® systems and is successful both in terms of its embeddedness in institutionalized practice and in supporting that university's operations. The key issue that emerged from the study showed that understanding complexity, institutionalized practice, and the power relations in existence enable the implementation to be more effective, as it can be managed when understood. The chapter argues that organizations reproduce practice and that an ERP challenges that. To deal with that challenge, social dramas emerge wherever power exists, and the resulting conflicts challenge the effectiveness of the systems put in place. In this case study, the key role of the project champion in resolving the social dramas became evident.

Paradigmatic approach to managing complexity in knowledge-driven marketing

This research develops a measure of Customer Lifetime Value, extending existing measures, that provides organisations having large customer databases the means to place a financial value on customers. Using this measure, new models are developed that provide a framework to use knowledge to drive marketing decisions.

Managing process model complexity via abstract syntax modifications

As a result of the growing adoption of Business Process Management (BPM) technology different stakeholders need to understand and agree upon the process models that are used to configure BPM systems. However, BPM users have problems dealing with the complexity of such models. Therefore, the challenge is to improve the comprehension of process models. While a substantial amount of literature is devoted to this topic, there is no overview of the various mechanisms that exist to deal with managing complexity in (large) process models. It is thus hard to obtain comparative insight into the degree of support offered for various complexity reducing mechanisms by state-of-the-art languages and tools. This paper focuses on complexity reduction mechanisms that affect the abstract syntax of a process model, i.e. the structure of a process model. These mechanisms are captured as patterns, so that they can be described in their most general form and in a language- and tool-independent manner. The paper concludes with a comparative overview of the degree of support for these patterns offered by state-of-the-art languages and language implementations.

Learning to manage complexity through simulation: students' challenges and possible strategies

Many have called for medical students to learn how to manage complexity in healthcare. This study examines the nuances of students' challenges in coping with a complex simulation learning activity, using concepts from complexity theory, and suggests strategies to help them better understand and manage complexity.Wearing video glasses, participants took part in a simulation ward-based exercise that incorporated characteristics of complexity. Video footage was used to elicit interviews, which were transcribed. Using complexity theory as a theoretical lens, an iterative approach was taken to identify the challenges that participants faced and possible coping strategies using both interview transcripts and video footage.Students' challenges in coping with clinical complexity included being: a) unprepared for 'diving in', b) caught in an escalating system, c) captured by the patient, and d) unable to assert boundaries of acceptable practice.Many characteristics of complexity can be recreated in a ward-based simulation learning activity, affording learners an embodied and immersive experience of these complexity challenges. Possible strategies for managing complexity themes include: a) taking time to size up the system, b) attuning to what emerges, c) reducing complexity, d) boundary practices, and e) working with uncertainty. This study signals pedagogical opportunities for recognizing and dealing with complexity.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.