Towards a business analytics capability maturity model

Business analytics (BA) systems are an important strategic investment for many organisations and can potentially contribute significantly to firm performance. Establishing strong BA capabilities is currently one of the major concerns of chief information officers. This research project aims to develop a BA capability maturity model (BACMM). The BACMM will help organisations to scope and evaluate their BA initiatives. This research-in-progress paper describes the current BACMM, relates it to existing capability maturity models and explains its theoretical base. It also discusses the design science research approach being used to develop the BACMM and provides details of further work within the research project. Finally, the paper concludes with a discussion of how the BACMM might be used in practice.

Becoming an analytics-based organisation : strategic agency in the change process in a retail organisation

The paper examines how the upward and downward strategic influences of the head of the BI unit in the case organization have evolved over time and the BI perspective became legitimate in the organization. The analysis covers a decade long period of time. We engaged in an Action Research (AR) inquiry where the change process was explored through the first-hand experiences of one of the co-authors. The model of the strategic agency of middle managers was applied in the analysis. We analyse the evolution as well as the enablers and constraints of the strategic agency of the head of the BI unit in the case organisation and identify the type of strategic agency exhibited in the case.

Enterprise systems for innovation in products and processes : beyond operational efficiency

It has been widely accepted now in industry and academia that Enterprise Systems (ES) can create value for adopting organizations by enabling operational efficiency. However, given the enormous investments they warrant, the potential of such systems to deliver more than improving operations is emerging as a popular area of investigation. This paper reports a research-in-progress that proposes innovation as a means of creating business value with Enterprise Systems. The primary contribution of this paper is a process model that proposes that Enterprise Systems can enable innovation - in products and processes, and supports it with empirical evidence using three case studies. The intention is to test this model further with more case studies and a survey.

Modelling engineering student academic performance using academic analytics

Internationally, the recruitment, management and retention of students has become a high priority for universities. The use of information technology systems and student data by institutions to understand and improve student academic performance is often referred to as ‘academic analytics’. This paper presents an academic analytics investigation into the modelling of academic performance of engineering students enrolled in a second-year class. The modelling method used was binary logistic regression, and the target predicted variable was ‘success status’—defined as those students from the total originally enrolled group that achieved a final unit grade of pass or better. This paper shows that student data stored in institutional systems can be used to predict student academic performance with reasonable accuracy, and it provides one methodology for achieving this. Importantly, significant predictor variables are identified that offer the ability to develop targeted interventions to improve student success and retention outcomes.

Breeding periodicity for male sea turtles, operational sex ratios, and implications in the face of climate change

Species that have temperature-dependent sex determination (TSD) often produce highly skewed offspring sex ratios contrary to long-standing theoretical predictions. This ecological enigma has provoked concern that climate change may induce the production of single-sex generations and hence lead to population extirpation. All species of sea turtles exhibit TSD, many are already endangered, and most already produce sex ratios skewed to the sex produced at warmer temperatures (females). We tracked male loggerhead turtles (Caretta caretta) from Zakynthos, Greece, throughout the entire interval between successive breeding seasons and identified individuals on their breeding grounds, using photoidentification, to determine breeding periodicity and operational sex ratios. Males returned to breed at least twice as frequently as females. We estimated that the hatchling sex ratio of 70:30 female to male for this rookery will translate into an overall operational sex ratio (OSR) (i.e., ratio of total number of males vs females breeding each year) of close to 50:50 female to male. We followed three male turtles for between 10 and 12 months during which time they all traveled back to the breeding grounds. Flipper tagging revealed the proportion of females returning to nest after intervals of 1, 2, 3, and 4 years were 0.21, 0.38, 0.29, and 0.12, respectively (mean interval 2.3 years). A further nine male turtles were tracked for short periods to determine their departure date from the breeding grounds. These departure dates were combined with a photoidentification data set of 165 individuals identified on in-water transect surveys at the start of the breeding season to develop a statistical model of the population dynamics. This model produced a maximum likelihood estimate that males visit the breeding site 2.6 times more often than females (95%CI 2.1, 3.1), which was consistent with the data from satellite tracking and flipper tagging. Increased frequency of male breeding will help ameliorate female-biased hatchling sex ratios. Combined with the ability of males to fertilize the eggs of many females and for females to store sperm to fertilize many clutches, our results imply that effects of climate change on the viability of sea turtle populations are likely to be less acute than previously suspected.

Designing an e-portfolio for assurance of learning focusing on adoptability and learning analytics

The Assurance of Learning for Graduate Employability framework is a quality assurance model for curriculum enhancement for graduate employability, enabling graduates to achieve "the skills, understandings and personal attributes that make [them] more likely to secure employment and be successful in their chosen occupations to the benefit of themselves, the workforce, the community and the economy" (Yorke, 2006). Of particular note is the framework's dependence on three foundations, including easy access to integrated and accessible tools for staff and student self-management. In other words, this approach to curriculum quality depends on staff and student access to tools that enable them to self-manage their learning. This paper examines two aspects which informed the design of a student e-portfolio system, iPortfolio, intended for students' self-management of their learning, particularly recording evidence of their achievement of capabilities. The paper focuses on two particular considerations in the design of the iPortfolio: adoptability and learning analytics. Adoptability means the phase preceding adoption, whether students have the devices, platforms and technology skills to be able to use such an innovation. The iPortfolio also facilitates learning analytics: it has the capability to gather data related to learning indicators for course quality assurance purposes. Both adoptability and analytics are very dynamic fields: new devices, platforms and applications constantly spark changes in user habits, and policy changes mean institutions need to be able to provide new data, often at short notice. In the conclusion, the paper suggests how tools such as the iPortfolio can be designed for 'future proofing' and sustainability.