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When improving business processes, process analysts can use data-driven methods, such as process mining, to identify improvement opportunities. However, despite being supported by data, process analysts decide which changes to implement. Analysts often use process visualisations to assess and determine which changes to pursue. This paper helps explore how process mining visualisations can aid process analysts in their work to identify, prioritise and communicate business process improvement opportunities.

The study follows the design science methodology to create and evaluate an artefact for visualising identified improvement opportunities (IRVIN).

A set of principles to facilitate the visualisation of process mining outputs for analysts to work with improvement opportunities was suggested. Particularly, insights into identifying, prioritising and communicating process improvement opportunities from visual representation are outlined.

Prior work focuses on visualisation from the perspectives – among others – of process exploration, process comparison and performance analysis. This study, however, considers process mining visualisation that aids in analysing process improvement opportunities.

This study aims to propose a tailored Lean Six Sigma framework providing an accessible Lean Six Sigma methodology for compound feed manufacturers with the aim of mitigating rising costs and increasingly complex demands from customers.

A Lean Six Sigma framework was designed combining Lean value stream mapping and Six Sigma structured problem-solving with a case study in an Irish compound feed manufacturer.

The study found that the Lean Six Sigma implementation framework provided a simplified approach, which fitted the resource availability within compound feed manufacturing.

The study is limited by the constraints of a sole case study in providing empirical evidence of the effectiveness of the framework. Nevertheless, a conceptual Lean Six Sigma model is proposed, which will assist compound feed manufacturers implementing a continuous improvement approach.

This paper proposes a simplified approach to the implementation of Lean Six Sigma in agricultural compound feed manufacturers and in small and medium-sized organisations. This is the first such study in Ireland and will add to the body of work on Lean in agriculture and aid other agri-businesses and compound feed manufacturers in understanding how Lean Six Sigma can benefit.

Lean Six Sigma in public and private healthcare organisations has received considerable attention over the last decade. Nevertheless, such process improvement methodologies are not generalizable, and their effective implementation relies on contextual variables. The purpose of this study is to explore the readiness of Italian hospitals for Lean Six Sigma and Quality Performance Improvement (LSS&QPI), with a focus on gender differences.

A survey comprising 441 healthcare professionals from public and private hospitals was conducted. Multivariate analysis of variance was used to determine the mean scores on the LSS&QPI dimensions based on hospital type, gender and their interaction.

The results showed that public healthcare professional are more aware of quality performance improvement initiatives than private healthcare professionals. Moreover, gender differences emerged according to the type of hospital, with higher awareness for men than women in public hospitals, whereas for private hospitals the opposite was true.

This study contributes to the Lean Six Sigma literature by focusing on the holistic assessment of LSS&QPI implementation.

This study informs healthcare managers about the revolution within healthcare organisations, especially public ones. Healthcare managers should spend time understanding Lean Six Sigma as a strategic orientation to promote the “lean hospital”, improving processes and fostering patient-centredness.

This is a preliminary study focussing on analysing inter-relationship between perceived importance of soft readiness factors such as gender dynamics as a missing jigsaw in the current literature. In addition, the research advances a holistic assessment of LSS&QPI, which sets it apart from the studies on single initiatives that have been documented to date.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

In the last few decades, the growth in management institutions in India has become significant. The Open and Distance Learning (ODL) institutions also have started offering management programmes at various levels. In the ODL scenario, the learning path has been shifting from the traditional Self-Learning Material (SLM) -based model to technology-mediated platform. The digital divide in India is also a widely discussed area. In this context, a need has been felt to understand the implications for educators, more specifically, for the programmes offered through technology-enabled ODL mode.

This study uses triangulation method covering literature review, personal interview and survey. Primary data have been collected through structured questionnaire in the Google Form administered on the learners of UG and PG progammes of management in Krishna Kanta Handiqui State Open University (KKHSOU), India. The sample size is 101, and the sampling frame is within Assam, a province of India. Select interviews (15 nos.) were also conducted with a cross section of learners to capture the emerging shift in the learning path and the limiting factors of digital divide.

Learners possess multiple digital devices for e-learning (41.8% uses laptop and 88.8% uses android phone). Interaction in WhatsApp and Telegram groups are mostly related with evaluation and course administration, rather than content and academic discussion. eSLMs are widely used. Though promoted, video lectures are not widely used. Some of the problems faced by the learners are low bandwidth, high cost of data subscription etc. Learners are not constrained by digital device, and they are engaged in positive communication with stake holders in digital platform.

This study will help in understanding the technology-enabled learning for management education in ODL mode in India. As a wide majority of the learners (88%) are dependent on small screen; print SLM and eSLM on a larger screen can provide augmented learning in case of complex topics like analysis of financial statements, project scheduling etc. Though the COVID-19 pandemic forced a shift in learning path, the transition is not full. The digitally constrained learners still look for solutions to complex learning problems mainly through print SLM and counselling. The talent of the students cannot be facilitated in WhatsApp and Telegram e-mentoring groups, like the way it could be done in learning management system (LMS)-mediated platforms.

Agile methods are increasingly being applied in the contexts of innovation beyond traditional information technology (IT) and physical product development projects, such as when process improvements are being implemented. Nevertheless, this phenomenon is still recent and little addressed in the literature, with few descriptions of empirical cases. This study aims to address this gap.

This multiple case study aims to present and discuss the application of Agile practices embedded in large companies’ innovation value chains, focusing on improvements of business processes. The following research question is pursued: How are large companies applying elements of Agile methods to their innovation processes when implementing incremental improvements in their operational processes? Based on the idea that the Agile-Stage-Gate model is an alternative to this challenge, this study investigates the application of this hybrid model in two large Brazilian companies by presenting their idiosyncrasies, lessons learned, adaptations, challenges and benefits.

Overall, it was observed that the experience with the application of the Agile-Stage-Gate model is positive for these companies, with better customer engagement, easier project control and increased productivity of the project team.

For those aiming to implement the Agile-Stage-Gate model, this paper identifies the main adaptations made in order to combine the purist approaches and critical success factors for its implementation.

Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.

The purpose of this article is to increase the understanding of how improvements can be facilitated in a public service containing multiple actors in terms of identifying, aligning and prerequisites for the improvements.

The research utilizes an interactive research approach where data were gathered though a conference, workshop and a survey. The study alternately combines quality management methods such as affinity and interrelationship diagrams with computer aided text mining and latent semantic analysis.

The research shows that practitioners must consider interconnectedness between improvements and benefits that are crossing organizational levels of the public service system as well as professional borders. In public service systems, the complex reality can be better understood when improvements and benefits are classified into different organizational layers and an interconnectedness and sequence of improvement areas are acknowledged.

The research is set in the Swedish public service of the tax-paid sick leave insurance. Future research would benefit by investigating similar cases in other nations and other services.

The used methodology can be applied by practitioners to enhance a unified understanding of the system required to improve. The study also guides practitioners for how to support, relive hinders and prioritize improvements.

The research fills a gap of understanding of improvements in public services with multiple actors. As this area is difficult to improve, a novel combination of qualitative and quantitative methods paved the way for deeper and more unified understanding of the system.

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.