As project management has become a critical subject in modern-world organisations, Operational Research (OR) needs to incorporate mechanisms to deal with rapid, unplanned changes as well as confusing information and stakeholders with conflicting values. Agile methods are widely used and tested in Software Engineering (SE) to deal with problems of the characteristics above. Because of this, after establishing that both OR interventions, as well as SE developments, have common stages and information evolution, this proposal aims to pose the challenge of applying agility to manage OR projects. Guidelines to adapt Agile Methodologies to OR are proposed, and a case vignette is studied as an initial test. Finally, future lines of work are considered to define how the larger project in which this proposal is embedded will continue.

During 2019, RMIT researchers interviewed executives from SMEs and larger companies across Australia about their views on digital operations and I4.0. This paper draws on those interviews, and experience gained from RMIT’s ongoing engagement with its partners in the advanced manufacturing sector, to examine the specific benefits, challenges and opportunities I4.0 presents for SMEs. Our in-depth interviews identified four common I4.0 issues facing each company: 1) acquiring the most relevant data, 2) integrating systems for better-aggregated data, 3) visualising the data, and 4) extracting more value from the data. Other issues and barriers identified through RMIT’s research include: a) lack of understanding of I4.0, b) low buy-in from top management, c) limited solutions tailored to the needs of SMEs, and d) data security concerns.

Operational Research (OR) models usually deal with uncertain, changing requirements. This leads to a continuous process of adapting and reworking the mathematical code. However, there are scarce mechanisms to control its quality. This is essential to Software Engineering (SE), as it enforces the use of Unit Testing: automatically running tests after any alterations, to assess specific parts of the code. This is done to discover where and how errors are happening, simplifying its correction while evaluating their possible ramifications. This article aims to define how these concepts can be adapted to them, how tests should be used to detect faults and to provide a workflow to use them while developing an OR model. It provides guidelines on what should be tested and what to expect of possible errors and a process to use it.

Advanced Planning Systems (APS) have become an important tool for manufacturing and production companies that require a specific system to optimize production, logistic, material and human resources, etc. with the goal of improving the economy of the companies and offer a good customer service. An APS must be integrated to the Enterprise’s System (such as an ERP), but this task usually lacks of a specific methodology to be performed and is generally made ad-hoc. With the ultimate objective to provide an approach to facilitate this integration, this work presents a characterization of the APS from a systemic point of view, using standardized Software Engineering concepts. The idea is to provide a definition and characterization of Advanced Planning Systems, by establishing the main goals of this type of system, and considering Functional Requirements, Quality Attributes and a reference model for the architecture. The selected choices are established on the base of several international standards from the Software Engineering area, such as the SEBoK (System Engineering Body of Knowledge) and the SQuaRE (Software product Quality Requirements and Evaluation) model, among others, and aim to serve as a base line for the general concept of APS.