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Public sector data analytics concerns the process of retrieving data, data analysis, publication of the results as well as re-using the data by government organizations to improve their operations and enhance public policy. This paper aims to explore the use of public sector data analytics in the Netherlands and the opportunities and challenges of this use.

This paper finds 74 applications of public sector data analytics, identified by a Web search and consultation with policymakers. The applications are categorized by application type, organization(s) involved and application domain, and illustrative examples are used to elaborate opportunities and challenges.

Public sector data analytics is most frequently used for inspection and enforcement of social services and for criminal investigation. Even though its usage is often experimental, it raises concerns for scope creep, repeated targeting of the same (group of) individuals, personal data use by third parties and the transparency of governmental processes.

Drawing on desk research, it was not always possible to identify which type of data or which technology was used in the applications that were found. Furthermore, the case studies are illustrative rather than providing an in-depth overview of opportunities and challenges of the use of data analytics in government.

Most studies either perform a literature overview or present a single case study; this paper presents a more comprehensive overview of how a public sector uses data analytics.

The purpose of this paper is to define the integration capability dimensions and create a model for self-assessing the integration capability in inter-organizational projects.

A theoretical construct of, referred in this study as integration capability framework is elaborated following a systematic literature review. Thereafter, an integration capability self-assessment model, based on maturity thinking, is derived from the theoretical framework. The self-assessment model is further developed and tested for validity within five inter-organizational project networks in cooperation with industry practitioners, representing construction, industrial engineering, and mining sectors.

The results show that inter-organizational projects can use the developed model in self-assessing the maturity levels of various integration mechanisms, thus the state of integration capability at any point in time during inter-organizational projects.

This study is an attempt to identify how the integration capability dimensions can be self-assessed in inter-organizational projects, through the maturity levels of various integration mechanisms. The results offer insights for both academics and project management practitioners.

Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The objective of this research is to explore integration and transition activities in large industrial projects. The purpose is to (a) obtain a better understanding of the integration and transition activities between the project front-end (FE) and project initiation phases (PIPs), (b) explore what, how and when these integrations and transitions occur, and (c) explore what the integration and transition activities mean to project practitioners.

A qualitative research design methodology is followed, based on interviews using open-ended questions. An expert panel is used to provide responses to questions pertaining to the integration and transition between the project FE and PIP. The research is focused on managing large projects in the South African electrical engineering industrial projects industry. A literature review combined with empirical analysis reflects the importance of integrating and transitioning in project business.

The findings provide guidance to researchers and practitioners on integration and transition mechanisms, how and when these occur. It highlights the benefits of integration and transition activities. Important lessons for researchers and practitioners are provided together with areas for future research.

This is an interpretative analysis of expert opinion. Expert panel members are experienced at senior decision-making level, and their expertise was accessed based on experience, education and knowledge. This extensive experience is shared in this paper providing insights into their opinions, experiences, success and failures. These inputs together with the literature review provide interesting implications for both a theoretical foundation as well as practical implications for practitioners.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

The aim of the study is to explore how the different combinations of traditional and agile project management (APM) enhance project success under different levels of teamwork quality.

The study used system approach, using cluster analysis, to examine the relationships between project success and traditional project management (TPM) and APM under different levels of teamwork quality. A cluster analysis approach provides a method to examine how the entire range of variables combine to improve project success.

The results of the study revealed three profiles of project managers’ differences in teamwork quality and type of project management used: pure agile, TPM leaning hybrid and APM (APM) leaning hybrid. The results found evidence that TPM leaning hybrid received the highest score in project success.

Organizations should develop teamwork skills to learn to use both TPM and APM so that specific risks presented by one approach use are compensated by the use of other. Finally, organizations should have good TPM practices before planning to implement agile practices.

The findings of this study suggest that TPM with high teamwork quality supported by APM can enhance project success. APM supported by TPM contributes to improved project success.