Semester 1 (15 credits)

Introduction to the nature engineering management, within the broader context of the organisation. Developing a Personal Learning Strategy (PLS) with an emphasis on a developing life-long learning skills; and a Personal Decision-Making Strategy (PDS) build on the foundations of the nature of knowledge, thinking skills and decision-making techniques. Building a personal Engineering Management toolbox, with practical engineering management methods, techniques and concepts. The importance of business models and the notion of business model innovation and disruption.  Principles of accounting and economics from an engineering management perspective.

Semester 1 (15 credits)

The nature of technology. Technology life cycle management: R&D, procurement, commissioning, operations, maintenance, decommissioning. Technology frameworks, platforms and ecosystems. Technology assessment. Technology strategy. Knowledge management, data and information management. Digital transformation.

Semester 2 (15 credits)

The concept of strategy. Environmental analysis. Systems thinking: concepts, modelling, applications and evaluation. Functional flow for business processes: Functional, operations, strategic systems. Governance and compliance. Management principles. Strategic impact of technology. Markets and marketing.

Semester 2 (15 credits)

Understanding the concept of innovation and its strategic business impact . The importance of the invention phase as well as the market, including the diffusion of innovations and adoption in the market. Sources of and barriers to innovation. The dynamics of technological change as a driver for technological innovation. Innovation modes, including product/process innovation, radical/incremental innovation, architectural/modular innovation, open innovation and technological disruption. Anticipating the technological future and managing emerging technologies. Modern innovation approaches and new product design (NPD). The innovative organisation. Corporate innovation strategy.

Semester 3 (15 credits)

The nature of uncertainty. Principles of statistics. Risk and risk management. Real options. Linear programming. Predictions and forecasting. Quantitative methods for decision support. Aspects of quality management. Applications of analytics.

Semester 3 (15 credits)

The nature of leadership and management: Transformational leadership and change management. Managing yourself. Managing people and HR processes. Organisational behaviour. The innovative organisation. Venture structures. Managing virtual and remote teams.

Semester 4 (15 credits)

For any professional environment to be successful in executing projects, it is not only important understand and be able to run the functional aspects of project management (i.e. methodologies, tools and techniques), but also important to understand the value and role the function of project management plays in the quest to deliver projects successful. This course therefore aims to build on existing project management knowledge, skills and experiences by reiterating project management best practices as well as focusing on the role project management plays in any environment. Furthermore, this course will also consider the role of the project leader within these environments to facilitate, not only successful projects, but to ensure successful organisations as a result of practicing project management correctly and delivering projects successfully.

Semester  4 (15 credits)

The nature of technological entrepreneurship and technological venturing. Characteristics of start-up companies and new corporate ventures. Business plan development and new product development (NPD). Execution and governance, partners and staffing. In this module, students will develop a complete business model for a technology-based start-up or a new corporate venture.

Semester 4 (15 credits)

This module will focus on various specialised topics in engineering management, driven by demand and interest. (This module will not necessarily be offered in every semester or every year).

Semester 3 (15 credits)

This module is offered by the Data Science group in the Department of Industrial Engineering, in block format. The data science module provides students with a foundation of what data science is, and allows them to identify the complexities that arise in the data science domain. One of the particularities of this module is that it equips students with a thorough knowledge of the cross-industry standard process for data mining (CRISP-DM) process model. The CRISP-DM is a workflow that helps data scientists understand the data within a business context, prepare the data, select the appropriate model, evaluate the model, and deploy the model. Moreover, this module explains the ethical challenges faced in data science, and critically evaluates the developments in the data regulation and information privacy sectors.

Semester 3, Year 2 (15 credits)

This module is offered by the Department of Civil Engineering, in block format. The purpose of the module is to expose students to financial management and financing aspects of projects. At the end of the module, students should understand time value of money, financial statements of organisations, personal finance, and the concept of project finance as it relates to infrastructure projects.

Semester 5 & 6 in Year 3 (60 credits)

The Research Assignment provides the student with the opportunity to undertake a research project which addresses a specific issue or problem in Engineering Management under the supervision of lecturer in the Faculty of Engineering, elsewhere in the University (or the industry). This includes the formal structuring of the problem to be addressed and learning how to conduct a research project using scientific methodology which leads to practical conclusions and recommendations. Students are encouraged to select a topic which is also of importance for their employer, thereby adding further value to the employer, to publish their findings in a recognised journal and present these at a conference.

A student will typically select a topic and conduct the bulk of the structuring of the problem to be addressed in the semester preceding the research itself. During this time, the student will also be designated a supervisor who has an interest in the topic.