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Total quality management is a valuable approach to continuously improve the quality of organizations; however, scholars debate its applicability to services, which require specific best practices that are different from those related to manufacturing. Moreover, digitization is pervading all kinds of services, but little has been written about total quality service practices in digital-based companies. For this purpose, the authors provide a holistic model of total quality service that reflects the peculiarities of such companies, guided by the question: how do total quality service practices change in digital-based service organizations?

The authors conduct an illustrative case study on Healthware Group, a global integrated digital health organization, to evaluate theoretical assumptions about total quality service practices in the digital environment.

The findings allow to validate the model provided. In addition, the study enables them to observe the changes the authors are witnessing in service provision in the digital era and the consequent transformation of best practices. To be accurate, the authors cannot refer to a full transformation in digital-based companies but rather to the enrichment and extension of TQS practices. The best illustration of these conclusions has been summarized in a set of propositions corresponding to seven of the key levers of a TQS model.

The paper represents the first attempt to discuss the relationship between total quality service and digitalization, offering a set of propositions for academics and insights for practitioners. The model can be used as a tool to visualize the different levers that successful implementation of TQS in digital-based services companies can rely on.

The purpose of this research was first to determine the competencies mandatory of risk managers, and second, to consider the implications of such competencies in determining modules appropriate for inclusion in any prospective undergraduate qualification with specialisation in risk management.

A qualitative research approach was followed, involving academics teaching risk management in a focus group and making use of interactive qualitative analysis (IQA).

The competencies identified were business management skills, financial knowledge, an understanding of the risk management process, governance and compliance, people management and technical skills. These will be explained in greater detail in the paper.

The implications for teaching are that an undergraduate curriculum in risk management will have to combine majors such as business management, financial management, risk management, industrial psychology and communication. These majors need to be complemented by modules in governance and compliance management, as well as information and communication technology.

The implication for practice is that risk management professionals and members of the Institute of Risk Management of South Africa need to avail themselves to serve on an advisory board of academic departments offering risk management qualifications. Risk management is a developing science and requires inputs about research and the curriculation of qualifications.

The implication for public policy is that the South African Qualifications Authority and the Council for Higher Education should reconsider their requirements for designators (specialised qualifications). The implications for research are that IQA provides clarity on the knowledge and skills required to develop a competency-based qualification in risk management. Further research should benchmark qualifications and propose a curriculum for a bachelor’s degree in risk management.

The use of IQA is a novel way of ensuring rigour and objectivity in arriving at a description of the required knowledge, skills, values and attributes of risk managers. This paper will assist in the compilation of a new curriculum for an undergraduate qualification in risk management; thus, ensuring such qualification will provide a competency-based qualification that will meet the needs of the profession.

The relationship of leadership to culture is explored in this study. The study was designed to determine if significant relationships existed between specific leadership practices and different cultural profiles. The treatment for this correlational study consisted of 15 teams with an assigned formal leader for each team. Significant relationships were found between the variables in 14 of the 20 relationships examined. It was concluded that different leadership practices resulted in different cultures.

Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given.

Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, production, sales, education, and sports, process mining software can be used in a broad range of organizations.

The paper provides an original view on process mining by relating it to the spreadsheets. The value of spreadsheet-like technology tailored toward the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.